Abstract
Cancer-associated thrombosis (CT) carries a high, heterogeneous, and poorly predicted
likelihood of mortality. Thus, we aimed to define predictors of 30-day mortality in
10,025 patients with CT. In a randomly selected derivation cohort, we used recursive
partitioning analysis to detect variables that select for a risk of mortality within
30 days. In a validation cohort, we evaluated our results using Cochran–Armitage test.
The most common types of cancer were lung (16%), breast (14%), and colorectal (14%);
median age was 69 years (range, 14–101); most had metastatic disease (63%); 13% of
patients died within 30 days. In the derivation cohort (n = 6,660), a white blood cell (WBC) count in the highest quartile predicted early
mortality (odds ratio, 7.8; 95% confidence interval [CI], 4.6–13.1); and the presence
of metastatic disease, pulmonary embolism (PE), and immobility defined the risk of
those with normal WBC count. We defined death risk according four sequential questions:
(1) Does the patient have an elevated WBC count? (Yes, group D). (2) If no, does the
patient have metastasis? (No, group A). (3) If yes, is the patient immobile? (Yes,
group D). (4) If no, does the patient have a PE? (Yes, group C; no, group B). In the
validation cohort (n = 3,365), the 30-day risk of death was 2.9% in group A (95% CI, 1.9–4.3), compared
with 25% in group D (95% CI, 22.5–27.5), and there was a rate escalation between groups
(p for trend < 0.01). In conclusion, with four sequential questions, the risk of death
in CT can be easily stratified. An elevated WBC count at baseline predicted 30-day
mortality better than metastases, PE, or immobility.
Keywords
mortality - cancer - venous thromboembolism
