Association of systemic corticosteroids with overall survival in patients receiving cancer immunotherapy for advanced melanoma, non-small cell lung cancer or urothelial cancer in routine clinical practice

Abstract

Corticosteroids (CS) are often prescribed for patients (pts) with cancer to alleviate disease symptoms, manage treatment-related adverse events, or treat underlying comorbidities. Immunosuppressive properties of CS may impact the effectiveness of cancer immunotherapy (CIT) if given concomitantly. This study explored the association of baseline CS use with outcomes in CIT-treated pts with advanced melanoma (aMel), advanced non-small cell lung cancer (aNSCLC) or advanced urothelial cancer (aUC). Retrospective observational study of pts in the Flatiron Health de-identified electronic health record–derived database diagnosed Jan 2011-Jun 2017 with aMel, aNSCLC or aUC and treated with CIT only in any line. Baseline CS use was defined as intravenous or intramuscular administration or oral orders ≤14 days prior and up to 30 days after start of CIT. Association of baseline CS use with overall survival (OS) was estimated using multivariable Cox proportional hazards models adjusted for key baseline characteristics. Most pts were white males aged 66-72 years at first CIT treatment. Most pts with aNSCLC (56%) or aUC (59%) received 2L CIT; patients with aMel (89%) used CIT in 1L. Pts taking baseline CS (19%-30%) were more likely to have stage IV disease at diagnosis, brain metastases, liver metastases (aNSCLC, aUC) and poorer ECOG PS scores (aUC) at baseline. The use of baseline CS was associated with a 23%-47% higher risk of death compared with no use in multivariable models. Baseline CS was associated with shorter survival for pts treated with CIT and not explained by measured confounders. These results suggest that avoidance of CS should be considered at the initiation of treatment, when possible and appropriate, to maximize the potential benefits of CIT. Further studies are needed to confirm these observations.

Jinjoo Shim

Digital Health Data Scientist

My research interests is to advance digital healthcare through AI/ML and data science.