JP5562209B2  Subject registration method for observational or epidemiological studies of pharmaceuticals  Google Patents
Subject registration method for observational or epidemiological studies of pharmaceuticals Download PDFInfo
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 JP5562209B2 JP5562209B2 JP2010245655A JP2010245655A JP5562209B2 JP 5562209 B2 JP5562209 B2 JP 5562209B2 JP 2010245655 A JP2010245655 A JP 2010245655A JP 2010245655 A JP2010245655 A JP 2010245655A JP 5562209 B2 JP5562209 B2 JP 5562209B2
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The present invention relates to a method and system for classifying and registering patients as subjects for pharmaceutical observational or epidemiological studies.
A clinical trial is conducted with patients as subjects in the application for approval of a new drug. In this clinical trial, subjects who can be subjects are randomly or randomly assigned to groups (hereinafter referred to as comparative groups) composed of factors that are thought to have an impact on prognosis (hereinafter referred to as comparative factors). wear. And a comparison object factor is evaluated by comparing the result of prognosis between the assigned comparison groups. Here, the comparison target factors are, for example, the presence or absence of a new treatment method, the conventional treatment method and the new treatment method, the conventional prevention method and the new prevention method, and the assignment is a method for identifying a subject based on a predetermined rule. Refers to belonging to a group (intervention) or its work. The assignment is performed so that the subject's background factor is uniform among the comparison groups.
A pharmaceutical product that has been approved for manufacture through clinical trials and the like as described above is subjected to observational research by the manufacturer after manufacture and sale. In observational studies, the effectiveness and safety of pharmaceuticals are confirmed by collecting subject information under routine medical care without intervention as in clinical trials. The purpose is to collect and provide information on
Observational studies are also conducted when clinical trials involving interventions are not possible due to cost and ethical considerations. In the observational study, the assignment of the subject to a specific group is not performed (no intervention), and the comparison target factor is determined by the doctor's judgment according to the subject's condition. The background factor is biased among the selected groups (hereinafter referred to as comparative groups). For this reason, there is a problem that the absence of intervention makes it difficult to compare information on the factors to be compared.
The purpose of the present invention is to calculate the balance between comparison groups with respect to background factors that are considered to have an effect on efficacy and safety when enrolling subjects in observational studies or epidemiological studies of pharmaceuticals as described above. It is to provide a method for improving the comparability of a comparison population by minimizing the imbalance between comparison groups.
In addition, by registering in the comparison group composed of the abovementioned comparison target factors, it is possible to reduce the bias of the background factors of the subjects among the comparison groups and improve the comparability of the comparison group. It is to provide a registration system that can obtain accurate information about the system.
The present invention is used as a method for controlling registration so as to eliminate bias in the distribution of background factors among comparative populations in observational or epidemiological studies, in order to confirm the safety and efficacy of pharmaceuticals.
Hereinafter, the procedure for registering the subject to be investigated will be described. The meanings of the terms used here are as follows.
(1) Factor to be compared and registration adjustment factor In the present invention, the factor to be compared is one to be compared in observational research or epidemiological research among factors held by the subject. We will investigate whether or not the effects of treatment, side effects, etc. will change due to the difference in factors, and if so, how much the change will be.
Factors to be compared include genetic polymorphisms, preferences, preexisting diseases, complications, exercise frequency, educational history, etc. of the subject, but may be appropriately set according to the purpose of observational research or epidemiological research, and are not limited thereto.
In addition, factors that are considered to have a clinical effect on the abovementioned comparison target factors are referred to as registration adjustment factors, and include gender, age, genotype, patient status, cancer metastasis status, presence / absence / type of pretreatment, and the like. The registration adjustment factor may be appropriately set according to the purpose of the observational study or epidemiological study and the comparison target factor, and is not limited thereto.
(2) Adjustment of Comparison Target Factor and Registration Adjustment Factor and Determination of Probability In the present invention, subjects are classified for each comparison target factor. At the time of classification, the level is recorded for the background information of the subject. The level is set for each registration adjustment factor, and is a sign for classifying the subject's characteristics for each registration adjustment factor. For example, when the registration adjustment factor is “gender”, the levels are set as male 1 and female 2. In this case, if the newly registered subject is male, “sex” is recorded as “1”.
Based on the sum of the number of subjects belonging to the same level and the comparison target factors for each of the registration adjustment factors of subjects already registered separately for each level, set the probability of transferring the subject to the main registration, and according to the probability Register in the comparison group.
Here, the “probability” may be appropriately determined according to the accuracy and purpose required in the research, such as to what extent the deviation of the registration adjustment factor between the comparison groups is tolerated.
