CN113945723B - System for predicting risk of occurrence of immune checkpoint inhibitor treatment-related pneumonia, storage medium and application thereof - Google Patents
System for predicting risk of occurrence of immune checkpoint inhibitor treatment-related pneumonia, storage medium and application thereof Download PDFInfo
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Abstract
The invention provides a kit, a system and a computer readable storage medium for predicting the occurrence risk of immune checkpoint inhibitor treatment-related pneumonia and application thereof, and relates to the technical field of medical diagnosis. The kit comprises a COPD diagnostic tool, a tumor cell PD-L1 expression state detection reagent and a baseline plasma IL-8 level detection reagent. The system comprises a data acquisition module, a risk assessment module and an output module. The computer readable storage medium includes a program for implementing the above system. The kit, the system and the storage medium can predict CIP occurrence risk with higher accuracy.
Description
Technical Field
The invention relates to the technical field of medical diagnosis, in particular to a system for predicting the occurrence risk of immune checkpoint inhibitor treatment-related pneumonia, a storage medium and application thereof.
Background
In recent years, immunotherapy typified by immune checkpoint inhibitors (immune checkpoint inhibitors, ICIs) including ICIs against programmed cell death protein 1 (programmed cell death protein 1, PD-1) or its ligand PD-L1 has been introduced in clinical practice to rescue the anti-tumor immune response of T cells by blocking the co-inhibitory signaling pathway of immune checkpoints to promote clearance of tumor cells, bringing new hopes for cancer treatment.
The deregulation of T cell function by ici can lead to a series of organ specific inflammatory side effects, known as immune related adverse events (irAEs), and current evidence suggests that irAEs may be involved in autoreactive T cells, cytokines, etc. which release excessive inflammatory cytokines through T cell activation leading to the occurrence of irAEs. Among the irAEs reported, immune checkpoint inhibitor-associated pneumonia (CIP) is the most common pulmonary toxicity to patients receiving ici, especially non-small cell lung cancer. CIP has a wide variety of clinical manifestations, ranging from asymptomatic, respiratory symptoms to respiratory failure and even death, and is one of the most important causes of ICIs related death. Moreover, CIP sometimes lacks typical imaging and pathology features, which can be life threatening if not diagnosed in time or mishandled. Past clinical trials reported a low incidence of CIP (about 3-5%), however, CIP was up to 5-19% in real world case reports. More importantly, since CIP can progress rapidly in a short period of time, even life threatening, while also affecting the effectiveness and consistency of lung cancer ICIs treatment.
Disclosure of Invention
In order to solve the problems, the invention provides a kit, a system, a storage medium and application thereof for predicting the occurrence risk of immune checkpoint inhibitor treatment-related pneumonia, which can effectively evaluate the occurrence risk of CIP, and early identify and diagnose the CIP so as to reduce the occurrence of CIP, and timely intervene and reasonably treat the CIP.
In order to achieve the above object, the present invention provides the following technical solutions:
the invention provides a kit for predicting the risk of occurrence of immune checkpoint inhibitor treatment-related pneumonia, which comprises a COPD diagnostic tool, a tumor cell PD-L1 expression state detection reagent and a baseline plasma IL-8 level detection reagent.
Preferably, the kit further comprises instructions for carrying out an evaluation formula determined according to the following method:
and (3) performing multi-factor analysis on whether the known immune checkpoint inhibitor treatment-related pneumonia happens or not, whether the patient suffers from COPD, tumor cell PD-L1 expression state and baseline plasma IL-8 level, quantifying each factor weight score, and establishing an alignment chart equation based on multi-factor logistic regression analysis.
Preferably, the instructions describe the following evaluation formula:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is the subject baseline plasma IL-8 score, with subject baseline plasma IL-8 levels <9.0pg/mL scored as 100 points, otherwise scored as 0 points.
The invention also provides a system for predicting the risk of the immune checkpoint inhibitor for treating the related pneumonia, which comprises a data acquisition module, a risk assessment module and an output module;
the data acquisition module acquires data including whether COPD is present, tumor cell PD-L1 expression levels, baseline plasma IL-8 levels;
the risk assessment module comprises a risk assessment formula determined according to the following mode;
and (3) performing multi-factor analysis on whether the known immune checkpoint inhibitor treatment-related pneumonia happens or not, whether the patient suffers from COPD, tumor cell PD-L1 expression state and baseline plasma IL-8 level, quantifying each factor weight score, and establishing an alignment chart equation based on multi-factor logistic regression analysis.
