Citations

Abstract Background The efficacy and safety of collagenase Clostridium histolyticum (CCH) have been demonstrated in the treatment of men with Peyronie’s disease (PD); however, the pivotal clinical trials excluded men with ventral penile curvature. Aim The study sought to evaluate outcomes of CCH treatment in men with ventral curvatures secondary to PD. Methods Men with PD treated with CCH were identified from a prospective database. Patients received up to 4 series of CCH injections using a progressively modified protocol over time. Results were compared between those with baseline ventral vs nonventral penile curvatures. Outcomes Changes in penile curvature, Peyronie’s Disease Questionnaire scores, International Index of Erectile Function scores, nonstandardized assessments, and adverse events. Results A total of 560 men with PD (85 ventral curvature, 475 nonventral curvature) were included in the analysis. Baseline median curvature was 60.0° (interquartile range, 48.8°-75.0°) in the ventral cohort and 65.0° (interquartile range, 45.0°-80.0°) in the nonventral cohort. Median change from baseline penile curvature was −25.0° in the ventral cohort vs −24.0° in the nonventral cohort (P = .08, between-group comparison), which corresponded to curvature reductions of 44.7% and 33.6%, respectively (P = .03). In the subset of patients who completed CCH treatment (ie, received 8 injections or discontinued early because of patient satisfaction with curvature reduction), median change from baseline was −35.0° in the ventral cohort vs −25.0° in the nonventral cohort (P < .05); median percent improvement was 48.3% and 37.5%, respectively (P = .11). Median change from baseline in Peyronie’s Disease Questionnaire and International Index of Erectile Function domain scores and adverse events were similar between cohorts, with the exception of possibly higher hematoma rates in the nonventral group (50% vs 37%; P = .05). No urethral injuries were sustained in either cohort. Clinical Implications Data support the use of CCH for the treatment of ventral as well as nonventral penile curvatures in men with PD. Strengths and Limitations Study strengths are the inclusion of a general clinical population of men with PD, the prospective design, and the relatively large series of men with ventral curvature. Limitations include the single-center and observational nature of the study. Conclusion CCH was safe and effective in the treatment of both ventral and nonventral penile curvatures in men with PD.

AbstractPurpose has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging–Dynamic Contrast‐Enhanced (OSIPI‐DCE) challenge was designed to benchmark methods to better help the efforts to standardize measurement.MethodsA framework was created to evaluate values produced by DCE‐MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' values, the applied software, and a standard operating procedure. These were evaluated using the proposed score defined with accuracy, repeatability, and reproducibility components.ResultsAcross the 10 received submissions, the score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0–1 = lowest–highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility.ConclusionsThis study reports results from the OSIPI‐DCE challenge and highlights the high inter‐software variability within estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real‐world clinical setting, many of these tools may perform differently with different benchmarking methodology.

Introduction: A single assessment of the SCAI shock classification robustly predicts mortality, and a repeat assessment may improve prognostication. Hypothesis: We hypothesized that frequent serial assignment of the SCAI shock stage could further improve risk stratification. Methods: Unique AHA Level 1 cardiac intensive care unit (CICU) admissions at a single center from 2015 to 2018 were reviewed retrospectively. Time-stamped electronic health record data were used to assign the SCAI shock stage in each 4-hour block during the first 24 hours of CICU admission. Shock was defined as SCAI shock stage C, D, or E. In-hospital mortality was evaluated using logistic regression. Results: Among 2,918 CICU patients, 1,537 (52.7%) met criteria for shock during >=1 block and 266 (9.1%) died in hospital. The SCAI shock stage on admission was: A, 37.6%; B, 31.5%; C, 25.9%; D, 1.8%; E, 3.3%. Patients with worsening SCAI shock stage after admission (first 4 hours) were at higher risk of mortality ( Figure A ), as were patients who met SCAI criteria for shock (particularly those with shock on admission, Figure B ). The pattern was consistent in patients with acute coronary syndromes, heart failure, or cardiac arrest (who had very high mortality). Each higher admission (aOR 1.36, 95% CI 1.18-1.56, AUC 0.70), maximum (aOR 1.59, 95% CI 1.37-1.85, AUC 0.73) and 24 hour mean (aOR 2.42, 95% CI 1.99-2.95, AUC 0.78) SCAI shock stage were incrementally associated with increasing in-hospital mortality. Discrimination was highest for the mean SCAI shock stage (p <0.05). Each additional 4 hour block meeting SCAI criteria for shock was associated with higher mortality (aOR 1.15, 95% CI 1.07-1.24). Conclusions: Dynamic assessment of shock using serial SCAI shock classification assignment can improve mortality risk stratification in CICU patients. Cumulative time in shock was a strong mortality risk indicator, highlighting the area under the curve of shock severity as an important determinant of outcomes.

