PATIENTS AND METHODS: A total of 7476 patients with routine health check-up data who underwent prostate biopsies from January 2008 to December 2021 in eight referral centres in Asia were screened. After data pre-processing and cleaning, 5037 patients and 117 features were analyzed. Seven AI-based algorithms were tested for feature selection and seven AI-based algorithms were tested for classification, with the best combination applied for model construction. The APAC score was established in the CH cohort and validated in a multi-centre cohort and in each validation cohort to evaluate its generalizability in different Asian regions. The performance of the models was evaluated using area under the receiver operating characteristic curve (ROC), calibration plot, and decision curve analyses.
RESULTS: Eighteen features were involved in the APCA score predicting HGPCa, with some of these markers not previously used in prostate cancer diagnosis. The area under the curve (AUC) was 0.76 (95% CI:0.74-0.78) in the multi-centre validation cohort and the increment of AUC (APCA vs. PSA) was 0.16 (95% CI:0.13-0.20). The calibration plots yielded a high degree of coherence and the decision curve analysis yielded a higher net clinical benefit. Applying the APCA score could reduce unnecessary biopsies by 20.2% and 38.4%, at the risk of missing 5.0% and 10.0% of HGPCa cases in the multi-centre validation cohort, respectively.
CONCLUSIONS: The APCA score based on routine health check-ups could reduce unnecessary prostate biopsies without additional examinations in Asian populations. Further prospective population-based studies are warranted to confirm these results.
MATERIALS AND METHODS: We analysed retrospective data of chest pain patients presenting to ED HUSM from 1st June 2020 till 31st January 2021 based on the patient's history, ECG findings, risk factors, age and troponin level. The patients were stratified as low risk (MHS and HEAR score of 0-3), intermediate risk (MHS and HEAR score of 4-6), and high risk (MHS of 7-10 and HEAR score of 7-8). The association of the MHS and HEAR score with MACE at 6 weeks' time was evaluated using simple logistic regression.
RESULTS: This study included 147 patients in the MHS analysis and 71 patients in HEAR score analysis. The incident rate of MACE in low, intermediate and high risk was 0%,16.3%, and 34.7%, in the MHS group, and 0%, 3.22%, and 6.66% in HEAR score group. The mean difference between MACE and non-MACE in MHS and HEAR score groups was -2.29 (CI: -3.13,1.44, p<0.001) and -2.51(CI: -5.23, 0.21, p=0.070), respectively. There was no significant association between the incidence rate of MACE with modified HEART score (MHS) and HEAR score groups (p>0.95).
CONCLUSION: HEAR score is not feasible to be used as a risk stratification tool for chest pain patients presenting to ED HUSM in comparison to MHS. Further studies are required to validate the results.
METHODS AND ANALYSIS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols statement was used as a template for this protocol. A systematic search of Medline, Embase and Global Health from database inception to present will be conducted to identify prospective studies reporting on the associations between major measures of body composition (body mass index, waist circumference, waist-hip ratio, total body fat, visceral adiposity tissue and lean mass) and risk of heart failure. Article screening and selection will be performed by two reviewers independently, and disagreements will be adjudicated by consensus or by a third reviewer. Data from eligible articles will be extracted, and article quality will be assessed using the Newcastle-Ottawa Scale. Relative risks (and 95% CIs) will be pooled in a fixed effect meta-analysis, if there is no prohibitive heterogeneity of studies as assessed using the Cochrane Q statistic and I2 statistic. Subgroup analyses will be by age, sex, ethnicity and heart failure subtypes. Publication bias in the meta-analysis will be assessed using Egger's test and funnel plots.
ETHICS AND DISSEMINATION: This work is secondary analyses on published data and ethical approval is not required. We plan to publish results in an open-access peer-reviewed journal, present it at international and national conferences, and share the findings on social media.
PROSPERO REGISTRATION NUMBER: CRD42020224584.
MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.
RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.
CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
OBJECTIVES: The purpose of this study was to describe trends in maternal pre-pregnancy hypertension among women in rural and urban areas in 2007 to 2018 in order to inform community-engaged prevention and policy strategies.
METHODS: We performed a nationwide, serial cross-sectional study using maternal data from all live births in women age 15 to 44 years between 2007 and 2018 (CDC Natality Database). Rates of pre-pregnancy hypertension were calculated per 1,000 live births overall and by urbanization status. Subgroup analysis in standard 5-year age categories was performed. We quantified average annual percentage change using Joinpoint Regression and rate ratios (95% confidence intervals [CIs]) to compare yearly rates between rural and urban areas.
RESULTS: Among 47,949,381 live births to women between 2007 and 2018, rates of pre-pregnancy hypertension per 1,000 live births increased among both rural (13.7 to 23.7) and urban women (10.5 to 20.0). Two significant inflection points were identified in 2010 and 2016, with highest annual percentage changes between 2016 and 2018 in rural and urban areas. Although absolute rates were lower in younger compared with older women in both rural and urban areas, all age groups experienced similar increases. The rate ratios of pre-pregnancy hypertension in rural compared with urban women ranged from 1.18 (95% CI: 1.04 to 1.35) for ages 15 to 19 years to 1.51 (95% CI: 1.39 to 1.64) for ages 40 to 44 years in 2018.
CONCLUSIONS: Maternal burden of pre-pregnancy hypertension has nearly doubled in the past decade and the rural-urban gap has persisted.
AIM: To identify the association of baseline GGT level and QRISK2 score among patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD).
