Evidence map›Paper›PMID 36104656›Full record

ArticleBMC cancer2022

Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort.

Liang Zhou, Yahui Zhang, Wenyu Chen, Niu Niu, Junjie Zhao, Weibo Qi, Yufen Xu

Abstract read
In one paragraph

Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

7 authors.

Liang Zhou *Bengbu Medical College Graduate Department, Bengbu, 233000, China.
Yahui Zhang *Bengbu Medical College Graduate Department, Bengbu, 233000, China.
Wenyu Chen *Departement of Respiratory, Affiliated Hospital of Jiaxing University, 314000, Zhejiang, People's Republic of China.
Niu NiuDepartment of Cardio-Thoracic Surgery, Affiliated Hospital of Jiaxing University, 314000, Zhejiang, People's Republic of China.
Junjie ZhaoDepartment of Cardio-Thoracic Surgery, Affiliated Hospital of Jiaxing University, 314000, Zhejiang, People's Republic of China.
Weibo QiDepartment of Cardio-Thoracic Surgery, Affiliated Hospital of Jiaxing University, 314000, Zhejiang, People's Republic of China. qiweibo0221@163.com.
Yufen XuDepartment of Medical Oncology, Affiliated Hospital of Jiaxing University, 314000, Zhejiang, People's Republic of China. xuyufen@zjxu.edu.cn.

Funding

Natural Science Foundation of Zhejiang province NO. LQ20H160057Science and technology project of Jiaxing 2019AY32030,2020AY30012,2021AY30024the Jiaxing Key Laboratory of Precision Treatment for Lung Cancer,Scientific Technology Plan Program for Healthcare in Zhejiang Province NO. 2021RC031,2022KY377the Key Discipline of Jiaxing Medicine Construction Project grant No.2019-zc-04,2019-zc-09,2019-zc-11
6 · The paper itself

Abstract

objectiveThis study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC).

methodsFor the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves.

resultsA Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718-0.735) and 0.721 (95% CI, 0.709-0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691-0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system.

conclusionWe developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsChinaHumansNomogramsPrognosisSEER ProgramNomogramNon-small cell lung cancerOverall survivalStage I and II

Identifiers

PMID36104656
PMCPMC9476583

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