JP6875451B2 - Dog cancer risk assessment method and cancer risk assessment system - Google Patents

Description

The present invention relates to a dog cancer risk assessment method and a cancer risk assessment system, and further, utilizes the concentration balance of element groups contained in dog serum (correlation between the concentrations of evaluation element groups). The present invention relates to a canine cancer risk assessment method and a cancer risk assessment system that evaluates the canine cancer risk by using the obtained index.

Conventionally, as a method for diagnosing human cancer, a method of directly seeing or touching (palpation, endoscopy, etc.) or a method of judging by an image showing the inside of the body (X-ray, CT examination, MRI examination, PET) Methods for examining blood and cells (blood test, cytology, biopsy, etc.) are known. However, the method of directly seeing or touching has the disadvantage that the target (affected part) is limited to the breast, rectum, stomach, large intestine, etc., and the method of diagnosing with images is simple, but the detection sensitivity. Not only is it low, but it also has the drawback of being exposed to radiation from the subject. In that respect, the method of examining blood and cells is preferable because the burden on the patient is small and the detection sensitivity is high. In particular, if the diagnosis can be made by analyzing the blood collected from the patient, the burden on the patient can be reduced and it is possible to carry out the mass examination, which is more preferable. This is true for humans and animals such as dogs. Therefore, for many years, it has been desired to realize a cancer screening method having such characteristics.

By the way, the leading cause of death in humans in recent years is malignant neoplasm (commonly known as cancer), and as the average life expectancy increases, the death rate due to cancer is also increasing. This situation is similar for animals that live with humans (eg pets or companion animals). In other words, this species of animal also becomes more likely to suffer from cancer as it gets older, and the rate of death from cancer also increases. According to the statistics of Japan Animal Club Co., Ltd. of pet insurance, cancer is the leading cause of death for dogs and cats as pets, accounting for 54% of all deaths. In addition, the skin is the most common cancer site affecting dogs and cats as pets, followed by the hematopoietic system, followed by the lymphatic system and digestive system.

Among many pets (pets), dogs live closely with humans, but with the recent increase in human lifespan, the average lifespan of dogs has also increased. Possible reasons for this include the development of veterinary medicine, the development of well-balanced pet food, and the development of preventive medicine including health examinations as part of health management. In this way, dogs have a longer lifespan. This may also be one of the factors that increased the incidence of cancer in dogs. Recently, most dogs are said to be in the pre-cancerous stage after the age of 10.

Similar to Japan, in the United States, cancer has the highest mortality rate for dogs aged 10 and over, accounting for about 50% of all deaths. It is reported that the cause of death of dogs of all ages accounts for 25%.

In general, the progression of cancer in dogs and cats is rapid, and in many cases, the cancer is terminally ill at the time of cancer diagnosis, so it is said that the therapeutic effect cannot be expected. The treatment methods, like humans, are mainly surgery, radiation therapy, and chemotherapy. Usually, the cure rate in the case of dogs is about 30 to 40%, which is slightly lower than the cure rate in humans, which is about 50%. Therefore, early detection of cancer is desired for dogs and cats as well as humans. However, at present, an appropriate cancer screening method has not been developed, and there is almost no response aimed at early detection and early treatment.

Conventionally, a medical examination called "cancer screening of animals" has been performed, but all of them are methods that imitate human cancer screening, and diagnosis by tumor markers, examination by CT, urinalysis, etc. are carried out. It's just done. However, all of these have low sensitivity and specificity, and the cost of examination is high. Therefore, it is difficult to detect cancer in dogs and cats at an early stage.

Other prior art related to the present invention include reports that zinc, chromium (Cr), and iron (Fe) in canine serum are associated with lymphoma and sarcoma (Non-Patent Document 1), and selenium (Se). ) Is a biomarker for canine diseases (Non-Patent Document 2). Regarding humans, there is a report on the relationship between the function of trace elements and diseases (Non-Patent Document 3). Furthermore, chromium (Cr), nickel (Ni), arsenic (As), cobalt (Co), titanium (Ti), rubidium (Rb), beryllium (Be), cadmium (Cd), etc. have carcinogenicity to animals. There is also a report that it does (Non-Patent Documents 4 and 5).

The applicant of the present application has developed a new cancer evaluation method and a cancer evaluation system utilizing the correlation between the onset of cancer and the element concentration in human serum, applied for a patent, and has already obtained a patent ( See Patent Document 1).

Patent Document 1 discloses a cancer evaluation method utilizing the correlation between the onset of cancer and the element concentration in human serum. This method applies the concentration data of the evaluation element group in the serum collected from the subject to the discriminant function for discriminating whether the subject belongs to the control group or the case group, and applies the concentration data to the serum. Whether or not the subject has developed some kind of cancer based on the correlation calculation step for calculating the correlation between the concentrations of the evaluation element group and the correlation calculated in the correlation calculation step. It has an index acquisition step to obtain an index. Then, as the evaluation element group, a combination of seven kinds of elements S, P, Mg, Zn, Cu, Ti, Rb, or Na, Mg, Al, P, K, Ca, Ti, Mn, Fe, A combination of 16 kinds of elements, Zn, Cu, Se, Rb, Ag, Sn, and S, is selected. According to this method, the risk of developing cancer in a subject can be estimated with high accuracy, and there are no drawbacks such as early degeneration and high cost as in the case of using the amino acid concentration in blood, and moreover, it is suitable for mass examination. Also has the effect of being readily applicable (see claims 1 and 2, paragraphs 0036, 0057 to 0061, paragraphs 0070 to 0074, FIGS. 1 and 14). This cancer evaluation method has the above-mentioned features and can be utilized as a screening method for human cancer.

Japanese Patent No. 6082478

Kazmierski K.J., et al., Serum Zinc, Chromium, and Iron Concentrations in Dogs with Lymphoma and Osteosarcoma. J Vet Intern. Med. 2001, 15, 585-588 Zelst M.V. et. Al., Biomarkers of selenium status in dogs, BMC Veterinary Research 2016 12:15 Yasuaki Arakawa, Trace Elements that Maintain Life Functions, Nihon Rinsho, Vol. 74, No. 7, 2016-7, 1058-1065 Yasuaki Arakawa, Cancer Immunity and Trace Elements (Part 1), Journal of the Japan Medical Association, Vol. 113, No. 8, 1995, BG-10-12 Yasuaki Arakawa, Cancer Immunity and Trace Elements (Part 2), Journal of the Japan Medical Association, Vol. 113, No. 10, 1995, BG-13-15

As described above, in order to realize early detection and early treatment of cancer in dogs, there is a demand for a screening method that has a low burden on dogs, high detection sensitivity, and can be performed even in mass screening.

Therefore, the present inventors discriminate between a cancer patient group (case group) and a control group (control group) by utilizing the balance of trace element concentrations in human serum disclosed in Patent Document 1 described above. Based on the knowledge and experience of developing the method and the knowledge disclosed in Non-Patent Documents 1 to 5 described above, the development of a new screening method capable of estimating the risk of developing cancer in dogs, which is highly useful as a pet. This is what led to the discovery of the possibility and the invention of the present invention.

An object of the present invention is to be able to estimate the cancer risk of a target dog with high accuracy, and to avoid the disadvantages of premature degeneration and high cost as in the case of using the amino acid concentration in blood, and at any site. The purpose is to provide a cancer risk assessment method and a cancer risk assessment system for dogs, which can also estimate cancer.

Another object of the present invention is to provide a cancer risk assessment method and a cancer risk assessment system for dogs, which are simple and inexpensive to carry out and are also suitable as a cancer screening method in a veterinary hospital. ..

Other objects of the invention not specified herein will become apparent from the following description and accompanying drawings.

(1) According to the first aspect of the present invention, a canine cancer risk assessment method is provided. The cancer risk assessment method for this dog is
The concentration data of the evaluation element group in the serum collected from the target dog and the age data of the target dog are applied to a discriminant function for discriminating whether the target dog belongs to the control group or the case group. Then, a correlation calculation step for calculating the correlation between the concentrations of the evaluation element group in the serum, and
Based on the correlation calculated in the correlation calculation step, an index acquisition step for obtaining an index as to whether or not the target dog has some kind of cancer is provided.
In the correlation calculation step, 17 kinds of elements for evaluation, Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, and Cs, are used. A combination of elements is used,
The index acquisition step is characterized in that the index is generated based on a discrimination score calculated by applying the concentration data and the age data to the discrimination function used in the correlation calculation step. It is a thing.

In the dog cancer risk evaluation method according to the first aspect of the present invention, in the correlation calculation step, the concentration data of the evaluation element group in the serum collected from the target dog and the age data of the target dog are obtained. The concentration data and the age data are applied to a discriminant function for discriminating whether the target dog belongs to the control group or the case group, and the correlation between the concentrations of the evaluation element group in the serum is calculated. .. As the evaluation element group, a combination of the above 17 kinds of elements is used.

Then, in the index acquisition step, an index as to whether or not the target dog has some kind of cancer is obtained based on the correlation obtained in the correlation calculation step, and the index is the correlation. It is generated based on the discrimination score obtained by applying the concentration data and the age data to the discrimination function used in the relational calculation step.

Therefore, the risk of developing cancer in the target dog can be estimated with high accuracy, and there are no drawbacks such as early degeneration and high cost as in the case of using the amino acid concentration in blood.

