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Development and evaluation of a computable phenotype to identify pediatric patients with leukemia and lymphoma

Charles A Phillips1, Hanieh Razzaghi1, Taylor Aglio2

  • 1Division of Oncology and Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.

Pediatric Blood & Cancer
|June 18, 2019
PubMed

Insights

This study developed an accurate electronic health record (EHR) computable phenotype to identify pediatric leukemia and lymphoma patients receiving chemotherapy. This tool is ready for use in clinical research, improving cohort identification for pediatric hematologic malignancies.

Area of Science:

  • Biomedical Informatics
  • Pediatric Oncology
  • Health Data Science

Background:

  • Electronic health records (EHR) offer new avenues for pediatric oncology research.
  • Identifying pediatric hematologic malignancies using EHR data has been underexplored.

Purpose of the Study:

  • To develop and validate a computable phenotype algorithm using EHR data to identify pediatric patients with leukemia and lymphoma who received chemotherapy.
  • To assess the accuracy of this algorithm within a pediatric clinical data research network.

Main Methods:

  • A computable phenotype was developed using EHR data from the PEDSnet network.
  • The algorithm required specific diagnosis codes, chemotherapy exposures, and provider encounters.
  • Performance was evaluated against institutional tumor registries and through masked medical record review at three institutions.

Main Results:

  • The computable phenotype demonstrated high accuracy, with sensitivity and positive predictive value of 100% at the development institution.
  • Performance remained strong at test institutions, showing 100% sensitivity and 96-100% positive predictive value.
  • Specificity was consistently high (99%) across all institutions.

Conclusions:

  • An EHR-based computable phenotype accurately identifies pediatric patients with leukemia and lymphoma undergoing chemotherapy.
  • This validated tool is ready for implementation in pediatric clinical studies.
  • Enhances cohort identification for pediatric hematologic malignancies research.
Abstract

Keywords:
computable phenotypeepidemiologyleukemias (acute)lymphomapediatric oncology

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