With recent improvements in therapy, median survival after diagnosis for patients with Multiple Myeloma (MM) now exceeds 5 years. However, for a variety of reasons most patients do not receive the most intensive therapy for MM, namely autologous stem cell transplantation (auto-SCT). In order to better understand which patients will receive the greatest benefit from auto-SCT, we developed a machine learning (ML) model to identify relevant predictors of 5-year mortality for MM patients who received auto-SCT. Previous studies have identified adverse cytogenetics (e.g., chromosome 13 deletion), elevated B2-microglobulin, elevated lactate dehydrogenase, and the receipt of more than 1 year of standard chemotherapy as prognostic risk factors. Using several ML techniques, we built a predictive model for 5-year mortality post-transplant and identified features that were most predictive.
Find the abstract for this project here.