(3) Registration Procedure The present invention is applicable to a plurality of comparison groups. First, consider a case where two groups are compared and evaluated. In this case, the comparison target factors are described as two, A and B.
As shown in FIG. 1, first, subject subjects are screened (STEP 1), the subject is explained to the study, and consent is obtained (STEP 2). Next, subjects are classified according to comparison target factors A and B (STEP 3). All subjects of A are registered (STEP 5).
On the other hand, when registering B, the following is adopted (STEP 4), thereby dynamically changing the factors such as the patient background (registration adjustment factor) between A and B at that time. (Variable with time). Such a registration procedure is referred to as “dynamic registration”.
Note that the registration adjustment factor approximates between A and B means that the registration adjustment factor level distribution (frequency distribution) in the group of subjects classified as A and the registration in the group of subjects classified as B This means that the level distribution of the adjustment factor (frequency distribution) is approximate. For example, when the registration adjustment factor is “sex”, the distribution of the “sex” level in the group of subjects classified as A, that is, the ratio between the number of men and the number of women, and the subjects classified as B This means that the ratio of the number of males and the number of females in the group is close.
In detail, based on the probability set as follows in the method of the present invention, it is determined whether or not it is adopted (whether or not this registration is possible) (STEP 4). If “No”, the subject is not participating (STEP 6). ), “Registration” (STEP 5) is made when “adopted”. The subject thus registered (mainly registered) is followed for the course of subsequent treatments (STEP 7). On the other hand, subjects who are not selected in STEP 4 are excluded from the scope of this survey, and are not followed up.
For each registration adjustment factor of the already registered subjects, Sa is the sum of the number of subjects of the comparison target factor A belonging to the same level as the subjects to be newly incorporated into the group of subjects of the comparison target factor B, and similarly B The number of subjects is Sb, the number of subjects registered in A and B (target registered cases) is ca and cb, and Xi (i = 1, 2,..., N) is the group of comparison factors A and B. As a section value indicating the degree of balance between the groups (comparison groups), n constants set in advance such that X1>X2>...>Xn> 0 are set, and Yi (i = 1, 2,..., N ) Is set to n constants (registration probabilities) set in advance such that 100 ≧ Y1>Y2>...>Yn> 0,
In B, the probability is Yi [%] when Xi × S1 ≦ (c1 / c2) × S2 for any i, for example, and 0 [%] otherwise (not registered). , 100 [%] (all registrations). That is, the registration of the subject is executed on the basis of the degree of balance between the groups of comparison target factors (between comparison groups) of the already registered subjects and the registration probability associated therewith. For example, n = 3, X1 = 1, X2 = 0.9, X3 = 0.8, Y1 = 100, Y2 = 10, Y3 = 5. (1.0, 1.00.9, 0.90.8, 0.8), the probabilities assigned to each section are 100%, 10%, 5%, and 0%, respectively. The addition of the selection condition of B and the selection probability, or the number of types of selection probability can be changed. Further, Sa and Sb may be not only the number of subjects but also the ratio of the number of subjects of the comparison target factors A and B belonging to the same level as the subject to be newly incorporated with respect to the number of subjects already registered.
Next, when there are three groups, it is as follows.
Among the plurality of groups, the total number of subjects in the first group is S1, the total number of subjects in the second group is S2, and the total number of subjects in the third group is S3. The number of subjects to be registered is c1, c2, c3, respectively, and Xi (i = 1, 2,..., N) is set as a segment value indicating the degree of balance between groups of comparison target factors (between comparison groups), X1> N constants set in advance so that X2>...>Xn> 0 are satisfied, and Yi (i = 1, 2,..., N) is set such that 100 ≧ Y1>Y2>...>Yn> 0. When n constants (registration probabilities) set in advance are set,
In the third group, for example, the probability is Yi [%] when Xi × S1 ≦ (c1 / c3) × S3 for any i, and 0 [%] otherwise.
In the second group, Yi [%] when Xi × S2 ≦ (c2 / c1) × S1 for any i, and 0 [%] otherwise, and in the third group, 100%. Xi and Yi may be set to different values in the second and third groups.
According to the present invention, as described above, among the subjects already registered in each group, the total number of subjects at the same level as the subjects temporarily registered for each of the registration adjustment factors, and subjects registered in each group Based on the number of subjects, the probability of transitioning temporarily registered subjects to full registration was set, and according to the probability, the temporarily registered subjects were registered in the corresponding group. The bias of factors such as the above becomes smaller, and accurate information on the comparison target factors can be obtained.
