Alice P.S. Kong

Associations of Hyperglycemia and Insulin Usage With the Risk of Cancer in Type 2 Diabetes: The Hong Kong Diabetes Registry

OBJECTIVE Insulin has mitogenic effects, although hyperglycemia may be a risk factor for cancer in type 2 diabetes. It remains uncertain whether use of insulin increases cancer risk because of its effect on cell growth and proliferation or decreases cancer risk because of its glucose-lowering effect. RESEARCH DESIGN AND METHODS A 1:2-matched new insulin user cohort on age (±3 years), smoking status, and likelihood of initiating insulin therapy (±0.05) was selected from a cohort of 4,623 Chinese patients with type 2 diabetes, free of cancer, and naive to insulin at enrollment. Stratified Cox regression analysis on the matched pairs was used to obtain hazard ratios (HRs) of insulin therapy and A1C for cancer risk. A structured adjustment scheme was used to adjust for covariates. RESULTS Of 973 new insulin users, 971 had matched nonusers (n = 1935). The cancer incidence in insulin nonusers was much higher than that in insulin users (49.2 vs. 10.2, per 1,000 person-years, P < 0.0001). After further adjustment for all other covariates with a P value less than 0.3 and nonlinear associations with cancer, A1C was associated with an increased cancer risk (HR per percentage 1.26, 95% CI 1.03–1.55), whereas use of insulin was associated with a decreased cancer risk (HR of insulin users vs. nonusers: 0.17, 0.09–0.32). Consistent results were found in analyses including all 973 insulin users and 3,650 nonusers. CONCLUSIONS In Chinese patients with type 2 diabetes, hyperglycemia predicts cancer, whereas insulin usage was associated with a reduced cancer risk.

Metabolic Syndrome Predicts New Onset of Chronic Kidney Disease in 5,829 Patients With Type 2 Diabetes: A 5-year prospective analysis of the Hong Kong Diabetes Registry

OBJECTIVE—Type 2 diabetes is the leading cause of end-stage renal disease worldwide. Aside from hyperglycemia and hypertension, other metabolic factors may determine renal outcome. We examined risk associations of metabolic syndrome with new onset of chronic kidney disease (CKD) in 5,829 Chinese patients with type 2 diabetes enrolled between 1995 and 2005. RESEARCH DESIGN AND METHODS—Metabolic syndrome was defined by National Cholesterol Education Program Adult Treatment Panel III criteria with the Asian definition of obesity. Estimated glomerular filtration rate (eGFR) was calculated using the abbreviated Modification of Diet in Renal Disease formula modified for the Chinese population. New onset of CKD was defined as eGFR <60 ml/min per 1.73 m2 at the time of censor. Subjects with CKD at baseline were excluded from the analysis. RESULTS—After a median follow-up duration of 4.6 years (interquartile range: 1.9–7.3 years), 741 patients developed CKD. The multivariable-adjusted hazard ratio (HR) of CKD was 1.31 (95% CI 1.12–1.54, P = 0.001) for subjects with metabolic syndrome compared with those without metabolic syndrome. Relative to subjects with no other components of metabolic syndrome except for diabetes, those with two, three, four, and five metabolic syndrome components had HRs of an increased risk of CKD of 1.15 (0.83–1.60, P = 0.407) 1.32 (0.94–1.86, P = 0.112), 1.64 (1.17–2.32, P = 0.004), and 2.34 (1.54–3.54, P < 0.001), respectively. The metabolic syndrome traits of central obesity, hypertriglyceridemia, hypertension, and low BMI were independent predictors for CKD. CONCLUSIONS—The presence of metabolic syndrome independently predicts the development of CKD in subjects with type 2 diabetes.

Development and validation of a total coronary heart disease risk score in type 2 diabetes mellitus.

