Genomic Classifier Performance in Intermediate-Risk Prostate Cancer: Results From NRG Oncology/RTOG 0126 Randomized Phase 3 Trial.

PURPOSE: Intermediate-risk prostate cancer is a heterogeneous disease state with diverse treatment options. The 22-gene Decipher genomic classifier (GC) retrospectively has shown to improve risk stratification in these patients. We assessed the performance of the GC in men with intermediate-risk disease enrolled in NRG Oncology/RTOG 01-26 with updated follow-up. METHODS AND MATERIALS: After National Cancer Institute approval, biopsy slides were collected from NRG Oncology/RTOG 01-26, a randomized phase 3 trial of men with intermediate-risk prostate cancer randomized to 70.2 Gy versus 79.2 Gy of radiation therapy without androgen deprivation therapy. RNA was extracted from the highest-grade tumor foci to generate the locked 22-gene GC model. The primary endpoint for this ancillary project was disease progression (composite of biochemical failure, local failure, distant metastasis, prostate cancer-specific mortality, and use of salvage therapy). Individual endpoints were also assessed. Fine-Gray or cause-specific Cox multivariable models were constructed adjusting for randomization arm and trial stratification factors. RESULTS: Two-hundred fifteen patient samples passed quality control for analysis. The median follow-up was 12.8 years (range, 2.4-17.7). On multivariable analysis, the 22-gene GC (per 0.1 unit) was independently prognostic for disease progression (subdistribution hazard ratio [sHR], 1.12; 95% confidence interval [CI], 1.00-1.26; P = .04), biochemical failure (sHR, 1.22; 95% CI, 1.10-1.37; P < .001), distant metastasis (sHR, 1.28; 95% CI, 1.06-1.55; P = .01), and prostate cancer-specific mortality (sHR, 1.45; 95% CI, 1.20-1.76; P < .001). Ten-year distant metastasis in GC low-risk patients was 4% compared with 16% for GC high-risk patients. In patients with lower GC scores, the 10-year difference in metastasis-free survival rate between arms was -7%, compared with 21% for higher GC patients (P-interaction = .04). CONCLUSIONS: This study represents the first validation of a biopsy-based gene expression classifier, assessing both its prognostic and predictive value, using data from a randomized phase 3 trial of intermediate-risk prostate cancer. Decipher improves risk stratification and can aid in treatment decision-making in men with intermediate-risk disease.

Conversion of Central Subfield Thickness Measurements of Diabetic Macular Edema Across Cirrus and Spectralis Optical Coherence Tomography Instruments.

Purpose: Develop equations to convert Cirrus central subfield thickness (CST) to Spectralis CST equivalents and vice versa in eyes with diabetic macular edema (DME). Methods: The DRCR Retina Network Protocol O data were split randomly to train (70% sample) and validate (30% sample) conversion equations. Data from an independent study (CADME) also validated the equations. Bland-Altman 95% limits of agreement between predicted and observed values evaluated the equations. Results: Protocol O included 374 CST scan pairs from 187 eyes (107 participants). The CADME study included 150 scan pairs of 37 eyes (37 participants). Proposed conversion equations are Spectralis = 40.78 + 0.95 × Cirrus and Cirrus = 1.82 + 0.94 × Spectralis regardless of age, sex, or CST. Predicted values were within 10% of observed values in 101 (90%) of Spectralis and 99 (88%) of Cirrus scans in the validation data; and in 136 (91%) of the Spectralis and 148 (99%) of the Cirrus scans in the CADME data. Adjusting for within-eye correlations, 95% of conversions are estimated to be within 17% (95% confidence interval, 14%-21%) of CST on Spectralis and within 22% (95% confidence interval, 18%-28%) of CST on Cirrus. Conclusions: Conversion equations developed in this study allow the harmonization of CST measurements for eyes with DME using a mix of current Cirrus and Spectralis device images. Translational Relevance: The CSTs measured on Cirrus and Spectralis devices are not directly comparable owing to outer boundary segmentation differences. Converting CST values across spectral domain optical coherence tomography instruments should benefit both clinical research and standard care efforts.

Validation of a 22-Gene Genomic Classifier in Patients With Recurrent Prostate Cancer: An Ancillary Study of the NRG/RTOG 9601 Randomized Clinical Trial.

