Estimating risk of venous thromboembolism in patients with cancer in the presence of competing mortality. (14th January 2015) - Ay, C.; Posch, F.; Kaider, A.; Zielinski, C.; Pabinger, I.
Summary Background In studies on cancer‐associated venous thromboembolism (VTE), patients not only are at risk for VTE but also may die from their underlying malignancy. Objectives In this competing‐risk (CR) scenario, we systematically compared the performance of standard (Kaplan–Meier estimator [1‐KM]), log‐rank test, and Cox model) and specific CR methods for time‐to‐VTE analysis. Patients and Methods Cancer patients (1542) were prospectively followed for a median of 24 months. VTE occurred in 112 (7.3%) patients, and 572 (37.1%) patients 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%, respectively). 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 Cox model 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 log‐rank test yielded a higher test statistic and smaller P‐value than Gray's test (χ2 on 1 degree of freedom: 29.88 vs. 21.34). Conclusion In patients with cancer who are at risk for VTE and death, standard and CR 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.