Derivation and Validation of a Risk Assessment Model for Immunomodulatory Drug–Associated Thrombosis Among Patients With Multiple Myeloma

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  • a Division of Hematology, University of Washington School of Medicine, and
  • | b Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington;
  • | c Research Service, St. Louis Veterans Affairs Medical Center, St. Louis, Missouri;
  • | d Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington;
  • | e Departments of Medicine and Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont;
  • | f Division of Medical Oncology, University of Washington School of Medicine, Seattle, Washington; and
  • | g Division of General Medical Sciences, Washington University School of Medicine, St. Louis, Missouri.
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Background: Although venous thromboembolism (VTE) is a significant complication for patients with multiple myeloma (MM) receiving immunomodulatory drugs (IMiDs), no validated clinical model predicts VTE in this population. This study aimed to derive and validate a new risk assessment model (RAM) for IMiD-associated VTE. Methods: Patients with newly diagnosed MM receiving IMiDs were selected from the SEER-Medicare database (n=2,397) to derive a RAM and then data from the Veterans Health Administration database (n=1,251) were used to externally validate the model. A multivariable cause-specific Cox regression model was used for model development. Results: The final RAM, named the “SAVED” score, included 5 clinical variables: prior surgery, Asian race, VTE history, age ≥80 years, and dexamethasone dose. The model stratified approximately 30% of patients in both the derivation and the validation cohorts as high-risk. Hazard ratios (HRs) were 1.85 (P<.01) and 1.98 (P<.01) for high- versus low-risk groups in the derivation and validation cohorts, respectively. In contrast, the method of stratification recommended in the current NCCN Guidelines for Cancer-Associated Venous Thromboembolic Disease had HRs of 1.21 (P=.17) and 1.41 (P=.07) for the corresponding risk groups in the 2 datasets. Conclusions: The SAVED score outperformed the current NCCN Guidelines in risk-stratification of patients with MM receiving IMiD therapy. This clinical model can help inform providers and patients of VTE risk before IMiD initiation and provides a simplified clinical backbone for further prognostic biomarker development in this population.

Submitted November 8, 2018; accepted for publication January 11, 2019.

Author contributions: Research design: Li, Garcia, Lyman, Sanfilippo. Statistical analysis: Li, Wu, Luo. Database extraction: Warnick. Data analysis and interpretation: Li, Garcia, Lyman, Sanfilippo. Draft of manuscript: Li. Review and editing of manuscript: Zakai, Libby, Gage.

Disclosures: Dr. Garcia has disclosed that he is a consultant for Janssen. Dr. Lyman has disclosed that he has received grant/research support from Bayer. The remaining authors have not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.

Funding: Research reported in this publication was supported by National Heart, Lung, and Blood Institute (NHLBI; grants T32HL007093 [Li] and K01HL136893 [Sanfilippo]) and the Conquer Cancer Foundation Young Investigator Award (Li).

Disclaimer: This study used the linked SEER-Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors.

Correspondence: Ang Li, MD, University of Washington, 825 Eastlake Avenue East, M/S CE3-300, Seattle, WA 98109. Email:

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