METHODS: This was a retrospective study involving 1535 biopsy-proven NAFLD patients from 10 Asian centers in 8 countries using data collected by the Gut and Obesity in Asia (referred to as "GO ASIA") workgroup. All patients with available baseline GGT levels and all 16 variables for the QRISK2 calculation (QRISK2-2017; developed by researchers at the United Kingdom National Health Service; https://qrisk.org/2017/; 10-year cardiovascular risk estimation) were included and compared to healthy controls with the same age, sex, and ethnicity. Relative risk was reported. QRISK2 score > 10% was defined as the high-CVD-risk group. Fibrosis stages 3 and 4 (F3 and F4) were considered advanced fibrosis.
RESULTS: A total of 1122 patients (73%) had complete data and were included in the final analysis; 314 (28%) had advanced fibrosis. The median age (interquartile range [IQR]) of the study population was 53 (44-60) years, 532 (47.4%) were females, and 492 (43.9%) were of Chinese ethnicity. The median 10-year CVD risk (IQR) was 5.9% (2.6-10.9), and the median relative risk of CVD over 10 years (IQR) was 1.65 (1.13-2.2) compared to healthy individuals with the same age, sex, and ethnicity. The high-CVD-risk group was significantly older than the low-risk group (median [IQR]: 63 [59-67] vs 49 [41-55] years; P < 0.001). Higher fibrosis stages in biopsy-proven NAFLD patients brought a significantly higher CVD risk (P < 0.001). Median GGT level was not different between the two groups (GGT [U/L]: Median [IQR], high risk 60 [37-113] vs low risk 66 [38-103], P = 0.56). There was no correlation between baseline GGT level and 10-year CVD risk based on the QRISK2 score (r = 0.02).
CONCLUSION: The CVD risk of NAFLD patients is higher than that of healthy individuals. Baseline GGT level cannot predict CVD risk in NAFLD patients. However, advanced fibrosis is a predictor of a high CVD risk.
PURPOSE: To determine if density of breast is an independent risk factor which will contribute to development of breast cancer.
MATERIALS AND METHODS: A prospective cohort study is carried out in two hospitals targeting adult female patients who presented to the Breast Clinic with symptoms suspicious of breast cancer. Participants recruited were investigated for breast cancer based on their symptoms. Breast density assessed from mammogram was correlated with tissue biopsy results and final diagnosis of benign or malignant breast disease.
RESULTS: Participants with dense breasts showed 29% increased risk of breast cancer when compared to those with almost entirely fatty breasts (odds ratio [OR] 1.29, 95% CI 0.38-4.44, P = .683). Among the postmenopausal women, those with dense breasts were 3.1 times more likely to develop breast cancer compared with those with fatty breasts (OR 3.125, 95% CI 0.72-13.64, P = .13). Moreover, the chance of developing breast cancer increases with age (OR 1.046, 95% CI 1.003-1.090, P risk of breast cancer cannot be ruled out. The study is limited by a small sample size and subjective assessment of breast density. More studies are required to reconcile the differences between studies of contrasting evidence.
OBJECTIVES: The objectives of this study was to determine whether patients with primary prevention (PP) indications with specific risk factors (1.5PP: syncope, nonsustained ventricular tachycardia, premature ventricular contractions >10/h, and low ventricular ejection fraction <25%) are at a similar risk of life-threatening arrhythmias as patients with secondary prevention (SP) indications and to evaluate all-cause mortality rates in 1.5PP patients with and without devices.
METHODS: A total of 3889 patients were included in the analysis to evaluate ventricular tachycardia or fibrillation therapy and mortality rates. Patients were stratified as SP (n = 1193) and patients with PP indications. The PP cohort was divided into 1.5PP patients (n = 1913) and those without any 1.5PP criteria (n = 783). The decision to undergo ICD implantation was left to the patient and/or physician. The Cox proportional hazards model was used to compute hazard ratios.
RESULTS: Patients had predominantly nonischemic cardiomyopathy. The rate of ventricular tachycardia or fibrillation in 1.5PP patients was not equivalent (within 30%) to that in patients with SP indications (hazard ratio 0.47; 95% confidence interval 0.38-0.57) but was higher than that in PP patients without any 1.5PP criteria (hazard ratio 0.67; 95% confidence interval 0.46-0.97) (P = .03). There was a 49% relative risk reduction in all-cause mortality in ICD implanted 1.5PP patients. In addition, the number needed to treat to save 1 life over 3 years was 10.0 in the 1.5PP cohort vs 40.0 in PP patients without any 1.5PP criteria.
CONCLUSION: These data corroborate the mortality benefit of ICD therapy and support extension to a selected PP population from underrepresented geographies.
METHODS: The study was initiated in September 2005 and patients were followed up to March 2014. Two hundred patients with oral leukoplakia, 100 patients with oral cancer and 100 healthy, age and sex matched adults with normal oral mucosa as controls were recruited. The DNA ploidy content was measured by high resolution flow cytometry, level of telomerase expression was identified by TRAP assay and intrinsic DNA repair capacity was measured by mutagen induced chromosome sensitivity assay of cultured peripheral blood lymphocytes. The Chi-square test or Fisher's Exact test was used for comparison of categorical variables between biomarkers. A p value less than or equal to 0.05 was considered as statistically significant. Analysis was performed with SPSS software version 16. Logistic regression was used to find the association between the dependent and three independent variables.
RESULTS: There was significant difference in the distribution of ploidy status, telomerase activity and DNA repair capacity among control, leukoplakia and oral cancer group (p<0.001). When the molecular markers were compared with histological grading of leukoplakia, both DNA ploidy analysis and telomerase activity showed statistical significance (p<0.001). Both aneuploidy and telomerase positivity was found to coincide with high-risk sites of leukoplakia and were statistically significant (p.