Evidence map›Paper›PMID 37653012›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2023

[Development and Validation of A Prognostic Nomogram to Guide Decision-making 
in Lung Large Cell Neuroendocrine Carcinoma].

Sheng Chen, Shaoxiang Li, Zipeng Wang, Wenxi Zhang, Liang Zhou, Wenjie Jiao

Open access · greenAbstract readEnglish Abstract
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Sheng ChenDepartment of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao 266071, China.
Shaoxiang LiDepartment of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao 266071, China.
Zipeng WangDepartment of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao 266071, China.
Wenxi ZhangDepartment of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao 266071, China.
Liang ZhouDepartment of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao 266071, China.
Wenjie JiaoDepartment of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao 266071, China.
Qingdao University · CNAffiliated Hospital of Qingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung large cell neuroendocrine carcinoma (LCNEC) is a rare and highly malignant lung tumor with a poor prognosis. Currently, most research on LCNEC is based on retrospective studies and lacks validation in the real world. The study aims to identify independent risk factors and establish and validate a predictive model for the prognosis of LCNEC.

methodsPatient data were extracted from Surveillance, Epidemiology, and End Results (SEER) and our department's hospitalization records from 2010 to 2015 and 2016 to 2020, respectively. Kaplan-Meier analysis was used to evaluate overall survival (OS). OS is defined as the time from diagnosis to death or last follow-up for a patient. Univariate and multivariate Cox regression analyses were performed to identify significant prognostic factors and construct a Nomogram for predicting the prognosis of LCNEC.

resultsIn total, 1892 LCNEC patients were included and divided into a training cohort (n=1288) and two validation cohorts (n=552, n=52). Univariate Cox regression analysis showed that age, gender, primary tumor site, laterality, T stage, N stage, M stage, surgery, and radiotherapy were factors that could affect the prognosis of LCNEC patients (P<0.05). Multivariate Cox analysis indicated that age, gender, primary tumor site, T stage, N stage, M stage, surgery, and radiotherapy were independent risk factors for the prognosis of LCNEC patients (P<0.05). Calibration curves and the concordance index (internal: 0.744±0.015; external: 0.763±0.020, 0.832±0.055) demonstrated good predictive performance of the model.

conclusionsPatients aged ≥65 years, male, with advanced tumor-node-metastasis (TNM) staging, and who have not undergone surgery or radiotherapy have a poor prognosis. Nomogram can provide a certain reference for personalized clinical decision-making for patients.

Indexed as

Carcinoma, NeuroendocrineLung NeoplasmsHumansLungMaleNomogramsPrognosisRetrospective StudiesLung large cell neuroendocrine carcinomaLung neoplasmsNomogramRisk factors

Identifiers

PMID37653012
PMCPMC10476212
OpenAlexW4386347762

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