Evidence map›Paper›PMID 42639184›Full record

ArticleCancer management and research2026

Clinical Research on Integrated Chinese and Western Medicine for Colorectal Cancer with Lung Metastases.

Yuxing Sun, Jiangyu Bian, Linfeng Wang, Tong Zhang

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

4 authors.

Yuxing SunDepartment of Oncology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.ORCID 0009-0001-5576-6455
Jiangyu BianDepartment of Oncology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.ORCID 0009-0003-0374-4662
Linfeng WangDepartment of Oncology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.ORCID 0009-0000-1763-5043
Tong ZhangDepartment of Oncology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.ORCID 0000-0002-4041-0499

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the impact of integrated traditional Chinese and Western medicine (TCM-WM) treatment on survival outcomes in patients with colorectal cancer (CRC) lung metastases. Methods: A retrospective cohort study was conducted utilizing medical records of patients diagnosed with CRC lung metastases from four tertiary Grade A hospitals between August 2013 and December 2022. Patients were stratified based on exposure to continuous traditional Chinese medicine treatment for ≥3 months. Patients meeting this exposure criterion were assigned to the TCM-WM cohort; those not meeting the criterion were assigned to the Western medicine (WM) cohort. Overall survival (OS) and 3-, 4-, and 5-year cumulative survival rates were compared between cohorts. Results: The study included 286 patients with CRC lung metastases: 122 in the TCM-WM cohort and 164 in the WM cohort. Median OS was 35.0 months in the TCM-WM cohort versus 28.5 months in the WM cohort, representing a statistically significant extension of 6.5 months [HR= 0.67, 95% CI:0.514-0.871, Conclusion: Integrated TCM-WM treatment significantly prolongs survival and reduces mortality risk in patients with CRC lung metastases. (Trial registration No. ITMCTR2025001663).

Indexed as

cohort studycolorectal cancer lung metastasesintegrated Chinese and Western medicine

Identifiers

PMID42639184
PMCPMC13502315

What OpenQuestion holds

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Registered trials

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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.