Blood. 2022 Jun 30:blood.2022015727. doi: 10.1182/blood.2022015727. Online ahead of print.
ABSTRACT
While venous thromboembolism (VTE) is an important treatment and disease-related complication in myeloma, a validated risk-prediction model including disease-specific variables such as cytogenetics or tumor burden is lacking. The aim of our study was to develop a new risk-prediction model for VTE in the context of modern anti-myeloma therapy. All consecutive patients diagnosed at Cleveland Clinic during 2008-2018 and with available data on baseline candidate risk-factors constituted the derivation cohort. The primary outcome was VTE (deep venous thrombosis/pulmonary embolism) within one year of treatment initiation. A multivariable model was utilized and weights were derived from subdistribution hazard ratios (sHR) to construct a risk-score. The model was validated both by internal bootstrap validation and in an external validation cohort. The derivation cohort consisted of 783 patients. A 5 component risk-prediction tool, named PRISM score, was developed, including the following variables: prior VTE, prior surgery, immunomodulatory drug (IMiD) use, abnormal metaphase cytogenetics, and Black race. The c-statistic of the model was 0.622 (95% CI, 0.567-0.674). The model stratified patients into low, intermediate, and high-risk, with 12-month cumulative VTE incidence of 2.7%, 10.8%, and 36.5% respectively. Risk of VTE increased significantly with increasing score in both derivation and external validation datasets, with the sHR per 1-point increase being 1.28 (95% CI, 1.19-1.39; p<0.001) and 1.23 (95% CI, 1.07-1.41; p=0.004) respectively. While PRISM score can guide clinicians in identifying patients at a high risk of VTE, additional external validation is necessary for incorporation into routine clinical practice.
PMID:35772005 | DOI:10.1182/blood.2022015727