Importance: Decipher (Decipher Biosciences Inc) is a genomic classifier (GC) developed to estimate the risk of distant metastasis (DM) after radical prostatectomy (RP) in patients with prostate cancer. Objective: To validate the GC in the context of a randomized phase 3 trial. Design, Setting, and Participants: This ancillary study used RP specimens from the phase 3 placebo-controlled NRG/RTOG 9601 randomized clinical trial conducted from March 1998 to March 2003. The specimens were centrally reviewed, and RNA was extracted from the highest-grade tumor available in 2019 with a median follow-up of 13 years. Clinical-grade whole transcriptomes from samples passing quality control were assigned GC scores (scale, 0-1). A National Clinical Trials Network-approved prespecified statistical plan included the primary objective of validating the independent prognostic ability of GC for DM, with secondary end points of prostate cancer-specific mortality (PCSM) and overall survival (OS). Data were analyzed from September 2019 to December 2019. Intervention: Salvage radiotherapy (sRT) with or without 2 years of bicalutamide. Main Outcomes and Measures: The preplanned primary end point of this study was the independent association of the GC with the development of DM. Results: In this ancillary study of specimens from a phase 3 randomized clinical trial, GC scores were generated from 486 of 760 randomized patients with a median follow-up of 13 years; samples from a total of 352 men (median [interquartile range] age, 64.5 (60-70) years; 314 White [89.2%] participants) passed microarray quality control and comprised the final cohort for analysis. On multivariable analysis, the GC (continuous variable, per 0.1 unit) was independently associated with DM (hazard ratio [HR], 1.17; 95% CI, 1.05-1.32; P = .006), PCSM (HR, 1.39; 95% CI, 1.20-1.63; P < .001), and OS (HR, 1.17; 95% CI, 1.06-1.29; P = .002) after adjusting for age, race/ethnicity, Gleason score, T stage, margin status, entry prostate-specific antigen, and treatment arm. Although the original planned analysis was not powered to detect a treatment effect interaction by GC score, the estimated absolute effect of bicalutamide on 12-year OS was less when comparing patients with lower vs higher GC scores (2.4% vs 8.9%), which was further demonstrated in men receiving early sRT at a prostate-specific antigen level lower than 0.7 ng/mL (-7.8% vs 4.6%). Conclusions and Relevance: This ancillary validation study of the Decipher GC in a randomized trial cohort demonstrated association of the GC with DM, PCSM, and OS independent of standard clinicopathologic variables. These results suggest that not all men with biochemically recurrent prostate cancer after surgery benefit equally from the addition of hormone therapy to sRT. Trial Registration: ClinicalTrials.gov identifier: NCT00002874.

Impact of Decipher on use of post-operative radiotherapy: Individual patient analysis of two prospective registries.

Objective: To assess the association between Genomic Classifier (GC)-risk group and post-radical prostatectomy treatment in clinical practice. Methods: Two prospective observational cohorts of men with prostate cancer (PCa) who underwent RP in two referral centers and had GC testing post-prostatectomy between 2013 and 2018 were included. The primary endpoint of the study was to assess the association between GC-risk group and time to secondary therapy. Univariable (UVA) and multivariable (MVA) Cox proportional hazards models were constructed to assess the association between GC-risk group and time to receipt of secondary therapy after RP, where secondary therapy is defined as receiving either RT or ADT after RP. Results: A total of 398 patients are included in the analysis. Patients with high-GC risk were more likely to receive any secondary therapy (OR: 6.84) compared to patients with low/intermediate-GC risk. The proportion of high-GC risk patients receiving RT at 2 years post-RP was 31.5%, compared to only 6.3% among the low/intermediate-GC risk patients. Conclusion: This study demonstrates that physicians in routine practice used GC to identify high risk patients who might benefit the most from secondary treatment. As such, GC score was independent predictor of receipt of secondary treatment.

Automated estimation of echocardiogram image quality in hospitalized patients.

We developed a machine learning model for efficient analysis of echocardiographic image quality in hospitalized patients. This study applied a machine learning model for automated transthoracic echo (TTE) image quality scoring in three inpatient groups. Our objectives were: (1) Assess the feasibility of a machine learning model for echo image quality analysis, (2) Establish the comprehensiveness of real-world TTE reporting by clinical group, and (3) Determine the relationship between machine learning image quality and comprehensiveness of TTE reporting. A machine learning model was developed and applied to TTEs from three matched cohorts for image quality of nine standard views. Case TTEs were comprehensive studies in mechanically ventilated patients between 01/01/2010 and 12/31/2015. For each case TTE, there were two matched spontaneously breathing controls (Control 1: Inpatients scanned in the lab and Control 2: Portable studies). We report the overall mean maximum and view specific quality scores for each TTE. The comprehensiveness of an echo report was calculated as the documented proportion of 12 standard parameters. An inverse probability weighted regression model was fit to determine the relationship between machine learning quality score and the completeness of a TTE report. 175 mechanically ventilated TTEs were included with 350 non-intubated samples (175 Control 1: Lab and 175 Control 2: Portable). In total, the machine learning model analyzed 14,086 echo video clips for quality. The overall accuracy of the model with regard to the expert ground truth for the view classification was 87.0%. The overall mean maximum quality score was lower for mechanically ventilated TTEs (0.55 [95% CI 0.54, 0.56]) versus 0.61 (95% CI 0.59, 0.62) for Control 1: Lab and 0.64 (95% CI 0.63, 0.66) for Control 2: Portable; p = 0.002. Furthermore, mechanically ventilated TTE reports were the least comprehensive, with fewer reported parameters. The regression model demonstrated the correlation of echo image quality and completeness of TTE reporting regardless of the clinical group. Mechanically ventilated TTEs were of inferior quality and clinical utility compared to spontaneously breathing controls and machine learning derived image quality correlates with completeness of TTE reporting regardless of the clinical group.