Further, in the correlation calculation step, it was found which of the 17 kinds of the elements used as the evaluation element group, the concentration data was significant for discrimination, and whether the patient was suffering from cancer. Since the element that is significant for discrimination and the element that is significant for discrimination vary depending on the type of cancer affected, it is also possible to estimate which part of the cancer is the cancer.

Furthermore, the target dog belongs to either the control group or the case group by automatically calculating with a computer using the concentration data of the evaluation element group in the serum collected from the target dog and the age data. Since it is possible to determine whether or not the dog is a large number, it is possible to easily and quickly determine whether or not the target dog is large. Therefore, it can be carried out easily and inexpensively, and is also suitable as a cancer screening method in animal hospitals.

(2) In a preferable example of the dog cancer risk assessment method according to the first aspect of the present invention, any of the concentration data among the 17 kinds of the elements used as the evaluation element group is significant for discrimination. It is speculated that the target dog has some kind of cancer, depending on whether or not it is present.

(3) In another preferable example of the dog cancer risk assessment method according to the first aspect of the present invention, Mg, S, Cu, selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has some kind of cancer depending on whether or not the concentration data of the four elements of Se is significant for discrimination.

(4) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, the concentration of Mg element selected from the 17 kinds of the elements used as the evaluation element group. As the data rises or falls over time, it is speculated that the subject dog's risk of developing cancer tends to decrease or increase. In this example, there is an advantage that it is possible to further present an estimate of the temporal change in the risk of developing cancer in the target dog.

(5) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, S, Cu, Se selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the three elements rises or falls with the passage of time, it is speculated that the risk of developing cancer in the target dog tends to increase or decrease. In this example, there is an advantage that it is possible to further present an estimate of the temporal change in the risk of developing cancer in the target dog.

(6) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, any of the concentration data among the 17 kinds of the elements used as the evaluation element group is discriminated. Depending on whether or not it is significant, the cancer site is estimated as well as the target dog is estimated to have cancer. This example has the advantage that the type of cancer can be identified and the cancer risk of the target dog can be notified.

(7) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, Fe, Cu 2 selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has liver cancer depending on whether or not the concentration data of the element is significant for discrimination. In this example, there is an advantage that the type of cancer can be specified as "liver cancer" and the cancer risk of the target dog can be notified.

(8) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, the concentration of Fe element selected from the 17 kinds of the elements used as the evaluation element group. As the data rise or fall over time, it is speculated that the risk of developing liver cancer in the target dog tends to decrease or increase. In this example, there is an advantage that it is possible to further present an estimate of the temporal change in the risk of developing liver cancer in the target dog.

(9) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, the concentration of Cu element selected from the 17 kinds of the elements used as the evaluation element group. As the data rise or fall over time, it is speculated that the risk of developing liver cancer in the target dog tends to increase or decrease. In this example, there is an advantage that it is possible to further present an estimate of the temporal change in the risk of developing liver cancer in the target dog.

(10) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, Mg, P, S selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog suffers from adrenal cancer depending on whether or not the concentration data of the seven elements of, Co, Zn, As, and Se are significant for discrimination. In this example, there is an advantage that the type of cancer can be specified as "adrenal cancer" and the cancer risk of the target dog can be notified.

(11) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, Mg, Zn, As selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the three elements rises or falls with the passage of time, it is speculated that the risk of developing adrenal cancer in the target dog tends to decrease or increase. In this example, there is an advantage that it is possible to further present an estimate of the temporal change in the risk of developing adrenal cancer in the target dog.

(12) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, P, S, Co selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the four elements of, Se increases or decreases with the passage of time, it is speculated that the risk of developing adrenal cancer in the target dog tends to increase or decrease. In this example, there is an advantage that it is possible to further present an estimate of the temporal change in the risk of developing adrenal cancer in the target dog.

(13) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, Na, Mg, As selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has lung cancer depending on whether or not the concentration data of the four elements of Sr and Sr are significant for discrimination. In this example, there is an advantage that the type of cancer can be identified as "lung cancer" and the cancer risk of the target dog can be notified.

(14) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, Mg and As 2 selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one element increases or decreases over time, it is speculated that the risk of lung cancer in the target dog tends to decrease or increase. This example has the advantage of being able to further provide an estimate of temporal changes in the risk of lung cancer in the subject dog.

(15) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, 2 of Na and Sr selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one element increases or decreases over time, it is speculated that the risk of lung cancer in the target dog tends to increase or decrease. This example has the advantage of being able to further provide an estimate of temporal changes in the risk of lung cancer in the subject dog.

(16) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, Na, K, Cu selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has prostate cancer depending on whether or not the concentration data of the three elements is significant for discrimination. This example has the advantage that the type of cancer can be identified as "prostate cancer" and the cancer risk of the target dog can be notified.

(17) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, the concentration of K element selected from the 17 kinds of the elements used as the evaluation element group. As the data rise or fall over time, it is speculated that the subject dog's risk of developing prostate cancer tends to decrease or increase. This example has the advantage of being able to further provide an estimate of temporal changes in the risk of developing prostate cancer in the subject dog.

(18) In still another preferred example of the canine cancer risk assessment method according to the first aspect of the present invention, Na and Cu 2 selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one element increases or decreases over time, it is speculated that the risk of developing prostate cancer in the target dog tends to increase or decrease. This example has the advantage of being able to further provide an estimate of temporal changes in the risk of developing prostate cancer in the subject dog.

(19) According to the second aspect of the present invention, a canine cancer risk assessment system is provided. This dog cancer risk assessment system
A data storage unit that stores the concentration data of the evaluation element group in the serum collected from the target dog and the age data of the target dog.
A discriminant function generator that generates a discriminant function for discriminating whether the target dog belongs to the control group or the case group, and
The concentration data of the target dog and the age data stored in the data storage unit are applied to the discrimination function generated by the discrimination function generation unit to correlate the concentration of the evaluation element group in the serum. It is provided with an evaluation result calculation unit that calculates the relationship and outputs the evaluation result of whether or not the target dog has some kind of cancer based on the correlation.
As the evaluation element group, a combination of 17 kinds of elements of Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo and Cs is used. ,
In the evaluation result calculation unit, a discrimination score is calculated by applying the density data and the age data stored in the data storage unit to the discrimination function generated by the discrimination function generation unit, and the discrimination score is used as the discrimination score. It is characterized in that the evaluation result is generated based on the above.

In the dog cancer risk evaluation system according to the second aspect of the present invention, the concentration data of the evaluation element group in the serum collected from the target dog and the age data of the target dog are stored in the data storage unit. The evaluation result calculation unit applies the concentration data stored in the data storage unit and the age data of the target dog to the discrimination function generated by the discrimination function generation unit to obtain the serum. The correlation between the concentrations of the evaluation element group is calculated. As the evaluation element group, a combination of the above 17 kinds of elements is used.

Then, based on the correlation obtained by the calculation, the evaluation result calculation unit outputs an evaluation result as to whether or not the target dog has some kind of cancer, and the evaluation result is the determination. It is generated based on the discrimination score obtained by applying the density data and the age data to the discrimination function generated by the function generation unit.

Therefore, the risk of developing cancer in the target dog can be estimated with high accuracy, and there are no drawbacks such as early degeneration and high cost as in the case of using the amino acid concentration in blood.

Further, in the evaluation result calculation unit, it was found which of the 17 kinds of the elements used as the evaluation element group was significant for the determination, and moreover, depending on the type of cancer. Since the element that is significant for discrimination fluctuates, it is also possible to estimate which part of the cancer is the cancer.

Furthermore, by automatically calculating with a computer using the concentration data of the evaluation element group in the serum collected from the target dog and the age data, whether the target dog belongs to the control group or the case group. Therefore, even if there are a large number of the target dogs, it is possible to easily and quickly discriminate. Therefore, it can be carried out easily and inexpensively, and is also suitable as a cancer screening method in animal hospitals.

(20) In a preferable example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, the concentration data of any of the 17 kinds of the elements used as the evaluation element group is significant for discrimination. It is speculated that the target dog has some kind of cancer, depending on whether or not it is.

(21) In another preferable example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Mg, S, Cu selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has some kind of cancer depending on whether or not the concentration data of the four elements of, Se is significant for the discrimination.

(22) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, the Mg element selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data rises or falls over time, it is speculated that the cancer risk of the target dog tends to decrease or increase. In this example, there is an advantage that the evaluation result can further provide an estimate of the temporal change in the cancer risk of the target dog.

(23) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, S, Cu, selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the three elements of Se rises or falls with the passage of time, it is speculated that the cancer morbidity risk of the target dog tends to increase or decrease. In this example, there is an advantage that the evaluation result can further provide an estimate of the temporal change in the cancer risk of the target dog.

(24) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, the concentration data of any of the 17 elements used as the evaluation element group is used. Depending on whether or not the discrimination is significant, it is estimated that the target dog has cancer, and the cancer site is also estimated. In this example, in the evaluation result, there is an advantage that the type of cancer can be specified in the evaluation result and the cancer risk of the target dog can be notified.

(25) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Fe, Cu selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has liver cancer depending on whether or not the concentration data of the two elements is significant for discrimination. In this example, there is an advantage that the type of cancer can be specified as "liver cancer" in the evaluation result and the cancer risk of the target dog can be notified.

(26) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, the Fe element selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data rises or falls with the passage of time, it is speculated that the risk of developing liver cancer in the target dog tends to decrease or increase. In this example, there is an advantage that the evaluation result can further present an estimate of the temporal change in the risk of developing liver cancer in the target dog.

