Researchers have developed a new tool for helping clinicians tailor personalized treatment plans for patients with a rare blood cancer called chronic myelomonocytic leukemia (CMML). The tool, called the international CMML Prognostic Scoring System (iCPSS), may help improve a patient’s chance of survival.
CMML is caused by genetic mutations in bone marrow stem cells that are acquired over one’s lifetime. The only curative treatment is a stem cell transplant, which replaces diseased cells with healthy donor cells. But it is a risky procedure that can cause severe complications such as infections or graft-versus-host disease. It is not a suitable option for many patients, and oncologists have limited data to help them choose which patients are best suited for transplantation.
To address that challenge, the research team created iCPSS using machine learning techniques to analyze clinical and genetic data from more than 3,000 patients. The tool helps clinicians identify which patients will have the best outcomes from stem cell transplantation and determine the optimal timing for the procedure. The researchers published their findings in the Journal of Clinical Oncology.
“Our tool can help physicians decide when is the best time to discuss transplantation with their patients,” says Luca Lanino, MD, a postdoctoral associate at Yale School of Medicine and the study’s first author.