Citations

e18802 Background: CUP is a rare cancer with an incidence of 7–12 cases per 100,000/year. CUP is defined as metastatic cancer with no identifiable primary tumor despite comprehensive evaluation. Despite its heterogeneous clinicopathological presentation, the treatment of CUP has primarily been with platinum-based combination chemotherapies but results are poor and survival is short. Here, we describe survival outcomes in real-world dataset of patients with CUP seen at a tertiary referral center. Methods: Retrospective study of patients treated at Mayo Clinic, Rochester MN, from 2010 to 2021. Survival probabilities were estimated with the Kaplan-Meier method. We used Cox proportional hazard regression with forward modeling to explore the association between each variable and death. Overall survival (OS) analysis was conducted in the entire cohort, and it was stratified by histological subtype. For the hypothesis test, we considered p < 0.05 to be statistically significant; all tests were two-sided. All data were analyzed by the SPSS version 22.0 software (SPSS, Chicago, IL, United States). Results: From a total of 214 patients, 198 patients were included in the survival analysis. The patients were predominantly white (87%), female (50.2%), with a mean age of 63 (SD: 13) without history of smoking (51%). The predominant histology was adenocarcinoma (30%), followed by neuroendocrine neoplasms (NEN) (27%), carcinoma NOS (25%), squamous cell carcinoma (SCC) (10%) and non-classifiable tumors (7%). The median follow-up time was 23 months, and medial OS was 23 months in the entire cohort. OS by histology was as follows: 51 months for NEN, 34 months for SCC, 18 months for carcinomas NOS and 11 months for adenocarcinomas (p < 0.001) (fig.1). Similar OS trends were observed when we restricted the analysis to poorly differentiated tumors. The 3- and 5-year cumulative survival by histology were as follows: 7% and 0% for adenocarcinoma, 25% and 8% for carcinoma NOS, 39% and 17% for SCC, and 56% and 22% for NEN. In Cox regression models we did not identify any prognostic factors among patients with adenocarcinoma. Conclusions: Patients with adenocarcinoma of unknown primary possess a considerable challenge and the OS is short. CUP of other histologies have higher OS. This study highlights the need of accurate tumor identification and better treatment, perhaps as a multiomics therapeutic approach.

Importance Scoring systems for Stevens-Johnson syndrome and epidermal necrolysis (EN) only estimate patient prognosis and are weighted toward comorbidities and systemic features; morphologic terminology for EN lesions is inconsistent. Objectives To establish consensus among expert dermatologists on EN terminology, morphologic progression, and most-affected sites, and to build a framework for developing a skin-directed scoring system for EN. Evidence Review A Delphi consensus using the RAND/UCLA appropriateness criteria was initiated with a core group from the Society of Dermatology Hospitalists to establish agreement on the optimal design for an EN cutaneous scoring instrument, terminology, morphologic traits, and sites of involvement. Findings In round 1, the 54 participating dermatology hospitalists reached consensus on all 49 statements (30 appropriate, 3 inappropriate, 16 uncertain). In round 2, they agreed on another 15 statements (8 appropriate, 7 uncertain). There was consistent agreement on the need for a skin-specific instrument; on the most-often affected skin sites (head and neck, chest, upper back, ocular mucosa, oral mucosa); and that blanching erythema, dusky erythema, targetoid erythema, vesicles/bullae, desquamation, and erosions comprise the morphologic traits of EN and can be consistently differentiated. Conclusions and Relevance This consensus exercise confirmed the need for an EN skin-directed scoring system, nomenclature, and differentiation of specific morphologic traits, and identified the sites most affected. It also established a baseline consensus for a standardized EN instrument with consistent terminology.

Abstract Remote monitoring is beneficial for the management of patients with cardiovascular implantable electronic devices by impacting morbidity and mortality. With increasing numbers of patients using remote monitoring, keeping up with higher volume of remote monitoring transmissions creates challenges for device clinic staff. This international multidisciplinary document is intended to guide cardiac electrophysiologists, allied professionals, and hospital administrators in managing remote monitoring clinics. This includes guidance for remote monitoring clinic staffing, appropriate clinic workflows, patient education, and alert management. This expert consensus statement also addresses other topics such as communication of transmission results, use of third-party resources, manufacturer responsibilities, and programming concerns. The goal is to provide evidence-based recommendations impacting all aspects of remote monitoring services. Gaps in current knowledge and guidance for future research directions are also identified.

AbstractRemote monitoring is beneficial for the management of patients with cardiovascular implantable electronic devices by impacting morbidity and mortality. With increasing numbers of patients using remote monitoring, keeping up with higher volume of remote monitoring transmissions creates challenges for device clinic staff. This international multidisciplinary document is intended to guide cardiac electrophysiologists, allied professionals, and hospital administrators in managing remote monitoring clinics. This includes guidance for remote monitoring clinic staffing, appropriate clinic workflows, patient education, and alert management. This expert consensus statement also addresses other topics such as communication of transmission results, use of third‐party resources, manufacturer responsibilities, and programming concerns. The goal is to provide evidence‐based recommendations impacting all aspects of remote monitoring services. Gaps in current knowledge and guidance for future research directions are also identified.