(27) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, the Cu element selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data rises or falls with the passage of time, it is speculated that the risk of developing liver cancer in the target dog tends to increase or decrease. In this example, there is an advantage that the evaluation result can further present an estimate of the temporal change in the risk of developing liver cancer in the target dog.

(28) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Mg, P, selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has adrenal cancer depending on whether or not the concentration data of the seven elements S, Co, Zn, As, and Se are significant for discrimination. In this example, there is an advantage that the type of cancer can be specified as "adrenal cancer" in the evaluation result and the cancer risk of the target dog can be notified.

(29) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Mg, Zn, selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the three elements of As increases or decreases over time, it is speculated that the risk of developing adrenal cancer in the target dog tends to decrease or increase. In this example, there is an advantage that the evaluation result can further present an estimate of the temporal change in the risk of developing adrenal cancer in the target dog.

(30) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, P, S, selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the four elements Co and Se rises or falls with the passage of time, it is speculated that the risk of developing adrenal cancer in the target dog tends to increase or decrease. In this example, there is an advantage that the evaluation result can further present an estimate of the temporal change in the risk of developing adrenal cancer in the target dog.

(31) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Na, Mg, selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has lung cancer depending on whether or not the concentration data of the four elements As and Sr are significant for discrimination. In this example, there is an advantage that the type of cancer can be specified as "lung cancer" in the evaluation result and the cancer risk of the target dog can be notified.

(32) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Mg, As selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the two elements rises or falls over time, it is speculated that the risk of developing lung cancer in the target dog tends to decrease or increase. This example has the advantage of being able to further provide an estimate of temporal changes in the risk of lung cancer in the subject dog.

(33) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Na, Sr selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the two elements rises or falls with the passage of time, it is speculated that the risk of lung cancer in the target dog tends to increase or decrease. In this example, there is an advantage that the evaluation result can further provide an estimate of the temporal change in the risk of lung cancer in the target dog.

(34) In yet another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Na, K, selected from the 17 kinds of the elements used as the evaluation element group. It is presumed that the target dog has prostate cancer depending on whether or not the concentration data of the three elements of Cu is significant for discrimination. In this example, there is an advantage that the type of cancer can be specified as "prostate cancer" in the evaluation result and the cancer risk of the target dog can be notified.

(35) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, the K element selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data rises or falls over time, it is speculated that the target dog's risk of developing prostate cancer tends to decrease or increase. In this example, there is an advantage that the evaluation result can further provide an estimate of the temporal change in the risk of developing prostate cancer in the target dog.

(36) In still another preferred example of the canine cancer risk cancer evaluation system according to the second aspect of the present invention, Na, Cu selected from the 17 kinds of the elements used as the evaluation element group. When the concentration data of at least one of the two elements rises or falls with the passage of time, it is speculated that the risk of developing prostate cancer in the target dog tends to increase or decrease. In this example, there is an advantage that the evaluation result can further provide an estimate of the temporal change in the risk of developing prostate cancer in the target dog.

According to the canine cancer risk assessment method according to the first aspect of the present invention and the canine cancer risk assessment system according to the second aspect, (a) it is possible to estimate the cancer risk of the target dog with high accuracy. In addition to being able to do so, there are no drawbacks such as early degeneration and high cost as in the case of using the amino acid concentration in the blood, and it is possible to estimate which part of the cancer is the cancer. (B) Easy and inexpensive implementation It is possible and has the effect of being suitable as a cancer screening method in a veterinary hospital.

It is a flowchart which shows the basic principle of the cancer risk assessment method of a dog of this invention. It is a functional block diagram which shows the basic structure of the cancer risk assessment system of a dog of this invention. It is a table which shows the facility which provided the serum sample in Examples 1 to 4 of the dog cancer risk assessment method of this invention, and the total number of all target dogs. The breakdown of all target dogs (cancer-affected group and control group) for which serum samples were provided in Examples 1 to 4 of the dog cancer risk assessment method of the present invention, and the cancer site (type) of the cancer-affected dog. ), Mean age and standard deviation. It is a table which shows the kind and sex of the dog which provided the serum sample in Examples 1 to 4 of the dog cancer risk assessment method of this invention. In Examples 1 to 4 of the dog cancer risk assessment method of the present invention, a table showing the type and sex of dogs provided with serum samples is a continuation of FIG. 5A. It is a table which shows the cancer site and sex of the target dog which provided the serum sample in Examples 1 to 4 of the dog cancer risk assessment method of this invention. It is a table which shows the average value and standard deviation of the element concentration of the serum sample of the control group (control) and the case group (cancer-affected dog) in Examples 1 to 4 of the dog cancer risk assessment method of this invention. It is a table which shows the discrimination result of all cancers in Example 1 of the cancer risk assessment method of a dog of this invention. It is a figure which shows the discriminant of all cancers used in Example 1 of the dog cancer risk assessment method of this invention. It is a graph which shows the ROC analysis result of the all cancer affected dogs obtained in Example 1 of the dog cancer risk assessment method of this invention. It is a graph which shows the relationship between the discrimination value of all cancers and cancer probability obtained in Example 1 of the dog cancer risk assessment method of this invention. It is a table which shows the discrimination result of liver cancer in Example 2 of the cancer risk assessment method of a dog of this invention. It is a figure which shows the discriminant of liver cancer used in Example 2 of the cancer risk assessment method of a dog of this invention. It is a graph which shows the ROC analysis result of the dog suffering from liver cancer obtained in Example 2 of the dog cancer risk assessment method of this invention. It is a graph which shows the relationship between the discrimination value of liver cancer and the cancer probability obtained in Example 2 of the dog cancer risk assessment method of this invention. It is a table which shows the discrimination result of adrenal gland cancer in Example 3 of the cancer risk assessment method of a dog of this invention. It is a figure which shows the discriminant of adrenal gland cancer used in Example 3 of the cancer risk assessment method of a dog of this invention. It is a graph which shows the ROC analysis result of the dog suffering from adrenal gland cancer obtained in Example 3 of the dog cancer risk assessment method of this invention. It is a graph which shows the relationship between the discriminant value of adrenal gland cancer, and the cancer probability obtained in Example 3 of the dog cancer risk assessment method of this invention. It is a table which shows the discrimination result of lung cancer in Example 4 of the cancer risk assessment method of a dog of this invention. It is a figure which shows the discriminant of lung cancer used in Example 4 of the cancer risk assessment method of a dog of this invention. It is a graph which shows the ROC analysis result of the dog suffering from lung cancer obtained in Example 4 of the dog cancer risk assessment method of this invention. It is a graph which shows the relationship between the discrimination value of lung cancer and the cancer probability obtained in Example 4 of the dog cancer risk assessment method of this invention. In Examples 1 to 4 of the dog cancer risk evaluation method of the present invention, among the concentration data and age data of 17 kinds of evaluation element groups, those having a positive correlation with cancer risk and those having a negative correlation with cancer risk are negative. It is a table which shows the correlation (the one which is judged to be significant by discriminant analysis and logistic regression analysis). It is a table which shows the basic statistics of a control group (control) and a case group (a dog with voluntary cancer) used in Example 1 of the dog cancer risk assessment method of this invention. It is a table which shows the basic statistics of a control group (control) and a case group (a dog suffering from liver cancer) used in Example 2 of the dog cancer risk assessment method of this invention. It is a table which shows the basic statistics of the control group (control) and the case group (adrenal cancer-affected dog) used in Example 3 of the dog cancer risk assessment method of this invention. It is a table which shows the basic statistics of the control group (control) and the case group (lung cancer-affected dog) used in Example 4 of the dog cancer risk assessment method of this invention. It is a table which shows the variable included in the discriminant function used in Example 1 (arbitrary cancer) of the dog cancer risk assessment method of this invention. It is a table which shows the variable included in the discriminant function used in Example 2 (liver cancer) of the dog cancer risk assessment method of this invention. It is a table which shows the variable included in the discriminant function used in Example 3 (adrenal cancer) of the dog cancer risk assessment method of this invention. It is a table which shows the variable included in the discriminant function used in Example 4 (lung cancer) of the dog cancer risk assessment method of this invention. It is a table which shows the facility which provided the serum sample in Example 5 of the dog cancer risk assessment method of this invention, and the total number of target dogs. Breakdown of target dogs (cancer-affected group and control group) for which serum samples were provided in Example 5 of the dog cancer risk assessment method of the present invention, cancer sites (types) of cancer-affected dogs, average It is a table showing age and standard deviation. FIG. 5 is a table showing the type and sex of dogs to which serum samples were provided in Example 5 of the dog cancer risk assessment method of the present invention. It is a table which shows the average value and standard deviation of the element concentration of the serum sample of the control group (control) and the case group (prostate cancer suffering dog) in Example 5 of the dog cancer risk assessment method of this invention. It is a table which shows the discrimination result of prostate cancer in Example 5 of the cancer risk assessment method of a dog of this invention. It is a figure which shows the discriminant of prostate cancer used in Example 5 of the cancer risk assessment method of a dog of this invention. It is a graph which shows the ROC analysis result of the dog with prostate cancer obtained in Example 5 of the dog cancer risk assessment method of this invention. It is a graph which shows the relationship between the discrimination value of all cancers, and the cancer probability obtained in Example 5 of the dog cancer risk assessment method of this invention. In Example 5 of the dog cancer risk evaluation method of the present invention, among the concentration data and age data of 17 kinds of evaluation element groups, those having a positive correlation with cancer risk and those having a negative correlation were obtained. It is a table which shows what has (thing which is judged to be significant by discriminant analysis and logistic regression analysis). It is a table which shows the basic statistics of the control group (control) and the case group (prostate cancer-affected dog) used in Example 5 of the dog cancer risk assessment method of this invention. It is a table which shows the variable included in the discriminant function used in Example 5 (prostate cancer) of the dog cancer risk assessment method of this invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

(Basic Principle of Dog Cancer Risk Assessment Method of the Present Invention)
The present inventors have developed cancer as described in Patent Document 1 described above as a new cancer screening method using the concentration (content) of an element group contained in the serum of a target dog. We have developed a cancer evaluation method that utilizes the correlation between the concentration of elements in human serum and human serum. The present inventors have made the present invention as a result of further diligent research based on the further knowledge obtained in the development process of the above-mentioned cancer evaluation method and the knowledge disclosed in the above-mentioned Non-Patent Documents 1 to 5. It has arrived.

