Peter C.Y. Tong

Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes

We performed a genome-wide association scan to search for sequence variants conferring risk of prostate cancer using 1,501 Icelandic men with prostate cancer and 11,290 controls. Follow-up studies involving three additional case-control groups replicated an association of two variants on chromosome 17 with the disease. These two variants, 33 Mb apart, fall within a region previously implicated by family-based linkage studies on prostate cancer. The risks conferred by these variants are moderate individually (allele odds ratio of about 1.20), but because they are common, their joint population attributable risk is substantial. One of the variants is in TCF2 (HNF1β), a gene known to be mutated in individuals with maturity-onset diabetes of the young type 5. Results from eight case-control groups, including one West African and one Chinese, demonstrate that this variant confers protection against type 2 diabetes.

Effectiveness of telephone counselling by a pharmacist in reducing mortality in patients receiving polypharmacy: randomised controlled trial.

Abstract Objective To investigate the effects of compliance and periodic telephone counselling by a pharmacist on mortality in patients receiving polypharmacy. Design Two year randomised controlled trial. Setting Hospital medical clinic. Participants 502 of 1011 patients receiving five or more drugs for chronic disease found to be non-compliant at the screening visit were invited for randomisation to either the telephone counselling group (n = 219) or control group (n = 223) at enrolment 12-16 weeks later. Main outcome measures Primary outcome was all cause mortality in randomised patients. Associations between compliance and mortality in the entire cohort of 1011 patients were also examined. Patients were defined as compliant with a drug if they took 80-120% of the prescribed daily dose. To calculate a compliance score for the whole treatment regimen, the number of drugs that the patient was fully compliant with was divided by the total number of prescribed drugs and expressed as a percentage. Only patients who complied with all recommended drugs were considered compliant (100% score). Results 60 of the 502 eligible patients defaulted and only 442 patients were randomised. After two years, 31 (52%) of the defaulters had died, 38 (17%) of the control group had died, and 25 (11%) of the intervention group had died. After adjustment for confounders, telephone counselling was associated with a 41% reduction in the risk of death (relative risk 0.59, 95% confidence interval 0.35 to 0.97; P = 0.039). The number needed to treat to prevent one death at two years was 16. Other predictors included old age, living alone, rate of admission to hospital, compliance score, number of drugs for chronic disease, and non-treatment with lipid lowering drugs at screening visit. In the cohort of 1011 patients, the adjusted relative risk for death was 1.61 (1.05 to 2.48; P = 0.029) and 2.87 (1.80 to 2.57; P < 0.001) in patients with compliance scores of 34-66% and 0-33%, respectively, compared with those who had a compliance score of 67% or more. Conclusion In patients receiving polypharmacy, poor compliance was associated with increased mortality. Periodic telephone counselling by a pharmacist improved compliance and reduced mortality. Trial registration International Standard Randomised Controlled Trial Number Register: SRCTN48076318.

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.

Associations of sleep duration with obesity and serum lipid profile in children and adolescents.

INTRODUCTION The association between sleep duration, obesity, and serum lipid profile in the youth population is under-explored. OBJECTIVE To evaluate the association between sleep duration, obesity and serum lipid profile in the youth population. METHODS We conducted a cross-sectional population-based study with students recruited from primary and secondary schools in Hong Kong. Anthropometric measurements, fasting lipid profiles and validated questionnaires on sleep duration were performed. A subgroup (n=138) was randomly selected for both questionnaires and actigraphy to assess the agreement between subjective and objective measurements of sleep duration. RESULTS We studied 2053 healthy children and adolescents aged 6-20 years. Their mean ages were 13.0±3.3 (boys) and 13.6±3.3 (girls) years. The average sleep duration during schooldays, weekends, and long holidays was 8.0±1.1, 9.6±1.2, and 9.8±1.2h in boys and 7.7±1.1, 9.9±1.2, and 10.1±1.2h in girls, respectively. Using logistic regression, age, and pubertal stage were associated with obesity in secondary school students, whereas male gender and short sleep duration were associated with obesity in primary school children. In secondary school children, those with long sleep duration, as compared to those with short sleep duration, were significantly associated with reduced risk to have high TC and LDL-C levels after adjustment for age, gender, BMI, and pubertal stage. There was no significant association between sleep duration and lipid levels in primary school children. CONCLUSION Reduced sleep duration was associated with obesity and atherogenic dyslipidemia in young school children in Hong Kong.