Clinical Utility of a Genomic Classifier in Men Undergoing Radical Prostatectomy: The PRO-IMPACT Trial.

PURPOSE: The optimal management of men with prostate cancer at high risk of recurrence postradical prostatectomy is controversial. The clinical utility of the Decipher test was evaluated prospectively on postoperative treatment decisions and patient-reported outcomes. METHODS AND MATERIALS: In the study, 246 eligible men across 19 centers were enrolled. Patients were dichotomized into those considering adjuvant or salvage radiation therapy (ART or SRT). Participating providers submitted a management recommendation before and after receiving the Decipher test results. Treatment received within 12 months and a validated survey on prostate cancer-related anxiety were collected longitudinally. RESULTS: Pre-Decipher, treatment was recommended for 12% and 40% for the ART and SRT arms, respectively. Post-Decipher, 17% and 30% of treatment recommendations changed in the ART and SRT arms, respectively. Post-Decipher treatment recommendation was administered 78% and 76% of the time in the ART and SRT arms, respectively. Multivariable analysis confirmed that the Decipher score was an independent predictor for change in management for both adjuvant and salvage patients. The number needed to test to change management for one patient was 4. Cancer-specific anxiety decreased among Decipher risk categories in both arms. CONCLUSIONS: Use of Decipher postradical prostatectomy test was associated with postoperative treatment decisions. Overall, high Decipher risk was associated with an increase in treatment intensity whereas low risk scores were associated with a decrease in therapy administered independent of clinical and pathologic risk factors.

Novel Microbial-Based Immunotherapy Approach for Crohn's Disease.

Background: Current Crohn's disease (CD) therapies focus on suppressing immune function and come with consequent risk, such as infection and cancer. Notwithstanding, most CD patients still experience disease progression. There is a need for new CD treatment strategies that offer better health outcomes for patients. Aims: To assess safety, efficacy, and tolerability of a novel microbial-derived immunotherapy, QBECO, that aims to restore rather than suppress immune function in CD. Methods: A randomized, double-blind, placebo-controlled trial was conducted in 68 patients with moderate-to-severe CD. Primary endpoints: safety and Week 8 clinical improvement. Secondary endpoints: Week 8 clinical response and remission. Week 8 responders continued blinded treatment through Week 16; non-responders received open-label QBECO from Weeks 9-16. Exploratory analyses included immune biomarker and genotype assessments. Results: QBECO was well-tolerated. Mean reduction in Crohn's Disease Activity Index (CDAI) score was -68 for QBECO vs. -31 for placebo at Week 8. Improvement with QBECO continued through Week 16 (-130 CDAI reduction). Week 8 QBECO clinical response, improvement and remission rates were 41.2%, 32.4%, 29.4% vs. 26.5%, 23.5%, 23.5% for placebo. TNFα inhibitor-naïve subjects achieved higher response rates at Week 8 with QBECO (64%) vs. placebo (26%). Specific immune biomarkers were identified that linked to QBECO response. Conclusion: This proof-of-concept study supports further investigation for the use of QBECO as a novel immunotherapy approach for CD. Biomarker analyses suggests it may be feasible to personalize CD treatment with QBECO. Larger trials are now needed to confirm clinical improvement and the unique biological findings. Clinical Trial Number: NCT01809275 (https://clinicaltrials.gov/ct2/show/NCT01809275).

Measuring the impact of influenza vaccination on healthcare worker absenteeism in the context of a province-wide mandatory vaccinate-or-mask policy.