In the present invention, first, the serogroup belonging to the cancer-affected dog group (case group) and the serogroup belonging to the control group (control group) are randomly divided into two groups according to sex, age, and cancer site. , One set is referred to as the "test serogroup" and the other set is referred to as the "evaluation serogroup". Next, the element concentration in the serum is measured using the test serum group, and the measured element concentration is statistically analyzed to obtain a discriminant. Then, the age data and element concentration data of the evaluation serogroup are applied to the obtained discriminant to obtain an index as to whether or not the target dog has some kind of cancer. The indicators further include, if necessary, estimates of where the cancer is affected and estimates of changes in the risk of developing cancer over time.

Hereinafter, the canine cancer risk assessment method of the present invention will be described in detail.

First, pretreatment was performed as follows to find the optimum measurement conditions for measuring the concentration of the element group contained in the serum of the target dog.

Nitrate is mixed with the test serogroup (including both the serogroup belonging to the case group and the serogroup belonging to the control group), proteins and amino acids are decomposed at 70 ° C to 80 ° C for 24 hours, and the concentration of the element group is measured. After pretreatment so as not to interfere with the above, it was diluted to a predetermined concentration using ultrapure water without metal contamination. The concentration of 75 kinds of element groups contained in the treatment liquid thus obtained was measured by using ICP mass spectrometry. Using the obtained results, the optimum measurement conditions for measuring the concentration of the element group contained in the test serogroup were found.

Inductively-Coupled Plasma Optical Emission Spectroscopy (ICP-OES), Inductively-Coupled Plasma Mass Spectroscopy (ICP-MS), Atomic Absorption Spectroscopy, ICP-Coupled Plasma Mass Spectroscopy, ICP-OES Analytical methods (Atomic Absorption Spectrometry, AAS), fluorescent X-ray analysis (XRF), etc. can be used, but this is the simplest method for selecting ICP mass spectrometry. This is because the quantitativeness of the measurement results is recognized as a strict method. Therefore, it goes without saying that if this condition changes, or if a more suitable analytical method is developed, an analytical method other than the ICP mass spectrometry may be used.

Using the same test serogroups (including both case group serogroups and control group serogroups) under the optimal measurement conditions found, ICP mass spectrometry was used to generate those serogroups. The content of 75 kinds of contained element groups was measured. Then, regarding the measured concentration data of the element group, the difference in the element concentration between the case group and the target group was statistically analyzed. In this analysis, discriminant analysis and binomial logistic regression analysis were used to clarify the elements involved in the difference between the case group and the control group and to determine the risk (probability) of developing cancer. At this time, considering the combination of elements, the combination that makes the most difference between the two elements, that is, the combination of the elements that can best distinguish between the case group and the control group, is combined over and over again by a computer. I changed and searched. As a result, as the "element group for evaluation", 17 kinds of elements of Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo and Cs It was found that the discriminant ability was the highest when the combination was used. Therefore, in the present invention, it has been decided to use the combination of these 17 kinds of elements as the "element group for evaluation".

When the "evaluation element group" is determined as described above, the element concentration of the element of the "evaluation element group" in the serum is measured using the same test serum group. Then, when the measured element concentration is discriminantly analyzed, a discriminant formula is obtained. Once the discriminant is obtained in this way, the discriminant value is calculated by applying the age data and element concentration data of the evaluation serogroup to the discriminant, and an index of whether or not the target dog has some kind of cancer. (Cancer morbidity index) is obtained. Gender data of the "element group for evaluation" may be further added to the age data and the element concentration data. Furthermore, by performing binomial logistic regression analysis using the calculated discriminant value, the cancer risk (probability) of the target dog can be clarified. Moreover, it is investigated which of the 17 types of elements used as the "element group for evaluation" is significant for discrimination, and whether the correlation of the elements judged to be significant for discrimination is positive or negative. As a result, it becomes possible to estimate which part of the cancer the target dog is affected by, and also to estimate the temporal change in the cancer morbidity risk (probability).

The details of the discriminant analysis and the binomial logistic regression analysis will be described below.

First, 17 kinds of element groups (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo) measured as "evaluation element group". , Cs), discriminant analysis was performed on two groups, a control group and a case group. Specifically, a test (t-test) of the difference between the population mean values of the two groups, the control group and the case group, was performed. This is to investigate how much the 17 kinds of element groups as the "evaluation element group" affect the discrimination between these two groups. In this test result, there is a difference between the two groups for each element alone, but the association between the elements is ignored in this analysis, and there are many problems to be used for risk assessment of cases. In order to solve this problem, it is necessary to perform analysis using multivariate analysis, that is, discriminant analysis, which can consider the relationships between elements.

Therefore, next, the discriminant function was obtained as follows. This is to analyze the concentration balance (correlation) between the elements. This is to know the correlation of the concentrations between the elements because it is difficult to use the concentration of each element as an index because there is an individual difference for each target dog.

The discriminant function can be expressed as the following mathematical formula (1).
Discrimination value (D) = function (F) (explanatory variables 1 to n, discrimination coefficient) (1)
(However, n is an integer of 2 or more)
The mathematical formula (1) can be written as the following mathematical formula (2) in consideration of the weights (degree of influence on discrimination) of each explanatory variable 1 to n.
Discrimination value (D) = (discrimination coefficient 1) x (explanatory variable 1) + (discrimination coefficient 2) x (explanatory variable 2) +
... (discrimination coefficient n) x (explanatory variable n) + constant (2)
Therefore, 17 kinds of element groups (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, selected from the result of the test (t test) of the difference between the population average values of the two groups. A discriminant function can be obtained by using the concentration of As, Se, Rb, Sr, Mo, Cs) and the age of the target dog as explanatory variables and using the discriminant coefficient as their weight. The desired discriminant function can be easily obtained by loading the concentration values (concentration data) of these 17 kinds of element groups and the age (age data) of the target dog into a known discriminant analysis program. Gender data may be added to the age data and element concentration data.

For example, if the discrimination value (discrimination score) (D) calculated in this way is 0 or less, the target dog is judged to be in the case group, and if the discrimination value (D) is 0 or more, it is classified as the control group. It is judged to enter.

Next, in order to determine the probability that the target dog will be in the case group or control group, a binomial logistic regression analysis will be performed to determine the incidence. The occurrence rate is given by the following mathematical formula (3) using the discriminant value (D) obtained in the above discriminant analysis.
Occurrence rate = 1 / [1 + exp (-discrimination value)] (3)
Since the incidence rate can be obtained by the mathematical formula (3), the probability that the target dog will be included in the case group can be obtained. In other words, the current risk of developing cancer in the target dog can be known with probability.

As a result of discriminant analysis, discrimination when the above-mentioned 17 elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Cs) are used. It turned out to be the most capable.

The cancer risk assessment method of the present invention includes 17 elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, which have been identified through the pretreatment as described above. Rb, Sr, Mo, Cs) is set as an evaluation element group, and the concentration of these element groups in the serum of the target dog is measured to indicate whether or not the target dog has some kind of cancer. Furthermore, it obtains an index indicating the site of the affected cancer.

In the canine cancer risk assessment method of the present invention, as shown in FIG. 1, first, a serum sample 2 collected from a target dog is placed in a test tube 1, and the serum is stored in an analyzer for analysis. The concentration of a predetermined element group (element group for evaluation) in the inside is measured (step S1). The element group for which the concentration is measured here is the above-mentioned 17 elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Cs). ..

Next, the concentration data of the evaluation element group in the serum obtained in step S1 is applied to a predetermined discriminant function (obtained by discriminant analysis as described above) and calculated (step S2). As a result, a correlation between the concentrations of the evaluation element group can be obtained.

Finally, based on the calculation result (correlation between the concentrations of the evaluation element groups) obtained in step S2, an index as to whether or not the target dog from which the serum sample 2 was collected has some kind of cancer is used. Generate. As a result, a desired evaluation result (index) regarding the cancer risk of the target dog is obtained (step S3).

As described above, in the dog cancer risk evaluation method of the present invention, in step S2 for calculating the correlation, the evaluation element group (Li, Na, Mg, P, S, K,) in the serum collected from the target dog, Concentration data of Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Cs) and age data of the same target dog (and gender data if necessary) are targeted. It is applied to a discriminant function for discriminating whether a dog belongs to a control group or a case group, and the correlation between the concentrations of the evaluation element group in the serum of the target dog is calculated.

Then, in step S3 for acquiring the index, an index as to whether or not the target dog has some kind of cancer is obtained based on the correlation obtained in step S2, and the index is used in step S2. It is generated based on the discrimination score obtained by applying the concentration data and the age data (and gender data if necessary) to the discrimination function.