According to the present invention, there is also provided a computer program for causing a computer to execute a registration process for registering a subject for medical observational research or epidemiological research. This is characterized by having the computer execute all the steps described above.
Furthermore, according to the present invention, the subject registration system for registering subjects for medical observation research or epidemiological research sets a comparison group divided by the level of the comparison target factor, and subjects belonging to each of the groups, A storage device that records a plurality of predetermined registration adjustment factors together with the level of the subject, a total number of subjects belonging to the same level of each registration adjustment factor among subjects already registered in each group, and in each group And a registration processing device for setting a probability of transitioning temporarily registered subjects to main registration based on the number of subjects to be registered, and registering the temporarily registered subjects in the corresponding group according to the probability. Features.
Further, in the subject registration system, the sum of the number of subjects in the first group among the plurality of comparison groups is S1, and the sum of the number of subjects in the second group is S2, and the first and second groups The number of subjects to be registered in C1 is c1, c2, and Xi (i = 1, 2,..., N) is set as a segment value indicating the degree of balance between groups of comparison target factors (between comparison groups). ……>Xn> 0 constants set in advance so that Xn> 0, and Yi (i = 1, 2,..., N) is set in advance so that 100 ≧ Y1>Y2>……>Yn> 0. When n constants (registration probabilities) are set,
The registration processing apparatus determines the probability as Yi [%] when Xi × S1 ≦ (c1 / c2) × S2 for any i in the first group, and 0 [%] otherwise. And the second group includes means for setting to 100 [%].
Alternatively, in the subject registration system, the sum of the number of subjects in the first group among the plurality of comparison groups is S1, the sum of the number of subjects in the second group is S2, and the number of subjects in the third group is The sum is S3, the number of subjects to be registered in the three groups is c1, c2, c3, and Xi (i = 1, 2,..., N) is the balance of the comparison target factors between the groups (between the comparison groups). As a segment value indicating the degree, n constants set in advance such that X1>X2>...>Xn> 0 are set, and Yi (i = 1, 2,..., N) is set as 100 ≧ Y1>Y2>.……> When n constants (registration probabilities) set in advance so that Yn> 0,
The registration processing apparatus determines the probability as Yi [%] when Xi × S1 ≦ (c1 / c3) × S3 for any i in the first group, and 0 [%] otherwise. In the second group, Yi [%] is set when Xi × S2 ≦ (c2 / c1) × S1 for any i, and is set to 0 [%] otherwise. The group of 3 is characterized by comprising means for setting 100%.
According to the computer program and subject registration system of the present invention, the method of the present invention can be carried out by a computer.
The embodiment of the present invention is used for the following observational studies, for example. However, the present invention is not limited to these examples, and can be applied to all case registrations in observational studies or epidemiological studies conducted at the manufacturing and sales stage after application for approval of a drug.
(1) Side effects of anticancer drugs such as CPT11 Factors to be compared: UGT1A1 gene polymorphism Registration regulators: gender, age, PS (performance status), regimen, molecular target drugs, facilities (2) Prasugrel or clopidogrel Antiplatelet drugs inhibit the occurrence of cardiovascular disease Comparative factors: P2Y12 gene polymorphism
Registration adjustment factors: gender, age, LDL cholesterol level, diabetes, hypertension, pretreatment drugs, smoking (3) Effects of antihypertensive drugs such as olmesartan and losartan on the onset of cerebrovascular diseases Factors to be compared: preference (high salt menu Inoculation frequency or salt intake)
Registration adjustment factors: gender, age, LDL cholesterol level, blood pressure level, diabetes, smoking (4) Impact of patient attributes on compliance status Comparable factors: educational background, medical history / complications, blood type, etc. Registration adjustment factors: Sex, age, pretreatment drugs (5) Effects of exercise habits on the development of cerebrovascular disease Comparative factors: exercise frequency Registration adjustment factors: gender, age, LDL cholesterol levels, diabetes, hypertension, pretreatment drugs, smoking
Of the above observational studies, the case where the method of the present invention is applied to a useresults survey, which is an observational study of anticancer agents, will be specifically described. In this embodiment, in order to investigate the side effects of a specific anticancer agent and take necessary measures such as treatment, case registration of a subject (in this case, a patient) to be investigated is performed.