OBJECTIVES: In 2012, British Columbia (BC) implemented a province-wide vaccinate-or-mask influenza prevention policy for healthcare workers (HCWs) with the aim of improving HCW coverage, and reducing illness in patients and staff. We assess post-policy impacts of HCW vaccination status on their absenteeism. METHODS: We matched individual HCW payroll data from December 1, 2012 to March 31, 2017 with annually self-reported vaccination status for BC health authority employees to assess sick rates (sick time as a proportion of sick time and productive time). We modelled adjusted odds ratios (OR) of taking any sick time, relative rates (RR) of sick time taken, and predicted mean sick rates by vaccination status in influenza (December 1-March 31) and non-influenza seasons (April 1 to November 30). We used two methods to assess changes in influenza season sick rates for HCWs who had a change in their vaccination status over the five years. RESULTS: HCWs who reported 'early' vaccination (before December 1 when the policy is in effect) were less likely to take sick time (OR 0.874, 95%CI: 0.866-0.881) and took less sick time (RR 0.907, 95%CI: 0.901-0.912) in influenza season compared to HCWs who did not report vaccination; whereas HCWs who reported 'late' (between December 1 and March 31, and subject to masking until vaccinated) had similar sick rates to HCWs who did not report vaccination. These trends were also observed in non-influenza season. Influenza season sick rates were similar for HCWs that had at least one year of 'early' vaccination and one year where vaccination was not reported over the five year period. CONCLUSIONS: Overall absenteeism is lower among HCWs who report vaccination versus those who do not report. However, absenteeism behaviours appear to be influenced by individual level factors other than vaccination status.

Measuring the impact of a mandatory province-wide vaccinate-or-mask policy on healthcare worker absenteeism in British Columbia, Canada.

OBJECTIVES: Vaccinate-or-mask (VOM) policies aim to improve influenza vaccine coverage among healthcare workers (HCW) and reduce influenza-related illness among patients and staff. In 2012, British Columbia (BC) implemented a province-wide VOM influenza prevention policy. This study describes an evaluation of policy impacts on HCW absenteeism rates from before to after policy implementation. METHODS: Using payroll data from regional and provincial Health Authorities (HA), we assessed all-cause sick rates (sick time as a proportion of sick time and productive time) before (2007-2011, excluding 2009-2010) and after (2012-2017) policy implementation, and during influenza season (December 1-March 31) and non-influenza season (April 1-November 30). We used a two-part negative binomial hurdle model to calculate odds ratios (OR) of taking any sick time, relative rates (RR) of sick time taken, and predicted mean sick rates, adjusting for age group, sex, job type, job classification, HA, year and vaccine effectiveness. RESULTS: During influenza season, HCWs in the post-policy period were less likely to take any sick time (OR 0.989, 95%CI: 0.979-0.999) but had higher rates of sick time (RR 1.038, 95%CI: 1.030-1.045). However, during non-influenza season, HCWs in the post-policy period were more likely to take any sick time (OR 1.015, 95%CI: 1.008-1.022) but had lower rates of sick time (RR 0.971, 95%CI: 0.966-0.976). There was an overall increase in predicted mean sick rate from pre to post-policy in influenza season (4.392% to 4.508%) and non-influenza season (3.815% to 3.901%). CONCLUSIONS: The observed year-round increase in sick rates from pre-to-post policy was likely influenced by other factors; however, opposite trends in how HCWs took sick time in the influenza and non-influenza seasons may reflect policy influences and need further research to explore reasons for these differences.

Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images.

Importance: Proper evaluation of the performance of artificial intelligence techniques in the analysis of digitized medical images is paramount for the adoption of such techniques by the medical community and regulatory agencies. Objectives: To compare several cross-validation (CV) approaches to evaluate the performance of a classifier for automatic grading of prostate cancer in digitized histopathologic images and compare the performance of the classifier when trained using data from 1 expert and multiple experts. Design, Setting, and Participants: This quality improvement study used tissue microarray data (333 cores) from 231 patients who underwent radical prostatectomy at the Vancouver General Hospital between June 27, 1997, and June 7, 2011. Digitized images of tissue cores were annotated by 6 pathologists for 4 classes (benign and Gleason grades 3, 4, and 5) between December 12, 2016, and October 5, 2017. Patches of 192 µm2 were extracted from these images. There was no overlap between patches. A deep learning classifier based on convolutional neural networks was trained to predict a class label from among the 4 classes (benign and Gleason grades 3, 4, and 5) for each image patch. The classification performance was evaluated in leave-patches-out CV, leave-cores-out CV, and leave-patients-out 20-fold CV. The analysis was performed between November 15, 2018, and January 1, 2019. Main Outcomes and Measures: The classifier performance was evaluated by its accuracy, sensitivity, and specificity in detection of cancer (benign vs cancer) and in low-grade vs high-grade differentiation (Gleason grade 3 vs grades 4-5). The statistical significance analysis was performed using the McNemar test. The agreement level between pathologists and the classifier was quantified using a quadratic-weighted κ statistic. Results: On 333 tissue microarray cores from 231 participants with prostate cancer (mean [SD] age, 63.2 [6.3] years), 20-fold leave-patches-out CV resulted in mean (SD) accuracy of 97.8% (1.2%), sensitivity of 98.5% (1.0%), and specificity of 97.5% (1.2%) for classifying benign patches vs cancerous patches. By contrast, 20-fold leave-patients-out CV resulted in mean (SD) accuracy of 85.8% (4.3%), sensitivity of 86.3% (4.1%), and specificity of 85.5% (7.2%). Similarly, 20-fold leave-cores-out CV resulted in mean (SD) accuracy of 86.7% (3.7%), sensitivity of 87.2% (4.0%), and specificity of 87.7% (5.5%). Results of McNemar tests showed that the leave-patches-out CV accuracy, sensitivity, and specificity were significantly higher than those for both leave-patients-out CV and leave-cores-out CV. Similar results were observed for classifying low-grade cancer vs high-grade cancer. When trained on a single expert, the overall agreement in grading between pathologists and the classifier ranged from 0.38 to 0.58; when trained using the majority vote among all experts, it was 0.60. Conclusions and Relevance: Results of this study suggest that in prostate cancer classification from histopathologic images, patch-wise CV and single-expert training and evaluation may lead to a biased estimation of classifier's performance. To allow reproducibility and facilitate comparison between automatic classification methods, studies in the field should evaluate their performance using patient-based CV and multiexpert data. Some of these conclusions may be generalizable to other histopathologic applications and to other applications of machine learning in medicine.

