CN111710425A - Method, system and device for evaluating cardiotoxicity of immune checkpoint inhibitor - Google Patents
Method, system and device for evaluating cardiotoxicity of immune checkpoint inhibitor Download PDFInfo
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Abstract
The invention provides an assessment method, a system and a storage device of cardiotoxicity of an immune checkpoint inhibitor, aiming at the situation that the risk of cardiovascular disease complications of oncology departments and surgeons is uncertain, the early clinical manifestation of CVD is easy to ignore, and adverse clinical events are caused by delayed treatment, a risk assessment calculator is adopted to assist non-cardiology departments in assessing the risk of the cardiovascular events, the risk assessment calculator can help the non-cardiology departments to rapidly identify high-risk groups at the early stage, and the cardiology departments seek professional treatment suggestions, so that the occurrence of the cardiovascular events is reduced, and the severity of the events is reduced.
Description
Technical Field
The invention relates to the technical field of cardiovascular disease diagnosis, in particular to a method, a device and equipment for evaluating cardiotoxicity of an immune checkpoint inhibitor.
Background
Cardiovascular disease (CVD) has previously been recognized as a common disease and leading cause of death that threatens human health. Although cardiology and oncology are generally considered to be independent disciplines, the cardiotoxicity caused by many antineoplastic drugs has been widely studied and specific guidelines have been proposed for such problems. However, cardiotoxicity related to immunotherapy has been rarely reported and has not received sufficient attention. With the continuous application of immune checkpoint inhibitor drugs, cardiotoxicity caused by the drugs is more and more common.
The mechanism by which immune checkpoint inhibitors induce cardiotoxicity is not well-defined, and according to prior studies, immune checkpoint inhibitors can be disrupted at least by cardiac immune tolerance mediated by the CTLA-4, PD-1 pathway. In addition, T-cell proliferation attacks the heart as well as tumor cells.
Patients currently receiving immune checkpoint inhibitor therapy for cardiovascular events during treatment are primarily seeking cardiology consultation and are prone to missed diagnosis in low-risk patients. There is now a lack of clinically straightforward predictive scoring systems for cardiovascular practical risk in patients receiving immune checkpoint inhibitor therapy, and a lack of scientific knowledge of the extent of actual cardiovascular risk in patients receiving immune checkpoint inhibitor therapy.
Disclosure of Invention
The invention aims to provide a method, a system and a device for evaluating the cardiotoxicity of an immune checkpoint inhibitor, which are used for summarizing high-risk factors of cardiovascular events of the immune checkpoint inhibitor and distributing weights according to the influence of different risk factors on the cardiovascular events so as to finish evaluation of the cardiotoxicity of the immune checkpoint inhibitor.
In order to achieve the above object, one aspect of the present invention provides a method for evaluating cardiac toxicity of an immune checkpoint inhibitor, comprising:
acquiring diagnosis and treatment information of an immune checkpoint inhibitor patient input on an interface for disease condition evaluation, and extracting a risk factor for evaluating cardiotoxicity according to the diagnosis and treatment information;
setting a data index for measuring the risk factor;
establishing a risk evaluation model for evaluating the cardiotoxicity of the immune checkpoint inhibitor patient according to the risk factor and the data index thereof;
the risk assessment model counts the data indexes of the risk factors to calculate the risk assessment value of the immune checkpoint inhibitor patient, and obtains a corresponding clinical diagnosis conclusion according to the risk assessment value.
Further, in the process of establishing the risk assessment model, the method further includes:
and setting the weight of the data index according to different risk factors, and calculating the risk assessment value of the patient according to the data index with different weights.
The risk factors include prior exposure of the patient to anthracycline therapy, prior history of mediastinal/left chest radiotherapy, comorbid cardiovascular disease, prior or combined anti-vascular or taxoid or other immunotherapy or anti-HER 2 therapy, new chest distress, breathlessness, history of dyspnea, new lower limb edema or worsening of original edema, new blood pressure changes, elevated troponin, elevated natriuretic peptides, elevated D dimers, electrocardiogram and cardiac overload.
