A new frailty-based outcome prediction model for multiple myeloma (MM) was found to be an easy-to-use tool in clinical practice and produced valid results based on a large real world cohort of patients with a new MM diagnosis, according to a recent study.
A new frailty-based outcome prediction model for multiple myeloma (MM) was found to be an easy-to-use tool in clinical practice and produced valid results based on a large real world cohort of patients in the United Kingdom, according to a recent study.
The retrospective study, published in PLoS One, was the first to evaluate clinical outcomes according to the Myeloma Risk Profile (MRP) in a high-risk real-world cohort of patients who have been treated with proteasome inhibitor–based VCD (bortezomib [Velcade]/cyclophosphamide/dexamethasone) therapy.
“Further evaluation of MRP in the real world when continuous therapies are used can further support its prognostic role in elderly myeloma patients,” the investigators wrote.
It is difficult to achieve optimal myeloma outcomes because patients often present with the disease at an older age, organ dysfunction, comorbidities, and frailty, the authors noted. Increased toxicity burden can lead to providers lowering the doses or discontinuing treatments for patients with MM. Because of this, the focus of clinical practice has shifted toward reducing the risk of undertreatment fit patients and overtreating frail patients.
Other risk prediction models, like the International Myeloma Working Group and the revised Myeloma Co-morbidity Index, have been validated but may be limited because they can be time consuming.
Additionally, “there remains an ongoing debate on whether the current frailty assessments, such as MRP, are in need of further harmonisation prior to implementation into myeloma treatment decision-making in routine care, such as the inclusion of biomarkers for ageing, and other parameters reflective of baseline patient-related characteristics,” said the investigators.
They conducted an analysis to validate the use of the MRP in patients with newly diagnosed MM ineligible for transplant. For inclusion in the study, patients had to have symptomatic MM that required treatment with systematic first-line therapy who could not receive a stem cell transplant due to their advanced age or comorbidities. All patients had to be treated within the UK Thames Valley Cancer Network with at least 1 cycle of VCD chemotherapy.
In total, 158 patients treated with VCD therapy between June 2012 and December 2018 were identified, and 100 were include in the final cohort. The patients had their overall MRP scores calculated and were categorized into 1 of 3 fitness groups,
Overall, 62 of the patients were classified as frail, 27 were of intermediate fitness, and 11 were considered fit. The analysis focused on frail (n = 62) vs nonfrail (n = 38) patients. The median age of the entire cohort was 76 years, and 53% were men.
Patients in the frail group were older and had worse progression-free survival a higher median C-reactive protein value. A higher proportion of frail patients had to discontinue therapy due to their disease progressing compared with patients who were fit or had intermediate fitness: 19.4% vs 15.8%.
The overall response rate for the whole cohort was 75% and was comparable between the subgroups. There were 222 adverse events (AEs) experienced by 80 patients. The median total AEs of any grade per patient in the total cohort was 2. A higher incidence of AEs was observed in the frail subgroup (85.5%) compared with the nonfrail subgroup (71.1%).
The study had some limitations, including the small sample size, the potential for confounding factors and a patient selection bias, and the possibility for medical chart misinterpretation and underreporting of toxicities.
Reference
Djebbari F, Rampotas A, Panitsas F, et al. Evaluation of the frailty characteristics and clinical outcomes according to the new frailty-based outcome prediction model (Myeloma Risk Profile-MRP) in a UK real-world cohort of elderly newly diagnosed Myeloma patients. PLoS ONE. Published online January 11, 2022. doi:10.1371/journal.pone.0262388
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