Evidence map›Paper›PMID 40160823›Full record

ArticleFrontiers in immunology2025

Development of a prognostic prediction model for non-smoking lung adenocarcinoma based on pathological information and laboratory hematologic indicators: a multicenter study.

Run Xiang, Peihong Hu, Xiaoxiong Xiao, Wen Li, Xiaoqing Liao, Jun Li, Wen Zhu, Xiaoqin Liu, Qiang Li

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2025. 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

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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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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

9 authors.

Run Xiang *State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China.
Peihong Hu *Department of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Xiaoxiong XiaoDepartment of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Wen LiDepartment of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiaoqing LiaoDepartment of Thoracic Surgery, Dazhu County People's Hospital, Dazhou, Sichuan, China.
Jun LiDepartment of Thoracic Surgery, Ziyang Yanjiang People's Hospital, Ziyang, Sichuan, China.
Wen ZhuState Key Laboratory of Biotherapy, Sichuan University, Chengdu, China.
Xiaoqin LiuDepartment of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Qiang LiDepartment of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop a simple and practical model to predict the prognostic survival of non-smoking patients with lung adenocarcinoma by combining general pathological information with laboratory hematologic indicators. Methods: Cox univariate and multivariate analyses were used to identify the variable indicators. A Cox proportional hazards model was constructed based on the selected variables to compare survival outcomes between the high-and low-risk groups of non-smoking patients with lung adenocarcinoma and to validate the model's performance. Subsequently, a nomogram model was established to systematically evaluate the impact of selected variables on prognosis. Results: Data of non-smoking patients with lung adenocarcinoma from four hospitals were retrospectively collected. We enrolled 1,172 patients, this includes 372 external validation data. Multivariate analysis identified six significant variables ( Conclusion: The prognostic model based on tumor TNM stage, tumor size, white blood cell count, neutrophil percentage, lymphocyte percentage, and hemoglobin levels effectively predicted the prognosis of non-smoking patients with lung adenocarcinoma. Compared with the more studied blood markers at present, the indicators of our model do not need conversion, Our model provides a useful reference for personalized diagnosis and treatment in clinical practice.

Indexed as

Adenocarcinoma of LungLung NeoplasmsAdultAgedFemaleHemoglobinsHumansMaleMiddle AgedNeoplasm StagingNomogramsPrognosisProportional Hazards ModelsRetrospective StudiesHemoglobinsgeneral pathological informationnomogramnon-smoking lung adenocarcinomaprognostic predictionproportional hazards model

Identifiers

PMID40160823
PMCPMC11949898

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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.