Analysis of factors influencing treatment quality of non-small cell lung cancer based on causal diagram model
10.11904/j.issn.1002-3070.2024.04.003
- VernacularTitle:基于因果图模型的非小细胞肺癌治疗质量影响因素分析
- Author:
Xuepei YAO
1
;
Shanqi BAI
;
Meina LIU
Author Information
1. 哈尔滨医科大学公共卫生学院卫生统计学教研室(哈尔滨 150001)
- Keywords:
Non-small cell lung cancer;
Influencing factors;
Causal diagram model;
Fast causal inference algorithm
- From:
Practical Oncology Journal
2024;38(4):227-234
- CountryChina
- Language:Chinese
-
Abstract:
Objective The aim of this study was to use the fast causal inference(FCI)algorithm to construct a causal graph model,analyze the direct and indirect factors that affect the quality of treatment for non-small cell lung cancer(NSCLC),and provide a basis for improving the quality of patient treatment.Methods Case information of NSCLC patients from 10 tertiary hospitals was collected;the influencing factors were determined as the research variable,and the incidence of adverse events was the evaluation indi-cator of patient treatment quality,i.e.the outcome variable;the FCI algorithm to mine case data were used to construct a causal dia-gram model of research variables and outcomes,and analyze causal relationships between research variables and outcome variables,as well as between different research variables.Results A total of 2,846 patients with an average age of 56.00±7.70 years were includ-ed in this study,and the incidence of adverse events was 9.63%.The causal diagram model consisted 24 nodes and 71 edges,inclu-ding 54 directed edges and 7 bidirectional edges.The direct factors affecting the occurrence of adverse events included hospital type,histological grade,lymph node dissection,and length of hospitalization;indirect factors included occupation,medical insurance type,current medical history,pathological stage,comprehensive treatment,surgical nature,and type of lung resection;The analysis of the in-teraction between factors showed that the current medical history,histological classification,comprehensive treatment,surgical nature,and type of lung resection determined whether the patient received lymph node dissection;The nature of surgery,method of lung resec-tion,and comprehensive treatment affected the length of hospitalization;Medical history affected the histological classification of lung cancer;The type of occupation and medical insurance affected the type of hospital where patients sought medical treatment.Conclusion In the analysis of factors affecting the quality of NSCLC treatment,the causal diagram model can obtain direct and indi-rect factors that affect the occurrence of adverse events,identify target variables that can be intervened,and provide a basis for impro-ving the quality of NSCLC treatment;Hospitals can reduce the incidence of adverse events by increasing the acceptance rate of lymph node dissection and comprehensive treatment.
