Validation of venous thromboembolism predictive model in hematologic malignancies

Ann Hematol. 2023 Dec;102(12):3613-3620. doi: 10.1007/s00277-023-05463-4. Epub 2023 Oct 2.

Abstract

Although several scores stratify venous thromboembolism (VTE) risk in solid tumors, hematologic malignancies (HM) are underrepresented. To develop an internal and external validation of a logistic regression model to predict VTE risk in hospitalized HM patients. Validation of the existing VTE predictive model was performed through a prospective case-control study in 496 hospitalized HM patients between December 2010 and 2020 at the Arnaldo Milián University Hospital, Cuba. The predictive model designed with data from 285 patients includes 5 predictive factors: hypercholesterolemia, tumoral activity, use of thrombogenic drugs, diabetes mellitus, and immobilization. The model was internally validated using bootstrap analysis. External validation was realized in a prospective cohort of 211 HM patients. The predictive model had a 76.4% negative predictive value (NPV) and an 81.7% positive predictive value (PPV) in the bootstrapping validation. The area under curve (AUC) in the bootstrapping set was 0.838. Accuracy was 80.1% and 82.9% in the internal and external validation, respectively. In the external validation, the model produced 89.7% of NPV, 67.7% of PPV, 74.6% of sensitivity, and 86.2% of specificity. The AUC in the external validation was 0.900. VTE predictive model is a reproducible and simple tool with good accuracy and discrimination.

Keywords: Hematologic malignancy; Primary prevention; Risk assessment model; Venous thromboembolism.

MeSH terms

  • Case-Control Studies
  • Hematologic Neoplasms* / complications
  • Humans
  • Neoplasms*
  • Retrospective Studies
  • Risk Assessment
  • Risk Factors
  • Venous Thromboembolism* / diagnosis
  • Venous Thromboembolism* / etiology