Chronic obstructive pulmonary disease prognosis / cost-utility evaluation method and model

Abstract

The invention relates to the technical field of medical evaluation, and particularly discloses a chronic obstructive pulmonary disease prognosis and cost-utility evaluation model which is realized through combination of a data collection module, a data design module, a prognosis analysis module, a cost-utility evaluation module and the like. The model can effectively predict prognosis conditions and cost utility conditions of chronic obstructive pulmonary disease treatment.

Description

Technical Field

[0001] The present application relates to the field of medical evaluation technology, and in particular to a chronic obstructive pulmonary disease prognosis / cost-utility evaluation method and model. Technical Background

[0002] Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease. Different patients have different symptoms. Some patients mainly have frequent acute exacerbations, while others mainly have dyspnea. The phenotype of COPD is defined as one or a group of disease characteristics, which can describe the differences between different COPD patients and are related to clinical prognosis (such as symptoms, acute exacerbations, efficacy, disease progression rate, and death). Patients with different COPD phenotypes have different clinical outcomes. Therefore, it is necessary to clarify the phenotypic characteristics of various types of COPD patients, select more individualized treatment plans, more accurate prognostic assessments, and monitoring indicators for patients with different manifestations, thereby improving clinical efficacy and enhancing the quality of life of patients.

[0003] In the context of disease management, acute exacerbation is an important clinical event of COPD, which leads to a decline in quality of life to a large extent. Studies have also shown that the quality of life of COPD patients assessed by daily living activities, emotional function, social role function and recreational pastimes is impaired in all aspects compared with healthy subjects. The concept of "quality of life" in the medical field refers to the comprehensive state of physical, psychological and social activities of patients during illness or treatment. Pulmonary function test is currently a recognized objective indicator for detecting airflow limitation, the "gold standard" for the diagnosis of COPD, and the most commonly used indicator for the evaluation of the severity of COPD, disease progression monitoring, prognosis and treatment response. Some studies have pointed out that only using clinical function indicators may underestimate the clinical manifestations of patients and overestimate the effect of clinical treatment. In addition, the clinical manifestations of some patients are not completely consistent with the pulmonary function level classification.

[0004] Acute exacerbation of COPD According to the Global Initiative for Chronic Obstructive Lung Disease (GOLD), the Chinese Expert Consensus on the Diagnosis and Treatment of Acute Exacerbations of Chronic Obstructive Lung Disease (AECOPD) (2017 Update), and the Guidelines for Primary Care Diagnosis and Treatment of COPD (2018), domestic and foreign guidelines have made recommendations for the management of stable and acute exacerbations of COPD. However, due to the promotion of the GOLD guidelines and the differences in doctors' compliance with them, as well as the influence of drug accessibility and medical insurance policies, in actual clinical practice, the treatment of COPD varies in different regions or between patients. Moreover, the research evidence recommended by domestic and foreign COPD guidelines to guide clinical diagnosis and treatment is mostly based on randomized controlled studies with strict inclusion criteria. Most of the selected patients are "standard" COPD patients, and other respiratory diseases such as bronchial asthma, bronchiectasis, and lung cancer have been excluded. In clinical diagnosis and treatment practice, the conditions of patients vary, so it is not clear whether the conclusions drawn in well-designed randomized controlled studies are applicable to COPD patients in the real world. There is currently insufficient real-world clinical practice data to determine its efficacy in the treatment of COPD.

[0005] In view of this, this application is proposed. Summary of the invention

[0006] To solve the above technical problems, this application investigates the diagnosis and treatment status of AECOPD patients in Shanxi Province, establishes a disease database of COPD patients in Shanxi Province, analyzes the disease characteristics and clinical outcomes of patients, and thus establishes a model to predict the risk of acute exacerbation, explores individualized treatment models for COPD, and provides a reference for the formulation of medical and health policies. Based on this research result, this application specifically proposes the following technical solutions:

[0007] The present application first provides a method for evaluating the prognosis of chronic obstructive pulmonary disease, a model for evaluating the prognosis of chronic obstructive pulmonary disease (COPD), characterized in that the model includes the following modules:

[0008] 1) Data collection module: used to collect clinical medical records and follow-up data of patients with acute exacerbation of COPD;

[0009] 2) Data design module: used to design baseline data questionnaire;

[0010] 3) Prognostic analysis module: including a. variable assignment and preprocessing for baseline data questionnaire; and b. prognostic analysis of adverse outcomes and factors affecting quality of life in COPD patients.

[0011] In some aspects, the 1) data collection module is specifically used to: collect clinical medical record data and follow-up data of patients with acute exacerbation of COPD based on a prospective observational study design;

[0012] Preferably, the follow-up data are the follow-up data at 3, 6, 9, 12, 15, 18, 21, and 24 months after discharge;

[0013] More preferably, the acute exacerbation of COPD patients refers to patients whose respiratory symptoms are acutely exacerbated, resulting in the need for additional treatment; the patients have at least two or more symptoms of cough, increased sputum volume, purulent sputum, dyspnea or wheezing, including aggravation of existing symptoms and new symptoms, which last for at least 48 hours, exceed daily variation, and require additional treatment;

[0014] Further preferably, the inclusion and exclusion criteria of the patients are as follows:

[0015] Inclusion criteria: (1) age ≥ 40 years, regardless of gender; (2) patients diagnosed with COPD by pulmonary function test, with FEV1 / FVC < 0.7 after inhalation of bronchodilators; (3) confirmed as acute exacerbation of COPD; (4) subjects voluntarily participated in this clinical trial and signed the informed consent form.

[0016] Exclusion criteria: (1) severe mental or neurological disorders that affect informed consent and / or the expression or observation of adverse reactions; (2) unable to complete the first questionnaire and undergo pulmonary function tests; (3) subjects who are participating in other drug clinical trials or intervention studies.

[0017] Exit cohort criteria: (1) The subject requests to withdraw from the clinical trial; (2) A serious adverse event or death occurs during the trial; (3) The patient is lost to follow-up; (4) The investigator or (and) the sponsor considers that the patient is not suitable to continue participating in this application.