As a premise, it is known that the risk of side effects varies depending on the patient's UGT1A1 gene polymorphism (divided into wild type, hetero type, and homo type) in the patient background between the comparative populations. And there are very few homozygous patients according to gene polymorphism in the clinical field. Therefore, in order to compare and evaluate the efficacy and safety of anticancer drugs between UGT1A1 gene polymorphisms, a small number of homozygous patients are actively registered, and wild type and heterozygous patients are controlled, As for the registration adjustment factor, the present invention is used as a method for controlling the registration so as to eliminate the bias in the distribution of the patient background among the comparison groups. In this case, as described in (1) above, sex, age, PS (performance status), regimen, molecular target drug, and facility are used as registration adjustment factors.
Here, “UGT1A1” is a kind of metabolic enzyme UDP glucuronosyl transferase (UGT) present in the liver, and its gene polymorphism (UGT1A1 * 28, UGT1A1 * 6) is a certain species. It is known to be involved in the development of side effects of anticancer drugs.
In the present specification, as for the genetic polymorphisms of a subject, when each has a wild type, a wild type, when any has a heterozygote, a heterotype, either is a homozygote (UGT1A1 * 6 / * 6, UGT1A1 * 28 / * 28) or any of them as a heterozygote (UGT1A1 * 6 / * 28) is called a homotype.
Hereinafter, a procedure for registering cases for registering subjects to be investigated will be described.
As shown in FIG. 2, the investigator (physician) conducts a genetic polymorphism test after patient screening (ST11) (ST12). Explain to the patient about participation and obtain consent (ST13).
Next, case registration by gene polymorphism is performed using the method of the present invention. As the premise, the number of planned cases c1, c2, c3 of each UGT1A1 gene polymorphism (wild type, hetero type, homo type) is set to 600, 1100, 300 based on clinical and statistical background, respectively. Among these, since the number of homozygous patients is as small as about 10% of the population, the target number of homotypic cases will be clarified at the time of contract with each facility so that the target number of homotypic cases reaches 300 cases. .
When the number of homotype cases reached at the time of contract is reached at each facility, discussion with the survey requester will be made regarding whether or not homotype cases can be registered at the facility thereafter. Similarly, if the number of genetic polymorphisms other than homotypes (wild type and heterotype) reaches the number of cases specified at the time of contract, then cases of genetic polymorphisms other than homotypes in the facility will be registered Shall not be accepted.
The investigator enters the input device (specifically, the input terminal) of the registration processing system (EDC: Electrical Data Capturing) until 14 days have passed since the start of treatment (planned) after obtaining consent in ST13. (However, registration after 15 days or more from the start date of treatment is not accepted).
Next, case registration by gene polymorphism is performed. This registration process is executed by, for example, a registration processing system including a host computer and an input terminal (including a display device) connected to the host computer. FIG. 3 shows the configuration of the main part.
The registration processing system shown in FIG. 3 includes a CPU 1 and a storage device 2 that stores (stores) data to be processed here and calculation results. The CPU 1 executes a dynamic registration process, which will be described later, according to a computer program stored as a function realizing means for realizing the method of the present invention. As the input terminal (including the display device), for example, a computer terminal or the like installed at the survey facility can be used.
Returning to FIG. 2, information including a comparison target factor (gene polymorphism) and a registration adjustment factor of the patient (subject) who has obtained consent in ST13 is input from the input terminal to the computer. At this time, the CPU 1 of the computer executes processing described below (ST14 to ST18 dynamic registration processing).
CPU1 is divided into two groups (homo type group and wild type or hetero type group) according to each genotype (ST14).
Further, the CPU 1 decides whether or not to adopt the wild type or hetero target subjects (cases) based on the probability set by the method of the present invention after primary registration (ST15: provisional registration). (Yes / No) is determined (ST16), and if it is “No”, the patient does not participate (ST18), and if “adopted”, the main registration (ST17) is performed. In this main registration, the CPU 1 records information on the patient (including gene polymorphism and registration adjustment factors) in the storage device 2 for each gene polymorphism. The cases registered (mainly registered) in this way are followed for the course of subsequent treatment and the like (ST19). On the other hand, cases that were not selected in ST16 are excluded from the scope of this survey, and are not followed up.
As for the homotype, all examples are registered (ST17). Therefore, all cases are subject to tracking (ST19).
In the case registration described above, in the procedure from ST14 to ST18 (dynamic registration), for wild type or hetero type, homotype patient background registered so far (facility, sex, age, performance at registration (PS)) It is determined whether or not a tentatively registered wildtype or heterotype patient is transferred to regular registration using a regimen (chemotherapy stage primary and secondary) and molecular target drug (presence or absence) as a registration regulator. At that time, the transition probability to the wild type or hetero type main registration is dynamically changed so that the distribution of the patient background is similar between the wild type or hetero type and the homo type. The dynamic probability is set as described later.