Preferably, the risk assessment module includes the following risk assessment formula:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is the subject baseline plasma IL-8 score, with subject baseline plasma IL-8 levels <9.0pg/mL scored as 100 points, otherwise scored as 0 points.
The invention also provides a computer readable storage medium containing computer instructions which, when executed by a processor, complete the system according to the above technical scheme.
The invention also provides an application of the kit, the system or the computer readable storage medium in preparing a reagent for preventing or diagnosing the immune checkpoint inhibitor treatment-related pneumonia of a tumor patient.
Preferably, the tumor patient comprises a non-small cell lung cancer patient.
Compared with the prior art, the invention has the beneficial effects that:
1. the kit, the system or the computer readable storage medium for predicting the risk of occurrence of the immune checkpoint inhibitor treatment-related pneumonia discovers that the expression level of PD, tumor cells PD-L1 and the baseline plasma IL-8 are independent risk factors for occurrence of CIP, and the CIP occurrence risk can be effectively predicted by comprehensively evaluating the three, the prediction accuracy is 0.883, the CIP risk evaluation of ICIs treatment patients is facilitated, clinical decision support is provided for subsequent ICIs management, and the establishment of personalized treatment schemes is facilitated.
2. The invention is used for predicting the factors of the immune checkpoint inhibitor treatment related pneumonia occurrence risk, is convenient to detect, is beneficial to clinical popularization and reduces the burden of patients.
Drawings
FIG. 1 is a predicted CIP risk nomograms constructed in example 1;
FIG. 2 is a graph of the prediction model ROC constructed in example 1;
FIG. 3 is a calibration curve of actual CIP occurrence probability and predicted probability in example 1.
Detailed Description
The invention provides a kit for predicting the risk of occurrence of immune checkpoint inhibitor treatment-related pneumonia, which comprises a COPD diagnostic tool, a tumor cell PD-L1 expression state detection reagent and a baseline plasma IL-8 level detection reagent. In the present invention, the COPD diagnostic tool may be any tool capable of determining whether a subject has COPD, including but not limited to COPD diagnostic instrumentation, diagnostic reagents, diagnostic guidelines, and patient medical record query sheets.
Preferably, the kit further comprises instructions for evaluating the formula determined according to the following method:
and (3) performing multi-factor analysis on whether the known immune checkpoint inhibitor treatment-related pneumonia happens or not, whether the patient suffers from COPD, tumor cell PD-L1 expression state and baseline plasma IL-8 level, quantifying each factor weight score, and establishing an alignment chart equation based on multi-factor logistic regression analysis.
In one embodiment of the present invention, the evaluation formula described in the specification determined according to the above method is:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is the subject baseline plasma IL-8 score, with subject baseline plasma IL-8 levels <9.0pg/mL scored as 100 points, otherwise scored as 0 points.
The invention also provides a system for predicting the risk of the immune checkpoint inhibitor for treating the related pneumonia, which comprises a data acquisition module, a risk assessment module and an output module; the data acquisition module acquires data including whether COPD is present, tumor cell PD-L1 expression levels, baseline plasma IL-8 levels; the risk assessment module comprises a risk assessment formula determined according to the following mode; multifactor analysis is performed on whether the samples of known immune checkpoint inhibitor treatment-related pneumonia occur or not, whether COPD, tumor cell PD-L1 expression states and baseline plasma IL-8 levels are suffered from, and the weight scores of all factors are quantified, so that a nomogram equation based on multifactor logistic regression analysis is established.
The data acquisition module is used for collecting data required by evaluation, wherein the data can be data obtained through detection of a related kit, and can also comprise all or part of data called in other detection projects. The data acquisition module transmits the obtained data to the risk assessment module for assessment, and the risk assessment module comprises a program capable of calculating an assessment formula. The risk assessment module outputs the result calculated based on the assessment formula to the output module, and the output module judges the calculation result to obtain a prediction result and outputs the prediction result. The system provided by the invention can rapidly and accurately predict the occurrence risk of the immune checkpoint inhibitor treatment-related pneumonia, and further provides reference basis for clinical diagnosis, medication guidance, prognosis evaluation and the like.
