CN113314220B - Disease course monitoring system, computer-readable storage medium, and electronic device - Google Patents
Disease course monitoring system, computer-readable storage medium, and electronic device Download PDFInfo
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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Abstract
The invention relates to a disease course monitoring system, a computer-readable storage medium and an electronic device. The system comprises a sample information module, a diagnosis module and an information output module; the sample information module is used for receiving and outputting the information of the detected object, wherein the information of the detected object comprises disease marker content values a1 and a2 before and after treatment, and variation data brought to a detection result by a random error of a detection method of a disease marker; the diagnosis module calculates variation interval reference values R1 and R2 caused by detection system errors and a variation ratio P of a measured value after treatment and a measured value before treatment, and outputs the magnitude relation between P and R1 and R2 to the information output module.
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Description
Technical Field
The invention relates to the field of disease diagnosis, in particular to a disease course monitoring system, a computer-readable storage medium and electronic equipment.
Background
Cancer biomarkers are indicators of the objective assessment of the physiological status, pathological course and collective response to physical or chemical therapy given to a patient with a tumor. The cancer biomarker can be clinically used for diagnosing tumors, can detect the development direction and the degree of severity in the process of generating the tumors, and has very important significance for evaluating the clinical treatment response of medicaments and predicting the disease risk of high-risk groups.
With the improvement of medical level, the early diagnosis rate of tumor is improved, and then patients in middle and late stages still account for the majority of patients when the diagnosis is confirmed, and the recurrence risk after the operation treatment, drug resistance generated in the process of radiotherapy and chemotherapy and the transfer risk of the patients still remain difficult problems to be solved.
The disease course monitoring performance of the cancer biomarker is mainly evaluated from two aspects, on one hand, whether the marker can effectively evaluate the treatment response or not is evaluated, the treatment response comprises the evaluation of the treatment effect of the operation, the existence of tumor cell residues, the evaluation of the existence of the response of patients to the auxiliary treatment such as the implemented radiotherapy and chemotherapy and the like, and the decision of helping clinicians to maintain or change the treatment scheme; another aspect is to assess the risk of relapse and metastasis.
K L method [ Methylated Glutathione S-transferase 1 (mGSTP1) is a potential plasma free DNA epigenetic marker of prognosis and response to chemotherapy in a serum-refractory cancer ] assessed whether the level of circulating Methylated GSTP1 (mGSTP1) in plasma DNA correlates with the results of PD (progression), SD (stabilization), PR (remission) given by mGSTP1 after one round of chemotherapy, but samples that declined after treatment were analyzed for correlation with the results of PD (progression), SD (stabilization), PR (remission) given by the standard of evaluation of body tumors (RECIST)Percentage changeThe value is only-100% at most, however, the increase after treatment can exceed +100% and even thousands, and the evaluation method generates serious inequality aiming at different trend results. Lanlan Shen [ DNA Methylation precursors survivval and Response to Therapy in Patents With Myelotherapy Synthesis ] describes ctDNA as metastatic colorectal cancer (mC) receiving chemotherapyRC) potential role of early predictors of patient response to treatment. By usingFoldchangeThe ROC analysis was performed on the value and the change value of SLD (sum of tumor major diameter) given by CT, and the 10-fold-reduction value was used as the threshold value of response to treatment, and the result showed that the positive predictive value of response to treatment was 65.2% and the negative predictive value was 73.7%. By usingFoldchangeTo a certain extent solvePercentage changeThe results of different variation trends are not equal, but the detection accuracy does not reach the level that can be clinically applied.
Therefore, an accurate disease course monitoring ability evaluation method will bring great promotion to the clinical application of the nucleic acid marker.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
A first aspect of the invention relates to a disease course monitoring system, the system comprising:
the system comprises a sample information module, a diagnosis module and an information output module;
the sample information module is used for receiving the information of the detected object and outputting the information to the diagnosis module, wherein the information of the detected object at least comprises a content value a1 of the nucleic acid disease marker before treatment and a content value a2 after treatment, and variation data brought by random errors of the detection method of the nucleic acid disease marker to the detection result;
the diagnosis module calculates variation interval reference values R1 and R2 caused by detection system errors and a variation ratio P of a treatment 'after' measurement value to a treatment 'before' measurement value, and outputs the magnitude relation between P and R1 and R2 to the information output module:
wherein Z represents a threshold value at a given confidence level and CV is the overall coefficient of variation of the variation data;
the size relationship includes any one of:
a）P > R2；
b）R1 ≤ P ≤R2；
c）P < R1。
a second aspect of the present invention relates to a computer-readable storage medium for storing a computer instruction, a program, a code set, or an instruction set, which when run on a computer, causes the computer to execute functions corresponding to the sample information processing module, the diagnosis module, and the information output module in the system as described above.
A third aspect of the present invention relates to an electronic device comprising:
one or more processors; and
a computer-readable storage medium for storing a computer instruction, a program, a set of codes, or a set of instructions that, when executed on a computer, causes the one or more processors to implement the functions corresponding to the sample information processing module, the diagnostic module, and the information output module in the system as described above.
