Evidence map›Paper›PMID 33842628›Full record

ArticleAnnals of translational medicine2021

Nomogram for predicting the survival rate of primary pulmonary mucoepidermoid carcinoma patients: a retrospective study based on SEER database.

Guo Lin, Hengrui Liang, Wei Wang, Jun Liu, Jianfu Li, Wenhua Liang, Jianxing He

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Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Guo LinDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Hengrui LiangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Wei WangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Jun LiuDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Jianfu LiDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Wenhua LiangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Jianxing HeDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrimary pulmonary mucoepidermoid carcinoma (PMEC) is a rare malignant tumor, and the clinical manifestations lack specificity. The study evaluates the prognostic factors and constructs a practicable nomogram to estimate the individualized survival status for PMEC patients.

methodsSurveillance, Epidemiology, and End Results (SEER) database was used to selected eligible patients between 1975 and 2016. The baseline characteristics including age, sex, race, marital status, tumor stage, differentiated degree, tumor laterality, primary tumor site, tumor size, lymph node metastases status, distant metastases status, surgery, chemotherapy, and radiation. We identified independent variables to build 3-, 5-, 10-year overall survival (OS) and cancer-specific survival (CSS) nomograms by univariate and multivariate analyses.

resultsA total of 438 PMEC patients met our selection criteria. In multivariate analysis, age, tumor stage, differentiated grade, tumor size, lymph node metastases status, distant metastases status, surgery and radiation were involved in the nomogram. The C-index (0.887 (95% CI: 0.863-0.911), calibrate plots and ROC curves (AUC =0.941, 0.951, 0.935 for 3-, 5-, 10-year OS, respectively) indicated the satisfied accuracy and practicability of our nomograms. Compared to TNM system, our model also showed a superior prediction (IDI =0.167, 0.171, 0.172, P<0.001).

conclusionsWe built OS (CSS) nomograms that can accurately estimate individualized survival time and identify the risk classification of PMEC.

Indexed as

Cancer-specific survival (CSS)NomogramOverall survivalPulmonary mucoepidermoid carcinoma (PMEC)Surveillance, Epidemiology, and End Results (SEER)

Identifiers

PMID33842628
PMCPMC8033396

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