Therefore, the risk of developing cancer in the target dog can be estimated with high accuracy, and there are no drawbacks such as early degeneration and high cost as in the case of using the amino acid concentration in blood.

In addition, 17 kinds of elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb) used as the evaluation element group in step S2 for calculating the correlation. , Sr, Mo, Cs), which concentration data is significant for discrimination, and the element that is significant for discrimination varies depending on the type of cancer. It is also possible to estimate the existence. Furthermore, it is also possible to estimate the temporal change in the risk of developing cancer by utilizing whether the correlation of the elements that is significant for discrimination is positive or negative.

Furthermore, it is possible to determine whether the target dog belongs to the control group or the case group by automatically calculating with a computer using the concentration data and the age data of the evaluation element group in the serum collected from the target dog. Even if there are a large number of target dogs, it is possible to easily and quickly discriminate. Therefore, it is also suitable as a cancer screening method in a veterinary hospital.

Thus, according to the dog cancer risk assessment method of the present invention, health management of socially beneficial dogs such as pet dogs, police dogs, drug detection dogs, disaster relief dogs, blind guide dogs, assistance dogs, therapy dogs, etc. It is possible to realize the above easily and inexpensively, and moreover, it can be expected to reduce the death of these dogs due to cancer, and has excellent effects.

(Basic configuration of the dog cancer risk assessment system of the present invention)
Next, the dog cancer risk assessment system of the present invention will be described.

The basic configuration of the dog cancer risk assessment system 10 of the present invention is shown in FIG. The dog cancer risk assessment system 10 of the present invention is for carrying out the dog cancer risk assessment method of the present invention described above, and as is clear from FIG. 2, the data storage unit 11 and the discriminant function It includes a generation unit 12 and an evaluation result calculation unit 13.

A serum element group concentration measuring unit 5 is provided outside the dog cancer risk assessment system 10, and a serum sample 2 collected from a target dog placed in a test tube 1 is used in serum. The concentration of the evaluation element group (17 kinds of Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Cs) is measured. The concentration data of the evaluation element group in the serum thus obtained by the serum element group concentration measuring unit 5 is supplied to the data storage unit 11 of the system 10. The data storage unit 11 of the target dog also stores age data (and gender data if necessary). As the serum element group concentration measuring unit 5, for example, a known ICP mass spectrometer is used.

The data storage unit 11 is a portion that stores the concentration data of the evaluation element group obtained by the serum element group concentration measurement unit 5 and the age data, and is usually composed of a known storage device. Is.

The discriminant function generation unit 12 is a part that generates a discriminant function used in the calculation in the evaluation result calculation unit 13, and is usually composed of a personal computer or the like including a known program.

The evaluation result calculation unit 13 performs a calculation by a predetermined method. Based on the calculation result output by the evaluation result calculation unit 13, the desired evaluation result, that is, the cancer risk of the target dog is evaluated.

When the canine cancer risk assessment method of the present invention described above is carried out in the canine cancer risk assessment system 10, for example, the risk of carcinogenesis is calculated by pattern analysis of the concentration of the evaluation element group in the serum. Submit the results that probabilistically express the possibility of cancer based on the risk. Specifically, dog serum (for example, 0.5 cc) collected at the time of medical examination at a veterinary hospital or a laboratory is collected, and a specific evaluation element group (Li, Na, Mg, P, S) is collected at the laboratory. , K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Cs). Then, based on the concentration data of the evaluation element group measured by the inspection institution and the age data of the target dog, an institution such as a risk assessment center (tentative name) calculates the cancer morbidity risk. The calculation result of the cancer risk is sent to the blood collection institution, and the blood collection institution gives it to the owner of the target dog. If cancer is suspected, we recommend that you receive a "current cancer screening" from the blood collection agency. Personal information will be encrypted at the blood collection organization or numbered serially, and the system will not reach the testing organization or risk assessment center.

From the results of Examples 1 to 4 described below, 17 elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu) in the serum of various target dogs shown in FIGS. 5A and 5B. , Zn, As, Se, Rb, Sr, Mo, Cs), age data, and gender data, from liver mass (liver cancer) to ovarian mass (ovarian cancer) shown in FIG. It was clarified that the risk of morbidity of any cancer (all cancers) up to the above and the morbidity risk of each of liver cancer, adrenal cancer, and lung cancer can be calculated. Depending on the discrimination value obtained using the element concentration in serum measured by one blood sampling, not only the risk of all cancers listed in FIG. 6 but also liver cancer, adrenal cancer, and lung cancer are different. As shown in FIGS. 24 and 29 to 32, it is possible to calculate the risk of morbidity at a cancer site because the elements (significant variables) that are significantly related to discrimination differ depending on the cancer site. Because it is. As can be seen from FIGS. 24 and 29 to 32, the only significant item common to all cancers, liver cancers, adrenal cancers and lung cancers is age, and the risk of developing any cancer increases with aging. It is shown. In addition, the effects of 17 elements contained in serum as a group of evaluation elements differ greatly depending on the cancer site, that is, the types of elements that are significant for discrimination and the positive and negative of their correlations differ. It is clear that. This difference makes it possible to estimate individual morbidity risks for liver, adrenal and lung cancers, as well as the morbidity risk for all cancers, and to estimate temporal changes in cancer morbidity risk. To be solved.

Furthermore, from the results of Example 5 described below, 17 elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, It is clear that the risk of morbidity for prostate tumor (prostate cancer) can be calculated using the concentration data of As, Se, Rb, Sr, Mo, Cs) and age data (without using gender data). Was made. Based on the discriminant value obtained using the element concentration in the serum measured by one blood sampling, the risk of all cancers listed in FIG. 6 and the risk of each of liver cancer, adrenal cancer, and lung cancer (Examples). In addition to 1-4), it is possible to calculate the risk of developing prostate cancer as shown in FIGS. 41 and 43, which are elements having a significant relevance to discrimination in prostate cancer. This is because (significant variable) is different from that in liver cancer, adrenal cancer and lung cancer. As can be seen from FIGS. 41 and 43, it has been shown that the risk of developing prostate cancer increases with aging. In addition, the 17 elements contained in the serum as an evaluation element group have a significantly different effect on prostate cancer from those on liver cancer, adrenal cancer and lung cancer, that is, elements that are significant for discrimination. It is clear that the positive and negative of the type and its correlation are different. It is understood that this difference also makes it possible to estimate the risk of morbidity for prostate cancer and to estimate the temporal change in the risk of morbidity.

Throughout Examples 1 to 4 and Example 5, the full age of the target dog was used as it was as the age data. The gender data in Examples 1 to 4 were set as male (male) = 1, female (female) = 2, castrated male and contraceptive female = 3, converted into numerical values.

Hereinafter, the present invention will be described in more detail based on Examples.

First, the dog serum samples used in Examples 1 to 4 below are controlled groups of dogs that are not suffering from cancer or other serious diseases at the time of blood sampling with the cooperation of the hospital treating the animals. A total of 75 dog serum samples were provided by the Mikan Animal Hospital and Yodada Animal Care Center in Kanagawa Prefecture for (control). In addition, we received a total of 297 serum samples of dogs that received cancer treatment from the University of Tokyo Veterinary School and Nihon University Animal Hospital in order to use dogs that received cancer treatment as a case group. Among the serum samples of these case groups, there was one case of unknown age, so excluding that one case, serum samples of 75 cases in the control group and 296 cases in the case group with clear gender and age (total of 371 cases). Was used for cancer risk assessment (see Fig. 3).

The type (breed) and sex of the target dogs to which the serum samples were provided, and the distinction between castrated males and contraceptive females are as shown in FIGS. 5A and 5B. The total number of dogs provided as a control group (control) was 78, and the total number of case groups (cancer-affected dogs) was 297, for a total of 375. However, of the 78 serum samples in the control group (control), 3 serum samples had problems, so 75 serum samples were used for cancer risk assessment. Of the 297 serum samples in the case group (dogs with cancer), one serum sample was excluded because the age was unknown, and 296 serum samples were used for cancer risk assessment. The mean ages and standard deviations of 75 of the control group, 296 of all cancers of the case group, 140 of liver cancer, 69 of adrenal cancer, and 35 of lung cancer are as shown in FIG. is there.

The cancer sites of the dogs in the case group are shown in FIG. 6 together with the sex and the presence or absence of castration / contraception. As is clear from FIG. 6, liver tumor (cancer) was 140 cases, adrenal tumor (cancer) was 69 cases, lung tumor (cancer) was 35 cases, melanoma was 11 cases, and breast cancer was 8 cases. Other cancer types were less than 5 cases. Therefore, in the analysis by cancer site, only three or more tumors, that is, liver tumor (cancer), adrenal tumor (cancer), and lung tumor (cancer) were evaluated. On the other hand, for all cancers in FIG. 6, all 296 case groups were evaluated.

The trace element concentration in the serum sample was measured by using ICP mass spectrometry (ICP-MS) on the pretreated serum sample after the above-mentioned pretreatment with nitric acid. .. The measured trace elements are 17 of Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, and Cs designated as the "element group for evaluation". It is a seed element. Therefore, the sex data and age data of the target dogs were added to the concentration data of these 17 kinds of elements to make a total of 19 variables, and discriminant analysis and binomial logistic regression analysis were performed.

