title: Prediction of the 20-year incidence of diabetes in older Chinese: Application of the competing risk method in a longitudinal study.
abstract: The competing risk method has become more acceptable for time-to-event data analysis because of its advantage over the standard Cox model in accounting for competing events in the risk set. This study aimed to construct a prediction model for diabetes using a subdistribution hazards model.We prospectively followed 1857 community residents who were aged ≥ 55 years, free of diabetes at baseline examination from August 1992 to December 2012. Diabetes was defined as a self-reported history of diabetes diagnosis, taking antidiabetic medicine, or having fasting plasma glucose (FPG) ≥ 7.0 mmol/L. A questionnaire was used to measure diabetes risk factors, including dietary habits, lifestyle, psychological factors, cognitive function, and physical condition. Gray test and a subdistribution hazards model were used to construct a prediction algorithm for 20-year risk of diabetes. Receiver operating characteristic (ROC) curves, bootstrap cross-validated Wolber concordance index (C-index) statistics, and calibration plots were used to assess model performance.During the 20-year follow-up period, 144 cases were documented for diabetes incidence with a median follow-up of 10.9 years (interquartile range: 8.0-15.3 years). The cumulative incidence function of 20-year diabetes incidence was 11.60% after adjusting for the competing risk of nondiabetes death. Gray test showed that body mass index, FPG, self-rated heath status, and physical activity were associated with the cumulative incidence function of diabetes after adjusting for age. Finally, 5 standard risk factors (poor self-rated health status [subdistribution hazard ratio (SHR) = 1.73, P = 0.005], less physical activity [SHR = 1.39, P = 0.047], 55-65 years old [SHR = 4.37, P < 0.001], overweight [SHR = 2.15, P < 0.001] or obesity [SHR = 1.96, P = 0.003], and impaired fasting glucose [IFG] [SHR = 1.99, P < 0.001]) were significantly associated with incident diabetes. Model performance was moderate to excellent, as indicated by its bootstrap cross-validated discrimination C-index (0.74, 95% CI: 0.70-0.79) and calibration plot.Poor self-rated health, physical inactivity, being 55 to 65 years of age, overweight/obesity, and IFG were significant predictors of incident diabetes. Early prevention with a goal of achieving optimal levels of all risk factors should become a key element of diabetes prevention.
authors.affiliation: School of Public Health, Capital Medical University Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, P.R. China Department of Biostatistics Department of Statistics & Operations Research, University of North Carolina, Chapel Hill, USA Beijing Neurosurgical Institute, Capital Medical University, Tiantanxili, Beijing, P.R. China The Graduate Entry Medical School, University of Limerick, Limerick, Ireland Beijing Geriatric Clinical and Research Center, Xuanwu Hospital, Capital Medical University, Beijing, P.R. China.
authors.forename: Xiangtong
authors.initials: X
authors.lastname: Liu
authors.forename: Jason Peter
authors.initials: JP
authors.lastname: Fine
authors.forename: Zhenghong
authors.initials: Z
authors.lastname: Chen
authors.forename: Long
authors.initials: L
authors.lastname: Liu
authors.forename: Xia
authors.initials: X
authors.lastname: Li
authors.forename: Anxin
authors.initials: A
authors.lastname: Wang
authors.forename: Jin
authors.initials: J
authors.lastname: Guo
authors.forename: Lixin
authors.initials: L
authors.lastname: Tao
authors.forename: Gehendra
authors.initials: G
authors.lastname: Mahara
authors.forename: Zhe
authors.initials: Z
authors.lastname: Tang
authors.forename: Xiuhua
authors.initials: X
authors.lastname: Guo
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001786:Blood Glucose / Q000032:analysis*; D002681:China / Q000453:epidemiology; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000453:epidemiology*; D005260:Female; D005544:Forecasting; D006801:Humans; D015994:Incidence; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors
chemical_list: D001786:Blood Glucose