Long-Term Safety of a Novel Antianginal Agent in Patients With Severe Chronic Stable Angina The Ranolazine Open Label Experience (ROLE)

ObjectivesThis report describes safety and tolerability data from 746 chronic angina patients treated in the ROLE (Ranolazine Open Label Experience) program.BackgroundRanolazine treats angina without depressing hemodynamic status. The long-term safety and tolerability of ranolazine have not been previously reported.MethodsPatients with severe functional impairment from angina (mean Duke Treadmill Score [DTS] of −14.4) who completed 1 of 2 randomized treadmill trials entered the ROLE program. Ranolazine was titrated to optimal dosages between 500 and 1,000 mg twice daily. Physical examination, laboratory tests, and adverse event reporting were performed periodically. We conducted analyses to evaluate possible predictors of ranolazine intolerance, such as advanced age, diabetes, poor exercise tolerance, or history of myocardial infarctions or congestive heart failure (CHF). The ROLE program’s mortality was compared against the DTS predictive model and other contemporary cohorts of high-risk CHD patients.ResultsMean follow-up was 2.82 years. Two years after initial dosing, 571 patients (76.7%) remained on therapy and 72 patients (9.7%) discontinued ranolazine due to adverse events. Among 6 factors evaluated, only age ≥64 years predicted for higher withdrawal rates. Patients with a history of CHF had lower withdrawal rates. Mean QTc interval was prolonged by 2.4 ms. No treatment discontinuations occurred due to QTc prolongation, and no Torsades de Pointes was reported. Sixty-four deaths occurred during a total of 2,102 patient-years (3.0% annually) during the ROLE program. When extending observations to all patients exposed to ranolazine during the double-blind trials (n = 972) preceding the ROLE program, annual mortality was 2.8% compared with >5% as predicted by DTS.ConclusionsLong-term therapy with ranolazine seems well tolerated in high-risk CHD patients. Survival analyses suggest that symptomatic improvements attributable to ranolazine are not offset by increased mortality

A 17-gene Assay to Predict Prostate Cancer Aggressiveness in the Context of Gleason Grade Heterogeneity, Tumor Multifocality, and Biopsy Undersampling

avai lable at www.sciencedirect.com journal homepage: www.europeanurology.com Genomic Prostate Score Outcome measures and statistical analysis: The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatec-predictive of aggressClinical validation Clinical utility tomy. Cox proportional hazards regressionmodels were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profileswere used together with clinical and pathologic characteristics to evaluate clinical utility. Results and limitations: Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were ive disease after adjustment for prostate-specific antigen, GleasonArticle inf

Patient-specific Meta-analysis of 2 Clinical Validation Studies to Predict Pathologic Outcomes in Prostate Cancer Using the 17-Gene Genomic Prostate Score.

ObjectiveTo perform patient-specific meta-analysis (MA) of two independent clinical validation studies of a 17-gene biopsy-based genomic assay as a predictor of favorable pathology at radical prostatectomy.Materials and methodsPatient-specific MA was performed on data from 2 studies (732 patients) using the Genomic Prostate Score (GPS; scale 0-100) together with Cancer of the Prostate Risk Assessment (CAPRA) score or National Comprehensive Cancer Network (NCCN) risk group as predictors of the likelihood of favorable pathology (LFP). Risk profile curves associating GPS with LFP by CAPRA score and NCCN risk group were generated. Decision curves and receiver operating characteristic curves were calculated using patient-specific MA risk estimates.ResultsPatient-specific MA-generated risk profiles ensure more precise estimates of LFP with narrower confidence intervals than either study alone. GPS added significant predictive value to each clinical classifier. A model utilizing GPS and CAPRA provided the most risk discrimination. In decision-curve analysis, greater net benefit was shown when combining GPS with each clinical classifier compared with the classifier alone. The area under the receiver operating characteristic curve improved from 0.68 to 0.73 by adding GPS to CAPRA, and 0.64 to 0.70 by adding GPS to NCCN risk group. The proportion of patients with LFP >80% increased from 11% using NCCN risk group alone to 23% using GPS with NCCN. Using GPS with CAPRA identified the highest proportion-31%-of patients with LFP >80%.ConclusionPatient-specific MA provides more precise risk estimates that reflect the complete body of evidence. GPS adds predictive value to 3 widely used clinical classifiers, and identifies a larger proportion of low-risk patients than identified by clinical risk group alone

Patient-specific Meta-analysis of 2 Clinical Validation Studies to Predict Pathologic Outcomes in Prostate Cancer Using the 17-Gene Genomic Prostate Score.

ObjectiveTo perform patient-specific meta-analysis (MA) of two independent clinical validation studies of a 17-gene biopsy-based genomic assay as a predictor of favorable pathology at radical prostatectomy.Materials and methodsPatient-specific MA was performed on data from 2 studies (732 patients) using the Genomic Prostate Score (GPS; scale 0-100) together with Cancer of the Prostate Risk Assessment (CAPRA) score or National Comprehensive Cancer Network (NCCN) risk group as predictors of the likelihood of favorable pathology (LFP). Risk profile curves associating GPS with LFP by CAPRA score and NCCN risk group were generated. Decision curves and receiver operating characteristic curves were calculated using patient-specific MA risk estimates.ResultsPatient-specific MA-generated risk profiles ensure more precise estimates of LFP with narrower confidence intervals than either study alone. GPS added significant predictive value to each clinical classifier. A model utilizing GPS and CAPRA provided the most risk discrimination. In decision-curve analysis, greater net benefit was shown when combining GPS with each clinical classifier compared with the classifier alone. The area under the receiver operating characteristic curve improved from 0.68 to 0.73 by adding GPS to CAPRA, and 0.64 to 0.70 by adding GPS to NCCN risk group. The proportion of patients with LFP >80% increased from 11% using NCCN risk group alone to 23% using GPS with NCCN. Using GPS with CAPRA identified the highest proportion-31%-of patients with LFP >80%.ConclusionPatient-specific MA provides more precise risk estimates that reflect the complete body of evidence. GPS adds predictive value to 3 widely used clinical classifiers, and identifies a larger proportion of low-risk patients than identified by clinical risk group alone