Evidence map›Paper›PMID 42304262›Full record

ArticleBMC cancer2026

Developing a quality evaluation indicator system for lung cancer diagnosis and treatment: a modified Delphi method study.

Liming Shi, Kailun Fei, Meicen Liu, Chengcheng Zhou, Juan Yang, Jincheng Yang, Jie Wang, Zhijie Wang, Wenjing Yang

Abstract read
In one paragraph

Article in BMC cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Liming ShiNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Kailun FeiNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Meicen LiuNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Chengcheng ZhouNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Juan YangNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jincheng YangNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jie WangNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. zlhuxi@163.com.
Zhijie WangNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. jie_969@163.com.
Wenjing YangNational Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. wenjing86824@126.com.

Funding

Chinese Academy of Medical Sciences Initiative for Innovative Medicine 2021-I2M-1-001
6 · The paper itself

Abstract

objectiveTo establish a quality evaluation index system for the diagnosis and treatment of lung cancer.

methodThe Donabedian health assessment model and Delphi method were used to construct an indicator system, and the Analytic Hierarchy Process was used to determine the weights of each level of indicators.

resultThe final indicator system constructed includes 3 primary indicators: structure, process and outcome, 15 secondary indicators, and 55 tertiary indicators. Structural indicators include staff, regulations, and facilities; Process indicators include diagnosis, multidisciplinary team (MDT), Neoadjuvant therapy, surgical treatment, adjuvant treatment, radiation therapy, systemic therapy, patient follow-up and patient-centered; Outcome indicators include effectiveness, safety and timeliness. Of the two rounds of Delphi experts consulting, the Expert Enthusiasm Coefficient were respectively 100.0% and 96.15%, the Expert Authority Coefficient were respectively 0.818 and 0.825, and Expert Coordination Coefficient was between 0.476 ~ 0.748.

conclusionThe quality evaluation indicator system of lung cancer has high credibility and can be used as a tool for evaluating the quality of lung cancer care.

Indexed as

Lung NeoplasmsQuality Indicators, Health CareDelphi TechniqueHumansDelphi MethodLung CancerQuality evaluation

Identifiers

PMID42304262
PMCPMC13543424

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.