The invention has the beneficial effects that:
1. the disease course monitoring system with higher accuracy is provided, and accurate interpretation of different disease courses (progress, stability and remission) of the disease is realized based on the nucleic acid marker;
2. by usingLog 2 FoldchangeThe values are used as an index for evaluating the change in the levels of the nucleic acid markers "before" and "after" the treatment, compared withPercentage changeThe magnitude of the numerical value is equal to the variation amplitude;
3. the method can be used as a supplement of a conventional ROC (rock characteristic) cut value method, and the defect of low accuracy caused by uneven distribution of sample types and small number of samples is overcome.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a ROC curve of the Vimentin gene for diagnosing bladder cancer in one embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the invention, one or more examples of which are described below. Each example is provided by way of explanation, not limitation, of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For instance, features illustrated or described as part of one embodiment, can be used on another embodiment to yield a still further embodiment.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The invention relates to a disease course monitoring system, which comprises:
the system comprises a sample information module, a diagnosis module and an information output module;
the sample information module is used for receiving the information of the detected object and outputting the information to the diagnosis module, wherein the information of the detected object at least comprises a content value a1 of a nucleic acid disease marker before treatment/diagnosis and a content value a2 after treatment, and variation data brought by random errors of a detection method of the nucleic acid disease marker to a detection result;
the diagnosis module calculates variation interval reference values R1 and R2 caused by detection system errors and a variation ratio P of a treatment 'after' measurement value to a treatment 'before' measurement value, and outputs the magnitude relation between P and R1 and R2 to the information output module:
wherein Z represents a threshold value at a given confidence level and CV is the overall coefficient of variation of the variation data;
the size relationship includes any one of:
a）P > R2；
b）R1 ≤ P ≤R2；
c）P < R1。
it will be readily appreciated that "before" and "after" treatment in the present invention is a set of relative concepts, considered with respect to the therapeutic factors desired to be studied, according to methods of controlling variables and the like, as is customary to those skilled in the art. For example, the study is expected to be treated with drug A, and the patient has been treated with drug B which is unrelated to the study before drug A, i.e., it has already been treated, but is not called "pre-treatment" before drug B is administered because drug B is not the subject of the study.
In some embodiments, the variant data comprises variant data resulting from at least one of:
the type of the instrument, the detection place, different instruments in the same place, continuous detection days of the same instrument, the number of running times in the same day, the number of detection compound holes in the same running, the number of batches of agents to be tested, different operators and the like.
In some embodiments, the variant data comprises mean data from repeated detection of a sample
And its standard deviation σ;
easily understood, mean value data
And the data of the standard deviation sigma of the standard deviation is collected from the same detection system as the data of a1 and a 2.
In some embodiments, Z is selected from one of the following values:
1.282, 1.645, 1.960, 2.326, or 2.576.
In some embodiments, the treatment comprises any one of a drug treatment, a surgical treatment, a radiation therapy, or a combination thereof.
The drug therapy may be a biological drug and/or a chemical drug.
In some embodiments, the nucleic acid disease marker is quantified, and ROC analysis is performed based on the difference between the content of the nucleic acid disease marker in the malignant experimental group and the content of the nucleic acid disease marker in the benign control group, and the content value capable of distinguishing the malignant experimental group and the benign control group is determined as a threshold value of the marker;
if the content of the nucleic acid disease marker in a malignant experimental group is in an ascending trend relative to that in a benign control group, the a1 data is received by the sample information processing module when a1 is greater than the threshold value;
if the content of the nucleic acid disease markers in the malignant experimental group is in a descending trend relative to the content of the benign control group, the sample information processing module receives the a1 data when the a1 is less than or equal to the threshold value.
It should be noted that in the present invention, "malignant" and "benign" are relative terms, and both represent the relative situation of the course of disease change in a given disease, and as long as the course of disease changes toward health, the definition of course of disease changes is benign, and the definition of the course of disease changes toward exacerbation, the definition of disease changes is malignant.
In some embodiments, the information processing module further receives input of:
one or more of race, photograph, age, gender, height, weight, ethnicity, image outcome, tumor protein marker outcome, dietary habits, medication history, mood status, time to visit, family genetic history, religious belief, frequency of smoking, type of exercise, and frequency of the subject.
In some embodiments, the information output module outputs information through a reporting system host interface.
In some embodiments, the information displayed by the reporting system main interface includes one, more or all of the following:
1) calling the information of the detected object in the sample information receiving function module and displaying the information;
2) date information recording and modification functions;
3) calling a disease course monitoring result text template for display and providing modification authority;
4) printing a report and establishing a custom report template; the user-defined items comprise the number of a detected object, a report head, a detection value, a reference value, a report picture, a health suggestion, an auditor and a printer.
In some embodiments, the date information comprises: one or more of a sampling time, a sample delivery time, an instrument detection date, a user information entry date, a received instrument detection result date, an audit report date, a print report date, and a send report date.