The data index of the risk factor is 1 if the anthracycline treatment is received before;
for example, the data index of the risk factor of the patient is 1 in the past history of mediastinal/left chest radiotherapy.
If the patient is treated by the previous treatment or the combined treatment of the anti-vascular history, the data index of the risk factor is 1;
the data index of the risk factor of the patient is 1 if the patient is treated previously or combined with taxus;
the data index of the risk factor of the patient is 1 as before or in combination with other immunotherapy;
the data index for the risk factor for the patient, as previously treated or in combination with Her2, is 1.
If the patient has a history of combined basic cardiovascular diseases, the data index of the risk factor is 1;
if the patient has a history of previous mediastinum/left chest radiotherapy, the data index of the risk factor is 1;
if the new blood pressure of the patient is changed with systolic pressure more than 140mmHg and/or diastolic pressure more than 90mmHg, the data index of the risk factor is 2;
if the patient has elevated troponin (cTnT/I) as a baseline elevation, the data index for the risk factor is 2;
if the patient's troponin elevation (cTnT/I) is a progressive elevation, the data index for the risk factor is 3;
e.g. a baseline increase in natriuretic peptide (BNP/NT-proBNP) in the patient, with a data index for a risk factor of 1;
such as a progressive increase in the natriuretic peptide (BNP/NT-proBNP) of the patient, with a data index for a risk factor of 2;
if the patient's D dimer is baseline elevated, the data index for the risk factor is 1;
if the patient's D dimer is progressively elevated, the data index for the risk factor is 2.
If the electrocardiogram of the patient is abnormal, the data index of the risk factor is 2;
if the heart of the patient exceeds the current abnormality, the data index of the risk factor is 2;
if the patient's heart has an LVEF < 50% or an LVEF drop of more than 10% from baseline, the data index for the risk factor is 3;
further, the clinical diagnosis conclusion output by the evaluation model comprises:
grade a, low risk, continue treatment;
grade B, intermediate risk, close monitoring during treatment;
grade C, high risk, stopping treatment, and suggesting a visit to the department of cardiology.
In another aspect, the invention also provides a system for assessing the cardiotoxicity of an immune checkpoint inhibitor, comprising:
the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring diagnosis and treatment information of an immune checkpoint inhibitor patient input on an interface for disease condition evaluation and extracting a risk factor for evaluating cardiotoxicity according to the diagnosis and treatment information;
a second module for setting a data index for measuring the risk factor;
a third module for establishing a risk assessment model for assessing cardiotoxicity of immune checkpoint inhibitor patients based on the risk factors and their data indicators;
and the fourth module is used for counting the data indexes of the risk factors by the risk assessment model to calculate the risk assessment value of the immune checkpoint inhibitor patient, and acquiring a corresponding clinical diagnosis conclusion according to the risk assessment value.
In another aspect, the present invention also provides a storage device having a plurality of instructions stored thereon, the instructions being adapted to be loaded by a processor to perform the steps of the method for assessing immune checkpoint inhibitor cardiotoxicity according to any one of claims 1 to 10.
The invention provides an assessment method, a system and a storage device of cardiotoxicity of an immune checkpoint inhibitor, aiming at the situation that oncologists and breast surgeons have uncertain occurrence risk of cardiovascular disease complications and easily ignore early clinical manifestations of CVD so as to delay treatment and cause adverse clinical events, a risk assessment calculator is adopted to assist non-cardiologists in assessing the risk of the cardiovascular events, the risk assessment calculator can help the non-cardiologists to rapidly identify high-risk groups at the early stage and seek professional treatment suggestions in a cardiologist, the occurrence of the cardiovascular events is favorably reduced, and the severity of the events is reduced.
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 only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flow chart of a method of assessing immune checkpoint inhibitor cardiotoxicity in accordance with an embodiment of the present invention.
Fig. 2 is a system block diagram of an immune checkpoint inhibitor cardiotoxicity assessment system in accordance with an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. A
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
Where similar language of "first/second" appears in the specification, the following description is added, and where reference is made to the term "first \ second \ third" merely for distinguishing between similar items and not for indicating a particular ordering of items, it is to be understood that "first \ second \ third" may be interchanged both in particular order or sequence as appropriate, so that embodiments of the application described herein may be practiced in other than the order illustrated or described herein.
