Predicting Cardiovascular Adverse Events in Multiple Myeloma

By Patrick Daly - Last Updated: April 12, 2023

Researchers recently investigated the increasing prevalence of cardiovascular adverse events (CVAEs) in patients with multiple myeloma (MM). Their study sought to identify clinical markers for predicting risk and prognosis in this population.

According to the study’s lead author, Shuai Yuan, being over 61 years old, having a high baseline office blood pressure, and being diagnosed with left ventricular hypertrophy (LVH) were all independent factors associated with CVAEs in patients with newly-diagnosed MM. The investigators’ prognostic model was presented in Frontiers on Oncology.

A 3-Item, 4-Point Risk Model for CVAEs in MM

This retrospective study recruited 253 patients with MM from 2 medical centers in China between June 2018 and July 2020. Participants were divided into a training and validation cohort to develop and confirm the prognostic model’s utility. Univariable analysis was used to assess baseline factors for associations with CVAE endpoints, and multivariable analysis was used to verify factors of interest.

In the 4-point prognostic model, being over 61 years old contributed 2 points, and LVH and high baseline office blood pressure each contributed 1 point. A score of 3-4 was defined as high risk, 2 points intermediate risk, and 0-1 point low risk.

According to the authors, the model had good calibration for 1- and 2-year CVAEs and the risk classifications showed significant differences in CVAEs during follow-up in both the training (P=.0001) and validation (P=.0018) cohorts. In addition, the C-index for predicting overall CVAE survival was 0.73 (95% CI, 0.67-0.79) in the training cohort and 0.66 (95% CI, 0.51-0.81) in the validation cohort.

To conclude, Yuan and colleagues suggested “patients at increased risk of CVAEs can be identified at treatment initiation and be more focused on cardiovascular protection in the treatment plan,” via their prognostic risk prediction model.

Related: Comparing Induction Regimens for Multiple Myeloma

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