Multiple Myeloma Coverage from Every Angle

Prognostic Model for Transplant-Ineligible Patients With Multiple Myeloma

By: Cordi Craig
Posted: Monday, April 8, 2019

Using features such as patient age and disease stage, researchers developed the U.K. Myeloma Research Alliance Risk Profile, a model that may help predict the outcome of patients with multiple myeloma who are unsuitable for high-dose therapy and stem cell transplantation. The model, developed by Gordon Cook, PhD, of the University of Leeds, United Kingdom, and colleagues, used routinely collected and widely available clinical parameters to predict overall survival. Their findings were published in The Lancet Haematology.

“The association of [the U.K. Myeloma Research Alliance Risk Profile] groups with the percentage of protocol dose delivered suggests that the [model] might be able to predict early treatment cessation, which could enable pre-emptive, up-front dose adjustment of patients, preventing toxicity and potentially enabling patients to stay on therapy for longer,” the authors concluded.

The U.K. Myeloma Research Alliance Risk Profile used data from 2 randomized controlled trials conducted in newly diagnosed transplant-ineligible patients with multiple myeloma. The trials were the NCRI Myeloma XI study (n = 1,852) and the MRC Myeloma IX study (n = 520).

The model was prognostic of overall survival and successfully internally and externally validated according to predefined criteria in NCRI Myeloma XI (prognostic separation D-statistic = 0.840) and MRC Myeloma IX (prognostic separation D-statistic = 0.654). (The D-statistic is a measure of discrimination for time-to-event endpoints, of which higher values indicate better discrimination.) The researchers found correlations for the model groups that defined low-, medium-, and high-risk patients with progression-free survival, early mortality, and the percentage of protocol dose delivered. The model groups remained prognostic irrespective of patients exposed to different therapeutic combinations and those with genetic high-risk disease, suggesting that patient age and fitness may impact survival and tolerability.

Disclosure: The study authors’ disclosure information can be found at

By continuing to browse this site you permit us and our partners to place identification cookies on your browser and agree to our use of cookies to identify you for marketing. Read our Privacy Policy to learn more.