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 application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.
The invention provides an assessment method, a system and a storage device of an immune checkpoint inhibitor cardiotoxicity, aiming at the situation that oncologists and breast surgeons have uncertain occurrence risk of cardiovascular disease complications and easily ignore early clinical manifestations of CVD so as to delay treatment and cause adverse clinical events, a risk assessment calculation method is adopted to assist non-cardiologists in assessing the risk of the cardiovascular events, and the risk assessment method can help the non-cardiologists to quickly identify high-risk groups at early stage and search professional treatment suggestions in cardiologists, thereby being beneficial to reducing the occurrence of the cardiovascular events and reducing the occurrence severity.
In a specific embodiment, in order to facilitate the use of medical staff during work, the present invention uses a mobile phone as an electronic device for operating the method of the present invention, and the electronic device includes: a processor and a memory for storing processor-executable instructions. Wherein the executable instructions stored in the memory are configured to run a wechat applet of the method for assessing cardiac toxicity of an immune checkpoint inhibitor of the present invention, the wechat applet being in data communication with other terminals, servers or other modalities of equipment for performing background program computations.
Hereinafter, a method, a system, and a storage device for evaluating the cardiotoxicity of an immune checkpoint inhibitor according to embodiments of the present invention will be described with reference to the accompanying drawings, and first, a method for evaluating the cardiotoxicity of an immune checkpoint inhibitor according to embodiments of the present invention will be described with reference to the accompanying drawings.
Fig. 1 is a flow chart of a method of assessing immune checkpoint inhibitor cardiotoxicity in accordance with an embodiment of the present invention. As shown in fig. 1, the evaluation method includes the steps of:
and S1, acquiring diagnosis and treatment information of the immune checkpoint inhibitor patient input on the disease condition evaluation interface, and extracting a risk factor for evaluating the cardiotoxicity according to the diagnosis and treatment information.
And S2, setting a data index for measuring the risk factor.
And S3, establishing a risk assessment model for assessing the cardiotoxicity of the immune checkpoint inhibitor patient according to the risk factors and the data indexes thereof.
And S4, the risk assessment model counts the data indexes of the risk factors to calculate the risk assessment value of the immune checkpoint inhibitor patient, and acquires the corresponding clinical diagnosis conclusion according to the risk assessment value.
Specifically, the treatment information of the immune checkpoint inhibitor patient in step S1 includes personal information, case, cardiovascular event, history of radiotherapy, history of chemotherapy, assay result, electrocardiogram, and cardiac rhythm of the patient. The input mode of the treatment information can be realized by handwriting input, an OCR mode, multi-source data import, network transmission and other modes.
In one embodiment of the present invention, after obtaining the clinical information, risk factors for assessing cardiotoxicity are extracted therefrom. Risk factors are high risk factors that summarize the evaluation of immune checkpoint inhibitor cardiovascular events, including: including previous exposure of patients to anthracycline therapy, previous history of mediastinal/left chest radiotherapy, comorbid basic cardiovascular disease, previous or combined anti-vascular or taxus or other immunotherapy or anti-HER 2 therapy, new chest distress, breathlessness, history of dyspnea, new lower limb edema or worsening of original edema, new blood pressure changes, elevated troponin, elevated natriuretic peptides, elevated D-dimers, electrocardiogram and cardiac overload.
Anthracyclines, including doxorubicin, epirubicin, and the like, can lead to potential risks of left ventricular dysfunction, heart failure, myocarditis, pericarditis, atrial fibrillation, ventricular tachycardia, ventricular fibrillation, and the like.
Paclitaxel drugs can cause bradycardia, heart block, and ectopic beating of the ventricles.
anti-Her 2 therapeutic agents include trastuzumab, pertuzumab, and may cause left-heart insufficiency and heart failure.
Immune checkpoint inhibitor patients with combined underlying cardiovascular disease are more prone to adverse cardiovascular events during treatment.
