Genetic polymorphisms at 19q13.33 are associated with [-2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer.

BACKGROUND: Prostate health index (phi), a derivative of [-2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility. METHODS: We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index. RESULTS: We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (Pcombined = 5.73 × 10-9 ), was also associated with phi values (Pcombined = 3.20 × 10-6 ). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p < .01). CONCLUSION: Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.

Cost-Effectiveness Analysis of Prostate Health Index in Decision Making for Initial Prostate Biopsy.

BACKGROUND: Clinical studies have suggested that prostate health index (phi) outperforms prostate-specific antigen (PSA) tests in prostate cancer detection. The cost-effectiveness of phi with different cutoffs is poorly understood in the context of decision making for prostate biopsy. METHODS: In a multicenter cohort, 3,348 men with elevated total PSA (tPSA) underwent initial prostate biopsy from August 2013 to May 2019. We constructed a decision model to evaluate the incremental cost-effectiveness ratios of different phi cutoffs. Total costs and reimbursement payments were based on the fee schedule of Shanghai Basic Medical Insurance and converted into United States dollars ($). Two willingness-to-pay thresholds were estimated as one or three times the average gross domestic product per capita of China ($7,760 or $23,279, respectively). RESULTS: The total costs of prostate biopsy and PSA tests were estimated at $315 and $19, respectively. The cost of phi test varied between $72 to $130 in different medical centers. Under different phi cutoffs (from 23 to 35), phi test predicted reductions of 420 (21.7%) to 972 (50.2%) in unnecessary biopsies, with a total gain of 23.77-57.58 quality adjusted life-years compared to PSA tests. All the cutoffs would be cost-effective for patients with tPSA levels of 2-10 ng/ml. Applying 27 as the cutoff was cost-effective for each tPSA range, with missing positive cases ranging from 11 (3.4%) to 33 (11.5%). CONCLUSIONS: Using phi test was cost-effective in the decision-making process for initial prostate biopsy, especially for patients with tPSA values between 2-10 ng/ml. The phi cutoff of 27 was cost-effective regardless of tPSA ranges and should be recommended from a health-economic perspective.

Broad- and narrow-sense validity performance of three polygenic risk score methods for prostate cancer risk assessment.

BACKGROUND: Several polygenic risk score (PRS) methods are available for measuring the cumulative effect of multiple risk-associated single nucleotide polymorphisms (SNPs). Their performance in predicting risk at the individual level has not been well studied. METHODS: We compared the performance of three PRS methods for prostate cancer risk assessment in a clinical trial cohort, including genetic risk score (GRS), pruning and thresholding (P + T), and linkage disequilibrium prediction (LDpred). Performance was evaluated for score deciles (broad-sense validity) and score values (narrow-sense validity). RESULTS: A training process was required to identify the best P + T model (397 SNPs) and LDpred model (3 011 362 SNPs). In contrast, GRS was directly calculated based on 110 established risk-associated SNPs. For broad-sense validity in the testing population, higher deciles were significantly associated with higher observed risk; Ptrend was 7.40 × 10-11 , 7.64 × 10-13 , and 7.51 × 10-10 for GRS, P + T, and LDpred, respectively. For narrow-sense validity, the calibration slope (1 is best) was 1.03, 0.77, and 0.87, and mean bias score (0 is best) was 0.09, 0.21, and 0.10 for GRS, P + T, and LDpred, respectively. CONCLUSIONS: The performance of GRS was better than P + T and LDpred. Fewer and well-established SNPs of GRS also make it more feasible and interpretable for genetic testing at the individual level.

Population-standardized genetic risk score: the SNP-based method of choice for inherited risk assessment of prostate cancer.

Several different approaches are available to clinicians for determining prostate cancer (PCa) risk. The clinical validity of various PCa risk assessment methods utilizing single nucleotide polymorphisms (SNPs) has been established; however, these SNP-based methods have not been compared. The objective of this study was to compare the three most commonly used SNP-based methods for PCa risk assessment. Participants were men (n = 1654) enrolled in a prospective study of PCa development. Genotypes of 59 PCa risk-associated SNPs were available in this cohort. Three methods of calculating SNP-based genetic risk scores (GRSs) were used for the evaluation of individual disease risk such as risk allele count (GRS-RAC), weighted risk allele count (GRS-wRAC), and population-standardized genetic risk score (GRS-PS). Mean GRSs were calculated, and performances were compared using area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV). All SNP-based methods were found to be independently associated with PCa (all P < 0.05; hence their clinical validity). The mean GRSs in men with or without PCa using GRS-RAC were 55.15 and 53.46, respectively, using GRS-wRAC were 7.42 and 6.97, respectively, and using GRS-PS were 1.12 and 0.84, respectively (all P < 0.05 for differences between patients with or without PCa). All three SNP-based methods performed similarly in discriminating PCa from non-PCa based on AUC and in predicting PCa risk based on PPV (all P > 0.05 for comparisons between the three methods), and all three SNP-based methods had a significantly higher AUC than family history (all P < 0.05). Results from this study suggest that while the three most commonly used SNP-based methods performed similarly in discriminating PCa from non-PCa at the population level, GRS-PS is the method of choice for risk assessment at the individual level because its value (where 1.0 represents average population risk) can be easily interpreted regardless of the number of risk-associated SNPs used in the calculation.

Adaptation and validation of the "cognitive complaints in bipolar disorder rating assessment" (COBRA) in Chinese bipolar patients.

BACKGROUND: There is no specific instrument available to measure cognitive deficits as reported by bipolar patients in China. Therefore, if discrepancies between bipolar patients' reports and the results of neuropsychological tests which have been described in other countries existing or not in Chinese bipolar disorder patients have not been known yet. And it is completely blank about the subjective cognition of these Chinese bipolar patients. OBJECTIVES: The aim of the study is to revise and validate a specific, user-friendly, brief instrument named the "cognitive complaints in bipolar disorder rating assessment" (COBRA) into Chinese version. METHODS: The total sample (N=255) included 125 bipolar disorder patients and 130 healthy controls. The psychometric properties of the COBRA (e.g. internal consistency, retest reliability, discriminative validity, concurrent validity, content validity, item analysis, confirmatory factor analysis, ROC curve and feasibility) were analyzed. RESULTS: The Chinese version of the COBRA had very high internal consistency (Cronbach's alpha=0.905) and retest reliability (ICC=0.902). Confirmatory factor analysis validated the one-factor model and the cut-off value to discriminate the patients and controls was 11.Bipolar patients experienced greater cognitive complaints compared to control group suggesting a discriminative validity of the instrument. No significant correlation was found between the COBRA and the total Montreal Cognitive Assessment Scale (MoCA), except for single measures related to executive function (phonemic fluency, p=0.045), verbal memory (delayed recall, p=0.004). LIMITATIONS: Cross-sectional design, no specific or unspecific but reliable instrument in Chinese to assess subjective cognitive difficulties in mental disorders for criterion validity or convergent validity analysis. CONCLUSIONS: The Chinese version of the COBRA showed to be a simple and reliable instrument to assess subjective cognitive complaints in Chinese bipolar patients.