Comparison of Glycated Hemoglobin Results Based on At-Home and In-Lab Dried Blood Spot Sampling to Routine Venous Blood Sampling In-Lab in Adult Patients With Type 1 or Type 2 Diabetes.

OBJECTIVES: Regular measurement of glycated hemoglobin (A1C) is logistically demanding. Home blotter-paper collection offers an alternative. This study tested the viability of at-home blotter-paper A1C measurement. METHODS: Objective: compare accuracy of A1C levels collected on blotter paper at home (home-blotter) and blotter-paper collection in laboratory (lab-blotter) with venous A1C (routine measurement). Agreement was assessed by Pearson correlation, Lin concordance correlation coefficient (CCC), positive and negative predictive values (PPVs, NPVs) and Bland-Altman plots and associated statistics. RESULTS: Home-blotter, lab-blotter and venous A1C correlated strongly (0.93, 0.93). Home- and lab-blotter results were upwardly biased (0.387%, 0.1%). Bias increased with time. Bias correction provided agreement for both blotters (CCC >0.9); blotters correctly identifying levels above 7% (53 mmol/mol) were 100% for corrected home-blotters and 87% (95% confidence interval) for corrected lab-blotters. NPVs (% blotters correctly identifying levels of 7% or lower [53 mmol/mol]) were 100% for corrected home-blotters and 83% for corrected lab-blotters. After correction, >92% of corrected blotters had errors of 8% or less. Of our subjects, 88.5% found home sampling preferable to routine laboratory sampling. CONCLUSIONS: Home-blotter collection is an alternative to routine collection.

Decipher test impacts decision making among patients considering adjuvant and salvage treatment after radical prostatectomy: Interim results from the Multicenter Prospective PRO-IMPACT study.

BACKGROUND: Patients with prostate cancer and their providers face uncertainty as they consider adjuvant radiotherapy (ART) or salvage radiotherapy (SRT) after undergoing radical prostatectomy. The authors prospectively evaluated the impact of the Decipher test, which predicts metastasis risk after radical prostatectomy, on decision making for ART and SRT. METHODS: A total of 150 patients who were considering ART and 115 who were considering SRT were enrolled. Providers submitted a management recommendation before processing the Decipher test and again at the time of receipt of the test results. Patients completed validated surveys on prostate cancer (PCa)-specific decisional effectiveness and PCa-related anxiety. RESULTS: Before the Decipher test, observation was recommended for 89% of patients considering ART and 58% of patients considering SRT. After Decipher testing, 18% (95% confidence interval [95% CI], 12%-25%) of treatment recommendations changed in the ART arm, including 31% among high-risk patients; and 32% (95% CI, 24%-42%) of management recommendations changed in the salvage arm, including 56% among high-risk patients. Decisional Conflict Scale (DCS) scores were better after viewing Decipher test results (ART arm: median DCS before Decipher, 25 and after Decipher, 19 [P<.001]; SRT arm: median DCS before Decipher, 27 and after Decipher, 23 [P<.001]). PCa-specific anxiety changed after Decipher testing; fear of PCa disease recurrence in the ART arm (P = .02) and PCa-specific anxiety in the SRT arm (P = .05) decreased significantly among low-risk patients. Decipher results reported per 5% increase in 5-year metastasis probability were associated with the decision to pursue ART (odds ratio, 1.48; 95% CI, 1.19-1.85) and SRT (odds ratio, 1.41; 95% CI, 1.09-1.81) in multivariable logistic regression analysis. CONCLUSIONS: Knowledge of Decipher test results was associated with treatment decision making and improved decisional effectiveness among men with PCa who were considering ART and SRT. Cancer 2017;123:2850-59. © 2017 American Cancer Society.

A New QT Interval Correction Formulae to Adjust for Increases in Heart Rate.