In some embodiments, the nucleic acid disease marker is a nucleic acid with a change in expression level, or a nucleic acid mutation, or a nucleic acid with a change in base modification.
In some embodiments, the nucleic acid disease marker is DNA or RNA.
The RNA can be mRNA, lncRNA, small ncRNA, tiny ncRNA (e.g., siRNA, miRNA, and piRNA), tRNA, rRNA, snRNA, snoRNA, or telomerase RNA.
Modification of nucleic acids such as methylation, demethylation.
In some embodiments, the information output module outputs according to the following criteria:
if the content of the nucleic acid disease marker in the malignant experimental group is in an ascending trend relative to the content of the benign control group, then:
a, outputting disease progress according to results, b, outputting stable disease according to results, and c, relieving disease according to results;
if the content of the nucleic acid disease marker in the malignant experimental group is in a descending trend relative to the content of the benign control group, then:
a results output disease remission, b results output disease stabilization, and c results output disease progression.
In some embodiments, the nucleic acid disease marker is a marker for a disease selected from the group consisting of:
tumors, immunological diseases or infectious diseases.
In some embodiments, the tumor is selected from: bone, bone junction, muscle, lung, trachea, heart, spleen, artery, vein, blood, capillary vessel, lymph node, lymphatic vessel, lymph fluid, oral cavity, pharynx, esophagus, stomach, duodenum, small intestine, colon, rectum, anus, appendix, liver, gallbladder, pancreas, parotid gland, sublingual gland, urinary kidney, ureter, bladder, urethra, ovary, fallopian tube, uterus, vagina, vulva, scrotum, testis, vas deferens, penis, eye, ear, nose, tongue, skin, brain, brainstem, medulla oblongata, spinal cord, cerebrospinal fluid, nerve, thyroid, parathyroid, adrenal gland, pituitary, pineal gland, pancreatic islet, thymus, gonad gland, sublingual gland, and parotid gland.
In some embodiments, the immune disease is selected from: systemic lupus erythematosus, multiple sclerosis, type I diabetes, psoriasis, ulcerative colitis, Sjogren's syndrome, scleroderma, polymyositis, rheumatoid arthritis, mixed connective tissue disease, primary biliary cirrhosis, autoimmune hemolytic anemia, hashimoto's thyroiditis, addison's disease, vitiligo, Graves ' disease, myasthenia gravis, ankylosing spondylitis, allergic osteoarthritis, allergic vasculitis, autoimmune neutropenia, idiopathic thrombocytopenic purpura, lupus nephritis, chronic atrophic gastritis, autoimmune infertility, endometriosis, passare's disease, pemphigus, discoid lupus, and dense deposit disease.
In some embodiments, the infectious disease is a viral, bacterial, fungal, or parasitic infection.
The virus may be selected from: one or more of adenoviridae (adenoviridae), arenaviridae (arenaviridae), astroviridae (astroviridae), orthoviridae (bunyaviridae), caliciviridae (caliciviridae), flaviviridae (flaviviridae), hepaviridae (hepeviridae), mononegavirales (mononegavirales), reticuloviridae (nidovirales), picornaviridae (picornaviridae), orthomyxoviridae (orthomyxoviridae), papilloma virus (papioviridae), parvovirus (paraviridae), polyomaviridae (polyomaviridae), poxviridae (poxviridae), reoviridae (reoviridae), retroviridae (retroviridae), and togaviridae (togaviridae);
the bacteria may be selected from: one or more of staphylococcus, streptococcus, listeria, erysipelothrix, nephrobacter, bacillus, clostridium, mycobacterium, actinomyces, nocardia, corynebacterium, rhodococcus, and/or one or more of anthrax, erysipelothrix, tetanus, listeria, mycobacterium aerodoides, extracoliform bacillus, proteus, dysentery, pneumonia, brucella, aeroginetobacter, haemophilus influenzae, haemophilus parainfluenzae, moraxella catarrhalis, acinetobacter, yersinia, legionella pneumophila, pertussis, parapertussia, shigella, pasteurella, vibrio cholerae, and parahemolytic bacillus;
the fungus may be selected from: one or more of coccidioidomycosis immitis, pediococcus pluvialis, histoplasma capsulatum, histoplasma donae, lobelomyces lobbiensis, paracoccidioides brasiliensis, blastomyces dermatitidis, sporothrix schenckii, penicillium marneffei, candida albicans, candida glabrata, candida tropicalis, candida vitis vinifera, aspergillus oryzae, Exophiala jeansi, chromocor miehei, chromocor verruckeri, chromocor dermatitidis, geotrichum candidum, pediococcus borealis, cryptococcus neoformans, myceliophthora sp, rhizopus oryzae, mucor india, Absidia, Coptomyces racemosus, Chaetomium fortunei, coniothrix guanidium, Isosporotrichum islandicum, Microsporum siberium, and Trichosporon darkans;
the parasite may be selected from: one or more of an alimentary canal endoparasite, a liver endoparasite, a lung endoparasite, a brain tissue parasite, a blood vessel endoparasite, a lymphatic endoparasite, a muscle tissue parasite, a cell endoparasite, a bone tissue parasite, and an intraocular parasite.
