Evidence map›Paper›PMID 42361328›Full record

ArticleJMIR cancer2026

Predicting Overall Survival in Patients With Multiple Primary Lung Cancer: Nomogram Development and Validation Study.

Wenzhi Luo, Kengliang Rao, Hongjia Chen, Cailian Hu, Shengming Liu, Jing Wang, Dongdong Zhang, Li Chen

Abstract readValidation Study
In one paragraph

Article in JMIR cancer, 2026. 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

8 authors.

Wenzhi Luo *Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Jinan University, 613 Huangpu Avenue West, Tianhe District, Guangzhou, Guangdong, China, 86 02038688888.ORCID 0009-0006-0935-9230
Kengliang Rao *Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Jinan University, 613 Huangpu Avenue West, Tianhe District, Guangzhou, Guangdong, China, 86 02038688888.ORCID 0009-0005-2534-7486
Hongjia Chen *Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Jinan University, 613 Huangpu Avenue West, Tianhe District, Guangzhou, Guangdong, China, 86 02038688888.ORCID 0009-0000-1533-1599
Cailian HuDepartment of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Jinan University, 613 Huangpu Avenue West, Tianhe District, Guangzhou, Guangdong, China, 86 02038688888.ORCID 0009-0002-2248-7959
Shengming LiuDepartment of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Jinan University, 613 Huangpu Avenue West, Tianhe District, Guangzhou, Guangdong, China, 86 02038688888.ORCID 0000-0003-0193-8300
Jing Wang *Department of Pulmonary and Critical Care Medicine, Meizhou People's Hospital, Meizhou, Guangdong, China.ORCID 0009-0000-0798-7432
Dongdong Zhang *Department of Thoracic Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.ORCID 0009-0001-0595-3316
Li Chen *Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Jinan University, 613 Huangpu Avenue West, Tianhe District, Guangzhou, Guangdong, China, 86 02038688888.ORCID 0000-0003-3674-5824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the rapid development of medical technology and the emphasis on early lung cancer screening, the detection rate of multiple primary lung cancer (MPLC) has increased in recent years. However, the prognostic determinants and clinical characteristics of patients with MPLC remain poorly characterized. Objective: This study aimed to develop and validate a nomogram for predicting overall survival (OS) in patients with MPLC using data from the Surveillance, Epidemiology, and End Results database. Methods: This study was reported in accordance with the TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guidelines. A cohort of 4177 patients with MPLC (2007-2015) was obtained from the Surveillance, Epidemiology, and End Results database. The patients were randomly divided into training (n=2923) and validation (n=1254) cohorts at a 7:3 ratio. Backward stepwise Cox regression identified 11 independent risk factors, which were integrated into a nomogram predicting 3-, 5-, and 8-year OS rates. Results: The nomogram demonstrated superior discriminative ability compared to the American Joint Committee on Cancer staging system, with higher area under the receiver operating characteristic curve values for 3-, 5-, and 8-year OS predictions in both cohorts (training cohort: 0.743, 0.751, and 0.759, respectively; validation cohort: 0.737, 0.734, and 0.695, respectively). Calibration curves and decision curve analysis confirmed its clinical utility. Conclusions: This study establishes a validated nomogram incorporating clinical and socioeconomic variables to optimize prognostic assessment and personalized treatment planning for patients with MPLC.

Indexed as

Lung NeoplasmsNeoplasms, Multiple PrimaryNomogramsAgedFemaleFollow-Up StudiesHumansMaleMiddle AgedNeoplasm StagingRisk FactorsROC CurveSEER ProgramSocioeconomic FactorsSurvival Ratemultiple primary lung cancernomogramoverall survivalSEER databaseSurveillance, Epidemiology, and End Results databasesurvival prediction

Identifiers

PMID42361328
PMCPMC13309065

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.