[0018] In some aspects, the 2) data design module includes two questionnaires: a baseline questionnaire and a follow-up questionnaire:

[0019] The contents of the baseline questionnaire included basic information of the patient, laboratory test results, treatment measures, diagnosis and treatment costs, SGRQ questionnaire, CAT questionnaire, PEACE questionnaire, and mMRC questionnaire;

[0020] The contents of the follow-up questionnaire included basic information of the patient, CAT questionnaire, SGRQ questionnaire, adverse outcomes and other follow-up information.

[0021] The basic information in the questionnaire includes:

[0022] The basic information of the patient, including: gender, age, occupation, medical insurance, marital status, admission route, number of hospital days, smoking index (number of cigarettes smoked per day × number of years of smoking), body mass index (BMI), personal history (including drinking history, family history, allergy history, surgical history, etc.) and whether the current illness has received treatment.

[0023] The test results include: red blood cell count (WBC), white blood cell count (BRC), hemoglobin concentration (HGB), hematocrit (HCT), platelet count (PLT), absolute lymphocyte value (LYMPH#), absolute neutrophil value (NEUT#), absolute eosinophil value (EO#), lymphocyte percentage (LYMPH%), neutrophil percentage (NEUT%), eosinophil percentage (EO%), alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT / AST, albumin (ALB), albumin (ALB), total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL), urea (UREA), creatinine (CREA), potassium (K), sodium (Na), chloride (Cl), calcium (Ca), urine specific gravity (SG), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and D-dimer (D-Dimer).

[0024] The treatment measures include: blood pressure monitoring, blood oxygen monitoring, short-acting bronchodilators, glucocorticoids, antibiotics (including whether used in combination), theophylline drugs, expectorants or antioxidants (including ambroxol, eucalyptol, bromhexine, N-acetylcysteine, carbocysteine, fudosteine, erdosteine) and nebulization therapy.

[0025] Medical treatment costs include: total cost, service fee, diagnosis fee, drug fee and triple fee (service fee + diagnosis fee + drug fee).

[0026] The adverse outcomes were acute exacerbation, outpatient visit, rehospitalization, or death within one year after discharge.

[0027] In some aspects, in the 3) prognostic analysis module: the variable assignment and preprocessing of the baseline data questionnaire SGRQ specifically include:

[0028] Variable assignment and preprocessing of the baseline data questionnaire, the variable assignment table is as follows:

[0029]

[0030]

[0031] In some aspects, in the 3) prognostic analysis module, the COPD patient adverse outcome prognostic analysis comprises the following steps:

[0032] Adverse outcomes were set as acute exacerbation, outpatient visit, rehospitalization and death. The inclusion test level was set at 0.05, and the exclusion test level was set at 0.10. A stepwise screening strategy was used to screen out the variables of hospitalization duration, treatment for this onset, hematocrit, urine specific gravity, and ambroxol. Age, gender, BMI and smoking index were then included to construct a Cox proportional hazard model for univariate and multivariate analysis. Preferably, the smoking index, hospitalization duration and urine specific gravity were screened out to have statistical significance for prognosis.

[0033] Preferably, the steps further include:

[0034] 1) After adjusting adverse outcomes to acute exacerbation, rehospitalization, and death, a Cox proportional hazard model was constructed based on the same method as above to conduct univariate and multivariate analysis to confirm whether the prognostic factors changed after the adverse outcomes were adjusted;

[0035] 2) Adjustment of screening strategy: The stepwise screening strategy was changed to the inclusion test level set at 0.05, the exclusion test level set at 0.15, and the inclusion test level set at 0.10, the exclusion test level set at 0.15, respectively, and the effects of different screening strategies on the screening of factors affecting the original adverse outcomes and the adjusted adverse outcomes were analyzed.

[0036] Combined with the adjustments, the main prognostic factors were comprehensively determined:

[0037] When the adverse outcomes were acute exacerbation, outpatient visit, rehospitalization and death, the basic prognostic factors were smoking index, length of hospital stay and urine specific gravity; when the adverse outcomes were acute exacerbation, rehospitalization and death, the main prognostic factors were length of hospital stay, SGRQ total score and NAC.

[0038] In some aspects, in the 3) prognosis analysis module, in the analysis of factors affecting quality of life:

[0039] For the total SGRQ score, the unit value of difference (UVD) of the total SGRQ score was constructed based on the minimal clinically important difference (MCID):

[0040]

[0041] Among them, SGRQ i is the total SGRQ score at follow-up time i, MCID SGRQ is the MCID of the total SGRQ score; SGRQThe dependent variable was included in the model for analysis, which means: when other variables remain unchanged, the total SGRQ score increases (or decreases) by a certain MCID due to a certain factor change; when UVD is included in the model, SGRQ When the absolute value of the change is greater than 1, it indicates that the change in the total score of SGRQ may have clinical practical significance;

[0042] The analysis of factors affecting life quality includes the following steps:

[0043] 1) The dependent variable is set as the unit change value of the total SGRQ score (UVD SGRQ );

[0044] 2) Independent variables include basic information of patients, test results, and treatment measures;

[0045] 3) Construct the generalized estimation model GEE to analyze the factors affecting quality of life;

[0046] 4) In the process of variable screening, the model with smaller QIC and QICC is selected as the optimal model; the influencing factors of quality of life are determined based on the model;

[0047] Preferably, the factors affecting the quality of life are age, smoking index, mMRC score and follow-up duration.

[0048] The present application also provides a model for cost-utility evaluation of chronic obstructive pulmonary disease (COPD), the model comprising the following modules:

[0049] 1) Data collection module: used to collect clinical medical records and follow-up data of patients with acute exacerbation of COPD;

[0050] 2) Data design module: used to design the COPD baseline data questionnaire;

[0051] 3) Cost-utility analysis module: a is used for variable assignment and preprocessing of the baseline data questionnaire, and b is used for cost-utility analysis.

[0052] In some aspects, the costs include total charges, service charges, diagnostic charges, drug charges, and triple charges (service charges + diagnostic charges + drug charges).

[0053] In some aspects, the data collection module and the data design module are the same as the data collection module and the data design module in the aforementioned prognostic evaluation model.