The average value and standard deviation of the concentrations of the 17 kinds of "elements for evaluation" obtained in Examples 1 to 4 described below are summarized in FIG. 7. FIG. 7 is an excerpt and arrangement of the relevant items from the basic statistics of FIGS. 25 to 28.

The dog serum samples used in Example 5 below are the Mikan Animal Hospital and the Animal Care Center mentioned in Examples 1 to 4 in order to be used as a control group (control) in the same manner as in Examples 1 to 4. Received a total of 46 dog serum samples. In addition, in order to form a case group, a total of 48 serum samples of dogs examined for prostate cancer treatment were provided by the Nihon University Animal Hospital mentioned in Examples 1 to 4 (see FIGS. 33 and 35). .. Since there was one case of unknown age among the serum samples of the control group, 45 cases of the control group and 48 cases of the case group with clear gender and age were selected (total 93 cases). , Used for risk assessment of prostate cancer (see FIG. 34). The type of target dog (breed) to which the serum sample was provided and the distinction between male and castrated male are as shown in FIG. 35. The mean ages of 45 animals in the control group and 48 animals in the case group and their standard deviations are as shown in FIG. 34.

In Example 5, the method for measuring the trace element concentration in the serum sample and the "element group for evaluation" used were the same as those used in Examples 1 to 4. In addition, discriminant analysis and binomial logistic regression analysis were performed with a total of 18 variables by adding the age data of the target dogs to the concentration data of 17 kinds of elements as the "element group for evaluation". No gender data was used.

The average value and standard deviation of the concentrations of the 17 kinds of "elements for evaluation" obtained in Example 5 described below are summarized in FIG. 36. FIG. 36 is an excerpt of the relevant items from the basic statistics of FIG. 42 and arranged.

In Example 1, the risk of developing cancer for all cancers (all cancers shown in FIG. 6) was estimated. As shown in FIG. 6, the target dogs for which the risk of developing cancer is estimated in Example 1 are 296 cases in the case group and 75 cases in the control group (control), and a total of 371 serum samples are evaluated. used. The data used for the evaluation were the age data of the target dog, the sex data, and the 17 elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu) used as the evaluation element group. , Zn, As, Se, Rb, Sr, Mo, Cs). The measurement results of the obtained element concentration are as shown in FIGS. 7 and 25.

The discriminant used for the discriminant analysis of all cancers is shown in FIG. Further, the discriminant result obtained by using the discriminant is shown in FIG. According to the discrimination result of FIG. 8, 269 cases out of 296 cases in the case group were hit (sensitivity = 90.9%), and 64 cases out of 75 cases were hit in the control group (specificity). = 85.3%). Therefore, the correct diagnosis rate was 89.76%, which was a high value.

When the area under the ROC curve (AUC) obtained from the discriminant analysis was obtained, a high value of 0.942 was obtained as shown in FIG.

From these results, 17 kinds of trace elements (elements for evaluation) (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, The discrimination score is calculated by inputting the concentration data of Mo, Cs) and the age data and sex data of the target dog into the discrimination formula of FIG. 9, and the discrimination score is used to calculate the risk of all cancer (probability). ) Was calculated. The result is shown in FIG.

As can be seen from FIG. 11, in the case of all cancers, the larger the negative value of the discrimination score, the higher the risk, and if the discrimination score is approximately -2.0 or less, the risk of developing all cancers is 90%. It can be evaluated (estimated) with the above probability.

Therefore, for a new serum sample, 17 kinds of trace elements (Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb) as an element group for evaluation in the new serum sample. , Sr, Mo, Cs), and the age data and gender data of the target dog are input to the discrimination formula of FIG. 9 to calculate the discrimination score, and the discrimination score is used to obtain a new discrimination score. For serum samples, it is possible to calculate the risk (probability) of all cancers.

The basic statistics used in Example 1 are as shown in FIG. 25, and the variables included in the discriminant function are as shown in FIG. 29.

In the cancer risk assessment for all cancers, as shown in FIGS. 24 and 29, in addition to the age data, the concentration data of the four elements Mg, S, Cu, and Se are significant for discrimination. Do you get it. In addition, the concentration data of the Mg element has a negative correlation, and the concentration data of the three elements S, Cu, and Se have a positive correlation, and the degree of the relationship is higher in Mg than in S, Cu, and Se. It turned out to be strong. Therefore, when the concentration data of Mg element increases (or decreases) with the passage of time, the risk that the target dog has some kind of cancer tends to decrease (or increase), and S, Cu, When the concentration data of at least one of the three elements of Se rises (or falls) over time, the risk that the target dog has some kind of cancer tends to increase (or decrease). Speculation could be added to the assessment of cancer risk. In this example, in addition to the evaluation of the cancer risk of the target dog, there is an advantage that the estimation of the temporal change can be further presented.

In Example 2, the risk of developing cancer for liver cancer was estimated. As shown in FIG. 6, the target dogs for which the risk of developing cancer is estimated in Example 2 are 140 cases in the case group and 75 cases in the control group (control), and a total of 215 serum samples are evaluated. used. The data used for the evaluation were the age data of the target dog, the sex data, and the concentration data of 17 kinds of elements used as the evaluation element group in Example 1. The measurement results of the obtained element concentration are as shown in FIGS. 7 and 26.

The discriminant used for the discriminant analysis of liver cancer is shown in FIG. Moreover, the discriminant result obtained by using the discriminant is shown in FIG. According to the discrimination result of FIG. 12, 127 out of 140 cases in the case group were hit (sensitivity = 90.7%), and 63 out of 75 cases were hit in the control group (specificity). = 84.0%). Therefore, the correct diagnosis rate was 88.37%, which was a high value.

When the area under the ROC curve (AUC) obtained from the discriminant analysis was obtained, a high value of 0.961 was obtained as shown in FIG.

From these results, the concentration data of 17 kinds of trace elements (elements for evaluation) (same as those used in Example 1) in the serum and the age data and sex data of the target dog were discriminated in FIG. The discrimination score was calculated by inputting into the formula, and the risk (probability) of liver cancer was calculated using the discrimination score. The result is shown in FIG. The cancer probability curve in FIG. 15 has the opposite positive and negative directions as in the case of all cancers.

As can be seen from FIG. 15, in the case of liver cancer, the larger the positive value of the discrimination score, the higher the risk, and if the discrimination score is about 3.0 or more, the risk of developing liver cancer is 90% or more. It can be evaluated (estimated) as the probability of.

Therefore, for the new serum sample, the concentration data of 17 kinds of trace elements (same as those used in Example 1) as the evaluation element group in the new serum sample, and the age data and sex data of the target dog are shown in the figure. If the discrimination score is calculated by inputting it into the discrimination formula of 13, it is possible to calculate the risk (probability) of liver cancer for the new serum sample by using the discrimination score.

The basic statistics used in Example 2 are as shown in FIG. 26, and the variables included in the discriminant function are as shown in FIG.

In the cancer risk assessment for liver cancer, as shown in FIGS. 24 and 30, in addition to the age data, the concentration data of the two elements Fe and Cu are significant for discrimination, and are significant in Example 1. It was found that it was different from the four elements of Mg, S, Cu, and Se that were judged to be. This is among the 17 kinds of the elements used as the evaluation element group based on the correlation between the concentrations of the evaluation element group calculated in the correlation calculation step (step S2 in FIG. 1). If the concentration data of the two elements Fe and Cu selected from the above are judged to be significant for discrimination, it is possible to infer that the type (site) of cancer related to the target dog is "liver cancer". Was understood to mean. Further, it was found that the concentration data of the Fe element had a negative correlation and the concentration data of the Cu element had a positive correlation, and the degree of the relationship was stronger in Cu than in Fe. Therefore, when the Fe element concentration data increases (or decreases) with the passage of time, the risk of the target dog suffering from liver cancer tends to decrease (or increase), and the Cu element concentration tends to increase. As the data rises (or falls) over time, it is speculated that the target dog is at an increasing (or decreasing) risk of developing liver cancer. I was able to add it to the evaluation. In this example, in addition to the evaluation of the liver cancer morbidity risk of the target dog, it is possible to further present an estimate of the temporal change of the morbidity risk.

In Example 3, the risk of developing cancer for adrenal cancer was estimated. As shown in FIG. 6, the target dogs for which the risk of developing cancer is estimated in this example are 69 cases in the case group and 75 cases in the control group (control), and a total of 144 serum samples were used as evaluation targets. did. The data used for the evaluation were the age data of the target dog, the sex data, and the concentration data of 17 kinds of elements (same as those used in Example 1) used as the element group for evaluation. The measurement results are as shown in FIG.

The discriminant used for the discriminant analysis of adrenal cancer is shown in FIG. Moreover, the discriminant result obtained by using the discriminant is shown in FIG. According to the discrimination result of FIG. 16, 64 out of 69 cases in the case group were hit (sensitivity = 92.8%), and 68 out of 75 cases were hit in the control group (specificity). = 90.7%). Therefore, the correct diagnosis rate was 91.67%, which was a high value.

When the area under the ROC curve (AUC) obtained from the discriminant analysis was obtained, a high value of 0.965 was obtained as shown in FIG.

From these results, the concentration data of 17 kinds of trace elements (elements for evaluation) (same as those used in Example 1) in the serum and the age data and sex data of the target dog were discriminated in FIG. The discrimination score was calculated by inputting into the formula, and the risk (probability) of adrenal cancer was calculated using the discrimination score. The result is shown in FIG. The cancer probability curve in FIG. 19 is also positive and negative as opposed to the case of all cancers.