Introduction: Poor sleep contributes to outcomes in heart failure (HF). Phenotypes reflecting multi-dimensional sleep health may better predict outcomes and support more precise interventions than single measures, but few studies have used this approach. Aims: 1) Describe phenotypes of sleep health and 2) Evaluate whether sleep health phenotypes predict symptoms, cognitive function, and time to first hospitalization and emergency department (ED) visits among HF patients. Methods: We performed secondary analysis of a randomized controlled trial of cognitive behavioral therapy for insomnia compared with HF self-management education with HF patients. We measured sleep [rest-activity rhythms, sleep duration, and efficiency (2-week wrist actigraphy/follow-ups); insomnia; CPAP use; and daytime sleepiness (Epworth Scale)]; perceived stress; fatigue; anxiety; depression; pain; and cognitive ability (Patient-Reported Outcomes Measurement System: PROMIS) at baseline and 3, 6, and 12 months post-intervention and tracked hospitalizations and ED visits. We used K-means clustering to identify sleep phenotypes and generalized linear mixed models and Cox models to predict outcomes, adjusted for demographic factors. Results: Among 166 participants (M age = 63.2 (SD = 12.8) years; 57% female; 23% NYHA Class 3/4 HF; 35% EF less than 45%), there were 4 phenotypes [poor sleep (14%); short sleep/high sleep efficiency (39%); long sleep/low sleep efficiency (25%); and healthy sleep (21%)] at baseline. The healthy sleep group was older and had lower BMIs and less comorbidity and had better outcomes compared to all other phenotypes. In particular, this group had better fatigue (-2.43±0.87), pain (-1.86±1.05), anxiety (-1.50±0.89), stress (-1.46±0.69), and cognitive ability (1.76±0.80) than the poor sleep group. The poor sleep group had shorter time to adverse events compared to the other phenotypes (Hazard ratios of 0.41 to 0.56 for hospitalizations and 0.35 to 0.60 for ED visits). Conclusions: Multidimensional aspects of sleep predict HF outcomes and may improve on prediction with single measures. Future tailored sleep interventions focused on phenotypes may more precisely improve outcomes among HF patients than traditional approaches.

Abstract Purpose: The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial. Patients and Methods: I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy “graduates” if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction. Results: There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%–99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease. Conclusions: The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority &gt;90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted.

Mucin-1 (MUC1) is a highly relevant antigen for cancer vaccination due to its overexpression and hypo-glycosylation in a high percentage of carcinomas. To enhance the immune response to MUC1, our group has developed C3-liposomes that encapsulate the MUC1 antigen along with immunostimulatory compounds for direct delivery to antigen-presenting cells (APCs). C3-liposomes bind complement C3, which interacts with C3-receptors on APCs, resulting in liposomal uptake and the delivery of tumor antigens to APCs in a manner that mimics pathogenic uptake. In this study, MUC1 and Toll-like receptor (TLR) agonists were encapsulated in C3-liposomes to provoke an immune response in transgenic mice tolerant to MUC1. The immune response to the C3-bound MUC1 liposomal vaccine was assessed by ELISA, ELISpot, and flow cytometry. Co-administering TLR 7/8 agonists with MUC1 encapsulated in C3-liposomes resulted in a significant antibody response compared to non-encapsulated MUC1. This antibody response was significantly higher in females than in males. The co-encapsulation of three TLR agonists with MUC1 in C3-liposomes significantly increased antibody responses and eliminated sex-based differences. Furthermore, this immunization strategy resulted in a significantly increased T cell-response compared to other treatment groups. In conclusion, the co-delivery of MUC1 and TLR agonists via C3-liposomes greatly enhances the immune response to MUC1, highlighting its potential for antigen-specific cancer immunotherapy.