[0054] In some aspects, in the 3) cost-utility analysis module, the variable assignments of the baseline data questionnaire are as follows:

[0055]

[0056]

[0057] Among them, the said SGRQ change score per 100 yuan is defined as the difference between the baseline and three-month SGRQ as a utility indicator for quantifying hospitalization;

[0058] The pretreatment includes: deleting the deceased cases and the cases without recorded hospitalization expenses in the whole study population, selecting the cases with three-month follow-up records to form the cost-utility subgroup, and dividing the subgroup into COPD acute exacerbation group and non-COPD acute exacerbation group according to the main discharge diagnosis.

[0059] In some aspects, in the 3) cost-utility analysis module, the cost-utility analysis comprises the following steps:

[0060] a. According to whether short-acting bronchodilators and glucocorticoids were used together, the patients were divided into a combined medication group and a non-combination medication group, and a cost-effectiveness difference analysis was performed;

[0061] b. Patients with acute exacerbation of COPD were divided into the antibiotic use group and the non-antibiotic use group, and the cost-utility difference between the two groups was analyzed;

[0062] c. Analyze the factors affecting cost-utility of patients with acute exacerbation of COPD;

[0063] Preferably, in a, whether there is a difference in cost-effectiveness between the combined medication group and the non-combination medication group, the total cost of a hospitalized patient is C1, the drug cost is C2, the diagnosis fee is C3, the service fee is C4, the triple fee (service fee + diagnosis fee + drug fee) is C5, the difference in SGRQ between the baseline and three months of the patient is U, and the formula Y is used. i =100U / C, calculate Y1, Y2, Y3, Y4, Y5 respectively. i Two independent sample t tests were performed with as the dependent variable and combined medication (combination of short-acting bronchodilators and glucocorticoids) as the independent variable;

[0064] In b, is there a difference in cost-utility between the antibiotic group and the non-antibiotic group for patients with acute exacerbation of COPD? i The settings are the same as above, with Y i As the dependent variable, whether antibiotics were used was used as the independent variable, and two independent sample t tests were performed;

[0065] In c, for the factors affecting the cost-effectiveness of patients with acute exacerbation of COPD, Y i The settings are the same as above, with Y iA regression equation was established with age, BMI, dyspnea, and exercise capacity as the dependent variable and general linear regression and multiple linear regression methods were used to analyze the possible influencing factors of cost-effectiveness.

[0066] More preferably, the cost-utility analysis determined that only dyspnea was statistically significant for total cost, service fee, diagnostic fee, drug fee, and triple fee.

[0067] The present application also provides a model for prognosis assessment and cost-utility assessment of chronic obstructive pulmonary disease (COPD), wherein the model includes the aforementioned prognosis assessment model and cost-utility assessment model. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 , flow chart of the registration study for patients with acute exacerbation of COPD. DETAILED DESCRIPTION

[0069] The embodiments of the present application will be described in detail below in conjunction with the examples, but it will be appreciated by those skilled in the art that the following examples are only used to illustrate the present application and should not be considered as limiting the scope of the present application. In the examples, if no specific conditions are specified, the conditions are carried out according to normal conditions or manufacturer recommendations. If the manufacturer is not specified for the reagents or instruments used, they are all conventional products that can be purchased from the market.

[0070] Definition of some terms

[0071] Unless otherwise defined below, the meaning of all technical terms and scientific terms used in the specific embodiments of the present application is intended to be the same as those generally understood by those skilled in the art. Although it is believed that the following terms are well understood by those skilled in the art, the following definitions are still set forth to better explain the present application.

[0072] As used in this application, an indefinite or definite article used when referring to a singular noun eg "a" or "an", "the" includes a plural of that noun.

[0073] As used in this application, the terms "comprises", "comprising", "having", "containing" or "involving" are inclusive or open-ended and do not exclude other unrecited elements or method steps. The term "consisting of" is considered a preferred embodiment of the term "comprising". If a group is defined below as comprising at least a certain number of embodiments, this should also be understood to disclose a group that preferably consists of only these embodiments.

[0074] The term "approximately" in this application indicates an accuracy range that can be understood by those skilled in the art and still ensures the technical effect of the characteristic in question. The term generally indicates ±10%, preferably ±5%, of the indicated value.

[0075] In addition, the terms first, second, third, (a), (b), (c), and the like in the specification and claims are used to distinguish similar elements and are not necessarily required to describe a sequential or chronological order. It should be understood that the terms so used are interchangeable under appropriate circumstances, and the embodiments described in this application can be implemented in other sequences than those described or illustrated in this application.

[0076] The above terms or definitions are provided only to help understand the present application. These definitions should not be construed as having a scope less than that understood by those skilled in the art.

[0077] The present application is described below in conjunction with specific embodiments.

[0078] Example 1 Patients and data collection

[0079] This application adopts a prospective observational study design. All patients with acute exacerbation of COPD who visit the research center hospital are enrolled after signing the informed consent. Patients fill out the baseline questionnaire during the visit, and follow up with patients at 3, 6, 9, 12, 15, 18, 21, and 24 months after discharge, which can be done by telephone or on-site visit. Each hospital has a respiratory physician as the person in charge, who is responsible for conducting patient surveys after brief training. Participants are required to complete the scale independently. See the specific process. Figure 1 .

[0080] It should be noted that the acute exacerbation of COPD patients described in this application refers to patients with acute worsening of respiratory symptoms, resulting in the need for additional treatment. Specifically, there are at least two or more major symptoms (such as cough, increased sputum volume, purulent sputum, dyspnea, wheezing, etc.), including aggravation of existing symptoms and new symptoms, which last for at least 48 hours, exceed daily variation, and require additional treatment, excluding other diseases such as heart failure, arrhythmia, pulmonary embolism, pneumothorax, pleural effusion, etc.

[0081] The specific inclusion and exclusion criteria for patients are as follows:

[0082] Inclusion criteria: (1) age ≥ 40 years, regardless of gender; (2) patients diagnosed with COPD by lung function test, with FEV1 / FVC < 0.7 after inhalation of bronchodilators; (3) confirmed as acute exacerbation of COPD; (4) subjects voluntarily participated in this clinical trial and signed the informed consent. The researchers judged that the subjects' compliance met the requirements of this application.