The present invention also relates to a computer-readable storage medium for storing a computer instruction, a program, a code set, or a set of instructions which, when run on a computer, causes the computer to perform functions corresponding to the sample information processing module, the diagnosis module, and the information output module in the system as described above.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The invention also relates to an electronic device comprising:
one or more processors; and
a computer readable storage medium for storing a computer instruction, a program, a set of codes, or a set of instructions that, when executed on a computer, causes the one or more processors to implement functions corresponding to the sample information processing module, the diagnostic module, and the information output module in the system as in any one of the above.
In some implementations, the electronic device can also include a transceiver. The processor is coupled to the transceiver, such as via a bus. It should be noted that the transceiver in practical application is not limited to one, and the structure of the electronic device does not constitute a limitation to the embodiments of the present application.
The processor may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. A processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, a DSP and a microprocessor, or the like.
A bus may include a path that transfers information between the above components. The bus may be a PCI bus or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc.
Embodiments of the present invention will be described in detail with reference to examples.
Example 1 evaluation model of nucleic acid markers for disease course monitoring
1. Determining the threshold of the marker: quantifying the marker, performing ROC analysis according to the content difference of the marker of the experimental group and the control group, determining the content value capable of distinguishing the two, and determining the threshold value of the marker; for the markers with the rising content in the experimental group, the markers are only added into the group to evaluate the treatment effect when the content of the markers before treatment is greater than a threshold value, and the monitoring detection is continuously carried out when the content of the markers before treatment is less than or equal to the threshold value; and for the marker with the content of the experimental group in the descending trend, the marker is selected to be used for evaluating the treatment effect only when the content of the marker before treatment is less than or equal to the threshold value, and the monitoring detection is continuously carried out when the content of the marker before treatment is more than the threshold value.
2. Determining a significant change threshold for a test nucleic acid marker
(1) Determination of the precision of the detection System
Determining a detection sample to be used for evaluation, wherein the detection sample at least comprises three concentration points of low concentration, medium concentration and high concentration under a system to be evaluated of the nucleic acid marker, the low concentration sample is generally at or close to the quantitative limit of the system, and the high concentration is generally a high value detected by a clinical sample in a linear range.
Determining influence factors influencing the precision of the detection system: including but not limited to factors such as instrument type, instrument model, test site, different instruments at the same site, consecutive days of testing on the same instrument, number of runs on the same day, number of replicate wells tested within the same run, number of test agent lots, different operators, etc.
And thirdly, determining the total coefficient of variation, namely the CV value, of the analysis method based on the detection results of the detection samples under different influence factors.
(2) Determining a significant change threshold
In order to ensure that the change between the two measurements made by the detection device over a time interval is not due to variations in the assay method itself, it is necessary to determine a threshold for significant change in the assay method used to detect the marker. The method comprises the following steps:
the coefficient of variation of the detection result brought by a certain specific detection method of the marker is as follows:
CV = (standard deviation/average) × 100%
Then, at a certain confidence level, the range of the detection value of the marker under the specific detection method is:
fromMean value-Z standard deviation (containing)ToMean + Z standard deviation (containing)I.e. by
Fromaverage-Z [ (CV average)/100%] (containing)ToAverage + Z [ (CV average)/100%] (containing)
Where Z represents the cut-off value at a given confidence level.
We define the marker content value "before" treatment and the marker content value "after" treatment as a1, and a2, assuming that "before" a1 is the mean value, if the marker content is substantially changed after "treatment, i.e. not due to the variation of the test method itself, the value of a2 will fall outside the detection range of a1, i.e.:
a2<a1-Z*[(CV* a1)/100%]or a2>a1+ Z*[(CV* a1)/100%]
The ratio of the change in the "post-treatment" measurement to the "pre-treatment" measurement is then:
changes are presented in a logarithmic manner by fold:
P=Log
2
fold change = Log
2
（a2/a1）
The CV of variation coefficient brought by a certain specific detection method to the detection result, the differences brought by the type of instruments, the detection places, different instruments in the same place, the continuous detection days of the same instrument, the operation times in the same day, the detection multiple hole number in the same operation, the batch times of the reagents to be tested, different operators and the like in the experimental process are selectively considered according to the experiment, and finally the total CV value is calculated.
The significantly varying threshold is determined by selecting the confidence level to be analyzed to determine the magnitude of Z, and substituting into a formula to obtain the threshold R.
R1=Log
2
(1-Z*CV/100%)
R2=Log
2
(1+Z*CV/100%)
Notably, the significantly varying threshold determines the magnitude of Z by selecting the confidence level to be analyzed, which is different from the Z value generated at the test performance, and the distribution of Z values is shown in table 1. The system was analyzed using a 95% confidence interval, so the corresponding Z value was 1.645.