OBJECTIVES: This study sought to develop a formula from a large population-based study that best fit the QT-heart rate (HR) relationship independent of the standard mathematical relationships. BACKGROUND: Attempts to adjust or correct for the impact of HR on the QT interval (QTc) have applied various mathematical equations to electrocardiographic (ECG) data rather than allowing the data to determine the form of the relationship. METHODS: A spline correction function was developed using the ECG data from NHANES (National Health and Nutrition Examination Surveys) II and III. The magnitude of linear, quadratic, and cubic trends in the relationship between HR and each QTc was quantified using an F-statistic with differences between QTcs compared using a permutation procedure. RESULTS: The effect of HR on QT was obliterated by the spline QT for both men and women. The cross-validated spline QTc was superior (i.e., flatter) to 6 other formulae, including ones proposed previously. In ECGs from the clinic with HRs faster than 70 beats/min, the QTcs from different formulae were significantly (p < 0.0001) different from one another. Individual values suggest the use of the longest and shortest QTc intervals as developed originally. The new QTc and its population percentile ranking can be provided for clinical ECGs. CONCLUSIONS: A new QTc formula was developed which eliminates the relationship between QT and HR. At faster HRs, the 2 most commonly used QTcs provide numerical values at the extremes of QTc. Compared to existing formulae, the new formula had the best performance.

Detailed analysis of the impact of age on the QT interval.

OBJECTIVE: To analyze the effect of age on the ECG QT interval, an important predictor of cardiovascular mortality and drug-induced cardiac arrhythmias, and determine whether QT-heart rate correction formulae (QTc) have differential relationships with age and sex. METHODS: Data were examined from the US National Health and Nutrition Examination Survey (NHANES) II and III, civilian population aged 25 to 90 years. QT weighted means and standard deviations were calculated for all ages. The QTc were evaluated for six QTc: proposed by Bazett (QTcBZT), Fridericia (QTcFRD), Hodges (QTcHDG), Dmitrienko (QTcDMT), Rautaharju (QTcRTHa) and Framingham (QTcFRM). RESULTS: QTc was strongly related to age and gender, for all formulae except for QTcBZT for women. The relationship between QTc and age was significant regardless of whether the relationship was approximated by a linear or non-linear (quadratic or cubic spline) model. QTc increased more dramatically with age in men. There was a significant (P < 0.001) positive relationship between QTc variance and age for each QTc formula for both men and women. There were a greater proportion of individuals with longer QTc with older ages especially age 80 years and above. CONCLUSION: QTc and its variance increase with age. Prolonged QTc is more prevalent in older individuals, especially men.

Usefulness of the Atrial Emptying Fraction to Predict Maintenance of Sinus Rhythm After Direct Current Cardioversion for Atrial Fibrillation.

Atrial volumes indexed to body surface area (AVI) are robust predictors of nonvalvular atrial fibrillation (AF) recurrence after direct current cardioversion (DCCV). The incremental value of atrial emptying fraction (EmF) compared with atrial volumes as a predictor for recurrent AF after DCCV has not been evaluated. We sought to compare the predictive ability of baseline left atrial (LA) EmF, right atrial (RA) EmF, LAVI, and RAVI for post-DCCV AF recurrence at 6 months. The first 95 patients enrolled in the AF Clinic Registry with adequate echocardiogram imaging constituted the study cohort. Each patient underwent echocardiogram within 6 months before cardioversion. Maximal LAVI and RAVI, LA EmF, and RA EmF were performed offline using 4-chamber single-plane Simpson's method, averaged over 5 cycles. The mean age of the study cohort was 64 ± 12 years, and 67% were men. Only 28 patients (29%) who underwent DCCV remained in sinus rhythm at 6 months of follow-up. The remaining, 67 (71%) had reverted to AF or underwent ablation during the 6 months of follow-up. The overall performance for prediction of AF recurrence was greatest for RA EmF, area under the receiver operator characteristic curve (AUC): RA EmF 0.92, LA EmF 0.89, RAVI 0.76, and LAVI 0.63. RA and LA EmF AUCs were significantly higher than for LAVI or RAVI (max p = 0.02). In conclusion, although RAVI and LAVI are strong predictors of AF recurrence after DCCV, RA and LA EmF outperformed in this cohort.

A Crossover Design for Comparative Efficacy: A 36-Week Randomized Trial of Bevacizumab and Ranibizumab for Diabetic Macular Edema.

