Key result
Models using ten traditional risk factors show modest discrimination for all-cause and cardiovascular death.
Why the study?
Cardiovascular disease is a leading cause of death in Japan, and new risk prediction models for long-term mortality in chronic phase CVD patients were needed.
Can a risk prediction model using traditional cardiovascular risk factors accurately predict long-term all-cause and cardiovascular mortality in patients with chronic ischemic CVD?
Cohort (n=15,058)
Can a risk prediction model using traditional cardiovascular risk factors accurately predict long-term all-cause and cardiovascular mortality in patients with chronic ischemic CVD?
Effect estimate: c-statistic 0.703 for all-cause death; 0.685 for cardiovascular death
A newly developed risk prediction model using ten traditional risk factors provides modest discrimination for predicting 5-year all-cause and cardiovascular mortality in Japanese patients with chronic ischemic CVD.
Japanese-derived models modestly predict long-term mortality in chronic CVD; leaves open external validation and clinical utility testing.
Background Cardiovascular disease (CVD) is a leading cause of death in Japan. The present study aimed to develop new risk prediction models for long-term risks of all-cause and cardiovascular death in patients with chronic phase CVD. Methods Among the subjects registered in the BioBank Japan database, 15,058 patients aged ≥40 years with chronic ischemic CVD (ischemic stroke or myocardial infarction) were divided randomly into a derivation cohort (n = 10,039) and validation cohort (n = 5019). These subjects were followed up for 8.55 years in median. Risk prediction models for all-cause and cardiovascular death were developed using the derivation cohort by Cox proportional hazards regression. Their prediction performances for 5-year risk of mortality were evaluated in the validation cohort. Results During the follow-up, all-cause and cardiovascular death events were observed in 2962 and 962 patients from the derivation cohort and 1536 and 481 from the validation cohort, respectively. Risk prediction models for all-cause and cardiovascular death were developed from the derivation cohort using ten traditional cardiovascular risk factors, namely, age, sex, CVD subtype, hypertension, diabetes, total cholesterol, body mass index, current smoking, current drinking, and physical activity. These models demonstrated modest discrimination (c-statistics, 0.703 for all-cause death; 0.685 for cardiovascular death) and good calibration (Hosmer-Lemeshow χ 2 -test, P = 0.17 and 0.15, respectively) in the validation cohort. Conclusions We developed and validated risk prediction models of all-cause and cardiovascular death for patients with chronic ischemic CVD. These models would be useful for estimating the long-term risk of mortality in chronic phase CVD.
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Hata et al. (2017) conducted a cohort in Chronic ischemic cardiovascular disease (n=15,058). Risk prediction models was evaluated on 5-year risk of all-cause and cardiovascular death (c-statistic 0.703 for all-cause death; 0.685 for cardiovascular death). Risk prediction models using ten traditional risk factors demonstrated modest discrimination for all-cause (c-statistic 0.703) and cardiovascular death (c-statistic 0.685).
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