As can be seen from FIG. 19, in the case of adrenal cancer, the higher the positive value of the discrimination score, the higher the risk, and if the discrimination score is approximately 3.0 or higher, the risk of developing adrenal cancer is 95% or higher. It can be evaluated (estimated) as the probability of.

Therefore, for the new serum sample, the concentration data of 17 kinds of trace elements (same as those used in Example 1) as the evaluation element group in the new serum sample, and the age data and sex data of the target dog are shown in the figure. If the discrimination score is calculated by inputting it into the discrimination formula of 17, it is possible to calculate the risk (probability) of adrenal cancer for the new serum sample using the discrimination score.

The basic statistics used in Example 3 are as shown in FIG. 27, and the variables included in the discriminant function are as shown in FIG. 31.

In the cancer morbidity risk assessment for adrenal cancer, as shown in FIGS. 24 and 31, in addition to age data, concentration data of seven elements of Mg, P, S, Co, Zn, As, and Se are discriminated. It was found that the four elements of Mg, S, Cu and Se, which were judged to be significant in Example 1, and the two elements of Fe and Cu, which were judged to be significant in Example 2, were different from each other. This is among the 17 kinds of the elements used as the evaluation element group based on the correlation between the concentrations of the evaluation element group calculated in the correlation calculation step (step S2 in FIG. 1). When the concentration data of the seven elements of Mg, P, S, Co, Zn, As, and Se selected from the above are judged to be significant for discrimination, the type (site) of cancer related to the target dog is "adrenal cancer". It was understood that it meant that it was possible to speculate that. It was also found that the concentration data of the three elements Mg, Zn, and As had a negative correlation, and the degree of the relationship was stronger in Zn and As than in Mg. Furthermore, it was found that the concentration data of the four elements P, S, Co, and Se had a positive correlation, and the degree of the relationship was stronger in P than in S, Co, and Se. Therefore, if the concentration data of at least one of the three elements Mg, Zn, and As increases (or decreases) over time, the risk of the target dog suffering from adrenal cancer tends to decrease (or increase). If the concentration data of at least one of the four elements P, S, Co, and Se rises (or falls) over time, there is a risk that the target dog will have adrenal cancer. The speculation that it is on the rise (or on the decline) could be added to the assessment of the risk of developing adrenal gland cancer. In this example, in addition to the evaluation of the adrenal cancer morbidity risk of the target dog, it is possible to further present an estimate of the temporal change in the morbidity risk.

In Example 4, the risk of developing cancer for lung cancer was estimated. As shown in FIG. 6, the target dogs for which the risk of developing cancer is estimated in this example are 35 cases in the case group and 75 cases in the control group (control), and a total of 110 serum samples were used as evaluation targets. did. The data used for the evaluation were the age data of the target dog, the sex data, and the concentration data of 17 kinds of elements (same as those used in Example 1) used as the element group for evaluation. The measurement results are as shown in FIG.

The discriminant used for the discriminant analysis of lung cancer is shown in FIG. Moreover, the discriminant result obtained by using the discriminant is shown in FIG. According to the discrimination result of FIG. 20, 34 out of 35 cases in the case group were hit (sensitivity = 97.1%), and 71 out of 75 cases were hit in the control group (specificity). = 94.7%). Therefore, the correct diagnosis rate was 95.45%, which was a high value.

When the area under the ROC curve (AUC) obtained from the discriminant analysis was obtained, as shown in FIG. 22, a high value of 0.989 was obtained.

From these results, the concentration data of 17 kinds of trace elements (elements for evaluation) (same as those used in Example 1) in the serum and the age data and sex data of the target dog were discriminated in FIG. 21. The discrimination score was calculated by inputting into the formula, and the risk (probability) of lung cancer was calculated using the discrimination score. The result is shown in FIG. The cancer probability curve in FIG. 23 is also positive and negative as opposed to the case of all cancers.

As can be seen from FIG. 23, in the case of lung cancer, the larger the positive value of the discrimination score, the higher the risk, and if the discrimination score is about 2.0 or more, the probability of developing lung cancer is 90% or more. Can be evaluated (estimated).
Noh.

Therefore, for the new serum sample, the concentration data of 17 kinds of trace elements (same as those used in Example 1) as the evaluation element group in the new serum sample, and the age data and sex data of the target dog are shown in the figure. If the discriminant score is calculated by inputting it into the discriminant of 21, it is possible to calculate the risk (probability) of lung cancer for the new serum sample using the discriminant score.

The basic statistics used in Example 4 are as shown in FIG. 28, and the variables included in the discriminant function are as shown in FIG. 32.

In the cancer morbidity risk assessment for lung cancer, as shown in FIGS. 24 and 32, in addition to the age data, the concentration data of the four elements Na, Mg, As, and Sr are significant for discrimination, and Example 1 The four elements of Mg, S, Cu, and Se judged to be significant, the two elements of Fe and Cu judged to be significant in Example 2, and Mg, P, S, judged to be significant in Example 3. It was found that it was different from the seven elements of Co, Zn, As, and Se. This is among the 17 kinds of the elements used as the evaluation element group based on the correlation between the concentrations of the evaluation element group calculated in the correlation calculation step (step S2 in FIG. 1). If the concentration data of the four elements Na, Mg, As, and Sr selected from the above are judged to be significant for discrimination, it is possible to infer that the type (site) of cancer related to the target dog is "lung cancer". It was understood that it meant to be. It was also found that the concentration data of the two elements Mg and As have a negative correlation, and the degree of the relationship is stronger in As than in Mg. Furthermore, it was found that the concentration data of the two elements Na and Sr had a positive correlation, and the degree of the relationship was stronger in Na than in Sr. Therefore, when the concentration data of at least one of the two elements Mg and As rises (or falls) over time, the risk of the target dog suffering from lung cancer tends to decrease (or increase). When the concentration data of at least one of the two elements, Na and Sr, rises (or falls) over time, the risk of the target dog suffering from lung cancer tends to increase (or decrease). Was able to be added to the assessment of lung cancer risk. In this example, in addition to the evaluation of the lung cancer morbidity risk of the target dog, it is possible to further present an estimate of the temporal change of the morbidity risk.

In Example 5, the risk of developing cancer for prostate cancer was estimated. As shown in FIG. 34, the target dogs for which the risk of developing cancer is estimated in this example are 48 cases in the case group and 45 cases in the control group (control), and a total of 93 serum samples were used as evaluation targets. did. The data used for the evaluation were the age data of the target dog and the concentration data of 17 kinds of elements (same as those used in Example 1) used as the element group for evaluation. The measurement results are as shown in FIG.

The discriminant used for the discriminant analysis of prostate cancer is shown in FIG. Further, the discriminant result obtained by using the discriminant is shown in FIG. 37. According to the discrimination result of FIG. 37, 47 out of 48 cases in the case group were hit (sensitivity = 97.9%), and 43 out of 45 cases were hit in the control group (specificity). = 95.5%). Therefore, the correct diagnosis rate was 96.77%, which was a high value.

When the area under the ROC curve (AUC) obtained from the discriminant analysis was obtained, as shown in FIG. 39, a high value of 0.993 was obtained.

Based on these results, the concentration data of 17 trace elements (elements for evaluation) (same as those used in Example 1) in the serum and the age data of the target dogs were input to the discriminant of FIG. 38. The discriminant score was calculated by the above, and the risk (probability) of prostate cancer was calculated using the discriminant score. The result is shown in FIG. The cancer probability curve in FIG. 40 is also positive and negative as opposed to the case of all cancers.

As can be seen from FIG. 40, in the case of prostate cancer, the larger the positive value of the discrimination score, the higher the risk. It can be evaluated (estimated) as the probability of.
Noh.

Therefore, for the new serum sample, the concentration data of 17 trace elements (same as those used in Example 1) as the evaluation element group in the new serum sample and the age data of the target dog (gender data is not available). (Use), if the discrimination score is calculated by inputting it into the discrimination formula of FIG. 38, it is possible to calculate the risk (probability) of prostate cancer for the new serum sample using the discrimination score. is there.

The basic statistics used in Example 5 are as shown in FIG. 42, and the variables included in the discriminant function are as shown in FIG. 43.

In the cancer morbidity risk assessment for prostate cancer, as shown in FIGS. 41 and 43, in addition to the age data, the concentration data of the three elements Na, K, and Cu are significant for discrimination, and Example 1 The four elements of Mg, S, Cu, and Se judged to be significant in Example 2, the two elements of Fe and Cu judged to be significant in Example 2, and Mg, P, S, Co, which were judged to be significant in Example 3. It was found that the seven elements of Zn, As, and Se were different from the four elements of Na, Mg, As, and Sr, which were judged to be significant in Example 4. This is among the 17 kinds of the elements used as the evaluation element group based on the correlation between the concentrations of the evaluation element group calculated in the correlation calculation step (step S2 in FIG. 1). If the concentration data of the three elements Na, K, and Cu selected from the above are judged to be significant for discrimination, it is possible to infer that the type (site) of cancer related to the target dog is "prostatic cancer". It was understood that it meant to be. It was also found that the concentration data of K element had a negative correlation. Furthermore, it was found that the concentration data of the two elements Na and Cu had a positive correlation, and the degree of the relationship was stronger in Cu than in Na. Therefore, when the concentration data of K element increases (or decreases) with the passage of time, the risk of the target dog suffering from prostate cancer tends to increase (or decrease), and Na, Cu It is speculated that if the concentration data of at least one of the two elements rises (or falls) over time, the target dog is at an increasing (or decreasing) risk of developing prostate cancer. , Could be added to the assessment of prostate cancer risk. In this example, in addition to the evaluation of the prostate cancer morbidity risk of the target dog, it is possible to further present an estimate of the temporal change in the morbidity risk.

