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

被引:1
|
作者
Noyd, David H. [1 ,7 ]
Chen, Sixia [2 ]
Bailey, Anna M. [2 ]
Janitz, Amanda E. [2 ]
Baker, Ashley A. [1 ]
Beasley, William H. [1 ]
Etzold, Nancy C. [3 ]
Kendrick, David C. [4 ]
Kibbe, Warren A. [5 ]
Oeffinger, Kevin C. [6 ]
机构
[1] Univ Oklahoma, Coll Med, Dept Pediat, Hlth Sci Ctr, Oklahoma City, OK USA
[2] Univ Oklahoma, Hudson Coll Publ Hlth, Dept Biostat & Epidemiol, Hlth Sci Ctr, Oklahoma City, OK USA
[3] Univ Oklahoma, Biostat & Epidemiol, Hlth Sci Ctr, Oklahoma City, OK USA
[4] Univ Oklahoma, Dept Med Informat, Hlth Sci Ctr, Tulsa, OK USA
[5] Duke Univ, Dept Biostat & Bioinformat, Sch Med, Durham, NC USA
[6] Duke Univ, Dept Med, Sch Med, Durham, NC USA
[7] Univ Oklahoma, Coll Med, Hlth Sci Ctr, Dept Pediat, Oklahoma City, OK 73104 USA
关键词
cardio-oncology; clinical research informatics; late effects from childhood cancer; survivorship; FOLLOW-UP; CARE; CARDIOMYOPATHY; PASSPORT; EXPOSURE; CHILDREN; OUTCOMES;
D O I
10.1002/pbc.30474
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundClinical 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. MethodsThe 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. ResultsThe 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). ConclusionsClinical 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.
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页数:10
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