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Healthcare 2016, 4(1), 16;

Incidence and Risk Factors of Thromboembolism with Multiple Myeloma in the Presence of Death as a Competing Risk: An Empirical Comparison of Statistical Methodologies

Institute for Pharmaceutical Outcomes and Policy, Department of Pharmacy Practice and Science, College of Pharmacy, University of Kentucky, Lexington, KY 40536, USA
Author to whom correspondence should be addressed.
Academic Editor: Sampath Parthasarathy
Received: 29 December 2015 / Revised: 19 February 2016 / Accepted: 23 February 2016 / Published: 26 February 2016
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Multiple myeloma (MM) has an inherent high risk of thromboembolic events associated with patient as well as disease- and treatment-related factors. Previous studies have assessed the association of MM-related thromboembolism using “traditional” Kaplan–Meier (KM) and/or Cox proportional hazard (PH) regression. In the presence of high incidence of death, as would be the case in cancer patients with advanced age, these statistical models will produce bias estimates. Instead, a competing risk framework should be used. This study assessed the baseline patient demographic and clinical characteristics associated with MM-related thromboembolism and compared the cumulative incidence and the measures of association obtained using each statistical approach. The cumulative incidence of thromboembolism was 9.2% using the competing risk framework and nearly 12% using the KM approach. Bias in the measures of covariate risk associations was highest for factors related to risk of death such as increased age (75% bias) and severe liver disease (50%) for the Cox PH model compared to the competing risk model. These results show that correct specification of statistical techniques can have a large impact on the results obtained. View Full-Text
Keywords: venous thromboembolism; multiple myeloma; competing risks venous thromboembolism; multiple myeloma; competing risks

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Brown, J.D.; Adams, V.R. Incidence and Risk Factors of Thromboembolism with Multiple Myeloma in the Presence of Death as a Competing Risk: An Empirical Comparison of Statistical Methodologies. Healthcare 2016, 4, 16.

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