Estimating risk of venous thromboembolism in patients with cancer in the presence of competing mortality.
J Thromb Haemost. 2014 Dec 20;
Authors: Ay C, Posch F, Kaider A, Zielinski C, Pabinger I
BACKGROUND: In studies on cancer-associated venous thromboembolism (VTE), patients are not only at risk for VTE but may also die from their underlying malignancy.
OBJECTIVES: In this competing-risk (CR) scenario, we systematically compared the performance of standard (Kaplan-Meier-estimator (1-KM), logrank-test (LRT), Cox model (CM)) and specific CR methods for time-to-VTE-analysis.
PATIENTS&METHODS: 1542 cancer patients were prospectively followed for a median of 24 months. VTE occurred in 112 patients (7.3%), and 572 patients (37.1%) died.
RESULTS: In comparison with the CR method, 1-KM slightly overestimated the cumulative incidence of VTE (Cumulative VTE incidence at 12 and 24 months (1-KM vs. CR): 7.22% vs. 6.74%, and 8.40% vs. 7.54%). Greater bias was revealed in tumor entities with high early mortality (e.g. pancreatic cancer, n=99, 24-month Cumulative VTE incidence: 28.37% vs. 19.30%). Comparing the (subdistribution-)hazard of VTE between patients with low and high baseline D-Dimer, the CM yielded a higher estimate than the corresponding CR model (Hazard vs. Subdistribution hazard ratio (95%CI):2.85 (1.92-4.21) vs. 2.47 (1.67-3.65)). For this comparison, the LRT yielded a higher test statistic and smaller p-value than Gray's test (χ(2) on 1 degree of freedom: 29.88 vs. 21.34).
CONCLUSION: In patients with cancer at risk for VTE and death, standard and competing risk methods for time-to-VTE analysis can generate differing results. For 1-KM, the magnitude of bias is a direct function of competing mortality. Consequently, bias tends to be negligible in cancer patient populations with low mortality, but can be considerable in populations at high risk of death. This article is protected by copyright. All rights reserved.
PMID: 25529107 [PubMed - as supplied by publisher]