PURPOSE: To investigate the comparative efficacy of bevacizumab (Avastin) and ranibizumab (Lucentis; both Genentech, Inc, South San Francisco, CA) for diabetic macular edema (DME) using a crossover study design. DESIGN: Randomized, double-masked, 36-week, 3-period crossover clinical trial. PARTICIPANTS: Fifty-six subjects with DME involving the center of the macula in one or both eyes. METHODS: Monthly intravitreous injections of bevacizumab (1.25 mg) or ranibizumab (0.3 mg). MAIN OUTCOME MEASURES: Comparison of mean changes in visual acuity and central retinal thickness, tested using a linear mixed-effects model. RESULTS: Based on the linear mixed-effects model, the 3-month estimated mean improvement in visual acuity was 5.3 letters for bevacizumab and 6.6 letters for ranibizumab (difference, 1.3 letters; P = 0.039). Estimated change in optical coherence tomography (OCT) central subfield mean thickness (CSMT) was -89 µm for bevacizumab and -137 µm for ranibizumab (difference, 48 µm; P < 0.001). Incorporating cumulative treatment benefit, the model yielded a predicted 36-week (9-month) average improvement in visual acuity of 7.1 letters (95% confidence interval [CI], 5.0-9.2) for bevacizumab and 8.4 letters (95% CI, 6.3-10.5) for ranibizumab, and a change in OCT CSMT of -128 µm (95% CI, -155 to -100) for bevacizumab and -176 µm (95% CI, -202 to -149) for ranibizumab. There was no significant treatment-by-period interaction (i.e., treatment difference was constant in all 3 periods), nor was there a significant differential carryover effect from one period to the next. CONCLUSIONS: This trial demonstrated a statistically significant but small relative clinical benefit of ranibizumab compared with bevacizumab for treatment of DME, using a markedly reduced sample size relative to a full comparative efficacy study. The effects on visual acuity and central retinal thickness for the 2 drugs are consistent with those reported at 1 year for the concurrent parallel-group trial by the Diabetic Retinopathy Clinical Research Network testing bevacizumab, ranibizumab, and aflibercept for DME. The 3-period crossover design allowed for meaningful and efficient comparison, suggesting that this approach may be useful for future comparative efficacy studies of anti-vascular endothelial growth factor drugs for DME.

Impairments in Dark Adaptation Are Associated with Age-Related Macular Degeneration Severity and Reticular Pseudodrusen.

PURPOSE: We investigate whether ocular and person-based characteristics were associated with dark adaptation (DA). DESIGN: Cross-sectional, single-center, observational study. PARTICIPANTS: One hundred sixteen participants older than 50 years of age with a range of age-related macular degeneration (AMD) severity. METHODS: Participants underwent best-corrected visual acuity (BCVA) testing, ophthalmoscopic examination, and multimodal imaging. Presence of reticular pseudodrusen (RPD) was assessed by masked grading of fundus images and was confirmed with optical coherence tomography. Eyes also were graded for AMD features (drusen, pigmentary changes, late AMD) to generate person-based AMD severity groups. One eye was designated the study eye for DA testing. Nonparametric statistical testing was performed on all comparisons. MAIN OUTCOME MEASURES: The primary outcome of this study was the rod intercept time (RIT), which is defined as the time for a participant's visual sensitivity to recover to a stimulus intensity of 5×10(-3) cd/m(2) (a decrease of 3 log units), or until a maximum test duration of 40 minutes was reached. RESULTS: A total of 116 study eyes from 116 participants (mean age, 75.4±9.4 years; 58% female) were analyzed. Increased RIT was associated significantly with increasing AMD severity, increasing age (r = 0.34; P = 0.0002), decreasing BCVA (r = -0.54; P < 0.0001), pseudophakia (P = 0.03), and decreasing subfoveal choroidal thickness (r = -0.27; P = 0.003). Study eyes with RPD (15/116 [13%]) had a significantly greater mean RIT compared with eyes without RPD in any AMD severity group (P < 0.02 for all comparisons), with 80% reaching the DA test ceiling. CONCLUSIONS: Impairments in DA increased with age, worse visual acuity, presence of RPD, AMD severity, and decreased subfoveal choroidal thickness. Analysis of covariance found the multivariate model that best fit the data included age, AMD group, and presence of RPD (R(2) = 0.56), with the presence of RPD conferring the largest parameter estimate.

Impact of a Genomic Classifier of Metastatic Risk on Postprostatectomy Treatment Recommendations by Radiation Oncologists and Urologists.

