Added survival benefit of whole brain radiotherapy in brain metastatic non-small cell lung cancer: Development and external validation of an individual prediction model

Abstract

BackgroundThe heterogeneous survival benefit of whole brain radiotherapy (WBRT) in brain metastatic non-small cell lung cancer (NSCLC) was prospectively evidenced in the Quality of Life after Treatment for Brain Metastases (QUARTZ) trial, resulting in inconsistent guideline recommendations and diverse clinical practices for giving WBRT. The objective of this study was to develop and externally validate an individual prediction model to demonstrate the added survival benefit of WBRT to assist decision making when giving WBRT is undetermined.MethodsFor model development, we collected 479 brain metastatic NSCLC patients unfit for surgery or stereotactic radiotherapy techniques at Siriraj Hospital. Potential predictors were age, sex, performance status, histology, genetic mutation, neurological symptoms, extracranial disease, previous systemic treatment, measurable lesions, further systemic treatment, and WBRT. Cox proportional hazard regression was used for survival analysis. We used multiple imputations to handle missing data and a backward selection method for predictor selection. Bootstrapping was used for internal validation, while model performance was assessed with discrimination (c-index) and calibration prediction accuracy. The final model was transformed into a nomogram and a web-based calculator. An independent cohort from Sawanpracharak Hospital was used for external validation.ResultsIn total, 452 patients in the development cohort died. The median survival time was 4.4 (95% CI, 3.8–4.9) months, with 5.1 months for patients who received WBRT and 2.3 months for those treated with optimal supportive care (OSC). The final model contained favorable predictors: female sex, KPS > 70, receiving additional systemic treatment, and WBRT. Having active extracranial disease, experiencing neurological symptoms, and receiving previous systemic treatment were adverse predictors. After optimism correction, the apparent c-index dropped from 0.71 (95% CI, 0.69–0.74) to 0.70 (95% CI, 0.69–0.73). The predicted and observed values agreed well in all risk groups. Our model performed well in the external validation cohort, with a c-index of 0.66 (95% CI, 0.59–0.73) and an acceptable calibration.ConclusionsThis model (https://siriraj-brainmetscore.netlify.app/) predicted the added survival benefit of WBRT for individual brain metastatic NSCLC patients, with satisfactory performance in the development and validation cohorts. The results certify its value in aiding treatment decision-making when the administration of WBRT is unclear.

Evaluation of potential predictive biomarkers for defining brain radiotherapy efficacy in NSCLC patients with brain me-tastases: A case report and review of literature

“…As a result, there is the need to define potential biomarkers which can help to identify patients who can really benefit from brain radiotherapy, avoiding useless treatments. So far, some scoring systems have been proposed [70][71][72]. Here, by presenting the clinical outcomes obtained from WBRT in a patient with brain metastases from an advanced NSCLC carrying a BRAF V600E mutation, we analysed the potential variables as well as the available scoring systems useful to predict clinical outcomes and benefits from brain radiotherapy in patients with NSCLC and brain metastases.…”

Evaluation of Potential Predictive Biomarkers for Defining Brain Radiotherapy Efficacy in Non-Small Cell Lung Cancer Patients with Brain Metastases: A Case Report and a Narrative Review

“…Hence, there is a need to define potential biomarkers which can assist with identifying patients with the greatest benefits to gain from brain radiotherapy, and those who could avoid treatments with little or no benefit. Thus far, a number of scoring systems have been proposed [10][11][12].…”