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.

Effects of Structured Versus Usual Care on Renal Endpoint in Type 2 Diabetes: The SURE Study A randomized multicenter translational study

OBJECTIVE Multifaceted care has been shown to reduce mortality and complications in type 2 diabetes. We hypothesized that structured care would reduce renal complications in type 2 diabetes. RESEARCH DESIGN AND METHODS A total of 205 Chinese type 2 diabetic patients from nine public hospitals who had plasma creatinine levels of 150–350 μmol/l were randomly assigned to receive structured care (n = 104) or usual care (n = 101) for 2 years. The structured care group was managed according to a prespecified protocol with the following treatment goals: blood pressure <130/80 mmHg, A1C <7%, LDL cholesterol <2.6 mmol/l, triglyceride <2 mmol/l, and persistent treatment with renin-angiotensin blockers. The primary end point was death and/or renal end point (creatinine >500 μmol/l or dialysis). RESULTS Of these 205 patients (mean ± SD age 65 ± 7.2 years; disease duration 14 ± 7.9 years), the structured care group achieved better control than the usual care group (diastolic blood pressure 68 ± 12 vs. 71 ± 12 mmHg, respectively, P = 0.02; A1C 7.3 ± 1.3 vs. 8.0 ± 1.6%, P < 0.01). After adjustment for age, sex, and study sites, the structured care (23.1%, n = 24) and usual care (23.8%, n = 24; NS) groups had similar end points, but more patients in the structured care group attained ≥3 treatment goals (61%, n = 63, vs. 28%, n = 28; P < 0.001). Patients who attained ≥3 treatment targets (n = 91) had reduced risk of the primary end point (14 vs. 34; relative risk 0.43 [95% CI 0.21–0.86] compared with that of those who attained ≤2 targets (n = 114). CONCLUSIONS Attainment of multiple treatment targets reduced the renal end point and death in type 2 diabetes. In addition to protocol, audits and feedback are needed to improve outcomes.

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.

Testosterone, Sex Hormone-Binding Globulin and the Metabolic Syndrome in Men : An Individual Participant Data Meta-Analysis of Observational Studies

Background Low total testosterone (TT) and sex hormone-binding globulin (SHBG) concentrations have been associated with the metabolic syndrome (MetS) in men, but the reported strength of association varies considerably. Objectives We aimed to investigate whether associations differ across specific subgroups (according to age and body mass index (BMI)) and individual MetS components. Data sources Two previously published meta-analyses including an updated systematic search in PubMed and EMBASE. Study Eligibility Criteria Cross-sectional or prospective observational studies with data on TT and/or SHBG concentrations in combination with MetS in men. Methods We conducted an individual participant data meta-analysis of 20 observational studies. Mixed effects models were used to assess cross-sectional and prospective associations of TT, SHBG and free testosterone (FT) with MetS and its individual components. Multivariable adjusted odds ratios (ORs) and hazard ratios (HRs) were calculated and effect modification by age and BMI was studied. Results Men with low concentrations of TT, SHBG or FT were more likely to have prevalent MetS (ORs per quartile decrease were 1.69 (95% CI 1.60-1.77), 1.73 (95% CI 1.62-1.85) and 1.46 (95% CI 1.36-1.57) for TT, SHBG and FT, respectively) and incident MetS (HRs per quartile decrease were 1.25 (95% CI 1.16-1.36), 1.44 (95% 1.30-1.60) and 1.14 (95% 1.01-1.28) for TT, SHBG and FT, respectively). Overall, the magnitude of associations was largest in non-overweight men and varied across individual components: stronger associations were observed with hypertriglyceridemia, abdominal obesity and hyperglycaemia and associations were weakest for hypertension. Conclusions Associations of testosterone and SHBG with MetS vary according to BMI and individual MetS components. These findings provide further insights into the pathophysiological mechanisms linking low testosterone and SHBG concentrations to cardiometabolic risk.

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.