TABLE 1 common confidence level and Z value at test efficacy
The interpretation method of the nucleic acid marker for disease course monitoring, which analyzes the disease progression by the change value of the measured value after treatment compared with the measured value before treatment: for the markers of the content variation trend of the experimental groups, the interpretation mode is shown in table 2:
TABLE 2
Example 2 application of evaluation model to evaluation of effects of surgical treatment by methylation marker Vimentin Gene
1. Test nucleic acid markers: methylation of Vimentin Gene (Vim Gene)
2. The samples used were evaluated: T-47D cell DNA (T-47D was purchased from China academy of sciences type culture Collection cell Bank, catalog number TCTU 87) was extracted using a DNA extraction reagent (Tiangen Biochemical technology Co., Ltd., Cat number: DP 304). Purification was carried out by sulfurization using EZ DNA Methylation-Gold Kito (Zymo, cat # D5006), and the concentration was measured using a micro ultraviolet spectrophotometer (Thermo, Nano-drop 2000). Test samples were prepared at 15152 copies/ml, 758 copies/ml, 76 copies/ml, respectively.
3. The three samples were processed in a full process according to the actual clinical sample processing procedure, and then tested in three Roche Light480 instruments (respectively placed in three different locations) for 3 batches of reagents, each batch of reagents was tested for 20 days, 2 tests were performed each day, and each sample was parallel to 2 samples in each test, so that a total of 720 data were obtained for each sample. And (5) determining the actual methylation copy number of the Vim gene and the internal reference through a standard curve, and normalizing the internal reference gene.
4. Determining a significant change value
At the 95% confidence level, a significant change threshold, R1, of-1.54 and R2, of 0.73 was calculated.
TABLE 3
Further, after determining the respective threshold values, an analysis of the progression of the disease is performed by the change value of the latter measurement compared to the former measurement. Using the method to evaluate the disease state, when P is more than 0.73, the current stage given by the Vim marker is considered to be in a progressive state; when P is-1.54 ≦ P ≦ 0.73, the disease is considered to be in a stable state, and when P < -1.54, the disease is considered to be in a state of remission.
5. Evaluation of the efficacy of treatment of patients with bladder cancer surgery
(1) Determination of threshold for Vim marker of bladder cancer
First, the diagnostic performance of bladder cancer was evaluated, 159 preoperative urine samples (96 bladder cancers and 63 non-bladder cancers) were collected, ROC analysis was performed according to the difference in the content of Vim markers between bladder cancers and non-bladder cancers, and the content value that can distinguish between the two was determined as the threshold value of Vim markers. As shown in fig. 1, when the threshold >13.93, the sensitivity was 80.21%, the specificity was 93.65%, and the AUC area reached 0.9055 (fig. 1).
(2) Evaluation of therapeutic Effect
Operation therapeutic effect
80 samples of bladder cancer surgical treatments (preoperative, postoperative pair) were collected this time, of which 76 were included in the cohort analyses above the threshold (13.93). In general, it is considered that a tumor is excised "after" being treated by surgery in the clinic, but there may be cases where the excision is incomplete and the tumor cells remain. In addition to further monitoring the course of disease using clinical gold standards, the method can be used to further evaluate the effect of surgical treatment, suggesting the presence of tumor cell residues.
This method (Log) was used in 76 cases of surgery matched samples2Fold change values), which showed 68 cases of remission and 8 stable cases, with 89.5% clinical agreement. For the patients treated by the operation, long-term follow-up monitoring is needed in the later period,in particular, the state of the disease course is closely concerned with the patient in which the patient is judged to be stable.
TABLE 4 evaluation of the effects of surgical treatment of bladder cancer
② monitoring recurrence
At present, the means of preventing bladder tumor recurrence in hospitals generally adopts postoperative follow-up examination, and the means mainly comprises cystoscopy, urocytology, B-ultrasound and the like. Cystoscopy biopsies suspicious diseased tissue, but it is invasive and expensive and painful to the patient. Compliance is poor for patients requiring constant cystoscopic monitoring. The positive rate of urine cytology examination is low, and the detection result is easy to be different by the difference of observed individuals, which brings inconvenience to clinical application. The method (significant change threshold) is one of the means for monitoring the course of bladder cancer, can provide targeted treatment for patients with high recurrence risk and low risk of bladder cancer, and can carry out follow-up with different densities.
In evaluating the effect of surgical treatment, the patient was judged to have SD status at 1 week after surgery and possibly tumor cell residue, and for this type of patient, the patient needs to pay close attention to the disease process status at follow-up. 20 follow-up patients are grouped in the group, the follow-up time is different from 12 months, 15 months, 18 months and 24 months, and specific results are shown in the following.
TABLE 5-1 Single time Point assay values
Note: "/" indicates that the current stage fails to track to the current time point
TABLE 5-2 Log at 2 consecutive time points2Fold change
Note: if the two continuous detection values are lower than the threshold value, the Log cannot be calculated2The Fold change value is represented by "-", the state is a non-recurrence state, and the monitoring is continuously carried out in the later period; the font is bolded and the symbol indicates the recurrence risk of the interpretation hint of the method.
