实用肿瘤学杂志 ›› 2025, Vol. 39 ›› Issue (6): 486-492.doi: 10.11904/j.issn.1002-3070.2025.06.005

• 治疗质量专题 • 上一篇    下一篇

基于潜在转变分析的乳腺癌治疗质量干预效果评价

焦奕霖1, 刘美娜1, 宋莉2   

  1. 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 150081);
    2.黑龙江省中毒抢救治疗中心
  • 收稿日期:2024-12-26 修回日期:2025-03-08 出版日期:2025-12-28 发布日期:2026-01-13
  • 通讯作者: 宋莉,E-mail:ss9216@163.com
  • 作者简介:焦奕霖,女,(2001—),硕士研究生,从事疾病治疗质量及干预效果评价研究。
  • 基金资助:
    国家自然科学基金(编号:82173614)

Evaluation of intervention effect on treatment quality of breast cancer based on potential transformation analysis

JIAO Yilin1, LIU Meina1, SONG Li2   

  1. 1. Department of Biostatistics,Public Health College of Harbin Medical University,Harbin 150081,China;
    2. Heilongjiang Provincial Center for Poisoning Treatment and Rescue
  • Received:2024-12-26 Revised:2025-03-08 Online:2025-12-28 Published:2026-01-13

摘要: 目的 描述医院乳腺癌治疗质量随时间的变化情况,评估已实施的医院乳腺癌治疗质量干预措施效果,为提高乳腺癌治疗质量和改善患者预后提供科学依据。方法 选取2019年10月1日—2025年1月31日参与研究的医院209家,按干预时间划分为:基线时间(T0)、干预阶段Ⅰ(T1)、干预阶段Ⅱ(T2)和干预阶段Ⅲ(T3),分别计算各时间医院乳腺癌术前检查、治疗及诊断维度质量得分及治疗过程指标的综合得分;依据上报数据,纳入接受干预措施的干预医院19家,采用倾向评分匹配法,按照医院等级、所有制形式、T0时间医院乳腺癌治疗质量各维度得分匹配对照医院190家。利用潜在剖面分析法(latent profile analysis,LPA)对医院乳腺癌治疗质量进行分类,并进一步采用潜在转变分析(latent transition analysis,LTA)探究干预措施对医院治疗质量变化的影响。结果 LPA分析将乳腺癌治疗质量分成两个类别:class1为高治疗质量组、class2为低治疗质量组;综合维度得分在两组中均有一定提高:低治疗质量组的得分由T0阶段的0.31提升至T3阶段的0.36,高治疗质量组则由0.54提高至0.58。LTA获得乳腺癌治疗质量变化情况,归属于“高治疗质量”潜类别的比例从T0的35.89%升高至T3的96.17%,提高约1.68倍;将干预作为解释变量纳入LTA模型后,结果表明干预是影响潜在类别转换的显著因素。结论 研究表明,干预是提高乳腺癌治疗质量的有效策略,干预措施在检查、治疗和诊断各维度呈现出积极效果,建议完善治疗维度的干预措施,以实现医院乳腺癌治疗质量的全面提高。

关键词: 乳腺癌, 治疗质量, 潜在转变分析, 干预效果

Abstract: Objective The aim of this study was to describe the changes of breast cancer treatment quality in hospitals over time,evaluate the effect of the intervention measures on the treatment quality of breast cancer that have been implemented in hospitals,and provide a scientific basis for improving breast cancer treatment quality and enhancing patient prognosis. Methods A total of 209 hospitals that participated in the study from October 1,2019 to January 31,2025 were selected.According to the intervention time,they were divided into four groups:baseline time(T0),intervention phase Ⅰ(T1),intervention phase Ⅱ(T2),and intervention phase Ⅲ(T3).The quality scores of preoperative examinations,treatment,and diagnosis of breast cancer and the comprehensive scores of treatment process indicators were calculated,respectively;According to the reported data,19 intervention hospitals were included in the intervention measures,and 190 control hospitals were matched by the propensity score matching method according to the hospital grade,ownership form,and the scores of breast cancer treatment quality dimensions of“T0”time hospitals.Latent profile analysis(LPA)was used to classify the treatment quality of breast cancer in hospitals.Latent transition analysis(LTA)was further used to explore the impact of intervention measures on the change of treatment quality in hospitals. Results The treatment quality of breast cancer was divided into two categories by LPA analysis:“class1”was the high treatment quality group,and“class2”was the low treatment quality group.The comprehensive dimension score had improved to some extent in both groups:the score in the low treatment quality group had increased from 0.31 at the“T0”stage to 0.36 at the“T3”stage,while the score of the high treatment quality group had increased from 0.54 to 0.58.The change in the treatment quality of breast cancer obtained by LTA,the proportion of the potential category in“high treatment quality”increased from 35.89% at“T0”to 96.17% of“T3”,an increase of about 1.68 times;When the intervention was included as an explanatory variable in LTA model,the results showed that the intervention significantly influenced latent class transitions. Conclusions The study shows that intervention is an effective strategy to improve the treatment quality of breast cancer,and the intervention measures show positive effects on the inspection,treatment and diagnosis dimensions.It is suggested to improve the intervention measures in the treatment dimension to achieve the overall improvement of breast cancer treatment quality in the hospital.

Key words: breast cancer, quality of treatment, latent transition analysis, intervention effect

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