History of radiotherapy, radiotherapy increases the risk of coronary heart disease, cardiomyopathy, valvular disease, pericardial disease and arrhythmia. Among them, left breast radiotherapy has a higher risk.
The common clinical manifestations of the new chest distress, short breath and dyspnea and heart disease comprise chest distress, short breath, dyspnea and the like, and the occurrence of the symptoms usually indicates that the patients have the conditions of cardiac insufficiency, pericardial effusion, pulmonary embolism and the like.
The new edema or the original edema of the lower limbs is aggravated, the new edema or the original edema is aggravated under the condition of cardiac insufficiency and the like, and when the asymmetric edema of the lower limbs occurs, the vascular thrombosis of the lower limbs needs to be highly alarmed.
Newly developed blood pressure changes, chemotherapy drugs can cause blood pressure fluctuations when blood pressure exceeds the normal range: systolic pressure is more than 140mmHg or less than 90mmHg, and/or diastolic pressure is more than 90mmHg (systolic pressure is more than 130mmHg and/or diastolic pressure is more than 80mmHg for diabetic patients), and adverse reaction of the chemical drugs needs to be considered.
Increased troponin, which has been shown to be predictive of decreased LVEF within 3 days after high dose chemotherapy. Troponin has excellent negative predictive value for the occurrence of cardiotoxicity during and immediately after treatment.
Elevated natriuretic peptides currently lack consensus regarding the role of NT-proBNP in the diagnosis and prognosis of immune checkpoint inhibitor cardiotoxicity. Some studies have shown that NT-proBNP can predict cardiotoxicity in patients with immune checkpoint inhibitors; other studies have shown that BNP has a unique advantage in detecting asymptomatic left ventricular systolic dysfunction. One study showed that NT-proBNP is superior to troponin in detecting subclinical left ventricular dysfunction; another study showed that NT-proBNP predicts 1-year mortality. However, as natriuretic peptides are elevated, it is necessary to exclude individual differences, changes with age, weight, renal function and BMI, and to carefully consider interference from these factors in interpreting the data.
The D-dimer is increased, a tumor patient is in a high-coagulation state, and when the D-dimer is increased, whether pulmonary embolism, lower limb thrombosis and the like are combined or not is excluded, the index has high sensitivity and low specificity.
Changes in electrocardiogram, anthracyclines, alkylating agents and the like can cause atrial fibrillation, ventricular premature and even ventricular fibrillation. Paclitaxel is prone to complications such as conduction block and bradycardia. Cardiotoxicity such as QTc prolongation occurs with cyclin-dependent kinase 4/6 inhibitors. When the electrocardiogram examination detects new arrhythmia, the occurrence of toxic and side effects related to chemotherapy drugs needs to be considered, and intervention should be performed as early as possible.
The treatment of cardiac insufficiency is likely to be caused by the therapeutic drugs of immune checkpoint inhibitors. The heart overload is an important detection means for determining whether the heart has structural and functional abnormalities, and when the heart overload occurs, the left ventricular ejection fraction is preserved (LVEF is more than or equal to 45 percent and less than 55 percent) or reduced (LVEF is less than 45 percent), which indicates that the patient has cardiac insufficiency.
In recent years, the role of cardiac MRI in detecting cardiotoxicity associated with cancer therapy has been studied. In addition to detecting early subclinical LVEF decline, cardiac MRI and MUGA can also detect subtle changes in cardiac architecture to help pinpoint specific causes of LVEF abnormalities. Thus, the toxic effects associated with cancer treatment can be detected; but clinical work is limited by inspection costs and limited supply.
In step S2, a data index for measuring the risk factor is set, and the data index can be weighted according to different risk factors in the model to adjust the accuracy of model calculation.
In a specific embodiment, the setting of the data index according to the different optional risk factors includes:
the data for the risk factor is 1 as in the prior anthracycline therapy.
For example, the data index of the risk factor of the patient is 1 in the past history of mediastinal/left chest radiotherapy.
The data index of the risk factor of the patient is 1 if the patient is treated by the previous treatment or the combination of the previous treatment and the anti-vascular history treatment.
The data index for the risk factor for the patient, either prior to or in combination with treatment with taxanes, is 1.