Of these 20 follow-up patients, 11 were diagnosed with recurrence by clinical cystoscopy, of which 9 were judged to be at risk of recurrence during the follow-up period using the method and 2 were judged to be in stable condition. During the follow-up period, 4 of the patients at risk of relapse as judged by this method were at least 3-6 months earlier than the time at which relapse was clinically indicated. In addition, 8 patients are clinically diagnosed as not having recurrence, and 2 patients are detected and judged to have recurrence risk by the method at the current follow-up stage, but clinical microscopic examination results are still not having recurrence, and further follow-up monitoring is needed at the later stage. The results can be reflected laterally, and the recurrence can be prompted earlier than clinical gold standards by utilizing a molecular monitoring means, so that a basis is provided for clinical research and evaluation of early treatment intervention measures. However, because the number of the analyzed samples is small, more follow-up samples need to be accumulated, so as to further embody the advantages of the disease course monitoring and evaluation of the method.
Example 3 use of an evaluation model in assessing the efficacy of chemotherapeutic treatments with methylation markers
Test nucleic acid markers: methylation of the Septin9 Gene
The samples used were evaluated: HCT116 cell DNA (HCT 116 was purchased from China academy of sciences type culture Collection cell Bank, catalog number TCTU 99) was extracted using a DNA extraction reagent (Tiangen Biochemical technology Co., Ltd., Cat. No. DP 304). Purification was carried out by sulfurization using EZ DNA Methylation-Gold Kito (Zymo, cat # D5006), and the concentration was measured using a micro ultraviolet spectrophotometer (Thermo, Nano-drop 2000). 3030, 303 and 38 copies/ml of test samples are prepared respectively.
The 3 samples were processed in a full flow according to the actual clinical sample processing flow and then individually placed on 3 Roche Light480 instruments (each placed on 3 different instruments)Site) were tested for 3 batches of reagents, each for 20 days, 2 trials per day, with 2 replicates per sample per trial, resulting in a total of 720 test data. According to the relative quantitative method, the formula 1000 x 2 is used-△△CtThe relative quantification of methylation for Septin9 was calculated.
Determining a significant change value
At the 95% confidence level, the significant change threshold was calculated to be-1.44 for R1 and 0.71 for R2
TABLE 6
Using the above-identified threshold value as an evaluation criterion of the disease state, the disease is considered to be in a progressive state when P >0.71, the disease is considered to be in a stable state when P-1.44. ltoreq. P.ltoreq.0.71, and the disease is considered to be in a remission state when P < -1.44.
Evaluation of chemotherapeutic treatment effect on intestinal cancer patients
(1) Determination of threshold for Septin9 marker for intestinal cancer
First, the Septin9 gene was evaluated for its ability to assist in diagnosis of intestinal cancer. When 135 colorectal cancer samples and 163 non-colorectal cancer samples (including gastric cancer, esophageal cancer, intestinal adenoma, intestinal polyp, healthy people and the like) are detected in the current time, ROC cut value analysis is carried out on relative quantification values of plasma samples of healthy people and intestinal cancer, when the threshold value is larger than 1.57, the sensitivity is 76.7%, the specificity is 91.4%, and the AUC area is 0.8983.
(2) Evaluation of therapeutic Effect
First, the therapeutic effect of chemotherapy
This cohort 64 samples of chemotherapy treatments (before and after chemotherapy) were evaluated for disease progression by clinical diagnosis (CT) and monitoring of disease status by S9. Based on RECIST evaluation, there were 25 PR patients, 20 SD patients, and 19 PD patients. Generally, CT clinical images assess that PR and SD are considered to be responsive to treatment, while PD is non-responsive to treatment. In the prior literature, the percent change and the fold change are reported to be used for evaluating the treatment effect of diseases, and when the 2 evaluation methods are used, ROC cut value analysis is carried out on a treatment response group and a non-response group to determine the optimal treatment response threshold value, and the clinical compliance rate is further evaluated according to the threshold value. The method adopts the significant change threshold value of the determination detection method as the cut off value of the disease course monitoring effect evaluation, so that the influence brought by the detection method can be effectively avoided. The specific results are shown in the following three tables.
TABLE 7-1 chemotherapy treatment sample test values
Note: RECIST is an objective assessment of tumor size during treatment as an assessment criterion for tumor burden. PR and SD are considered to be responsive to treatment, with attribute defined as 1; PD was considered non-responsive to treatment and attribute was defined as 0.