There are no validated risk scores for predicting coronary heart disease (CHD) in Chinese patients with type 2 diabetes mellitus. This study aimed to validate the UKPDS risk engine and, if indicated, develop CHD risk scores. A total of 7,067 patients without CHD at baseline were analyzed. Data were randomly assigned to a training data set and a test data set. Cox models were used to develop risk scores to predict total CHD in the training data set. Calibration was assessed using the Hosmer-Lemeshow test, and discrimination was examined using the area under the receiver-operating characteristic curve in the test data set. During a median follow-up of 5.40 years, 4.97% of patients (n = 351) developed incident CHD. The UKPDS CHD risk engine overestimated the risk of CHD with suboptimal discrimination, and a new total CHD risk score was developed. The developed total CHD risk score was 0.0267 x age (years) - 0.3536 x sex (1 if female) + 0.4373 x current smoking status (1 if yes) + 0.0403 x duration of diabetes (years) - 0.4808 x Log(10) (estimated glomerular filtration rate [ml/min/1.73 m(2)]) + 0.1232 x Log(10) (1 + spot urinary albumin-creatinine ratio [mg/mmol]) + 0.2644 x non-high-density lipoprotein cholesterol (mmol/L). The 5-year probability of CHD = 1 - 0.9616(EXP(0.9440 x [RISK SCORE - 0.7082])). Predicted CHD probability was not significantly different from observed total CHD probability, and the adjusted area under the receiver-operating characteristic curve was 0.74 during 5 years of follow-up. In conclusion, the UKPDS CHD risk engine overestimated the risk of Chinese patients with type 2 diabetes mellitus and the newly developed total CHD risk score performed well in the test data set. External validations are required in other Chinese populations.

Development and validation of stroke risk equation for Hong Kong Chinese patients with type 2 diabetes: the Hong Kong Diabetes Registry.

OBJECTIVE—We sought to develop stroke risk equations for Chinese patients with type 2 diabetes in Hong Kong. RESEARCH DESIGN AND METHODS—A total of 7,209 Hong Kong Chinese type 2 diabetic patients without a history of stroke at baseline were analyzed. The data were randomly and evenly divided into the training subsample and the test subsample. In the training subsample, stepwise Cox models were used to develop the risk equation. Validation of the U.K. Prospective Diabetes Study (UKPDS) stroke risk engine and the current stroke equation was performed in the test dataset. The life-table method was used to check calibration, and the area under the receiver operating characteristic curve (aROC) was used to check discrimination. RESULTS—A total of 372 patients developed incident stroke during a median of 5.37 years (interquartile range 2.88–7.78) of follow-up. Age, A1C, spot urine albumin-to-creatinine ratio (ACR), and history of coronary heart disease (CHD) were independent predictors. The performance of the UKPDS stroke engine was suboptimal in our cohort. The newly developed risk equation defined by these four predictors had adequate performance in the test subsample. The predicted stroke-free probability by the current equation was within the 95% CI of the observed probability. The aROC was 0.77 for predicting stroke within 5 years. The risk score was computed as follows: 0.0634 × age (years) + 0.0897 × A1C + 0.5314 × log10 (ACR) (mg/mmol) + 0.5636 × history of CHD (1 if yes). The 5-year stroke probability can be calculated by: 1 − 0.9707EXP (Risk Score − 4.5674). CONCLUSIONS—Although the risk equation performed reasonably well in Chinese type 2 diabetic patients, external validation is required in other populations.

Development and Validation of an All-Cause Mortality Risk Score in Type 2 Diabetes: The Hong Kong Diabetes Registry

