Enhancing risk stratification and treatment decision in multiple myeloma with SKY92 gene expression profiling in real-world data.
Academic Article
Overview
abstract
Over the years, numerous prognostic markers for multiple myeloma (MM) risk classification have been identified; however, their variability can lead to inconsistent clinical interpretations. Gene expression profiling (GEP) signatures, such as SKY92, offer a more accurate method for patient stratification. The PRospective Observational Multiple Myeloma Impact Study (NCT02911571) aimed to validate SKY92's prognostic performance using real-world data and assess its impact on risk classification and treatment decisions compared to conventional markers. In a study of 251 newly diagnosed MM patients, physicians completed questionnaires to capture risk classification, hypothetical treatment plans and their confidence in those plans before and after unblinding SKY92 results. Poor concordance was observed between initial clinical risk assessment (iCRA) and SKY92 results (high risk: 51% iCRA vs. 28% SKY92, Cohen's κ = 0.21). SKY92 showed superior performance in identifying high-risk patients, leading to better predictions of progression-free survival and overall survival (p ≤ 0.0001) than traditional risk markers. Unblinding SKY92 results led to hypothetical treatment revisions for 50% of patients (p < 0.001) and increased physicians' confidence in treatment decisions for 40% of cases. These findings support SKY92's prognostic value in identifying high-risk MM patients, outperforming traditional risk markers and demonstrating the potential added value of its integration into clinical practice for more personalized risk assessment.