TABLE 7-2 evaluation of chemotherapeutic Effect and comparison
TABLE 7-2 shows
TABLE 7-3 summary of chemotherapeutic treatment efficacy evaluation modalities
When the judgment is carried out by using percent change (percentage change), ROC cut value analysis is carried out, and the rate of consistency with clinic reaches 82.81 percent when the threshold value is less than or equal to-41.71; when using fold change criteria, ROC cut analysis showed a 82.81% clinical concordance at a threshold of ≦ 0.58; the interpretation of the method shows that 25 cases of 25 PR patients are interpreted as PR due to the significant change value, 20 SD patients are interpreted as SD, 13 cases of 19 PD patients are interpreted as PD, and the clinical consistency rate reaches 90.63%. Compared with the other 2 evaluation methods, the clinical compliance rate of the method is higher. In addition, the significant change threshold of the method can be used for definitely giving the treatment state of the patient, and the indication effect is possible to have a certain indication effect on the decision of maintaining or changing the treatment scheme by a clinician.
② monitoring of metastasis and relapse
The patients are effectively followed up in 40 cases, and the time after the operation (or the operation plus the standard chemotherapy) of the patients is 3-24 months by data statistics. The relapse status was determined by clinical diagnosis (CT or pathology) and Septin9 and CEA were detected simultaneously, with specific results as shown in the table below.
TABLE 8-1 relative quantitation of Septin9 at different time points
TABLE 8-1 shows
TABLE 8-2 significant change values for Septin9 at 2 consecutive time points
TABLE 8-2 shows
TABLE 8-3 CEA detection values at different time points
Note: the font is thickened and the mark is marked to indicate that the CEA index is judged to be positive
TABLE 8-4 comparison of the present method with clinical CT and CEA assays
As shown in Table 8-2, during the follow-up period, the interpretation of the present method suggested 9 cases of risk of recurrence, of which 4 cases suggested a recurrence earlier than the clinical diagnosis, with the number of days advanced varying between 90 days or 180 days. In addition, 4 cases of clinical diagnosis have no relapse, but the result of the interpretation of the method is the relapse state, and 3 cases of clinical diagnosis have relapse, but the interpretation of the method does not indicate the relapse risk, and follow-up monitoring is further needed for the later period of patients of the type.
As can be seen from tables 8-4, S9 (this method) has a detection sensitivity of 69.2% for monitoring the recurrence of colorectal cancer, a specificity of 85.2%, and an overall compliance of 80%. The detection sensitivity of CEA on the monitoring of colorectal cancer recurrence is 15%, the specificity is 92.6%, and the overall coincidence rate is 87.88%. As can be seen, the CEA index is relatively poor in evaluating disease progression. The results show that the method is used for early warning the recurrence and metastasis of the tumor compared with the traditional tumor marker and imaging detection. However, the number of accumulated samples is small at present, and the sample size needs to be further increased so as to evaluate the advantages of the detection method compared with clinical application.
Example 4 application of evaluation model to RNA marker assessment of the effectiveness of chemotherapy treatment of breast cancer
Test nucleic acid markers: miRNA let-7a
The samples used were evaluated: T-47D cellular RNA (T-47D was purchased from China academy of sciences type culture Collection cell Bank, catalog # TCTU 87) was extracted using a blood total RNA extraction reagent (Tiangen Biochemical technology Co., Ltd., Cat # DP 433). The concentration was measured using a micro ultraviolet spectrophotometer (Thermo, Nano-drop 2000) and cDNA synthesis was performed according to the instructions of the reverse PrimeScriptTM RT MasterMix kit (Takara Co., Ltd., cat # RR 036A). The template for miRNA quantification was transcribed using a stem-loop RT primer using the Mir-X miRNA First Strand Synthesis Kit (Takara, Cat.: 638315). 4545 copies/mL, 909 copies/mL, and 30 copies/mL of the test sample were prepared.
The 3 samples are processed in a full flow according to a real clinical sample processing flow, then 3 batches of reagent tests are respectively carried out on 3 Roche Light480 instruments (respectively placed at 3 different places), each batch of reagent is respectively tested for 20 days, 2 tests are carried out every day, 2 samples are parallel in each test, thus 720 data are obtained in total for each sample, and the content of miRNA let-7a is calculated in a relatively quantitative mode.
Determining a significant change value
At the 95% confidence level, a significant change threshold, R1, of-2.87 and R2, of 0.90 was calculated.
TABLE 9
In evaluating the disease state using this method, the disease is considered to be currently in a progressive state when P < -2.87, in a steady state when P < -2.87 ≦ 0.90, and in a remission state when P > 0.90.
Evaluation of the effectiveness of chemotherapy treatment of Breast cancer
Determining a threshold for a breast cancer miRNA let-7a marker
In recent years, the incidence rate of breast cancer is on a remarkable rising trend, and the breast cancer becomes the malignant tumor with the highest incidence rate for women in China. The occurrence, development, metastasis and drug resistance of breast cancer are related to some endogenous miRNAs, and miRNA let-7a is a type of cancer suppressor gene which is low in expression in most malignant tumors of human beings. Researches show that Let-7 expression abnormality has a direct relation with the occurrence and prognosis of various tumors such as gastric cancer, lung cancer, breast cancer and the like, and becomes an important target for tumor treatment and prognosis evaluation. When 80 breast cancer samples and 103 non-breast cancer samples (benign breast lesions and healthy people) are detected in total, ROC cut value analysis is carried out on relative quantitative values of healthy people and breast cancer blood samples, and when a threshold value is less than or equal to 15.81, the sensitivity is 72.5%, the specificity is 91.26%, and the AUC area is 0.9002.