BACKGROUND Diabetes reduces life expectancy by 10 to 12 years, but whether death can be predicted in type 2 diabetes mellitus remains uncertain. METHODS A prospective cohort of 7583 type 2 diabetic patients enrolled since 1995 were censored on July 30, 2005, or after 6 years of follow-up, whichever came first. A restricted cubic spline model was used to check data linearity and to develop linear-transforming formulas. Data were randomly assigned to a training data set and to a test data set. A Cox model was used to develop risk scores in the test data set. Calibration and discrimination were assessed in the test data set. RESULTS A total of 619 patients died during a median follow-up period of 5.51 years, resulting in a mortality rate of 18.69 per 1000 person-years. Age, sex, peripheral arterial disease, cancer history, insulin use, blood hemoglobin levels, linear-transformed body mass index, random spot urinary albumin-creatinine ratio, and estimated glomerular filtration rate at enrollment were predictors of all-cause death. A risk score for all-cause mortality was developed using these predictors. The predicted and observed death rates in the test data set were similar (P > .70). The area under the receiver operating characteristic curve was 0.85 for 5 years of follow-up. Using the risk score in ranking cause-specific deaths, the area under the receiver operating characteristic curve was 0.95 for genitourinary death, 0.85 for circulatory death, 0.85 for respiratory death, and 0.71 for neoplasm death. CONCLUSIONS Death in type 2 diabetes mellitus can be predicted using a risk score consisting of commonly measured clinical and biochemical variables. Further validation is needed before clinical use.

Independent associations between low-density lipoprotein cholesterol and cancer among patients with type 2 diabetes mellitus

Background: The risk association between low-density lipoprotein (LDL) cholesterol and cancer remains controversial and largely unexplored for people not receiving statin therapy. Methods: We examined the risk association between LDL cholesterol and cancer among patients with type 2 diabetes mellitus who were free of cancer at enrolment and whose statin use was known. We considered a variety of nonlinear relationships in our analysis. Results: During a median follow-up period of 4.90 years, cancer developed in 270 (4.4%) of 6107 patients. Among the 3800 patients who did not receive statin therapy, the risk association between LDL cholesterol and cancer was represented by a V-shaped curve. Compared with patients whose LDL cholesterol was at least 2.80 mmol/L but less than 3.80 mmol/L, the risk of cancer, death from any cause or the composite outcome of cancer or death was greater among those with an LDL cholesterol level of less than 2.80 mmol/L (hazard ratio for cancer 1.74, 95% confidence interval [CI] 1.20–2.52) and those with an LDL cholesterol level of 3.80 mmol/L or greater (hazard ratio for cancer 1.87, 95% CI 1.29–2.71). Using 3.8 mmol/L as a reference point, we found that the hazard ratio for cancer for every millimole per litre absolute change in LDL cholesterol was 1.54 (95% CI 1.19–1.99) among patients not using statins; the hazard ratio was reduced to 1.24 (1.01–1.53) for the entire sample (statin users and those not using statins). These associations persisted after adjustment for covariates and exclusion of patients with less than 2.5 years of follow-up. Interpretation: Among patients with type 2 diabetes, the association between LDL cholesterol and cancer was V-shaped, whereby both low and high levels of LDL cholesterol were associated with elevated risk of cancer.

BMI and Waist Circumference in Predicting Cardiovascular Risk Factor Clustering in Chinese Adolescents

Objective: To derive the optimal BMI and waist circumference (WC) cut‐off values to predict clustering of cardiovascular risk factors in Hong Kong Chinese adolescents.

Low HDL Cholesterol, Metformin Use and Cancer Risk in Type 2 Diabetes – the Hong Kong Diabetes Registry

