Citations

Abstract Title: Real-world analysis of adverse events in patients with triple-negative breast cancer receiving therapy per KEYNOTE-522 Background: KEYNOTE-522 was a randomized, double-blind, placebo-controlled phase 3 trial which resulted in the FDA approval of pembrolizumab with neoadjuvant chemotherapy for patients (pts) with newly diagnosed, high-risk, early-stage triple-negative breast cancer (TNBC). Given the improvement in pathological complete response (pCR) and event-free survival rates, this regimen has emerged as standard-of-care (SOC) therapy. To date, real world outcome analyses are limited. Methods: In this retrospective, multicenter study, we examined pts with early-stage TNBC who received planned treatment per KEYNOTE-522 as SOC. 16 sites were included in the analysis. IRB approval was obtained from each participating site. Number and length of treatment delays, treatment related toxicities (both chemotherapy and immune-related) of all grades, and pCR rate were collected from the electronic medical record of each participating site, and deidentified data were shared for central analysis. Results: 577 pts were included in this analysis. The median age of the cohort was 52 [range 27-77]. 457 pts had T1-2 disease and 139 had T3-4 disease. 316 pts had N0 disease and 261 had N1-3 disease. 506 pts had baseline ECOG 0, 62 had ECOG 1, and 9 had ECOG 2-3. Of the 482 patients who had surgery at the time of this analysis, 219 patients had pCR (54.5%) and 192 pts were still receiving treatment. 217 patients (37%) had an adverse drug event (ADE) causing dose reductions and 228 patients (39.5%) had to discontinue treatment early. There were 360 unplanned care visits, with 91 patients having 2+ visits. 66 patients had hospitalizations due to the regimen with 102 total hospitalizations. 179 (31%) of patients had grade 3+ immune related adverse events (irAEs), including many that are rare and potentially serious. 317 (54%) had an immune related adverse effect (see Table 1). There was no significant difference in the frequency of grade 3+ irAE based on age or body mass index. We observed no difference in residual disease between patients who discontinued treatment early and those who did not. However, if patients had an ADR causing a dose reduction, pts were significantly more likely to have residual disease (P=0.039) Conclusions: In a multicenter real-world analysis, the KEYNOTE-522 regimen was associated with a high frequency of dose reductions, early treatment discontinuations, ER visits, and hospitalizations. This may have accounted for a lower pCR rate than observed in the landmark clinical trial. Most grade 3+ irAEs occurred at greater frequency in our real-world analysis. Providers should carefully monitor for toxicity to ensure optimal patient outcomes. Table 1 Citation Format: Mara Hofherr, Katherine Clifton, Spenser January, Emily Owen, Farah Raheem, Lida A. Mina, Suganya Arunachalam Karikalan, Lauren Lyons, Meredith Watson Rose, Katherine Madden, Jerline Hsin, Aimee Keegan, Wai Yu, Shawna Kraft, Allison Schepers, Emily Armgardt, Douglas Mazewski, Alison Svoboda, Kayla Harwood, Jodi Taraba, Yonatan Resnick, Shelly Hummert, Lisa Grate, Sidney Keisner, Jacob Hobbs, Todd Davis, Kristin Bastian, Dawn Minikel, Traci White, William Adler, Avneek Singh Sandu, Fouad Boulbol, Kelsey Finch, Andrew Davis. Real-World Analysis of Adverse Events in Patients with Triple Negative Breast Cancer Receiving Therapy per KEYNOTE-522 [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS14-06.

INTRODUCTION: Despite research efforts, predicting Clostridioides difficile incidence and its outcomes remains challenging. The aim of this systematic review was to evaluate the performance of machine learning (ML) models in predicting C. difficile infection (CDI) incidence and complications using clinical data from electronic health records. METHODS: We conducted a comprehensive search of databases (OVID, Embase, MEDLINE ALL, Web of Science, and Scopus) from inception up to September 2023. Studies employing ML techniques for predicting CDI or its complications were included. The primary outcome was the type and performance of ML models assessed using the area under the receiver operating characteristic curve. RESULTS: Twelve retrospective studies that evaluated CDI incidence and/or outcomes were included. The most commonly used ML models were random forest and gradient boosting. The area under the receiver operating characteristic curve ranged from 0.60 to 0.81 for predicting CDI incidence, 0.59 to 0.80 for recurrence, and 0.64 to 0.88 for predicting complications. Advanced ML models demonstrated similar performance to traditional logistic regression. However, there was notable heterogeneity in defining CDI and the different outcomes, including incidence, recurrence, and complications, and a lack of external validation in most studies. DISCUSSION: ML models show promise in predicting CDI incidence and outcomes. However, the observed heterogeneity in CDI definitions and the lack of real-world validation highlight challenges in clinical implementation. Future research should focus on external validation and the use of standardized definitions across studies.

AbstractIntroductionVentricular tachycardia storm or electrical storm (ES) is a common complication following left ventricular assist device (LVAD) implantation. The factors contributing to ES and outcomes are less studied. The study aimed to determine the factors associated with ES and the probability of survival in patients undergoing LVAD in three tertiary centers over a span of 15 years.MethodsWe performed a retrospective cohort study on all patients who underwent LVAD implantation at the Mayo Clinic (Rochester, Phoenix, and Jacksonville) from January 1, 2006 to December 31, 2020. ES was defined as ≥3 episodes of sustained ventricular tachycardia over a period of 24 h with no identifiable reversible cause. Detailed chart reviews of the electronic health records within the Mayo Clinic and outside medical records were performed.ResultsA total of 883 patients who underwent LVAD implantation were included in our study. ES occurred in 7% (n = 61) of patients with a median of 13 days (interquartile range [IQR]: 5–297 days) following surgery. We found 57% of patients (n = 35) developed ES within 30 days, while 43% (n = 26) patients developed ES at a median of 545 (IQR 152–1032) days after surgery. Following ES, 26% of patients died within 1 year. Patients with ES had a significant association with a history of ventricular arrhythmias and implantable cardioverter defibrillator (ICD) shocks before the procedure. ES was significantly associated with reduced survival compared to patients without ES (hazards ratio [HR]: 1.92, 95% CI: 1.39–2.64, p < .001).ConclusionFollowing LVAD implantation, the rate of ES was 7% with majority of ES occurring within 30 days of LVAD. Risk factors for ES included pre‐implant history of ventricular arrhythmias and ICD shock. ES was significantly associated with reduced survival compared to patients without ES.