Evaluation of chemotherapeutic Effect
The method is used for evaluating the chemotherapy effect of 40 breast cancer chemotherapy patients, and the breast cancer chemotherapy patients are divided into CR, PR, SD and PD according to the evaluation standard of the curative effect of solid tumor (RECIST) by combining the clinical curative effect judgment method, and the specific detection results are shown in the following table.
TABLE 10 evaluation of chemotherapeutic Effect of Breast cancer
As shown in table 10, CT examination of 40 patients with chemotherapy showed that 25 of them were clinically evaluated as being effective in treatment to achieve remission after chemotherapy, 11 were evaluated as being stable, and 4 were not effective in treatment and were judged to be progressive. In the process of interpretation by using the method, 25 cases of remission, 10 stable cases and 5 advanced cases are judged, and the clinical coincidence rate reaches 80%. In addition, the disease was stable according to RECIST criteria in 2 patients judged to be PR by this protocol. The above results show that using this method to interpret disease progression, higher clinical compliance rates can be achieved, and that this monitoring may help clinical decision making in patients whose RECIST criteria do not measure disease.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (8)
1. A disease course monitoring system, the system comprising:
the system comprises a sample information module, a diagnosis module and an information output module;
the sample information module is used for receiving the information of the detected object and outputting the information to the diagnosis module, wherein the information of the detected object at least comprises a content value a1 of the nucleic acid disease marker before treatment and a content value a2 after treatment, and variation data brought by system errors of the detection method of the nucleic acid disease marker to the detection result;
the diagnosis module calculates variation interval reference values R1 and R2 caused by detection system errors and a variation ratio P of a treatment 'after' measurement value to a treatment 'before' measurement value, and outputs the magnitude relation between P and R1 and R2 to the information output module:
wherein Z represents a threshold value at a given confidence level and CV is the overall coefficient of variation of the variation data;
the variation data comprises average value data obtained by repeated detection of a certain sample
And its standard deviation σ;
the size relationship includes any one of:
a）P > R2；
b）R1 ≤ P ≤R2；
c）P < R1；
the information output module outputs the following standard:
if the content of the nucleic acid disease marker in the malignant experimental group is in an ascending trend relative to the content of the benign control group, then:
a, outputting disease progress according to results, b, outputting stable disease according to results, and c, relieving disease according to results;
if the content of the nucleic acid disease marker in the malignant experimental group is in a descending trend relative to the content of the benign control group, then:
a results output disease remission, b results output disease stabilization, and c results output disease progression.
2. The disease process monitoring system of claim 1, wherein the variant data comprises variant data from at least one of the following factors:
the method comprises the following steps of instrument type, instrument model, detection place, different instruments in the same place, continuous detection days of the same instrument, operation times in the same day, detection multiple holes in the same operation, batch times of agents to be tested and different operators.
3. A disease process monitoring system as claimed in claim 1, wherein the treatment comprises any one of a drug treatment, a surgical treatment, a radiotherapy or a combination thereof.
4. The disease course monitoring system according to claim 1, wherein the nucleic acid disease markers are quantified, and ROC analysis is performed according to the difference between the contents of the nucleic acid disease markers in the malignant experiment group and the benign control group, and the content value capable of distinguishing the malignant experiment group and the benign control group is determined as a threshold value of the markers;
if the content of the nucleic acid disease marker in a malignant experimental group is in an ascending trend relative to that in a benign control group, the a1 data is received by the sample information processing module when a1 is greater than the threshold value;
if the content of the nucleic acid disease markers in the malignant experimental group is in a descending trend relative to the content of the benign control group, the sample information processing module receives the a1 data when the a1 is less than or equal to the threshold value.
5. The disease course monitoring system according to any one of claims 1 to 4, wherein the nucleic acid disease marker is a nucleic acid having a change in expression level, a nucleic acid mutation, or a nucleic acid having a change in base modification.
6. The disease course monitoring system according to any one of claims 1 to 4, wherein the nucleic acid disease markers are markers for:
tumors, immunological diseases or infectious diseases.
7. A computer-readable storage medium storing a computer instruction, a program, a set of codes, or a set of instructions which, when executed on a computer, causes the computer to perform functions corresponding to the sample information module, the diagnosis module, and the information output module in the system according to any one of claims 1 to 6.
8. An electronic device, comprising:
one or more processors; and
a computer-readable storage medium for storing a computer instruction, a program, a set of codes, or a set of instructions that, when executed on a computer, cause the one or more processors to implement the corresponding functions of the sample information module, the diagnostic module, and the information output module in the system of any one of claims 1-6.
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