Validation of venous thromboembolism predictive model in hematologic malignancies

被引:0
|
作者
Agnerys López Sacerio
Mara Caridad Tejeda Ramón
Aliuska Morales Helguera
Yunierkis Pérez Castillo
Javier Cruz Rodríguez
Jorge Felix Guerra Rodríguez
Anna Falanga
机构
[1] Arnaldo Milián University Hospital,Hematology Department
[2] Central University “Martha Abreu” de Las Villas,Chemical Bioactive Center
[3] University of Las Américas,Bio
[4] Arnaldo Milián University Hospital,Chemoinformatics Group and School of Physical and Mathematical Sciences
[5] Hospital Papa Giovanni XXIII,Surgical Department
[6] University of Milan Bicocca,Department of Transfusion Medicine and Hematology
来源
Annals of Hematology | 2023年 / 102卷
关键词
Venous thromboembolism; Hematologic malignancy; Risk assessment model; Primary prevention;
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学科分类号
摘要
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.
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页码:3613 / 3620
页数:7
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