First, for newly incorporated wild type or hetero type patients (temporary registration), the total number of patients belonging to the level of each registration adjustment factor among the already registered wild type is Swild, and similarly, hetero type, The number of homozygous patients is assumed to be Shete and Shomo, respectively. These three numerical values are calculated by the following equations.
<Total number of patients for each genetic polymorphism>
Swild = number of wildtype patients by gender + number of wildtype patients in the same age group + number of wildtype patients in the same PS + number of wildtype patients in the same regimen + wildtype patients with the same molecular target drug Number + number of wildtype patients in the same facility Shete = number of heterotype patients by gender
+ Heterogeneous patients in the same age category + heterozygous patients in the same PS + heterozygous patients in the same regimen + heterozygous patients with the same molecular target drug + heterozygous patients in the same institution Shomo = number of homotype patients by gender + number of homotype patients in the same age group + number of homotype patients in the same PS + number of homotype patients in the same regimen + homotype patients with the same molecular target drug Number + number of homotype patients in the same facility The above “identical” means that it is the same as each registration adjustment factor of the temporarily registered patient.
<Dynamic probability>
Using the abovementioned Swild, Sheet, and Shomo, the transition probability from provisional registration to registration is determined as follows for a newly provisionally registered patient. Since the main purpose of the survey is to compare the efficacy and safety of wild type and homo type, and wild type and hetero type, migration using each comparison genotype (Swild and Shomo, Swild and Shete) Set the probability.
As described above, the target number of cases is c1 (wild type): c2 (hetero type): c3 (homo type) = 600: 1100: 300.
For wild type:
If Swild ≤ 2 (= c1 / c3) x Shomo, register with 100% probability
If 0.9 x Swild <2 x Shomo, register with 10% probability
If 0.8 × Swild <2 × Somo, register with a probability of 5%. Otherwise, set the probability to 0% (do not register).
For hetero type:
If Shete ≦ 11/6 (= c2 / c1) × Swild, register with 100% probability
If 0.9 × Shete <11/6 × Swild, register with 10% probability
If 0.8 × Shete <11/6 × Swild, register with a probability of 5%. Otherwise, set the probability to 0% (do not register).
For homo type:
Register with 100% probability (all cases registered).
Supplementally, in the example of setting the probability as described above, n, Xi (i = 1, 2,..., N), Yi (i = 1, 2,..., N) in the present invention are set to n = 3, In this example, X1 = 1, X2 = 0.9, X3 = 0.8, Y1 = 100, Y2 = 10, and Y3 = 5.
Also, the process of registering (mainly registering) with probability P% generates a random number within a range of values from 1 to 100, for example, and registers depending on whether or not the value of the random number is equal to or less than P. It is sufficient to determine whether or not. The random number may be generated by a known random number generator.
Registration adjustment factors (levels are represented by 1, 2,...) Are determined as follows.
(A) Gender (male is 1 and female is 2)
(B) Age (1 for those under 65 and 2 for over 65)
(C) PS (PS0 is 1 and PS12 is 2)
(D) Regimen (FOLFIRI (primary treatment) is 1, IRIS (primary treatment) is 2, FOLFIRI (secondary treatment) is 3, IRIS (secondary treatment) is 4, CPT11 alone (secondary treatment) ) Is 5)
(E) Molecular target drugs (none (primary treatment) 1; bevacizumab (primary treatment) 2; none (secondary treatment) 3; cetuximab (secondary treatment) 4; bevacizumab (secondary treatment) 5)
(F) Facility (facility numbers 1 nationwide)
<Dynamic registration>
The registration processing system shown in FIG. 3 determines registration conditions for each genetic polymorphism for a newly provisionally registered patient (subject). Therefore, the CPU 1 determines whether or not to perform the main registration based on the probability set as described above, and determines the patient determined to be the main registration together with the level of the registration adjustment factors A to F according to the genetic polymorphism group ( a) Register in (b) and (c). Here, (a) is a control registration, and (b) and (c) are groups of comparative registration. In this embodiment, homotype (Homo) is control registration, wildtype (Wild) and heterotype (Hetero). Is a group for comparison registration.
Specifically, in the case of registering a temporarily registered patient in the abovedescribed procedure, as shown in FIG. 4, the patient is registered in one of the registration groups (a), (b), and (c) for each gene polymorphism. And a value representing the level of the registration adjustment factor A to F is stored.
