Risk prediction of bladder cancer among person with diabetes: A derivation and validation study.

AIMS: This study aimed to devise and validate a clinical scoring system for risk prediction of bladder cancer to guide urgent cystoscopy evaluation among people with diabetes. METHODS: People with diabetes who received cystoscopy from a large database in the Chinese population (2009-2018). We recruited a derivation cohort based on random sampling from 70% of all individuals. We used the adjusted odds ratios (aORs) for independent risk factors to devise a risk score, ranging from 0 to 5: 0-2 'average risk' (AR) and 3-5 'high risk' (HR). RESULTS: A total of 5905 people with diabetes, among whom 123 people with BCa were included. The prevalence rate in the derivation (n = 4174) and validation cohorts (n = 1731) was 2.2% and 1.8% respectively. Using the scoring system constructed, 79.6% and 20.4% in the derivation cohort were classified as AR and HR respectively. The prevalence rate in the AR and HR groups was 1.57% and 4.58% respectively. The risk score consisted of age (18-70: 0; >70: 2), male sex (1), ever/ex-smoker (1) and duration of diabetes (≥10 years: 1). Individuals in the HR group had 3.26-fold (95% CI = 1.65-6.44, p = 0.025) increased prevalence of bladder than the AR group. The concordance (c-) statistics was 0.72, implying a good discriminatory capability of the risk score to stratify high-risk individuals who should consider earlier cystoscopy. CONCLUSIONS: The risk prediction algorithm may inform urgency of cystoscopy appointments, thus allowing a more efficient use of resources and contributing to early detection of BCa among people planned to be referred.

Antihypertensive treatments and risks of lung Cancer: a large population-based cohort study in Hong Kong.

BACKGROUND: There is a growing concern that the use of anti-hypertensives may be associated with an increased risk of cancer, but it remains uncertain for the association between anti-hypertensives and lung cancer risk, as well as their interaction with aspirin in chemoprotective effects. METHODS: The goal of this study is to assess the association between anti-hypertensives use and the risk of lung cancer, as well as the chemopreventive impacts from the combination usage of aspirin and anti-hypertensives. A retrospective cohort study was conducted based on all the public hospital electronic medical records in Hong Kong. Patients with prescription records of anti-hypertensives (ACEi/ARB, CCB, ß-blocker,α-blocker) and/or aspirin were included as the exposure groups. Using the Cox proportional hazards model with inverse probability weighting, we estimated hazard ratios (HRs) with 95% confidence intervals (CIs) for lung cancer risk from anti-hypertensives usage or combination usage of aspirin with anti-hypertensives. The likelihood ratio test and interaction model were adopted for exploring the interaction effects with aspirin. RESULTS: A total of 6592 and 84,116 lung cancer cases were identified from the groups of anti-hypertensives users and anti-hypertensives users with aspirin, respectively. The group of non-aspirin patients who received anti-hypertensives showed a significantly lower risk of lung cancer (HR: 0.63, 95% CI: 0.60-0.66), compared to those without anti-hypertensives. When aspirin and α-blocker were used simultaneously, it could lower the risk of lung cancer significantly (HR: 0.53, 95% CI: 0.34-0.84). Moreover, the lower risk of lung cancer persisted with a longer follow-up period of anti-hypertensives usage. Combination usage with aspirin in the users of ACEi/ARB, CCB, and α-blocker showed significant interaction effects. However, the smoking effect could not be eliminated in this analysis. DISCUSSION: Anti-hypertensive treatment was associated with a lower risk of lung cancer, which is associated with the anti-hypertensives exposure period. The potential interaction on the chemopreventive influence from combination usage of α-blocker and aspirin might exist. More corroborations on these findings are needed to focus on the different settings in future studies.

Prediction algorithm for gastric cancer in a general population: A validation study.

BACKGROUND: Worldwide, gastric cancer is a leading cause of cancer incidence and mortality. This study aims to devise and validate a scoring system based on readily available clinical data to predict the risk of gastric cancer in a large Chinese population. METHODS: We included a total of 6,209,697 subjects aged between 18 and 70 years who have received upper digestive endoscopy in Hong Kong from 1997 to 2018. A binary logistic regression model was constructed to examine the predictors of gastric cancer in a derivation cohort (n = 4,347,224), followed by model evaluation in a validation cohort (n = 1,862,473). The algorithm's discriminatory ability was evaluated as the area under the curve (AUC) of the mathematically constructed receiver operating characteristic (ROC) curve. RESULTS: Age, male gender, history of Helicobacter pylori infection, use of proton pump inhibitors, non-use of aspirin, non-steroidal anti-inflammatory drugs (NSAIDs), and statins were significantly associated with gastric cancer. A scoring of ≤8 was designated as "average risk (AR)". Scores at 9 or above were assigned as "high risk (HR)". The prevalence of gastric cancer was 1.81% and 0.096%, respectively, for the HR and LR groups. The AUC for the risk score in the validation cohort was 0.834, implying an excellent fit of the model. CONCLUSIONS: This study has validated a simple, accurate, and easy-to-use scoring algorithm which has a high discriminatory capability to predict gastric cancer. The score could be adopted to risk stratify subjects suspected as having gastric cancer, thus allowing prioritized upper digestive tract investigation.

Diagnostic performance of digital cognitive tests for the identification of MCI and dementia: A systematic review.

BACKGROUND: The use of digital cognitive tests is getting common nowadays. Older adults or their family members may use online tests for self-screening of dementia. However, the diagnostic performance across different digital tests is still to clarify. The objective of this study was to evaluate the diagnostic performance of digital cognitive tests for MCI and dementia in older adults. METHODS: Literature searches were systematically performed in the OVID databases. Validation studies that reported the diagnostic performance of a digital cognitive test for MCI or dementia were included. The main outcome was the diagnostic performance of the digital test for the detection of MCI or dementia. RESULTS: A total of 56 studies with 46 digital cognitive tests were included in this study. Most of the digital cognitive tests were shown to have comparable diagnostic performances with the paper-and-pencil tests. Twenty-two digital cognitive tests showed a good diagnostic performance for dementia, with a sensitivity and a specificity over 0.80, such as the Computerized Visuo-Spatial Memory test and Self-Administered Tasks Uncovering Risk of Neurodegeneration. Eleven digital cognitive tests showed a good diagnostic performance for MCI such as the Brain Health Assessment. However, all the digital tests only had a few validation studies to verify their performance. CONCLUSIONS: Digital cognitive tests showed good performances for MCI and dementia. The digital test can collect digital data that is far beyond the traditional ways of cognitive tests. Future research is suggested on these new forms of cognitive data for the early detection of MCI and dementia.