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

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

Affiliations

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

Ang Li et al. J Thromb Haemost. 2021 Oct.

Erratum in

  • Corrigendum.
    [No authors listed] [No authors listed] J Thromb Haemost. 2022 Mar;20(3):785-786. doi: 10.1111/jth.15627. J Thromb Haemost. 2022. PMID: 35220657 Free PMC article. No abstract available.

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.

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Figures

FIGURE 1
FIGURE 1
Patient selection for study inclusion and exclusion. This flow diagram indicates the inclusion and exclusion criteria for patient selection for the current study using the CCC19 consortium. * Some patients had unknown ICU admission status. CCC19, COVID‐19 and Cancer Consortium registry; ICU, intensive care unit
FIGURE 2
FIGURE 2
Forest plot for multivariable logistic regression analysis for association between potential clinical variables and venous thromboembolism (VTE) and pulmonary embolism (PE; n = 2804). This forest plot shows the adjusted odds ratios (OR) for either VTE or PE for each of the chosen clinical covariates. * Adapted from Khorana Score: very‐high risk = pancreas, stomach, esophageal; high risk: lung, ovarian, kidney, bladder, testicular, lymphoma
FIGURE 3
FIGURE 3
Relative importance of variables in the predictive model. This figure shows the relative strengths of each predictor within the final multivariable model assessed via the model chi‐square statistics. VTE, venous thromboembolism

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