According to this embodiment, among the subjects already registered in each group according to genetic polymorphism, the total number of subjects having the same level (value) for the registration adjustment factors A to F, Swild, Sheet, and Shomo, and registration in each group Based on the number of subjects c1, c2, and c3 to be set, a probability of transitioning from temporary registration to main registration is set for subjects provisionally registered in advance, and according to the probability, a group corresponding to the type of subjects temporarily registered Since (a), (b) and (c) are registered, factors such as the background of subjects (registration adjustment factors) between groups (a) and (c) or (b) and (c) to be compared The bias is reduced and accurate information can be obtained.
As mentioned above, although embodiment of this invention was described, this invention is not limited to this. For example, the group in which subjects are registered is divided according to genetic polymorphism, but the dividing conditions differ depending on the purpose and object of the investigation, and for example, it is possible to divide by blood type.
Next, a simulation for verifying the effect of the present invention will be described below.
The inventor of the present application used the gene polymorphism as an example of the factor to be compared, and performed the following simulation for the case where the subject is classified and registered into a wild type and a homotype according to the gene polymorphism.
In this simulation, the total target number of cases of wild type and homo type, the registration probability (Yi) of wild type, and the probability of occurrence of wild type and homo type (hereinafter referred to as occurrence probability by gene polymorphism) are calculated. Each was set with three patterns. Therefore, the total number of patterns of combinations of the target number of cases, wildtype registration probability, and occurrence probability by gene polymorphism was 27 types.
Three types of setting patterns of the target number of cases, the wild type registration probability (Yi), and the occurrence probability by gene polymorphism are as follows.
Target number of cases;
(A1) 200 (100 cases per group)
(A2) 1500 (750 examples per group)
(A3) 4000 (2000 cases per group)
Wild type registration probability;
(B1) 100%, 80%, 50%, 0%
(B2) 100%, 50%, 25%, 0%
(B3) 100%, 10%, 5%, 0%
Occurrence probability by gene polymorphism;
(C1) Wild type: Homo type = 85%: 15%
(C2) Wild type: Homo type = 50%: 50%
(C3) Wild type: Homo type = 65%: 35%
Here, the number of cases “per group” related to the target number of cases means the target number of cases of each gene polymorphism (wild type and homotype respectively). Therefore, in the simulation, the target number of cases of the wild type and the homo type is the same.
The occurrence probability for each gene polymorphism is a probability that defines whether the genetic polymorphism of the subject that appears virtually on the simulation is a wild type or a homotype. Further, the registration probability of a homozygous subject is 100% as in the abovedescribed embodiment.
In the following description, the four registration probability values in the above (B1), (B2), and (B3) are represented by reference numerals BB1, BB2, BB3, and BB4 in order from the largest value.
In the simulation, the registration adjustment factor is only gender, and the sex of the subject to appear virtually is determined probabilistically. In this case, the probability that the subject is male (hereinafter referred to as male occurrence probability) is 10% or 20% in each of the case where the subject to be virtually filed is the wild type and the case of the homo type. , 30%, 40%, 50%, 60%, 70%, 80%, and 90%. Therefore, the total number of patterns of the combination of the male occurrence probability in the wild type and the male occurrence probability in the homo type was 81.
The simulation sets the target number of cases, the wild type registration probability and the genetic polymorphism occurrence probability, and the male occurrence probability in each of the wild type and homotype in the above combination patterns, and each combination Simulation was performed for each pattern as follows.
That is, a virtual subject appears by a computer. In this case, the genetic polymorphism and sex of each subject to appear virtually are determined according to the set genetic polymorphism occurrence probability and male occurrence probability, respectively.
Next, a virtual subject is registered by the same processing as ST14 to ST18 in FIG. In this case, when the virtual subject is homotype, registration (main registration) is performed with a registration probability of 100%.
On the other hand, if the virtual subject is of the wild type, the registration probability is determined as follows, and whether or not the virtual subject is registered (mainly registered) according to the determined registration probability (adopted) Or not). If the subject is adopted, the subject is registered, and if not adopted, the subject is not registered.
If 0.98 x Swild ≤ Shomo, registration probability = BB1 [%] (= 100%)
If 0.95 × Swild ≦ Somo <0.98 × Swild, registration probability = BB2 [%]
If 0.9 × Swild ≦ Somo <0.95 × Swild, registration probability = BB3 [%]
Otherwise, registration probability = BB4 [%] (= 0%)
In this example, the registration probabilities are set as follows: n, X1, X2, X3, Y1, Y2, and Y3 in the present invention are set to n = 3, X1 = 0.98, X2 = 0.95, This corresponds to the case where X3 = 0.9, Y1 = BB1 (= 100), Y2 = BB2, and Y3 = BB3.