The present invention quickly and easily estimates the risk (presence or absence) of cancer in socially beneficial dogs such as pet dogs, police dogs, drug detection dogs, disaster relief dogs, guide dogs, assistance dogs, and therapy dogs. Is widely applicable to the desired field.

1 Test tube 2 Serum sample 5 Serum element group concentration measurement unit 10 Dog cancer risk assessment system 11 Data storage unit 12 Discrimination function generation unit 13 Evaluation result calculation unit

Claims (36)

The concentration data of the evaluation element group in the serum collected from the target dog and the age data of the target dog are applied to a discriminant function for discriminating whether the target dog belongs to the control group or the case group. Then, a correlation calculation step for calculating the correlation between the concentrations of the evaluation element group in the serum, and
Based on the correlation calculated in the correlation calculation step, an index acquisition step for obtaining an index as to whether or not the target dog has some kind of cancer is provided.
In the correlation calculation step, 17 kinds of elements for evaluation, Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo, and Cs, are used. A combination of elements is used,
The index acquisition step is characterized in that the index is generated based on a discrimination score calculated by applying the concentration data and the age data to the discrimination function used in the correlation calculation step. How to assess the risk of cancer in dogs. It is presumed that the target dog has some kind of cancer depending on which of the 17 concentration data of the 17 elements used as the evaluation element group is significant for discrimination. The dog cancer risk assessment method according to claim 1, wherein the method is performed. Depending on whether or not the concentration data of the four elements Mg, S, Cu, and Se selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination, the target dog is something. The method for assessing a dog's cancer risk according to claim 1, wherein it is presumed that the patient has cancer. When the concentration data of the Mg element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing cancer in the target dog tends to decrease or The dog cancer risk assessment method according to claim 3, wherein it is presumed that the number is increasing. When the concentration data of at least one of the three elements S, Cu, and Se selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the target dog The canine cancer risk assessment method according to claim 3, wherein it is presumed that the risk of developing cancer in dogs is increasing or decreasing. With the presumption that the target dog has cancer, depending on which of the 17 concentration data of the 17 elements used as the evaluation element group is significant for discrimination. The canine cancer risk assessment method according to claim 1, wherein the cancer site is also estimated. The target dog has liver cancer depending on whether or not the concentration data of the two elements Fe and Cu selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination. The method for assessing the cancer risk of a dog according to claim 1 or 6, wherein it is presumed to be affected by the disease. When the concentration data of the Fe element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing liver cancer in the target dog decreases. The method for assessing cancer risk in dogs according to claim 7, wherein it is presumed that there is a tendency or an increasing tendency. When the concentration data of the Cu element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing liver cancer in the target dog increases. The canine cancer risk assessment method according to claim 7, wherein it is presumed that there is a tendency or a decreasing tendency. Depending on whether or not the concentration data of the seven elements of Mg, P, S, Co, Zn, As, and Se selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination. The dog cancer risk assessment method according to claim 1 or 6, wherein it is presumed that the target dog has adrenal cancer. When the concentration data of at least one of the three elements Mg, Zn, and As selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the target dog The canine cancer risk assessment method according to claim 10, wherein it is presumed that the risk of developing adrenal gland cancer is decreasing or increasing. When the concentration data of at least one of the four elements P, S, Co, and Se selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the said The dog cancer risk assessment method according to claim 10, wherein it is presumed that the risk of developing adrenal gland cancer in the target dog is increasing or decreasing. Depending on whether or not the concentration data of the four elements Na, Mg, As, and Sr selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination, the target dog The method for assessing cancer risk in dogs according to claim 1 or 6, wherein it is presumed that the patient has lung cancer. When the concentration data of at least one of two elements of Mg and As selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, lung cancer of the target dog The canine cancer risk assessment method according to claim 13, wherein it is presumed that the risk of morbidity is decreasing or increasing. When the concentration data of at least one of the two elements Na and Sr selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, lung cancer of the target dog The method for assessing cancer risk in dogs according to claim 13, wherein it is presumed that the risk of morbidity is increasing or decreasing. Depending on whether or not the concentration data of the three elements Na, K, and Cu selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination, the target dog has a prostate cancer. The method for assessing the cancer risk of a dog according to claim 1 or 6, wherein it is presumed that the patient is suffering from cancer. When the concentration data of K element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing prostate cancer in the target dog tends to decrease. Or the cancer risk assessment method for dogs according to claim 16, wherein it is presumed that the number is increasing. When the concentration data of at least one of the two elements Na and Cu selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the prostate of the target dog The method for assessing cancer risk in dogs according to claim 16, wherein it is presumed that the risk of developing cancer is increasing or decreasing. A data storage unit that stores the concentration data of the evaluation element group in the serum collected from the target dog and the age data of the target dog.
A discriminant function generator that generates a discriminant function for discriminating whether the target dog belongs to the control group or the case group, and
The concentration data of the target dog and the age data stored in the data storage unit are applied to the discrimination function generated by the discrimination function generation unit to correlate the concentration of the evaluation element group in the serum. It is provided with an evaluation result calculation unit that calculates the relationship and outputs the evaluation result of whether or not the target dog has some kind of cancer based on the correlation.
As the evaluation element group, a combination of 17 kinds of elements of Li, Na, Mg, P, S, K, Ca, Fe, Co, Cu, Zn, As, Se, Rb, Sr, Mo and Cs is used. ,
In the evaluation result calculation unit, a discrimination score is calculated by applying the density data and the age data stored in the data storage unit to the discrimination function generated by the discrimination function generation unit, and the discrimination score is used as the discrimination score. A canine cancer risk assessment system, characterized in that the assessment results are generated based on the above. It is presumed that the target dog has some kind of cancer depending on which of the 17 concentration data of the 17 elements used as the evaluation element group is significant for discrimination. The dog cancer risk assessment system according to claim 19. Depending on whether or not the concentration data of the four elements Mg, S, Cu, and Se selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination, the target dog is something. The canine cancer risk assessment system according to claim 19, wherein it is presumed to have cancer. When the concentration data of the Mg element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing cancer in the target dog tends to decrease or The dog cancer risk assessment system according to claim 21, wherein it is presumed to be on the increase. When the concentration data of at least one of the three elements S, Cu, and Se selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the target dog The canine cancer risk assessment system according to claim 21, wherein it is presumed that the risk of developing cancer is increasing or decreasing. With the presumption that the target dog has cancer, depending on which of the 17 concentration data of the 17 elements used as the evaluation element group is significant for discrimination. The canine cancer risk assessment system according to claim 19, wherein the cancer site is also estimated. Depending on whether or not the concentration data of the two elements Fe and Cu selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination, the target dog develops liver cancer. The canine cancer risk assessment system according to claim 19 or 24, wherein it is presumed to be affected. When the concentration data of the Fe element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing liver cancer in the target dog decreases. The canine cancer risk assessment system according to claim 25, wherein it is presumed to be trending or increasing. When the concentration data of the Cu element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing liver cancer in the target dog increases. The canine cancer risk assessment system according to claim 25, wherein it is presumed to be trending or decreasing. Depending on whether or not the concentration data of the seven elements of Mg, P, S, Co, Zn, As, and Se selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination. The canine cancer risk assessment system according to claim 19 or 24, wherein it is presumed that the target dog has adrenal cancer. When the concentration data of at least one of the three elements Mg, Zn, and As selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the target dog 28. The canine cancer risk assessment system according to claim 28, wherein it is presumed that the risk of developing adrenal cancer is decreasing or increasing. When the concentration data of at least one of the four elements P, S, Co, and Se selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the said The canine cancer risk assessment system according to claim 28, wherein it is estimated that the risk of developing adrenal gland cancer in the target dog is increasing or decreasing. Depending on whether or not the concentration data of the four elements Na, Mg, As, and Sr selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination, the target dog The canine cancer risk assessment system according to claim 19 or 24, wherein it is presumed to have lung cancer. When the concentration data of at least one of two elements of Mg and As selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, lung cancer of the target dog The canine cancer risk assessment system according to claim 31, wherein it is presumed that the risk of morbidity is decreasing or increasing. Lung cancer in the target dog when the concentration data of at least one of the two elements Na and Sr selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time. The canine cancer risk assessment system according to claim 31, wherein it is presumed that the risk of morbidity is increasing or decreasing. Depending on whether or not the concentration data of the three elements Na, K, and Cu selected from the 17 kinds of the elements used as the evaluation element group are significant for discrimination, the target dog has a prostate cancer. The canine cancer risk assessment system according to claim 19 or 24, wherein it is presumed to be affected by cancer. When the concentration data of K element selected from the 17 kinds of the elements used as the evaluation element group increases or decreases with the passage of time, the risk of developing prostate cancer in the target dog tends to decrease. Or the canine cancer risk assessment system according to claim 34, wherein it is presumed to be on the rise. When the concentration data of at least one of the two elements Na and Cu selected from the 17 kinds of the elements used as the evaluation element group rises or falls with the passage of time, the prostate of the target dog The canine cancer risk assessment system according to claim 34, wherein it is presumed that the risk of developing cancer is increasing or decreasing.

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