Evidence map›Paper›PMID 42158420›Full record

ArticleFrontiers in oncology2026

Association between treatment decisions and survival outcomes in lung cancer patients under a multidisciplinary team model: the impact of MDT-recommended treatment plans on treatment completion rates, survival time, and treatment conversion.

Qian Yi, Hailong Wei

Abstract read
In one paragraph

Article in Frontiers in oncology, 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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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Qian YiDepartment of Respiratory and Critical Care Medicine, the People's Hospital of Leshan, Leshan, Sichuan, China.
Hailong WeiDepartment of Respiratory and Critical Care Medicine, the People's Hospital of Leshan, Leshan, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The complexity of lung cancer management requires coordinated care. This study aimed to evaluate the impact of Multidisciplinary Team (MDT)-recommended treatment plans on the treatment course and survival outcomes of lung cancer patients. Methods: This single-center, retrospective cohort study enrolled consecutive patients with primary lung cancer who were initially diagnosed and received first anti-cancer treatment between January 1, 2020, and January 30, 2023. Patients were categorized into MDT (n=115) or non-MDT (n=105) groups based on whether the initial treatment decision was made via a formal MDT discussion. Key measures included treatment completion rate, treatment conversion, overall survival (OS), progression-free survival (PFS), and safety profiles. Follow-up data were collected until July 31, 2025. Results: The MDT group demonstrated a significantly higher rate of completing the initial treatment as planned (86.09% vs. 68.57%, P = 0.002), a lower treatment conversion rate (19.13% vs. 39.05%, P = 0.001), and a longer time to conversion (8.41 vs. 5.16 months, P<0.001). Patients in the MDT group had significantly longer median OS (45.21 vs. 28.64 months, P<0.001) and PFS (19.80 vs. 13.53 months, P<0.001). Multivariate analyses confirmed MDT participation as an independent factor associated with improved OS (HR = 0.605, P = 0.009) and a higher likelihood of treatment completion (OR = 3.438, P = 0.002). Conclusion: The MDT model is associated with better treatment adherence, delayed treatment conversion, and significantly improved survival outcomes in lung cancer patients, and facilitates more precise initial treatment selection.

Indexed as

lung cancermultidisciplinary teamsurvival analysistreatment adherencetreatment decision

Identifiers

PMID42158420
PMCPMC13180563

What Socratic holds

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LicenceCC BY
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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 Socratic graph.