The data index for the risk factor for a patient, either prior to or in combination with other immunotherapy, is 1.
The data index for the risk factor for the patient, as previously treated or in combination with Her2, is 1.
If the patient has a history of combined basic cardiovascular diseases, the data index of the risk factor is 1.
For example, the data index of the risk factor of the patient is 1 in the past history of mediastinal/left chest radiotherapy.
If the new blood pressure of the patient is changed by the systolic pressure of more than 140mmHg and/or the diastolic pressure of more than 90mmHg, the data index of the risk factor is 2.
If the patient's troponin elevation (cTnT/I) is an elevation at baseline, the data index for the risk factor is 2.
For example, the patient's troponin elevation (cTnT/I) is a progressive elevation, and the data for the risk factor is 3.
For example, the patient has an elevated baseline natriuretic peptide (BNP/NT-proBNP) and a risk factor data index of 1.
Such as a progressive increase in the natriuretic peptide (BNP/NT-proBNP) of the patient, the data index for the risk factor is 2.
If the patient's D dimer is baseline elevated, the data index for the risk factor is 1.
If the patient's D dimer is progressively elevated, the data index for the risk factor is 2.
If the electrocardiogram of the patient is abnormal, the data index of the risk factor is 2.
If the heart of the patient is out of order, the data index of the risk factor is 2.
For example, the patient's heart has an LVEF < 50% or an LVEF drop of more than 10% from baseline, with a risk factor of 3.
In step S3, a risk assessment model for assessing the cardiac toxicity of the immune checkpoint inhibitor patient is established according to the risk factors and their data indexes.
The risk factors and data indicators of the risk assessment model can be expressed in the following table.
In step S4, the risk assessment model calculates the data index of the risk factor to calculate the risk assessment value of the immune checkpoint inhibitor patient, and obtains the corresponding clinical diagnosis conclusion according to the risk assessment value. For example, when the risk assessment value exceeds a set threshold, then a clinical diagnostic conclusion associated with the threshold is output to complete the diagnosis of the patient.
In a particular embodiment, evaluating the clinical diagnostic conclusions output by the model may include:
grade A (0-4 points), low risk, continue treatment;
grade B (5-8 points), intermediate risk, close monitoring during treatment;
grade C (not less than 9 points), high risk, stopping treatment, and suggesting a diagnosis for cardiology.
Fig. 2 is a system block diagram of an immune checkpoint inhibitor cardiotoxicity evaluation system according to an embodiment of the present invention, and as shown in fig. 2, an immune checkpoint inhibitor cardiotoxicity evaluation system according to an embodiment of the present invention includes:
the system comprises a first module 1, a second module and a third module, wherein the first module is used for acquiring diagnosis and treatment information of an immune checkpoint inhibitor patient input on an interface for disease condition evaluation and extracting a risk factor for evaluating cardiotoxicity according to the diagnosis and treatment information;
a second module 2, configured to set a data index for measuring the risk factor;
a third module 3, configured to establish a risk assessment model for assessing cardiotoxicity of immune checkpoint inhibitor patients according to the risk factors and data indicators thereof;
and the fourth module 4 is used for counting the data indexes of the risk factors by the risk assessment model to calculate the risk assessment value of the immune checkpoint inhibitor patient, and acquiring a corresponding clinical diagnosis conclusion according to the risk assessment value.
Specifically, the treatment information acquired by the first module 1 includes personal information of the patient, case, cardiovascular events, history of radiotherapy, history of chemotherapy, test results, electrocardiogram, and cardiac arrhythmia. The first module 1 realizes the input of treatment information through modes such as handwriting input, an OCR mode, multi-source data import, network transmission and the like.
In one embodiment of the present invention, after acquiring the diagnosis and treatment information, the first module 1 needs to extract a risk factor for evaluating cardiotoxicity. Risk factors are high risk factors that summarize the evaluation of immune checkpoint inhibitor cardiovascular events, including: including previous exposure of patients to anthracycline therapy, previous history of mediastinal/left chest radiotherapy, comorbid basic cardiovascular disease, previous or combined anti-vascular or taxus or other immunotherapy or anti-HER 2 therapy, new chest distress, breathlessness, history of dyspnea, new lower limb edema or worsening of original edema, new blood pressure changes, elevated troponin, elevated natriuretic peptides, elevated D-dimers, electrocardiogram and cardiac overload.