In this simulation, the registration process described above is performed with the target number of cases (per group) in which the number of registrations of homozygous subjects (number of cases) and the number of registrations of wildtype subjects (number of cases) are set. This is done until the target number of cases is reached. In this case, when one of the homotype and the wildtype reaches the target number of cases, subsequent registration (main registration) is prohibited for the one gene polymorphism. Then, when both the homo type and the wild type reach the target number of cases, this simulation is terminated.
Furthermore, this simulation is performed for each combination pattern of the target number of cases, wild type registration probability (Yi) and gene polymorphism occurrence probability, and male occurrence probability in each of the wild type and homotype. Only repeated. The number of iterations of this simulation (target number of cases, wild type registration probability (Yi), occurrence probability by gene polymorphism, and male occurrence probability in each of the wild type and homotype are set in one combination pattern. Was repeated 1000 times.
Next, an evaluation index was calculated based on the above simulation results. In this example, the target number of cases, the wild type registration probability (Yi), the occurrence probability by gene polymorphism, and the male occurrence probability in each of the wild type and the homotype were registered in each simulation. The average value AVE_FIG (b) and standard deviation SD_FIG (c) of the difference between the proportion of males in the population of wildtype subjects and the proportion of men in the population of homotype wildtype subjects (hereinafter referred to as proportion differences) Calculated as the evaluation index.
The average value AVE_FIG (b) and standard deviation SD_FIG (c) of the ratio difference are calculated by the following equations 1 and 2.
The average value AVE_FIG (b) of the above ratio difference shows that the smaller the magnitude (absolute value) is, the more balanced the comparison population is. More specifically, in the registered wild type population of subjects It represents that the frequency distribution of gender (registration adjustment factor) and the frequency distribution of gender (registration adjustment factor) in a population of homozygous subjects are highly approximate distributions.
In addition, the smaller the value of the standard deviation SD_FIG (c), the more effectively the effect of reducing the imbalance between comparison groups is obtained (reproducible). More specifically, the registered wild type This shows that the frequency distribution of gender (registration adjustment factor) in the population of subjects and the frequency distribution of gender (registration adjustment factor) in the population of homozygous subjects is a stable approximation with high reproducibility.
Representative examples of the above simulation results are shown in FIGS.
5 (a), (b), and (c) are obtained from a simulation in which the target number of cases, wildtype registration probability, and occurrence probability by gene polymorphism are (A1), (B3), and (C1). FIG. 5A shows the average value AVE_FIG (b) and the standard deviation SD_FIG of the ratio difference for each combination pattern (81 types in total) of the male occurrence probability in the wild type and the homo type. FIG. 5B is a table showing calculated values of (c) (calculated values of SD_FIG (c) are in parentheses), and FIG. 5 (b) is a horizontal axis, a vertical axis, FIG. 5C is a graph showing the distribution of the standard deviation SD_FIG (c) of the ratio difference in the map with contour lines.
Similarly, FIGS. 6A, 6B, and 6C are simulations in which the target number of cases, the wild type registration probability, and the occurrence probability by gene polymorphism are (A1), (B3), and (C2). 7 (a), (b), and (c) show the target number of cases, wild type registration probability, and occurrence probability by gene polymorphism as (A3), (B3), and (C1). 8A, 8B, and 8C show the target number of cases, wild type registration probability, and occurrence probability by gene polymorphism (A3), (B3), (C2). The data obtained from the simulation.
The following items were confirmed by the above simulation. That is, the average value AVE_FIG (b) of the ratio difference hardly changes depending on the difference in the number of target cases, but the standard deviation SD_FIG (c) of the ratio difference becomes smaller as the target number of cases increases. From this, it can be seen that the larger the target number of cases, the more stably the imbalance of the distribution of registration adjustment factors (background factors) among the comparison groups can be reduced.
Moreover, regarding the occurrence probability by gene polymorphism, the average value AVE_FIG (b) of the ratio difference became smaller as the ratio of the wild type to the homotype increased. From this, it can be seen that the more the registration candidates of the subjects who perform dynamic registration (here, wildtype subjects), the more the imbalance in the distribution of registration adjustment factors among the comparison groups can be reduced.
In addition, the average value AVE_FIG (b) of the ratio difference hardly changed due to the difference in the wild type registration probability for dynamic registration (specifically, the difference between BB2 and BB3). The number of registered cases has increased.
1 ... CPU, 2 ... storage device.
