International journal of cancer · 2026
Prediction of the individual risk for the development of brain metastases in patients with non-oncogene-addicted non-small cell lung cancer: Real-world data from the German prospective CRISP registry (AIO-TRK-0315).
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Acker Fabian, Wenger Katharina, Reck Martin, Waller Cornelius F, Hoffknecht Petra, Bethge Andre, Nusch Arnd, Reiser Marcel, Bernhardt Christiane, Bendel Michael, Lennartz Carolin, Fleitz Annette, Jänicke Martina, Ludwig Paula, Groth Annika, Griesinger Frank, Thomas Michael, Eberhardt Wilfried E E, Sebastian Martin, CRISP Registry Group
Аннотация
Brain metastases (BM) from non-small cell lung cancer (NSCLC) are a relevant cause of morbidity and mortality. This study aims to identify a population at high risk for BM in order to inform personalized follow-up strategies in the future. We have therefore developed and validated a point-based risk classifier for the risk of BM1 in patients with metastatic non-oncogene-addicted NSCLC without BM at disease onset. A total of 3139 patients were included from the German CRISP lung cancer registry and randomly assigned to a derivation and validation set (2:1). In the derivation set, a Fine and Gray model was developed considering BM and death competing risks. A point-based risk classifier was derived and evaluated in the validation set. Of the baseline variables included in the risk model, ≥4 versus 0 extrathoracic metastatic sites (hazard ratio [HR], 2.69; 95% CI, 1.45-5.00), N3 vs. N0 disease (2.29; 1.41-3.72), and age < 65 vs. ≥75 years (2.03; 1.39-2.98) were the strongest predictors of BM development. Using the risk classifier, high-risk patients in the derivation set had a cumulative incidence of BM of 23.7% (95% CI, 16.7-30.1) at 18 months compared to 10.3% (8.9-11.7) in low-risk patients (HR, 2.44; 95% CI, 1.87-3.19). In the validation set, the cumulative incidence of BM at 18 months was 14.7% (11.5-17.8) and 8.9% (6.2-11.6) in the high-risk and low-risk groups, respectively (HR, 1.54; 95% CI, 1.08-2.20). In conclusion, our point-based risk classifier is able to identify NSCLC patients at high risk for BM development that may benefit from intensified brain surveillance.