In the present invention, the data acquisition module preferably includes a data receiving device and/or a storage device, where the data receiving device may be a computer or the like capable of inputting external data, or may be an electronic component containing a data instruction for calling a hospital system or a related system; the storage device is mainly used for storing the acquired data. In the present invention, the output module preferably includes a liquid crystal display.
In some embodiments of the invention, the risk assessment module includes the following risk assessment formula:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is the subject baseline plasma IL-8 score, with subject baseline plasma IL-8 levels <9.0pg/mL scored as 100 points, otherwise scored as 0 points.
The invention also provides a computer readable storage medium containing computer instructions which, when executed by a processor, complete the system according to the above technical scheme.
The invention also provides an application of the kit, the system or the computer readable storage medium in preparing a reagent for preventing or diagnosing the immune checkpoint inhibitor treatment-related pneumonia of a tumor patient. Preferably, the tumor patient comprises a non-small cell lung cancer patient, namely, the kit, the system or the computer readable storage medium can be applied to preparing a reagent for preventing or diagnosing the immune checkpoint inhibitor treatment-related pneumonia of the non-small cell lung cancer patient.
The technical solutions provided by the present invention are described in detail below with reference to examples, but they should not be construed as limiting the scope of the present invention.
Example 1 construction of a kit, system, and computer-readable storage Medium for predicting the risk of developing immune checkpoint inhibitor treatment-associated pneumonia
1. The present invention has been put into 164 cases of NSCLC patients receiving anti-PD-1/anti-PD-L1 treatment from 3 months 2017 to 12 months 2020, of which 20 (12.2%) developed CIP after ICIs treatment. Although less than half of the patients in the cohort (43.9%) had a history of COPD, the proportion of COPD patients in the CIP group was greater (70.0%). 136 patients in the cohort had assessed tumor cell PD-L1 expression, 51 of which (37.5%) observed tumor cell PD-L1 expression > 50% and 85 (62.5%) had tumor cell PD-L1 expression below 50%. Furthermore, baseline plasma IL-8 levels were significantly lower in the CIP group than in the non-CIP group, while no statistical differences were observed in the other cytokines in the CIP-present or non-CIP group.
2. Statistical analysis: the logistic regression analysis was used to perform single factor analysis and multi-factor analysis on both CIP and non-CIP groups to evaluate the impact of risk factors on CIP. The single factor analysis results show that: the presence or absence of COPD, tumor cell PD-L1 expression status and baseline plasma IL-8 levels are associated with risk of CIP occurrence, all with significant differences (P < 0.05). The multi-factor analysis result shows that: COPD (OR, 7.485;95%CI,1.083-51.72; P=0.041) is present, tumor cells PD-L1 express > 50% (OR, 6.857;95%CI,1.086-43.299; P=0.041), baseline plasma IL-8 levels <9.0 (OR, 0.08;95%CI,0.012-0.534; P=0.009) are independent risk factors for CIP occurrence.
3. And (3) establishing an evaluation model: taking COPD, a tumor cell PD-L1 expression state and a baseline plasma IL-8 level as independent variables, grading and quantifying weights of the independent variables, and then constructing an alignment chart (figure 1) based on multi-factor logistic regression analysis, wherein the alignment chart comprises a score scale of a first row, and the score range is 0-100; whether the second behavioural patient had COPD before ICIs treatment, wherein the presence or absence of COPD gave a corresponding score for the first row; the tumor cell PD-L1 expression condition of the patient in the third behavior, wherein, if the tumor cell PD-L1 expression is higher than 50 percent, a corresponding score is obtained corresponding to the first row; baseline plasma IL-8 levels in patients with the fourth behavior, wherein whether the baseline plasma IL-8 levels exceed 9.0pg/mL corresponds to a corresponding score for the first line; the fifth row is the total score of the patient, and the scores corresponding to the 3 indexes from the second row to the fourth row in the first row are added to obtain the total score of the patient; the probability of CIP occurrence of the patient in the sixth row is obtained by correspondingly projecting the total patient score of the fifth row onto the sixth row.
