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Informatics tools to implement late cardiovascular risk prediction modeling for population management of high-risk childhood cancer survivors.

Authors :
Noyd DH
Chen S
Bailey AM
Janitz AE
Baker AA
Beasley WH
Etzold NC
Kendrick DC
Kibbe WA
Oeffinger KC
Source :
Pediatric blood & cancer [Pediatr Blood Cancer] 2023 Jun 07, pp. e30474. Date of Electronic Publication: 2023 Jun 07.
Publication Year :
2023
Publisher :
Ahead of Print

Abstract

Background: Clinical informatics tools to integrate data from multiple sources have the potential to catalyze population health management of childhood cancer survivors at high risk for late heart failure through the implementation of previously validated risk calculators.<br />Methods: The Oklahoma cohort (n = 365) harnessed data elements from Passport for Care (PFC), and the Duke cohort (n = 274) employed informatics methods to automatically extract chemotherapy exposures from electronic health record (EHR) data for survivors 18 years old and younger at diagnosis. The Childhood Cancer Survivor Study (CCSS) late cardiovascular risk calculator was implemented, and risk groups for heart failure were compared to the Children's Oncology Group (COG) and the International Guidelines Harmonization Group (IGHG) recommendations. Analysis within the Oklahoma cohort assessed disparities in guideline-adherent care.<br />Results: The Oklahoma and Duke cohorts both observed good overall concordance between the CCSS and COG risk groups for late heart failure, with weighted kappa statistics of .70 and .75, respectively. Low-risk groups showed excellent concordance (kappa > .9). Moderate and high-risk groups showed moderate concordance (kappa .44-.60). In the Oklahoma cohort, adolescents at diagnosis were significantly less likely to receive guideline-adherent echocardiogram surveillance compared with survivors younger than 13 years old at diagnosis (odds ratio [OD] 0.22; 95% confidence interval [CI]: 0.10-0.49).<br />Conclusions: Clinical informatics tools represent a feasible approach to leverage discrete treatment-related data elements from PFC or the EHR to successfully implement previously validated late cardiovascular risk prediction models on a population health level. Concordance of CCSS, COG, and IGHG risk groups using real-world data informs current guidelines and identifies inequities in guideline-adherent care.<br /> (© 2023 Wiley Periodicals LLC.)

Details

Language :
English
ISSN :
1545-5017
Database :
MEDLINE
Journal :
Pediatric blood & cancer
Publication Type :
Academic Journal
Accession number :
37283294
Full Text :
https://doi.org/10.1002/pbc.30474