Evidence map›Paper›PMID 37776257›Full record

ArticleCancer control : journal of the Moffitt Cancer Center

Development and Validation of Prognostic Nomograms for Lung Squamous Cell Carcinoma With Brain Metastasis in Patients Aged 45 Years or Older: A Population-Based Study.

Feng Yang, Lianjun Gao, Qimin Wang, Wei Gao

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Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Feng YangDepartment of Respiratory and Critical Care Medicine, China Rehabilitation Research Center, Rehabilitation School of Capital Medical University, Beijing, China.ORCID 0009-0004-5971-9201
Lianjun GaoDepartment of Respiratory and Critical Care Medicine, China Rehabilitation Research Center, Rehabilitation School of Capital Medical University, Beijing, China.
Qimin WangDepartment of Respiratory and Critical Care Medicine, China Rehabilitation Research Center, Rehabilitation School of Capital Medical University, Beijing, China.
Wei GaoDepartment of Respiratory and Critical Care Medicine, China Rehabilitation Research Center, Rehabilitation School of Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe aimed to establish nomograms to predict the survival in patients aged ≥45  years with lung squamous cell carcinoma and brain metastasis.

methodsWe collected patients diagnosed as lung squamous cell carcinoma with brain metastasis aged ≥45 years between 2010 and 2019 from the Surveillance, Epidemiology, and End Results database. Prognostic factors were determined by the univariate and multivariate Cox regression analysis, and then the nomogram was constructed to predict cancer-specific survival and overall survival. Nomograms were evaluated by decision curve analysis, the area under the receiver operating characteristic curve, calibration plot, concordance index, and risk group stratification.

resultsIn total, 2437 patients were included, with 1706 and 731 in the cohorts of training and validation, respectively. The age, N stage, T stage, liver metastasis, chemotherapy, bone metastasis, along with radiotherapy were significant in predicting the survival, and adopted for the establishment of nomograms. In the training and validation sets, the concordance index were .713(95%CI:0.699-.728) & .700(95%CI:0.677-.722) in predicting cancer-specific survival and .715(95%CI:0.701-.729) & .712(95%CI:0.690-.735) in predicting overall survival, respectively. Besides, the area under the receiver operating characteristic curve for predicting cancer-specific survival and overall survival in the training set were all >.7 at 1-, 2-, and 3- years. Calibration plots proved the survival predicted by nomograms were consistent with the actual values. decision curve analysis revealed better clinical validity of the nomogram in predicting cancer-specific survival and overall survival at 1-year than TNM staging. Patients were stratified into the high-/low-risk groups according to the optimal cutoff value of 100.21 for cancer-specific survival and 91.98 for overall survival. A web-based probability calculator was constructed finally.

conclusionTwo nomograms were developed for the prognostic prediction of lung squamous cell carcinoma patients with brain metastasis aged ≥45 years, providing guidance for decision-making in clinical practice.

Indexed as

Brain NeoplasmsCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellLung NeoplasmsHumansLungNeoplasm StagingNomogramsPrognosisSEER Programbrain metastasiscancer-specific survivallung squamous cell carcinomanomogramsoverall survivalsurveillance, epidemiology and end results database

Identifiers

PMID37776257
PMCPMC10542326

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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.