[0083] Exclusion criteria: (1) severe mental or neurological disorders that affect informed consent and / or the expression or observation of adverse reactions; (2) unable to complete the first questionnaire and undergo pulmonary function tests; (3) subjects who are participating in other drug clinical trials or intervention studies.

[0084] Exit cohort criteria: (1) The subject requests to withdraw from the clinical trial; (2) A serious adverse event or death occurs during the trial; (3) The patient is lost to follow-up; (4) The investigator or (and) the sponsor considers that the patient is not suitable to continue participating in this application.

[0085] Ethics and informed consent

[0086] This study was approved by the institutional review board of the principal investigator’s hospital (Shanxi Medical University Second Hospital, Approval No. (2019)YX(303)) and the institutional review boards of participating hospitals. Informed consent was collected during hospitalization according to the approval of the local ethics committee.

[0087] This application is in four tertiary or secondary hospitals, including the Second Hospital of Shanxi Medical University, Gujiao Central Hospital, Pianguan County People's Hospital, and Jincheng General Hospital. The clinical medical records and follow-up data of patients diagnosed with acute exacerbation of chronic obstructive pulmonary disease (COPD) from April 2021 to May 2022 and who meet the inclusion and exclusion criteria of this application were collected. The specific patient conditions are shown in Table 3. A total of 135 patient medical records were included in this study, including 114 male patients, accounting for 84.44%, and 21 female patients, accounting for 15.56%; the average age was 67.91±9.35 years old, and the main diagnosis was acute exacerbation of 72 patients, accounting for 53.3%.

[0088] A total of 104 patients (86 males and 18 females) were screened out for the cost-utility subgroup; the youngest patient was 40 years old, the oldest was 89 years old, and the average age was 66.81 years old (see Table 1 below).

[0089] Table 1 Basic information of COPD patients

[0090]

[0091]

[0092] Note: Data are expressed as number (%) or mean ± standard deviation

[0093] The differences between the entire study population and the cost-utility subgroups were analyzed from multiple dimensions, including age, gender, acute onset, smoking history, history of cardiovascular disease, PaO2, and BMI. The results showed that the cost-utility subgroup was representative of the entire study population, and the results were applicable to the entire study population to a certain extent.

[0094] Example 2: Data design and preprocessing

[0095] The data in this application covers the following aspects, including HIS, LIS, PACS, RIS systems, mMRC, CAT, SGRQ scales, etc.:

[0096] 1. Prepare a COPD baseline questionnaire, including a baseline questionnaire and a follow-up questionnaire:

[0097] The contents of the baseline questionnaire included basic information of the patient, laboratory test results, treatment measures, diagnosis and treatment costs, SGRQ questionnaire, CAT questionnaire, PEACE questionnaire, and mMRC questionnaire;

[0098] The contents of the follow-up questionnaire included basic information of the patient, CAT questionnaire, SGRQ questionnaire, adverse outcomes and other follow-up information.

[0099] The basic information in the questionnaire includes the following:

[0100] Basic information: gender, age, occupation, medical insurance, marital status, admission route, length of hospital stay, smoking index (number of cigarettes smoked per day × number of years of smoking), personal history (including drinking history, family history, allergy history, surgical history, etc.), whether the current illness was treated;

[0101] Laboratory results: red blood cell count (WBC), white blood cell count (BRC), hemoglobin concentration (HGB), hematocrit (HCT), platelet count (PLT), absolute lymphocyte count (LYMPH#), absolute neutrophil count (NEUT#), absolute eosinophil count (EO#), lymphocyte percentage (LYMPH%), neutrophil percentage (NEUT%), eosinophil percentage (EO%), alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT / AST, albumin (ALB), albumin (ALB), total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL), urea (UREA), creatinine (CREA), potassium (K), sodium (Na), chloride (Cl), calcium (Ca), urine specific gravity (SG), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), D-dimer, etc.

[0102] Treatment measures: blood pressure monitoring, blood oxygen monitoring, short-acting bronchodilators, glucocorticoids, antibiotics (including whether used in combination), theophylline drugs, expectorants or antioxidants (including ambroxol, eucalyptol, bromhexine, N-acetylcysteine, carbocysteine, fudosteine, erdosteine), nebulization therapy, etc.

[0103] Medical expenses, including: total fee, service fee, diagnosis fee, drug fee and triple fee (service fee + diagnosis fee + drug fee)

[0104] Adverse outcomes: include acute exacerbation, outpatient visits, hospital readmission, and death.

[0105] 2. Variable assignment and preprocessing for prognostic analysis

[0106] In the prognostic analysis and cost-utility analysis, the variable assignments used are shown in Table 2 and Table 3 respectively:

[0107] Table 2 Prognostic analysis variable assignment table

[0108]

[0109]

[0110] 3. Variable assignment and related definitions of cost-utility analysis

[0111] Table 3 Cost-utility analysis variable assignment table

[0112]

[0113]

[0114] In this application, hospitalization expenses are divided into the following sections: total expenses, service fees (general medical service fees + general treatment operation fees + nursing fees + other comprehensive medical service fees), diagnosis fees (pathology diagnosis fees + laboratory diagnosis fees + imaging diagnosis fees + clinical diagnosis project fees), and drug fees (Western medicine fees + antibacterial drug fees + Chinese patent medicine fees + Chinese herbal medicine fees). The difference between baseline and three months of SGRQ is defined as the utility indicator for quantifying hospitalization treatment.

[0115] This application deleted the deceased cases and the cases without recorded hospitalization expenses from the entire study population, selected the cases with three-month follow-up records to form a cost-utility subgroup, and divided the subgroup into COPD acute exacerbation group and non-COPD acute exacerbation group according to the main discharge diagnosis.

[0116] Example 3: Prognostic evaluation analysis

[0117] This paper uses the quantitative data of the research object to or median(* +, ,* ., ) for description, and count data are described by constituent ratio n(%). The statistical analysis content of this application is mainly divided into two parts: patient prognosis analysis, life quality influencing factor analysis, and cost-utility analysis. All statistical analyses in this application were completed using R 4.1, SAS 9.4, and SPSS25.

