[Evidence mapping analysis of clinical studies on Chinese patent medicines for non-small cell lung cancer from past five years].

医学 中成药 随机对照试验 替代医学 指南 系统回顾 样本量测定 肺癌 家庭医学 临床试验 干预(咨询) 荟萃分析 梅德林 生物仿制药 重症监护医学 大样本 循证医学 科克伦合作 传统医学 中医药 研究设计 内科学 临床研究 证据质量 质量(理念) 医学物理学 数据提取 医疗保健 专利分析
作者
Yuan Xun-xun,CQ Ning,Zhen-zhen FENG,Jian-Sheng Li
出处
期刊:PubMed [National Institutes of Health]
卷期号:51 (8): 2377-2387
标识
DOI:10.19540/j.cnki.cjcmm.20260112.501
摘要

Based on clinical research literature from the past five years on Chinese patent medicines for the treatment of non-small cell lung cancer(NSCLC), this study employed an evidence mapping approach to systematically evaluate the distribution characteristics of the evidence, intervention measures, outcome indicators, and methodological quality. A systematic search of eight Chinese and English databases, including CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Web of Science, and Cochrane Library, was conducted for studies published between January 2021 and September 2025, yielding a total of 222 eligible publications. These comprised 133 randomized controlled trials, 46 non-randomized controlled trials, 37 systematic reviews/Meta-analyses, 4 overviews of systematic reviews, and 2 guidelines or expert consensus documents. The results showed that original studies were predominantly single-center, with sample sizes mainly ranging from 50 to 100 participants. A total of 25 Chinese patent medicines were involved, among which Aidi Injection, Compound Kushen Injection, and Kanglaite Injection were the most widely used. Methodological quality assessment revealed that 29.32% of randomized controlled trials had a high risk of bias, 82.86% of systematic reviews/Meta-analyses were rated as low or critically low quality, and the strength of guideline recommendations was generally insufficient. In summary, the current clinical evidence for Chinese patent medicines in the treatment of NSCLC is characterized by uneven distribution and insufficient methodological quality. There is an urgent need to conduct multicenter collaborative studies, optimize study design and key outcome measures, and strengthen the evaluation of long-term efficacy and health economics to promote the generation of high-quality evidence and its clinical translation.
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