Format

Send to

Choose Destination
J Epidemiol. 2017 Mar;27(3S):S71-S76. doi: 10.1016/j.je.2016.10.007. Epub 2016 Dec 27.

Risk prediction models for mortality in patients with cardiovascular disease: The BioBank Japan project.

Author information

1
Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
2
Department of Public Policy, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
3
Laboratory of Genome Technology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
4
Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
5
Department of Public Health, Hokkaido University Graduate School of Medicine, Hokkaido, Japan.
6
Department of Health Sciences, University of Yamanashi, Yamanashi, Japan.
7
Laboratory of Molecular Medicine, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
8
RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
9
Hisayama Research Institute for Lifestyle Diseases, Fukuoka, Japan.
10
Tokushukai Hospitals, Japan.
11
Nippon Medical School, Japan.
12
Juntendo University, Japan.
13
Nihon University, Japan.
14
Iwate Medical University, Japan.
15
Tokyo Metropolitan Institute of Gerontology, Japan.
16
The Cancer Institute Hospital of JFCR, Japan.
17
Aso Iizuka Hospital, Japan.
18
Osaka Medical Center for Cancer and Cardiovascular Diseases, Japan.
19
Shiga University of Medical Science, Japan.
20
National Hospital Organization, Osaka National Hospital, Japan.
21
Fukujuji Hospital, Japan.

Abstract

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 χ2-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.

KEYWORDS:

All-cause death; Cardiovascular death; Ischemic stroke; Myocardial infarction; Risk prediction model

PMID:
28142037
PMCID:
PMC5350588
DOI:
10.1016/j.je.2016.10.007
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center