Evidence map›Paper›PMID 36910626›Full record

ArticleFrontiers in oncology2023

Multivariate analysis of prognostic factors in patients with lung cancer.

Changjiang Liu, Minting Ma, Xuetao Zhou, Zefeng Zhang, Yang Guo

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Changjiang LiuDepartment of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
Minting MaDepartment of Medical Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
Xuetao ZhouDepartment of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
Zefeng ZhangDepartment of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
Yang GuoDepartment of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Lung cancer is the leading cause of cancer-related mortality in China. The purpose of this study was to determine the effect of non-therapeutic and therapeutic factors of patients with lung cancer on survival rate. Methods: In this retrospective study, a total of 458 patients diagnosed as lung cancer at the Department of Thoracic Surgery, the Fourth Affiliated Hospital of Hebei Medical University from September 2008 to October 2013 were enrolled. The COX proportional hazards model was used to analyze the possible factors affecting the survival of patients. Model variables included age, sex, family history, smoking, tumor location, pathological type, stage, chemotherapy, radiotherapy, operation, and targeted therapy. Results: The median survival time (MST) was 32.0 months (95% CI: 29.0-34.0 months), while the 1-, 3-, and 5-year survival rates were 70.74%, 36.90%, and 30.13%, respectively. The univariate analysis showed that stage, chemotherapy, radiotherapy, and operation significantly affected the median survival time of patients. Multivariate cox regression analysis suggested that sex (female Conclusion: Our study showed that male, early stage, operation were protective factors for the survival of patients, while female, advanced stage, chemotherapy were risk factors for the survival of patients. Larger studies are required to address the usefulness of these prognostic factors in defining the management of patients with lung cancer.

Indexed as

agelung cancermultivariate analysisprognosissex

Identifiers

PMID36910626
PMCPMC9993855

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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.