The evaluation formula of the nomogram is as follows:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is the subject baseline plasma IL-8 score, with subject baseline plasma IL-8 levels <9.0pg/mL scored as 100 points, otherwise scored as 0 points.
4. Model verification: an ROC curve was drawn, an area under the ROC curve (AUC) was calculated, and internal verification was performed by random resampling 1000 times to draw a calibration curve of the prediction model to evaluate accuracy and discrimination ability of the alignment prediction model.
5. Test results: the alignment graph model AUC constructed by the invention reaches 0.883 (95% CI, 0.806-0.959), and has high prediction accuracy (figure 2).
By analysis of the calibration curve, the prediction curve and the calibration prediction curve, there is good agreement between the observed probability and the predicted probability of the risk of CIP occurrence (fig. 3).
Example 2
A kit for predicting the risk of developing immune checkpoint inhibitor-treatment-related pneumonia, comprising a COPD diagnostic tool, a tumor cell PD-L1 expression status detection reagent, and a baseline plasma IL-8 level detection reagent, further comprising instructions for recording an evaluation formula as follows:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is the subject baseline plasma IL-8 score, with subject baseline plasma IL-8 levels <9.0pg/mL scored as 100 points, otherwise scored as 0 points.
Example 3
A system for predicting the occurrence risk of immune checkpoint inhibitor treatment-related pneumonia comprises a data acquisition module, a risk assessment module and an output module;
the data acquisition module acquires data including whether COPD is present, tumor cell PD-L1 expression levels, baseline plasma IL-8 levels;
the risk assessment module operates on the collected data according to the following risk assessment formula:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is a subject baseline plasma IL-8 score, with a subject baseline plasma IL-8 level <9.0pg/mL scored as 100 points, otherwise scored as 0 points;
the output module comprises a liquid crystal display.
In running the above system, data of whether COPD, tumor cell PD-L1 expression level, baseline plasma IL-8 level was entered into the data acquisition module. The data acquisition module transmits the data to the risk assessment module, the risk assessment module budgets the data according to an assessment formula and outputs a calculation result to the output module, and the output module displays a judgment result through the liquid crystal display.
Example 4
A computer readable storage medium containing computer instructions that, when executed by a processor, perform the formula of embodiment 3, perform the system of embodiment 3.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (4)
1. A system for predicting the occurrence risk of immune checkpoint inhibitor treatment-related pneumonia, which is characterized by comprising a data acquisition module, a risk assessment module and an output module;
the data acquisition module acquires data including whether COPD is present, tumor cell PD-L1 expression levels, baseline plasma IL-8 levels;
the risk assessment module comprises a risk assessment formula determined according to the following mode;
carrying out multi-factor analysis on whether the known immune checkpoint inhibitor treatment-related pneumonia happens or not, judging whether the patient suffers from COPD, tumor cell PD-L1 expression state and baseline plasma IL-8 level, quantifying each factor weight score, and establishing a nomogram equation based on multi-factor logistic regression analysis;
the risk assessment module includes the following risk assessment formulas:
P＝[-3.008+(a×2.013)+(b×1.925)+(c×-2.520)]×100％
wherein, P is the probability of occurrence of immune checkpoint inhibitor treatment-related pneumonia;
a is the COPD score of the subject, the subject suffering from COPD is scored as 80, otherwise scored as 0;
b is the PD-L1 score of the tumor cells of the subject, wherein the PD-L1 expression of the tumor cells of the subject is more than or equal to 50 percent and is marked as 76, otherwise, the PD-L1 expression of the tumor cells of the subject is marked as 0;
c is the subject baseline plasma IL-8 score, with subject baseline plasma IL-8 levels <9.0pg/mL scored as 100 points, otherwise scored as 0 points.
2. A computer readable storage medium containing computer instructions which, when executed by a processor, perform the system of claim 1.
3. Use of the system of claim 1 or the computer readable storage medium of claim 2 for the preparation of a reagent for preventing or diagnosing immune checkpoint inhibitor therapy-related pneumonia in a tumor patient.
4. The use of claim 3, wherein the tumor patient comprises a non-small cell lung cancer patient.
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