OBJECTIVE The AMP-activated protein kinase (AMPK) pathway is a master regulator in energy metabolism and may be related to cancer. In type 2 diabetes, low HDL cholesterol predicts cancer, whereas metformin usage is associated with reduced cancer risk. Both metformin and apolipoprotein A1 activate the AMPK signaling pathway. We hypothesize that the anticancer effects of metformin may be particularly evident in type 2 diabetic patients with low HDL cholesterol. RESEARCH DESIGN AND METHODS In a consecutive cohort of 2,658 Chinese type 2 diabetic patients enrolled in the study between 1996 and 2005, who were free of cancer and not using metformin at enrollment or during 2.5 years before enrollment and who were followed until 2005, we measured biological interactions for cancer risk using relative excess risk as a result of interaction (RERI) and attributable proportion (AP) as a result of interaction. A statistically significant RERI >0 or AP >0 indicates biological interaction. RESULTS During 13,808 person-years of follow-up (median 5.51 years), 129 patients developed cancer. HDL cholesterol <1.0 mmol/L was associated with increased cancer risk among those who did not use metformin, but the association was not significant among those who did. Use of metformin was associated with reduced cancer risk in patients with HDL cholesterol <1.0 mmol/L and, to a lesser extent, in patients with HDL cholesterol ≥1.0 mmol/L. HDL cholesterol <1.0 mmol/L plus nonuse of metformin was associated with an adjusted hazard ratio of 5.75 (95% CI 3.03–10.90) compared with HDL cholesterol ≥1.0 mmol/L plus use of metformin, with a significant interaction (AP 0.44 [95% CI 0.11–0.78]). CONCLUSIONS The anticancer effect of metformin was most evident in type 2 diabetic patients with low HDL cholesterol.

Use of sulphonylurea and cancer in type 2 diabetes—The Hong Kong Diabetes Registry

BACKGROUND Hyperglycaemia is a risk factor for cancer and some sulphonylureas have anti-oxidant properties. This study examined associations between use of sulphonylureas and cancer. METHODS A consecutive cohort of 6103 Hong Kong Chinese patients with T2DM, free of cancer, was analysed using Cox models. Sulphonylurea usage was defined as use of the drugs at or within 2.5 years before enrolment and/or during follow-up periods. We adjusted for identified risk factors of cancer, use of other drugs, non-linear associations of lipids with cancer and probabilities of use of these drugs at different times and doses where appropriate. RESULTS During a median of 4.91 years of follow-up, 271 developed cancer. Glibenclamide, gliclazide and glipizide were ever used in 32.5% (n = 1983), 47.8% (n = 2920) and 13.5% (n = 823). After adjustment for covariates, use of gliclazide and glibenclamide was associated with reduced cancer risk in a dose-dependent manner. In addition, there were interactions between metformin and glibenclamide/glipizide use towards lower adjusted cancer risks. CONCLUSIONS In T2DM, use of glibenclamide and gliclazide may be associated with reduced cancer risk.

Overweight, family history of diabetes and attending schools of lower academic grading are independent predictors for metabolic syndrome in Hong Kong Chinese adolescents

Background: Overweight and metabolic syndrome (MES) are emerging in both adult and paediatric populations. Aims: To study the prevalence of and associated risk factors for the MES, using the National Cholesterol Education Program definition, among Hong Kong Chinese adolescents studying in secondary schools. Methods: This was a cross-sectional, population-based study. A sample of 2115 Chinese adolescents was randomly selected from 14 secondary schools throughout Hong Kong. Data on anthropometric parameters, fasting blood and urine samples were collected in the school setting. Information regarding the adolescent’s family history of diabetes, perinatal history, socioeconomic status and school grading was evaluated. Results: The prevalence of MES was 2.4% (95% confidence interval (CI) 1.8 to 3.1), with no significant difference between boys (2.9%) and girls (2%). The prevalence of various components of MES was 32.2% (30.2 to 34.2) for hypertension, 10.9% (9.6 to 12.2) for increased triglyceride, 9.0% (7.8 to 10.2) for central adiposity, 2.4% (1.7 to 3) for low high-density lipoprotein cholesterol and 0.3% (0.1 to 0.6) for impaired fasting glucose. On multivariate analysis, overweight (odds ratio 32.2; 95% CI 13.2 to 78.4), positive family history of diabetes (4.3; 1.3 to 14.1) and studying at schools of lower academic grading (5.5; 2.2 to 13.7) were found to be independent risk factors for MES. Conclusion: A comparable prevalence of MES (2%) is observed in our study group Chinese adolescent girls and in US girls (2.1%), but a lower prevalence in Chinese boys (2.9%) than in US boys (6.1%). In our study, 41.8% harbour at least one component of the syndrome. Both families and schools should be alerted to this growing epidemic.