Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes

• Published in: Korean circulation journal Vol. 50; no. 1; pp. 72 - 84
• Main Authors: Cho, In Jeong, Sung, Ji Min, Kim, Hyeon Chang, Lee, Sang Eun, Chae, Myeong Hun, Kavousi, Maryam, Rueda-Ochoa, Oscar L, Ikram, M Arfan, Franco, Oscar H, Min, James K, Chang, Hyuk Jae
• Format: Journal Article
• Language: English
• Published: Korea (South) The Korean Society of Cardiology 01.01.2020; 대한심장학회
• Subjects: Original; 내과학; Cardiovascular diseases; Artificial intelligence
• ISSN: 1738-5520; 1738-5555
• DOI: 10.4070/kcj.2019.0105

We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. Two CVD prediction models were developed from National Health Insurance Service-Health Screening Cohort (NHIS-HEALS): a Cox regression model and a DL model. Performance of each model was assessed in the internal and 2 external validation cohorts in Koreans (National Health Insurance Service-National Sample Cohort; NHIS-NSC) and in Europeans (Rotterdam Study). A total of 412,030 adults in the NHIS-HEALS; 178,875 adults in the NHIS-NSC; and the 4,296 adults in Rotterdam Study were included. Mean ages was 52 years (46% women) and there were 25,777 events (6.3%) in NHIS-HEALS during the follow-up. In internal validation, the DL approach demonstrated a C-statistic of 0.896 (95% confidence interval, 0.886-0.907) in men and 0.921 (0.908-0.934) in women and improved reclassification compared with Cox regression (net reclassification index [NRI], 24.8% in men, 29.0% in women). In external validation with NHIS-NSC, DL demonstrated a C-statistic of 0.868 (0.860-0.876) in men and 0.889 (0.876-0.898) in women, and improved reclassification compared with Cox regression (NRI, 24.9% in men, 26.2% in women). In external validation applied to the Rotterdam Study, DL demonstrated a C-statistic of 0.860 (0.824-0.897) in men and 0.867 (0.830-0.903) in women, and improved reclassification compared with Cox regression (NRI, 36.9% in men, 31.8% in women). A DL algorithm exhibited greater discriminative accuracy than Cox model approaches. ClinicalTrials.gov Identifier: NCT02931500.