And setting a data index for measuring the risk factor, wherein the data index can set the weight of the data index in the model according to different risk factors so as to adjust the calculation accuracy of the model.
In a specific embodiment, the second module 2 sets the data index according to different optional risk factors, including:
the data for the risk factor is 1 as in the prior anthracycline therapy.
For example, the data index of the risk factor of the patient is 1 in the past history of mediastinal/left chest radiotherapy.
The data index of the risk factor of the patient is 1 if the patient is treated by the previous treatment or the combination of the previous treatment and the anti-vascular history treatment.
The data index for the risk factor for the patient, either prior to or in combination with treatment with taxanes, is 1.
The data index for the risk factor for a patient, either prior to or in combination with other immunotherapy, is 1.
The data index for the risk factor for the patient, as previously treated or in combination with Her2, is 1.
If the patient has a history of combined basic cardiovascular diseases, the data index of the risk factor is 1.
For example, the data index of the risk factor of the patient is 1 in the past history of mediastinal/left chest radiotherapy.
If the new blood pressure of the patient is changed by the systolic pressure of more than 140mmHg and/or the diastolic pressure of more than 90mmHg, the data index of the risk factor is 2.
If the patient's troponin elevation (cTnT/I) is an elevation at baseline, the data index for the risk factor is 2.
For example, the patient's troponin elevation (cTnT/I) is a progressive elevation, and the data for the risk factor is 3.
For example, the patient has an elevated baseline natriuretic peptide (BNP/NT-proBNP) and a risk factor data index of 1.
Such as a progressive increase in the natriuretic peptide (BNP/NT-proBNP) of the patient, the data index for the risk factor is 2.
If the patient's D dimer is baseline elevated, the data index for the risk factor is 1.
If the patient's D dimer is progressively elevated, the data index for the risk factor is 2.
If the electrocardiogram of the patient is abnormal, the data index of the risk factor is 2.
If the heart of the patient is out of order, the data index of the risk factor is 2.
For example, the patient's heart has an LVEF < 50% or an LVEF drop of more than 10% from baseline, with a risk factor of 3.
In a specific embodiment, the third module 3 builds a risk assessment model for assessing the cardiotoxicity of immune checkpoint inhibitor patients based on the risk factors and their data indicators.
The risk factors and data indicators of the risk assessment model can be expressed in the following table.
In a specific embodiment, the clinical diagnosis conclusion output by the fourth module 4 may include:
grade A (0-4 points), low risk, continue treatment;
grade B (5-8 points), intermediate risk, close monitoring during treatment;
grade C (not less than 9 points), high risk, stopping treatment, and suggesting a diagnosis for cardiology.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. A method for assessing immune checkpoint inhibitor cardiotoxicity, comprising:
acquiring diagnosis and treatment information of an immune checkpoint inhibitor patient input on an interface for disease condition evaluation, and extracting a risk factor for evaluating cardiotoxicity according to the diagnosis and treatment information;
setting a data index for measuring the risk factor;
establishing a risk evaluation model for evaluating the cardiotoxicity of the immune checkpoint inhibitor patient according to the risk factor and the data index thereof;
the risk assessment model counts the data indexes of the risk factors to calculate the risk assessment value of the immune checkpoint inhibitor patient, and obtains a corresponding clinical diagnosis conclusion according to the risk assessment value.
2. The method of claim 1, wherein during the establishment of the risk assessment model, the method further comprises:
and setting the weight of the data index according to different risk factors, and calculating the risk assessment value of the patient according to the data index with different weights.
