Developing and optimizing a computable phenotype for incident venous thromboembolism in a longitudinal cohort of patients with cancer.

ABSTRACT:

Background

Research on venous thromboembolism (VTE) that relies only on the International Classification of Diseases (ICD) can misclassify outcomes. Our study aims to discover and validate an improved VTE computable phenotype for people with cancer.

Methods

We used a cancer registry electronic health record (EHR)-linked longitudinal database. We derived three algorithms that were ICD/medication based, natural language processing (NLP) based, or all combined. We then randomly sampled 400 patients from patients with VTE codes (n = 1111) and 400 from those without VTE codes (n = 7396). Weighted sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated on the entire sample using inverse probability weighting, followed by boots

SUBMITTER: Li A 

PROVIDER: S-EPMC9130880 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature