Survival predictive nomograms for non-surgical lung squamous-cell carcinoma patients with brain metastases: a SEER-based retrospective cohort study with external validation

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Abstract Objectives Brain metastasis (BM) is a devastating complication in patients with lung squamous cell carcinoma (LUSC), often precluding surgical intervention. The majority of LUSC patients with BM are managed non-surgically and face a poor prognosis. There is a lack of validated prognostic tools for this significant patient population. This study aims to fulfill this gap among this cohort. Methods A retrospective cohort of 1,581 non-surgical LUSC patients with BM was identified from the SEER database (2010–2015) and randomly split into training (n=1,106) and internal validation (n=475) cohorts. An external validation cohort consisted of 102 patients from the real world. Univariable and multivariable Cox regression analyses were performed to identify independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS). Nomograms were constructed and validated internally and externally using calibration curves, time-dependent receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and Kaplan-Meier analysis. Results Multivariable analyses identified independent factors for OS and CSS. The constructed nomograms demonstrated relatively high area under the curve (AUC) valuesfor predicting 1-, 2-, and 3-year OS and CSS in the training (>0.74), internal validation (>0.69), and external validation cohorts (>0.76). Calibration curves showed satisfactory agreement between predicted and observed outcomes. DCA confirmed the clinical utility of the nomograms across a range of threshold probabilities. Risk stratification based on nomogram scores effectively distinguished between low-risk and high-risk groups. Conclusion This study developed and validated nomograms for predicting OS and CSS in non-surgical LUSC patients with BM. These tools demonstrate relatively good performance and clinical utility.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.