OBJECTIVE: To evaluate how a genomic classifier (GC) that predicts the risk of metastasis after prostatectomy would impact adjuvant treatment recommendations made by radiation oncologists and urologists. The 2 specialties often disagree about postprostatectomy adjuvant treatment recommendations. MATERIALS AND METHODS: Twenty-six radiation oncologists and 20 urologists with genitourinary oncology expertise reviewed de-identified clinical results from 11 patients after radical prostatectomy and made adjuvant treatment recommendations. The same cases were later randomized and reassigned, and treatment recommendations were made using the clinical information and GC test results together. RESULTS: Using clinical information alone, observation was recommended in 42% of decisions made by urologists vs 23% by radiation oncologists (P < .0001). The GC test results altered 35% and 45% of treatment recommendations made by radiation oncologists and urologists, respectively. Multivariate analysis showed GC risk was the strongest factor influencing treatment recommendations by both specialties, with an adjusted odds ratio of 4.17 (95% confidence interval [CI], 2.26-7.70) and 6.51 (95% CI, 4.29-9.88) for radiation oncologists and urologists, respectively. GC results indicating high metastatic risk resulted in intensification of treatment, whereas low metastatic risk resulted in less aggressive recommendations. The GC results increased interdisciplinary agreement in treatment recommendations, as the odds of a recommendation for adjuvant treatment by urologists vs radiation oncologists increased from 0.27 (95% CI, 0.17-0.44) to 0.46 (95% CI, 0.29-0.75) after results of the GC test were available. CONCLUSION: The GC test significantly influenced adjuvant postprostatectomy treatment recommendations, reduced disagreement between radiation oncologists and urologists, and has the potential to enhance personalization of postprostatectomy care.

Longitudinal clinical findings and outcome among patients with Cryptococcus gattii infection in British Columbia.

BACKGROUND: Cryptococcus gattii (Cg) infection emerged in British Columbia in 1999. A longitudinal, clinical description of patients has not been reported. METHODS: Medical records were reviewed for Cg patients identified through surveillance (1999-2007). Risk factors for Cg mortality were explored using multivariate Cox regression; longitudinal patterns in serum cryptococcal antigen (SCrAg) titers and the probability of chest cryptococcomas over time were estimated using cubic B-splines in mixed-effects regression models. RESULTS: Among 152 patients, 111 (73.0%) were culture confirmed. Isolated lung infection was present in 105 (69.1%) patients; 47 (30.9%) had central nervous system infection, with or without lung involvement. Malignancy was the provisional diagnosis in 64 (42.1%) patients. Underlying diseases were present in 91 (59.9%) patients; 23 (15.1%) were immunocompromised, and 23 (15.1%) had asymptomatic disease. There were only 2 (1.8%) culture positive relapses, both within 12 months of follow-up. The estimated median time to resolution of lung cryptococcomas and decline in SCrAg titer to <1:8 was 2.8 and 2.9 years, respectively. Cg-related and all-cause mortality among culture-confirmed cases at 12 months' follow-up was 23.3% and 27.2%, respectively. Cg-related mortality was associated with age >50 years (hazard ratio [HR], 15.6; 95% confidence interval [CI], 1.9-130.5) and immunocompromise (HR, 5.8; CI, 1.5-21.6). All Cg-related mortality occurred among culture-positive cases within 1 year of diagnosis. CONCLUSIONS: Cryptococcomas and serum antigenemia were slow to resolve. However, late onset of failed therapy or relapse was uncommon, suggesting that delayed resolution of these findings does not require prolongation of treatment beyond that recommended by guidelines.

Best method for right atrial volume assessment by two-dimensional echocardiography: validation with magnetic resonance imaging.

AIM: Echocardiographic methods for estimating right atrial (RA) volume have not been standardized. Our aim was to evaluate two-dimensional (2D) echocardiographic methods of RA volume assessment, using RA volume by magnetic resonance imaging (MRI) as the reference. METHODS AND RESULTS: Right atrial volume was assessed in 51 patients (mean age 63 ± 14 years, 33 female) who underwent comprehensive 2D echocardiography and cardiac MRI for clinically indicated reasons. Echocardiographic RA volume methods included (1) biplane area length, using four-chamber view twice (biplane 4C-4C); (2) biplane area length, using four-chamber and subcostal views (biplane 4C-subcostal); and (3) single plane Simpson's method of disks (Simpson's). Echocardiographic RA volumes as well as linear RA major and minor dimensions were compared to RA volume by MRI using correlation and Bland-Altman methods, and evaluated for inter-observer reproducibility and accuracy in discriminating RA enlargement. All echocardiography volumetric methods performed well compared to MRI, with Pearson's correlation of 0.98 and concordance correlation ≥0.91 for each. For bias and limits of agreement, biplane 4C-4C (bias -4.81 mL/m(2) , limits of agreement ±9.8 mL/m(2) ) and Simpson's (bias -5.15 mL/m(2) , limits of agreement ±10.1 mL/m(2) ) outperformed biplane 4C-subcostal (bias -8.36 mL/m(2) , limits of agreement ±12.5 mL/m(2) ). Accuracy for discriminating RA enlargement was higher for all volumetric methods than for linear measurements. Inter-observer variability was satisfactory across all methods. CONCLUSIONS: Compared to MRI, biplane 4C-4C and single plane Simpson's are highly accurate and reproducible 2D echocardiography methods for estimating RA volume. Linear dimensions are inaccurate and should be abandoned.