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BackgroundChronic kidney disease (CKD) is more prevalent in Taiwan than in most countries. This population-based cohort study evaluated the dementia risk associated with CKD.MethodsUsing claims data of 1,000,000 insured residents covered in the universal health insurance of Taiwan, we selected 37049 adults with CKD newly diagnosed from 2000–2006 as the CKD cohort. We also randomly selected 74098 persons free from CKD and other kidney diseases, frequency matched with age, sex and the date of CKD diagnosed. Incidence and hazard ratios (HRs) of dementia were evaluated by the end of 2009.ResultsSubjects in the CKD cohort were more prevalent with comorbidities than those in the non-CKD cohort (p <0.0001). The dementia incidence was higher in the CKD cohort than in the non-CKD cohort (9.30 vs. 5.55 per 1,000 person-years), with an overall HR of 1.41 (95% confidence interval (CI), 1.32-1.50), controlling for sex, age, comorbidities and medicaitions. The risk was similar in men and women but increased sharply with age to an HR of 133 (95% CI, 68.9-256) for the elderly. However, the age-specific CKD cohort to non-CKD cohort incidence rate ratio decreased with age, with the highest ratio of 16.0 (95% CI, 2.00-128) in the youngest group. Among comorbidities and medications, alcoholism and taking benzodiazepines were also associated with dementia with elevated adjusted HRs of 3.05 (95% CI 2.17-4.28) and 1.23 (95% CI 1.14-1.32), respectively.ConclusionsPatients with CKD could have an elevated dementia risk. CKD patients with comorbidity deserve attention to prevent dementia.

BackgroundCancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient’s class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments.MethodsWe compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models.ResultsA public breast cancer dataset was used to compare several performance metrics using five prediction models. 1) For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2) The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3) Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results.Conclusions1) Different performance metrics for evaluation of a survival prediction model may give different conclusions in its discriminatory ability. 2) Evaluation using a high-risk versus low-risk group comparison depends on the selected risk-score threshold; a plot of p-values from all possible thresholds can show the sensitivity of the threshold selection. 3) A randomization test of the significance of Somers’ rank correlation can be used for further evaluation of performance of a prediction model. 4) The cross-validated power of survival prediction models decreases as the training and test sets become less balanced.

Background Epidemiological data concerning the association between diabetes and the subsequent development of gastric cancer are controversial. This population-based retrospective cohort study investigated the subsequent risk of gastric cancer for diabetic patients. Methods From claims data of the universal health insurance of Taiwan, we identified 19,625 persons aged C20 years newly diagnosed with diabetes during 2000-2005. A comparison group (n = 78,500), frequency matched by age, sex, and calendar year, was randomly selected from people without diabetes. Incidence and hazard ratios (HR) of gastric cancer were ascertained during the follow-up period until 2008. We also explored associations of antidiabetic medicines with the incidence of gastric cancer. Results During the follow-up period, 47 subjects in the diabetic group and 216 subjects in the comparison group suffered gastric cancer, with the incidence rates of 4.34 and 4.86 per 10,000 person-years, respectively. During the first 4 years after diabetes diagnosis, the incidence of gastric cancer was relatively low in diabetic patients [adjusted HR = 0.63; 95 % confidence interval (CI) = 0.42-0.97]. However, after that time, the diabetic group had a 76 % (95 % CI = 1.06-2.91) higher risk of developing gastric cancer than the comparison group. In diabetic patients, alpha-glucosidase inhibitors were associated with a significantly decreased risk of gastric cancer (adjusted HR = 0.38; 95 % CI = 0.15-0.96). Conclusions Our findings suggested that the association between diabetes and subsequent risk of gastric cancer may vary over time. Increased risk of gastric cancer was observed in patients with longer duration of diabetes.