[0118] 1. Patient prognosis analysis

[0119] In the prognostic analysis section, the main focus is on the prognostic analysis of adverse outcomes and factors affecting quality of life in COPD patients:

[0120] a. For factors affecting adverse outcomes in COPD patients, α in = 0.05 and α out =0.10, and a Cox proportional hazard model was constructed for univariate and multivariate analysis. In the sensitivity analysis: (1) the adverse outcome was adjusted to acute exacerbation, rehospitalization, or death, and the same predictive indicators and analysis methods as in the above modeling were used to model whether the prognostic factors changed after the adverse outcome adjustment; (2) the stepwise screening strategy was changed to α in = 0.05 and α out =0.15 (defined as new strategy 1), α in = 0.10 and α out =0.15 (defined as new strategy 2), and the influence of screening strategy on influencing factors was studied.

[0121] b. For the factors affecting the quality of life of COPD patients, a generalized estimation model (GEE) was constructed for analysis. In the process of variable screening, the model with smaller QIC and QICC was selected as the optimal model.

[0122] Experimental results:

[0123] 1. Analysis of factors affecting the prognosis of COPD patients

[0124] Table 4 Screening of factors affecting prognosis in COPD patients

[0125]

[0126]

[0127] Using α in = 0.05 and α out =0.10, the selected variables are shown in Table 4. On this basis, demographic variables such as age, gender, BMI and smoking index were included, and the Cox proportional hazard model was constructed for univariate and multivariate analysis. The results are shown in Table 5.

[0128] The results of univariate analysis showed that age, duration of hospitalization, treatment for this episode, ambroxol, and NAC had a statistically significant effect on the prognosis of patients. However, in the results of multivariate analysis, factors such as smoking index, duration of hospitalization, and urine specific gravity had a statistically significant effect on the prognosis of patients. Among them, for every 1 unit increase in the smoking index, the probability of adverse outcomes (acute exacerbation, medical treatment, rehospitalization, and death) in patients was 1.008 times the original; for every day increase in hospitalization, the probability of adverse outcomes in patients increased by 0.235 times; for every 1 unit increase in urine specific gravity, the probability of adverse outcomes in patients increased by 67.148 times. However, factors such as age, treatment for this episode, ambroxol, and NAC may be affected by demographic variables, so they are not statistically significant in multivariate analysis.

[0129] Table 5 Factors affecting the prognosis of COPD patients

[0130]

[0131]

[0132] Note: *Item: The multivariate analysis took the hospital grade as a covariate, and included all variables in the univariate model for analysis; **Item: The normal category in BMI was used as the reference standard.

[0133] Therefore, smoking index, length of hospital stay, and urine specific gravity are risk factors for adverse outcomes (acute exacerbation, medical consultation, rehospitalization, and death).

[0134] 2. Sensitivity analysis

[0135] In order to evaluate the sensitivity or stability of the model, this section evaluates the model and screens out key prognostic factors by adjusting the types of adverse outcomes and screening strategies.

[0136] 1) Adjustment for adverse outcomes

[0137] The adverse outcomes of patients were adjusted to acute exacerbation, rehospitalization and death (considering that outpatient patients may have planned outpatient follow-up visits, which will have a certain impact on the analysis results, the outpatient visit item was deleted). The same modeling method as above was used, and the variable screening results are shown in Table 6.

[0138] Table 6 Screening of prognostic factors in COPD patients after adjusting for adverse outcomes

[0139]

[0140] The results of univariate and multivariate analysis after adding demographic characteristic variables are shown in Table 7.

[0141] Table 7 Factors affecting the prognosis of COPD patients after adjustment for adverse outcomes

[0142]

[0143] Note: *Item: The multivariate analysis took the hospital grade as a covariate, and included all variables in the univariate model for analysis; **Item: The normal category in BMI was used as the reference level.

[0144] The results of univariate analysis showed that the factors affecting the adverse outcomes of patients included length of hospital stay, mMRC score, SGRQ total score and the use of NAC, all of which were statistically significant. In the results of multivariate analysis, it can be seen that variables such as length of hospital stay, SGRQ total score and NAC were statistically significant for the occurrence of adverse outcomes of patients. For every day increase in length of hospital stay, the probability of adverse outcomes in patients increased by 0.256 times; for every unit increase in the SGRQ total score, the probability of adverse outcomes in patients increased by 1.271 times; the probability of adverse outcomes in patients using NAC drugs was 0.258 times that of patients not using NAC drugs.

[0145] It can be seen that the length of hospital stay and SGRQ total score are risk factors for adverse outcomes (acute exacerbation, rehospitalization and death) after adjustment, while NAC is a protective factor.

[0146] 2) Effects of different screening strategies on influencing factors

[0147] a. Screening of factors affecting original adverse outcomes under various strategies

[0148] Change the stepwise screening strategy to α in = 0.05 and α out =0.15, corresponding to the new strategy 1, α in = 0.10 and α out =0.15, corresponding to the new strategy 2. The results of variable screening are shown in Tables 8 and 9 respectively.

[0149] Table 8 Screening of factors affecting original adverse outcomes under the new strategy 1

[0150]

[0151] Table 9 Screening of factors affecting original adverse outcomes under the new strategy 2

[0152]

[0153]

[0154] The results in the above table show that compared with the original single-factor screening strategy (Table 4), the new strategy 1 has no change. The variables screened under the new strategy 2 have reduced ambroxol and increased C-reactive protein, inhaled budesonide suspension and ALT. This shows that factors such as hospitalization duration, treatment of this illness, hematocrit, and urine specific gravity have a greater impact on the occurrence of adverse outcomes in patients, while the influence of factors such as ambroxol, C-reactive protein, inhaled budesonide suspension and ALT also have reference opinions in this study.

[0155] b. Screening of factors affecting adverse outcomes after adjustment under various strategies

[0156] On the basis of the adjusted adverse outcomes, variables were screened using the aforementioned new strategies 1 and 2. The specific results are shown in Tables 10 and 11.

