The CoVID-TE risk assessment model for venous thromboembolism in hospitalized patients with cancer and COVID-19

J Thromb Haemost. 2021 Oct;19(10):2522-2532. doi: 10.1111/jth.15463. Epub 2021 Aug 13.

Abstract

Background: Hospitalized patients with COVID-19 have increased risks of venous (VTE) and arterial thromboembolism (ATE). Active cancer diagnosis and treatment are well-known risk factors; however, a risk assessment model (RAM) for VTE in patients with both cancer and COVID-19 is lacking.

Objectives: To assess the incidence of and risk factors for thrombosis in hospitalized patients with cancer and COVID-19.

Methods: Among patients with cancer in the COVID-19 and Cancer Consortium registry (CCC19) cohort study, we assessed the incidence of VTE and ATE within 90 days of COVID-19-associated hospitalization. A multivariable logistic regression model specifically for VTE was built using a priori determined clinical risk factors. A simplified RAM was derived and internally validated using bootstrap.

Results: From March 17, 2020 to November 30, 2020, 2804 hospitalized patients were analyzed. The incidence of VTE and ATE was 7.6% and 3.9%, respectively. The incidence of VTE, but not ATE, was higher in patients receiving recent anti-cancer therapy. A simplified RAM for VTE was derived and named CoVID-TE (Cancer subtype high to very-high risk by original Khorana score +1, VTE history +2, ICU admission +2, D-dimer elevation +1, recent systemic anti-cancer Therapy +1, and non-Hispanic Ethnicity +1). The RAM stratified patients into two cohorts (low-risk, 0-2 points, n = 1423 vs. high-risk, 3+ points, n = 1034) where VTE occurred in 4.1% low-risk and 11.3% high-risk patients (c statistic 0.67, 95% confidence interval 0.63-0.71). The RAM performed similarly well in subgroups of patients not on anticoagulant prior to admission and moderately ill patients not requiring direct ICU admission.

Conclusions: Hospitalized patients with cancer and COVID-19 have elevated thrombotic risks. The CoVID-TE RAM for VTE prediction may help real-time data-driven decisions in this vulnerable population.

Keywords: COVID-19; SARS-CoV-2; clinical decision rules; thrombosis; venous thromboembolism.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19*
  • Cohort Studies
  • Humans
  • Neoplasms* / complications
  • Neoplasms* / epidemiology
  • Risk Assessment
  • SARS-CoV-2
  • Venous Thromboembolism* / diagnosis
  • Venous Thromboembolism* / epidemiology