Background: Increased sympathetic drive resulting in decreased heart rate variability (HRV), has been linked to cardiovascular diseases such as heart failure and myocardial infarction (MI). Dynamic electrophysiological changes due to acute ischemia and chronic MI are known to be pro-arrhythmic. Objective: Evaluate the changes in autonomic tone resulting from substrate remodeling during the development of chronic MI in an in-vivo ovine model. Methods: ECG recordings were collected at baseline, post occlusion and 6 weeks post MI, in young adult sheep (n=16). Time domain, frequency domain and non-linear measures of HRV were evaluated from 10 minutes of ECG data at the 3 time points. RR interval, heart rate, SDRR (standard deviation of the RR intervals), RMSSD (root mean square of successive differences between normal heartbeats), QTc interval, pNN 50 , LF/HF ratio and SD1/SD2 ratio were calculated and compared between baseline, post acute coronary artery occlusion and after 6 weeks of chronic MI. 24-hour telemetry was also performed in an ambulatory animal for 6 weeks to monitor the progression of alterations in the T-wave morphology or duration, i.e. T-wave alternans, a known marker of ventricular tachyarrhythmias, with chronic MI. Results: Chronic MI led to significantly decreased RR interval (Fig.1A) and increased heart rate (Fig.1B), along with a significant prolongation of the QTc interval (Fig.1C). Significant rise was also observed in the SDRR (Fig1D) and LF/HF ratio (Fig1E) indicating a shift towards increased sympathetic tone and reduced parasympathetic drive. In addition to the autonomic changes, a significant rise in T-wave alternans burden (Fig1F) and localized action potential alternans inducibility was observed with progression of MI indicating increased arrhythmogenicity. Conclusion: Skewed autonomic balance is evident in chronic MI and may be closely linked to increased arrhythmogenicity.

Endocrine therapy is the main treatment for hormone receptor-positive (HR+) breast cancer. However, advanced tumors develop resistance to endocrine therapy, rendering it ineffective as the disease progresses. There are several molecular mechanisms of primary and secondary endocrine resistance. Resistance can develop due to either alteration of the estrogen receptor pathway (e.g., ESR1 mutations) or upstream growth factors signaling pathways (e.g., PI3K/Akt/mTOR pathway). Despite progress in the development of molecularly targeted anticancer therapies, the emergence of resistance remains a major limitation and an area of unmet need. In this article, we review the mechanisms of acquired endocrine resistance in HR+ advanced breast cancer and discuss current and future investigational therapeutic approaches.

The interplay between neurology and cardiology has gained significant attention in recent years, particularly regarding the shared pathophysiological mechanisms and clinical comorbidities observed in epilepsy and arrhythmias. Neuro-cardiac electrophysiology mapping involves the comprehensive assessment of both neural and cardiac electrical activity, aiming to unravel the intricate connections and potential cross-talk between the brain and the heart. The emergence of artificial intelligence (AI) has revolutionized the field by enabling the analysis of large-scale data sets, complex signal processing, and predictive modeling. AI algorithms have been applied to neuroimaging, electroencephalography (EEG), electrocardiography (ECG), and other diagnostic modalities to identify subtle patterns, classify disease subtypes, predict outcomes, and guide personalized treatment strategies. In this review, we highlight the potential clinical implications of neuro-cardiac mapping and AI in the management of epilepsy and arrhythmias. We address the challenges and limitations associated with these approaches, including data quality, interpretability, and ethical considerations. Further research and collaboration between neurologists, cardiologists, and AI experts are needed to fully unlock the potential of this interdisciplinary field.

AbstractNanoparticles form long‐range micropatterns via self‐assembly or directed self‐assembly with superior mechanical, electrical, optical, magnetic, chemical, and other functional properties for broad applications, such as structural supports, thermal exchangers, optoelectronics, microelectronics, and robotics. The precisely defined particle assembly at the nanoscale with simultaneously scalable patterning at the microscale is indispensable for enabling functionality and improving the performance of devices. This article provides a comprehensive review of nanoparticle assembly formed primarily via the balance of forces at the nanoscale (e.g., van der Waals, colloidal, capillary, convection, and chemical forces) and nanoparticle‐template interactions (e.g., physical confinement, chemical functionalization, additive layer‐upon‐layer). The review commences with a general overview of nanoparticle self‐assembly, with the state‐of‐the‐art literature review and motivation. It subsequently reviews the recent progress in nanoparticle assembly without the presence of surface templates. Manufacturing techniques for surface template fabrication and their influence on nanoparticle assembly efficiency and effectiveness are then explored. The primary focus is the spatial organization and orientational preference of nanoparticles on non‐templated and pre‐templated surfaces in a controlled manner. Moreover, the article discusses broad applications of micropatterned surfaces, encompassing various fields. Finally, the review concludes with a summary of manufacturing methods, their limitations, and future trends in nanoparticle assembly.