3. The method of any of claims 1 or 2, wherein the risk factors comprise prior exposure of the patient to anthracycline therapy, prior history of mediastinal/left chest radiotherapy, comorbidities with underlying cardiovascular disease, prior or combined treatment with anti-vascular or taxus or other immunotherapy or anti-HER 2 therapy, new chest tightness, breathlessness, history of dyspnea, new lower limb edema or worsening of previous edema, new blood pressure changes, elevated troponin, elevated natriuretic peptides, elevated D-dimers, electrocardiogram and cardiac hyperactive heart.
4. The method of claim 3, wherein the risk factor data for a previous anthracycline therapy is 1;
for example, the data index of the risk factor of the patient is 1 in the past history of mediastinal/left chest radiotherapy.
5. The method of claim 3, wherein the immune checkpoint inhibitor is administered to the subject in need of treatment,
if the patient is treated by the previous treatment or the combined treatment of the anti-vascular history, the data index of the risk factor is 1;
the data index of the risk factor of the patient is 1 if the patient is treated previously or combined with taxus;
the data index of the risk factor of the patient is 1 as before or in combination with other immunotherapy;
the data index for the risk factor for the patient, as previously treated or in combination with Her2, is 1.
6. The method of claim 3, wherein the immune checkpoint inhibitor cardiotoxicity assessment method,
if the patient has a history of combined basic cardiovascular diseases, the data index of the risk factor is 1;
for example, the data index of the risk factor of the patient is 1 in the past history of mediastinal/left chest radiotherapy.
7. The method of claim 3, wherein the immune checkpoint inhibitor cardiotoxicity assessment method,
if the new blood pressure of the patient is changed by the systolic pressure of more than 140mmHg and/or the diastolic pressure of more than 90mmHg, the data index of the risk factor is 2.
8. The method of claim 3, wherein the immune checkpoint inhibitor cardiotoxicity assessment method,
if the patient has elevated troponin (cTnT/I) as a baseline elevation, the data index for the risk factor is 2;
if the patient's troponin elevation (cTnT/I) is a progressive elevation, the data index for the risk factor is 3;
e.g. a baseline increase in natriuretic peptide (BNP/NT-proBNP) in the patient, with a data index for a risk factor of 1;
such as a progressive increase in the natriuretic peptide (BNP/NT-proBNP) of the patient, with a data index for a risk factor of 2;
if the patient's D dimer is baseline elevated, the data index for the risk factor is 1;
if the patient's D dimer is progressively elevated, the data index for the risk factor is 2.
9. The method of claim 3, wherein the immune checkpoint inhibitor cardiotoxicity assessment method,
if the electrocardiogram of the patient is abnormal, the data index of the risk factor is 2;
if the heart of the patient exceeds the current abnormality, the data index of the risk factor is 2;
for example, the patient's heart has an LVEF < 50% or an LVEF drop of more than 10% from baseline, with a risk factor of 3.
10. The method for assessment of cardiac toxicity of an immune checkpoint inhibitor as claimed in either of claims 1 or 2, wherein the clinical diagnostic conclusions outputted by the assessment model include:
grade a, low risk, continue treatment;
grade B, intermediate risk, close monitoring during treatment;
grade C, high risk, stopping treatment, and suggesting a visit to the department of cardiology.
11. An immune checkpoint inhibitor cardiotoxicity assessment system comprising:
the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring diagnosis and treatment information of an immune checkpoint inhibitor patient input on an interface for disease condition evaluation and extracting a risk factor for evaluating cardiotoxicity according to the diagnosis and treatment information;
a second module for setting a data index for measuring the risk factor;
a third module for establishing a risk assessment model for assessing cardiotoxicity of immune checkpoint inhibitor patients based on the risk factors and their data indicators;
and the fourth module is used for counting the data indexes of the risk factors by the risk assessment model to calculate the risk assessment value of the immune checkpoint inhibitor patient, and acquiring a corresponding clinical diagnosis conclusion according to the risk assessment value.
12. A storage device, wherein the storage medium stores a plurality of instructions adapted to be loaded by a processor to perform the steps of the method for assessing immune checkpoint inhibitor cardiotoxicity according to any one of claims 1 to 10.
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| CN112967750A (en) * | 2021-03-23 | 2021-06-15 | 复旦大学附属中山医院 | Model for predicting clopidogrel antiplatelet effect and application thereof |
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