[0157] Table 10 Screening of factors affecting adverse outcomes after adjustment under the new strategy 1

[0158]

[0159] Table 11 Screening of factors affecting adverse outcomes after adjustment under the new strategy 2

[0160]

[0161]

[0162] The results in the above table show that compared with the results of the adjusted adverse outcomes under the original screening strategy (Table 6), the new strategy 1 has no change; the variables screened under the new strategy 2 have been expanded to include ALB, absolute value of lymphocytes, urine specific gravity, terbutaline hydrochloride inhalation solution, hematocrit, ALT, and calcium ions. This indicates that the duration of hospitalization, SGRQ total score, and the use of NAC have a greater impact on the occurrence of adverse outcomes in patients, while the effects of factors such as ALB, absolute value of lymphocytes, urine specific gravity, terbutaline hydrochloride inhalation solution, hematocrit, ALT, and calcium ions also have reference opinions in this study.

[0163] Conclusion: From the above results, it can be seen that the performance of the model in this application is relatively stable. It can derive consistent major prognostic influencing factors based on different strategies, and can also derive other minor influencing factors.

[0164] These major prognostic factors include: when the adverse outcomes are acute exacerbation, outpatient visit, rehospitalization and death, the basic prognostic factors are smoking index, length of hospital stay and urine specific gravity; when the adverse outcomes are acute exacerbation, rehospitalization and death, the major prognostic factors are length of hospital stay, SGRQ total score and NAC.

[0165] 3. Analysis of factors affecting the quality of life of COPD patients

[0166] The SGRQ questionnaire contains sub-scores in three aspects: patient symptoms, behaviors, and impacts, which are combined into the total SGRQ score. In order to make the analysis results more clinically meaningful and interpretable, this application combines the SGRQ total score with its corresponding MCID to construct the new indicator UVDSGRQ as the dependent variable for analysis. Specifically, for the SGRQ total score, in order to effectively reduce its degree of discreteness and reduce the impact of its large variance on the overall model, while making the model parameters more clinically meaningful, this application constructs the unit value of difference (UVD) of the SGRQ total score based on the minimum clinically important difference (MCID):

[0167]

[0168] In the above formula, SGRQ i is the total SGRQ score at follow-up time i, MCID SGRQ is the MCID of the total SGRQ score. According to previous studies, the MCID of the total SGRQ score is usually set at 4 points. SGRQ The analysis was included in the model as a dependent variable, which means that when other variables remain unchanged, the total SGRQ score increases (or decreases) by a certain MCID due to a change in a certain factor. SGRQ When the absolute value of the change is greater than 1, it often indicates that the change in the total SGRQ score may have clinical significance.

[0169] The specific steps are as follows:

[0170] 1) The dependent variable is set as the unit change value of the total SGRQ score (UVD SGRQ );

[0171] 2) Independent variables include indicators of the patient's basic condition, test results, treatment measures, etc.;

[0172] 3) Construct a generalized estimation model (GEE) to analyze the factors affecting quality of life;

[0173] 4) In the process of variable screening, the model with smaller QIC and QICC is selected as the optimal model.

[0174] The generalized estimating equation was used to analyze the factors affecting the quality of life of COPD patients. The link function of this model was the Gamma function, and the corresponding QIC and QICC were 845.71 and 846.69, respectively. The specific results are shown in Table 12.

[0175] Table 12 Factors related to the quality of life of COPD patients

[0176]

[0177] Note: *Item: The normal category is used as the reference level in BMI; **Item: Because the value is too small, the current number of digits retained cannot be displayed, and the original value is approximately 0.0000494; ***Item: Because the value is too small, the current number of digits retained cannot be displayed, and the original value is approximately 0.0000107.

[0179] As can be seen from the table, age, smoking index, mMRC score and follow-up duration are factors affecting the quality of life of COPD patients, and they are statistically significant. SGRQ The value of the smoking index will decrease by 0.0067, and the corresponding SGRQ total score will decrease by 0.0268 points; for every 1 unit increase in the smoking index, the UVD SGRQ The value of UVD will increase by 0.0001, and the corresponding SGRQ total score will increase by 0.0004 points; for every increase of 1 level in mMRC score, SGRQ The value of UVD SGRQ The value of will increase by 0.0039, and the corresponding SGRQ total score will increase by 0.0156 points. Therefore, factors such as age, smoking index, mMRC score and follow-up time are the main factors affecting the quality of life of COPD patients.

[0180] Example 4: Cost-effectiveness analysis

[0181] The cost-utility analysis is mainly divided into three parts: according to whether short-acting bronchodilators and glucocorticoids are used together, the patients are divided into combined medication group and non-combination medication group, and the difference in cost-utility is analyzed; patients with acute exacerbation of COPD are divided into antibiotic use group and non-antibiotic use group, and the difference in cost-utility is analyzed between the two groups; analysis of factors affecting cost-utility in patients with acute exacerbation of COPD.

[0182] a. To determine whether there is a difference in cost-effectiveness between the combined medication group and the non-combination medication group, the total cost of a hospitalized patient is C1, the drug cost is C2, the diagnosis fee is C3, the service fee is C4, and the triple fee (service fee + diagnosis fee + drug fee) is C5. The difference in the patient's baseline and three-month SGRQ is U. The formula Yi = 100U / C is used to calculate Y1, Y2, Y3, Y4, and Y5. iTwo independent sample t-tests were performed with the combination of short-acting bronchodilators and glucocorticoids as the dependent variable and the combination of short-acting bronchodilators and glucocorticoids as the independent variable.

[0183] b. Is there a difference in cost-utility between the antibiotic group and the non-antibiotic group in patients with acute exacerbation of COPD? i The settings are the same as above, with Y i Two independent sample t-tests were performed with the use of antibiotics as the dependent variable and whether or not to use antibiotics as the independent variable.

[0184] c. Factors that affect the cost-effectiveness of patients with acute exacerbation of COPD: Y i The settings are the same as above, with Y i A regression equation was established with age, BMI, dyspnea and exercise capacity as the dependent variable and general linear regression and multiple linear regression methods were used to analyze the possible influencing factors of cost-effectiveness.