Claims (7)
 A method for enrolling subjects for medical observational or epidemiological studies,
Determining a comparison factor and a registration adjustment factor for the subject;
Recording the subject's information for the determined comparison target factor and registration adjustment factor;
Based on the total number of subjects belonging to the same level of the registration adjustment factor among the subjects already registered in each of the plurality of comparison groups classified according to the comparison target factors, and the target number of registered subjects of each comparison group Setting a probability of transitioning from temporary registration to full registration for a subject temporarily registered in advance;
And subjecting the provisionally registered subject to full registration according to the probability.  The subject registration method according to claim 1,
Of the plurality of comparison groups, the total number of subjects in the first group is S1, the total number of subjects in the second group is S2, and the number of subjects registered in the first and second groups is c1, c2 and Xi (i = 1, 2,..., n) are n constants set in advance so that X1>X2>...>Xn> 0, and Yi (i = 1, 2,... n) is set to n constants set in advance such that 100 ≧ Y1>Y2>...>Yn> 0,
In the first group, the probability is Yi [%] when Xi × S1 ≦ (c1 / c2) × S2 for any i, and 0 [%] otherwise, and the second A subject registration method characterized in that, in a group, the percentage is set to 100 [%].  The subject registration method according to claim 1,
Among the plurality of comparison groups, the total number of subjects in the first group is S1, the total number of subjects in the second group is S2, and the total number of subjects in the third group is S3. The number of subjects registered in the group is c1, c2, c3, and Xi (i = 1, 2,..., N) is set to n constants set in advance so that X1>X2>...>Xn> 0. , Yi (i = 1, 2,..., N) is set to n constants set in advance such that 100 ≧ Y1>Y2>...>Yn> 0,
The probability is Yi [%] when Xi × S1 ≦ (c1 / c3) × S3 for any i in the first group, and 0 [%] otherwise.
In the second group, Yi [%] when Xi × S2 ≦ (c2 / c1) × S1 for any i, and 0 [%] otherwise.
In the third group, the subject registration method is 100 [%].  A computer program for causing a computer to execute a registration process for registering a subject for medical observational research or epidemiological research,
Obtaining a comparison factor and a registration adjustment factor, and recording a level of the comparison factor and registration adjustment factor of the subject;
The total number of subjects belonging to the same level of each registration adjustment factor among the subjects already registered in each of the plurality of comparison groups classified according to the comparison target factors, and the number of registered subjects targeted for each comparison group Based on the above, a step of setting a probability of transitioning from temporary registration to full registration for a subject temporarily registered in advance;
A computer program comprising the step of fully registering a provisionally registered subject according to the probability.  In a subject registration system for registering subjects for medical observational research or epidemiological research, a comparison device and a registration adjustment factor are acquired, and a comparison is made with a storage device that records the level of the comparison subject factor and the registration adjustment factor of the subject. The total number of subjects belonging to the same level of each registration adjustment factor among the subjects already registered in each of the plurality of comparison groups classified according to the target factors, and the target number of registered subjects of each comparison group And a registration processing device that sets a probability of transitioning from temporary registration to main registration for a preliminarily registered subject, and registers the temporarily registered subject according to the probability. Registration system.
 In the subject registration system according to claim 5,
Of the plurality of comparison groups, the total number of subjects in the first group is S1, the total number of subjects in the second group is S2, and the number of subjects registered in the first and second groups is c1, c2 and Xi (i = 1, 2,..., n) are n constants set in advance so that X1>X2>...>Xn> 0, and Yi (i = 1, 2,... n) is set to n constants set in advance such that 100 ≧ Y1>Y2>...>Yn> 0,
The registration processing apparatus determines the probability as Yi [%] when Xi × S1 ≦ (c1 / c2) × S2 for any i in the first group, and 0 [%] otherwise. And a means for setting to 100% in the second group, the subject registration system.  In the subject registration system according to claim 5,
Among the plurality of comparison groups, the total number of subjects in the first group is S1, the total number of subjects in the second group is S2, and the total number of subjects in the third group is S3. The number of subjects registered in the group is c1, c2, c3, and Xi (i = 1, 2,..., N) is set to n constants set in advance so that X1>X2>...>Xn> 0. , Yi (i = 1, 2,..., N) is set to n constants set in advance such that 100 ≧ Y1>Y2>...>Yn> 0,
The registration processing apparatus determines the probability as Yi [%] when Xi × S1 ≦ (c1 / c3) × S3 for any i in the first group, and 0 [%] otherwise. In the second group, Yi [%] is set when Xi × S2 ≦ (c2 / c1) × S1 for any i, and is set to 0 [%] otherwise. In the group of 3, the subject registration system comprising means for setting to 100 [%].
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