[0185] 1. Cost structure of direct economic burden

[0186] Among the 104 inpatients, the lowest hospitalization cost was 4306.57 yuan, the highest was 30906.72 yuan, and the median hospitalization cost was 10074.56 yuan. The direct economic burden includes the following five charging items, among which drug fees account for the highest proportion, followed by diagnosis fees, service fees, other fees, and surgery and treatment fees. See Table 13 for details.

[0187] Table 13 Composition and ranking of direct economic burden items of 104 inpatients

[0188]

[0189]

[0190] 2. Analysis of factors affecting cost-effectiveness of AECOPD patients is shown in Table 14.

[0191] Table 14 Analysis of factors affecting total cost-effectiveness

[0192]

[0193] Table 14 shows that after the single factor analysis of the total cost-utility, the effect of dyspnea on the total cost-utility is statistically significant. The dyspnea level increases by one level, and the corresponding increase in SGRQ for 100 yuan of total cost is 0.371. After the multi-factor analysis of the total cost-utility, dyspnea is an influencing factor of the total cost-utility. The dyspnea level increases by one level, and the corresponding increase in SGRQ for 100 yuan of total cost is 0.348. After eliminating the interference of other factors, only the effect of dyspnea on the cost-utility of the total cost is still statistically significant.

[0194] Table 15 Analysis of factors affecting the cost-effectiveness of service fees

[0195]

[0196] As shown in Table 15, after the univariate analysis of the cost-effectiveness of service fees, it was found that dyspnea had a statistically significant effect on the cost-effectiveness of service fees. When the dyspnea level increased by one level, the corresponding increase in SGRQ for a service fee of 100 yuan was 0.406. After the multivariate analysis of the cost-effectiveness of service fees, dyspnea was an influencing factor of the cost-effectiveness of service fees. When the dyspnea level increased by one level, the corresponding increase in SGRQ for a service fee of 100 yuan was 0.413. After eliminating the interference of other factors, only the effect of dyspnea on the cost-effectiveness of service fees was still statistically significant.

[0197] Table 16 Analysis of factors affecting the cost-effectiveness of diagnostic fees

[0198]

[0199] After the univariate analysis of the cost-utility of diagnostic fees, it was found that age and dyspnea had a statistically significant effect on the cost-utility of diagnostic fees. For every 1-year increase in age, the SGRQ corresponding to a 100-yuan diagnostic fee increased by 0.232; for every level increase in dyspnea, the SGRQ corresponding to a 100-yuan diagnostic fee increased by 0.294. After the multivariate analysis of the cost-utility of diagnostic fees, dyspnea was found to be an influencing factor of the cost-utility of diagnostic fees. For every level increase in dyspnea, the SGRQ corresponding to a 100-yuan diagnostic fee increased by 0.266. After eliminating the interference of other factors, only dyspnea remained statistically significant. As shown in Table 16.

[0200] Table 17 Analysis of factors affecting drug cost-effectiveness

[0201]

[0202]

[0203] Table 17 shows that after a univariate analysis of the cost-effectiveness of drug expenses, the effect of dyspnea on the cost-effectiveness of drug expenses is statistically significant. For every one-level increase in the dyspnea level, the corresponding increase in SGRQ for every 100 yuan of drug expenses is 0.282. After a multivariate analysis of the cost-effectiveness of drug expenses, dyspnea is an influencing factor of the cost-effectiveness of drug expenses. For every one-level increase in the dyspnea level, the corresponding increase in SGRQ for every 100 yuan of drug expenses is 0.242. After eliminating the interference of other factors, only the effect of dyspnea on the cost-effectiveness of drug expenses is still statistically significant.

[0204] Table 18 Analysis of factors affecting the cost-effectiveness of triple fee (service fee + diagnosis fee + drug fee)

[0205]

[0206]

[0207] After the univariate analysis of the cost-effectiveness of the triple fee, it was found that dyspnea had a statistically significant effect on the cost-effectiveness of the triple fee. For each level of dyspnea increase, the corresponding increase in SGRQ of 100 yuan triple fee was 0.342. After the multivariate analysis of the cost-effectiveness of the triple fee, dyspnea was an influencing factor of the cost-effectiveness of the triple fee. For each level of dyspnea increase, the corresponding increase in SGRQ of 100 yuan triple fee was 0.307. After eliminating the interference of other factors, only dyspnea still had a statistically significant effect on the cost-effectiveness of the triple fee, as shown in Table 18.

[0208] Therefore, dyspnea is a positively correlated factor affecting the cost-effectiveness of five types of expenses: total cost, service fee, diagnosis fee, drug fee, and triple fee.

[0209] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A model for evaluating the prognosis of chronic obstructive pulmonary disease (COPD), characterized in that: The model includes the following modules: 1) Data collection module: used to collect clinical medical records and follow-up data of patients with acute exacerbation of COPD; 2) Data design module: used to design baseline data questionnaire; 3) Prognostic analysis module: including a. variable assignment and preprocessing for baseline data questionnaire; and b. prognostic analysis of adverse outcomes and factors affecting quality of life in COPD patients.

2. The model according to claim 1, characterized in that In the 1) data collection module, the acute exacerbation of COPD patients refers to patients whose respiratory symptoms have acutely worsened, resulting in the need for additional treatment; the patients have at least two or more symptoms of cough, increased sputum volume, purulent sputum, dyspnea or wheezing, including aggravation of existing symptoms and new symptoms, which last for at least 48 hours, exceed daily variation, and require additional treatment; The follow-up data are the follow-up data at 3, 6, 9, 12, 15, 18, 21, and 24 months after discharge.

3. The model according to claim 1, characterized in that In the 2) data design module, the baseline data questionnaire includes a baseline questionnaire and a follow-up questionnaire: The baseline questionnaire includes basic information of the patient, test results, treatment measures, medical expenses, SGRQ questionnaire, CAT questionnaire, PEACE questionnaire and mMRC questionnaire; The follow-up questionnaire content includes the patient's basic information, CAT questionnaire, SGRQ questionnaire, and adverse outcomes; Preferably, the adverse outcome is acute exacerbation, outpatient visit, re-hospitalization or death within one year after the patient is discharged from hospital.

4. The model according to claim 1, characterized in that In the 3) prognostic analysis module, the variable assignments of the baseline data questionnaire are as follows: Preferably, the pretreatment includes: analyzing the factors affecting the quality of life, constructing the change unit value (UVD) of the SGRQ total score based on the minimum clinically significant change value (MCID) for the SGRQ total score. SGRQ ): Among them, SGRQ i is the total SGRQ score at follow-up time i, MCID SGRQ is the MCID of the total SGRQ score; its meaning is: when other variables remain unchanged, the MCID of the total SGRQ score increases (or decreases) by a certain number of units due to a change in a certain factor; when UVD in the model SGRQ When the absolute value of the change is greater than 1, it indicates that the change in the total SGRQ score may have clinical significance.

5. The model according to claim 1, characterized in that In the 3) prognosis analysis module, the COPD patient adverse outcome prognosis analysis includes the following steps: Statistical description: The quantitative data of the research objects are analyzed using or median(* +, ,* ., ) are used to describe the count data, and the count data are described by the composition ratio n (%); Prognostic analysis: Adverse outcomes were set as acute exacerbation, outpatient visit, rehospitalization and death. The inclusion test level was set at 0.05, and the exclusion test level was set at 0.

10. A stepwise screening strategy was used to screen out the variables of hospitalization duration, treatment of the current illness, hematocrit, urine specific gravity and ambroxol. Then, age, gender, BMI and smoking index were included, and the Cox proportional hazard model was constructed for univariate and multivariate analysis to obtain the prognostic factors. Preferably, the steps further include: 1) After adjusting adverse outcomes to acute exacerbation, rehospitalization, and death, a Cox proportional hazard model was constructed based on the same method as above to conduct univariate and multivariate analysis to confirm whether the prognostic factors changed after the adverse outcomes were adjusted; 2) Adjustment of screening strategy: The stepwise screening strategy was changed to the inclusion test level set at 0.05, the exclusion test level set at 0.15, and the inclusion test level set at 0.10, the exclusion test level set at 0.15, respectively, and the effects of different screening strategies on the screening of factors affecting the original adverse outcomes and the adjusted adverse outcomes were analyzed. Combined with the adjustments, the main prognostic factors were comprehensively determined: When the adverse outcomes were acute exacerbation, outpatient visit, rehospitalization and death, the basic prognostic factors were smoking index, length of hospital stay and urine specific gravity; when the adverse outcomes were acute exacerbation, rehospitalization and death, the main prognostic factors were length of hospital stay, SGRQ total score and NAC.

6. The model according to claim 1, characterized in that In the 3) prognosis analysis module, the analysis of factors affecting quality of life includes the following steps: 1) The dependent variable is set as the unit change value of the total SGRQ score (UVD SGRQ ); 2) Independent variables include basic information of patients, test results, and treatment measures; 3) Construct the generalized estimation model GEE to analyze the factors affecting quality of life; 4) In the process of variable screening, the model with smaller QIC and QICC is selected as the optimal model; the influencing factors of quality of life are determined based on the model; Preferably, the factors affecting the quality of life are age, smoking index, mMRC score and follow-up duration.

7. A model for cost-utility assessment of chronic obstructive pulmonary disease (COPD), characterized in that: The model includes the following modules: 1) Data collection module: used to collect clinical medical records and follow-up data of patients with acute exacerbation of COPD; 2) Data design module: used to design the COPD baseline data questionnaire; 3) Cost-utility analysis module: a) used for variable assignment and preprocessing of the baseline data questionnaire, and b) used for cost-utility analysis; Preferably, the types of costs include: total cost, service fee, diagnosis fee, drug fee and triple fee (service fee + diagnosis fee + drug fee).

8. The model according to claim 7, characterized in that In the 3) cost-effectiveness analysis module, the variable assignments of the baseline data questionnaire are as follows: The SGRQ change score per 100 yuan is the SGRQ difference between the baseline and the three months corresponding to the corresponding cost of 100 yuan; it represents the utility index of quantitative hospitalization; The pretreatment includes: deleting the deceased cases and the cases without recorded hospitalization expenses in the whole study population, selecting the cases with three-month follow-up records to form the cost-utility subgroup, and dividing the subgroup into COPD acute exacerbation group and non-COPD acute exacerbation group according to the main discharge diagnosis.

9. The model according to claim 7, characterized in that In the cost-utility analysis module 3), the cost-utility analysis includes the following steps: a. According to whether short-acting bronchodilators and glucocorticoids were used together, the patients were divided into a combined medication group and a non-combination medication group, and a cost-effectiveness difference analysis was performed; b. Patients with acute exacerbation of COPD were divided into the antibiotic use group and the non-antibiotic use group, and the cost-utility difference between the two groups was analyzed; c. Analyze the factors affecting cost-utility of patients with acute exacerbation of COPD; Preferably, in a, whether there is a difference in cost-effectiveness between the combined medication group and the non-combination medication group, the total cost of a hospitalized patient is C1, the drug cost is C2, the diagnosis fee is C3, the service fee is C4, the triple fee (service fee + diagnosis fee + drug fee) is C5, the difference in SGRQ between the baseline and three months of the patient is U, and the formula Y is used. i =100U / C calculate Y1, Y2, Y3, Y4, Y5 respectively; take Y i As the dependent variable, whether or not to use combined medication was the independent variable, and two independent sample t tests were performed; In b, is there a difference in cost-utility between the antibiotic group and the non-antibiotic group for patients with acute exacerbation of COPD? i The settings are the same as above, with Y i As the dependent variable, whether antibiotics were used was used as the independent variable, and two independent sample t tests were performed; In c, for the factors affecting the cost-effectiveness of patients with acute exacerbation of COPD, Y i The settings are the same as above, with Y i As the dependent variable, the regression equation was established with age, BMI, dyspnea, and exercise capacity as independent variables; General linear regression and multiple linear regression methods were used to analyze the possible influencing factors of cost-effectiveness. The analysis determined that dyspnea had a statistically significant effect on total cost, service fee, diagnostic fee, drug fee, and triple fee.

10. A model for prognosis assessment and cost-utility assessment of chronic obstructive pulmonary disease (COPD), characterized in that: Including the model described in any one of claims 1-6 and the model described in any one of claims 7-9.

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