Purpose Identifying actionable oncogenic mutations have changed the therapeutic landscape in different types of tumors. This study investigated the utility of comprehensive genomic profiling (CGP), a hybrid capture-based next-generation sequencing (NGS) assay, in clinical practice in a developing country. Methods In this retrospective cohort study, CGP was performed on clinical samples from patients with different solid tumors recruited between December 2016 and November 2020, using hybrid capture-based genomic profiling, at the individual treating physicians’ request in the clinical care for therapy decisions. Kaplan–Meier survival curves were estimated to characterize the time-to-event variables. Results Patients median age was 61 years (range: 14–87 years), and 64.7% were female. The most common histological diagnosis was lung primary tumors, with 90 patients corresponding to 52.9% of the samples (95% CI 45.4-60.4%). Actionable mutations with FDA-approved medications for specific alterations correspondent to tumoral histology were identified in 58 cases (46.4%), whereas other alterations were detected in 47 different samples (37.6%). The median overall survival was 15.5 months (95% CI 11.7 months-NR). Patients who were subjected to genomic evaluation at diagnosis reached a median overall survival of 18.3 months (95% CI 14.9 months-NR) compared to 14.1 months (95% CI 11.1 months-NR) in patients who obtained genomic evaluation after tumor progression and during standard treatment ( P = .7). Conclusion CGP of different types of tumors identifies clinically relevant genomic alterations that have benefited from targeted therapy and improve cancer care in a developing country to guide personalized treatment to beneficial outcomes of cancer patients.

Pain assessment is a complex task largely dependent on the patient’s self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI in clinical settings are still largely unknown to many medical professionals. In this literature review, we present a conceptual understanding of the application of AI to detect pain through facial expressions. We provide an overview of the current state of the art as well as the technical foundations of AI/ML techniques used in pain detection. We highlight the ethical challenges and the limitations associated with the use of AI in pain detection, such as the scarcity of databases, confounding factors, and medical conditions that affect the shape and mobility of the face. The review also highlights the potential impact of AI on pain assessment in clinical practice and lays the groundwork for further study in this area.

Introduction EXCELLENT (NCT03685578; Cerenovus) is a large, prospective, international, real‐world registry of endovascular clot removal in acute ischemic stroke (AIS) with EmboTrap as the first line mechanical thrombectomy (MT) device, which included collection and analysis of the retrieved thrombus material. Methods Between September 2018 and March 2021, 1000 “all‐comer” patients were enrolled at 34 global sites (27 US, 5 EU, 1 UK, 1 Israel) and treated according to standard of care at each center (with Embrotrap as first line). The study employed blind endpoint evaluation, including a core imaging lab and an independent 90‐day mRS assessment. Retrieved clot was collected per each MT maneuver from 538 subjects across 26 sites and clot analysis was performed by independent central labs blinded to clinical data. Results mITT population included 998 subjects. Mean age was 69.9±14.18 years (range 18–102), 51.8% (517/998) subjects were female and 9.9% (97/997) had a pre‐stroke mRS 3–5. Baseline NIHSS was 15.6±6.87 (range 0–36); 10.1% (82/815) subjects had a large core (ASPECTS 0–5); 5.8% (57/990) had posterior stroke; 56.3% (523/929) underwent MT ≤ 6hrs of onset and 38.1% (380/998) received IV‐tPA prior to MT. First pass eTICI 2c‐3 was achieved in 38.3% (377/984) and final 2b‐3 in 94.5 % (930/984; median number of passes = 1) of subjects. 90‐day mRS≤2 or ≤pre‐stroke was 46.9% (429/915) and 90‐day all‐cause mortality was 19.0% (175/921). The univariate analysis of clot components showed high red blood cell and low platelet content were significant predictors of good mRS outcome (p < 0.001 and 0.009) and negative predictors of 90‐day mortality (p < 0.001 and 0.017, respectively). Conclusions This large multi‐center, all‐comer cohort reflects the population undergoing thrombectomy today in a real world‐setting. Final angiographic, clinical and thrombus composition results, along with multivariate analysis of predictors of clinical outcomes, will be presented at the time of the conference.

Abstract Objectives Disease flares in the post–coronavirus disease 2019 (COVID-19) vaccination period represent a prominent concern, though risk factors are poorly understood. We studied these flares among patients with idiopathic inflammatory myopathies (IIMs) and other autoimmune rheumatic diseases (AIRDs). Methods The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with &gt;7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models. Results Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7–235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P &lt; 0.001) were associated with disparity between self-reported and IS-denoted flares. Conclusion A diagnosis of IIMs confers an equal risk of flares in the post–COVID-19 vaccination period to AIRDs, with active disease, female gender and comorbidities conferring a higher risk. Disparity between patient- and physician-reported outcomes represents a future avenue for exploration.

Pain is a complex and subjective experience, and traditional methods of pain assessment can be limited by factors such as self-report bias and observer variability. Voice is frequently used to evaluate pain, occasionally in conjunction with other behaviors such as facial gestures. Compared to facial emotions, there is less available evidence linking pain with voice. This literature review synthesizes the current state of research on the use of voice recognition and voice analysis for pain detection in adults, with a specific focus on the role of artificial intelligence (AI) and machine learning (ML) techniques. We describe the previous works on pain recognition using voice and highlight the different approaches to voice as a tool for pain detection, such as a human effect or biosignal. Overall, studies have shown that AI-based voice analysis can be an effective tool for pain detection in adult patients with various types of pain, including chronic and acute pain. We highlight the high accuracy of the ML-based approaches used in studies and their limitations in terms of generalizability due to factors such as the nature of the pain and patient population characteristics. However, there are still potential challenges, such as the need for large datasets and the risk of bias in training models, which warrant further research.

Abstract Purpose: This global phase I trial investigated the safety, efficacy, pharmacokinetics, and pharmacodynamics of lisaftoclax (APG-2575), a novel, orally active, potent selective B-cell lymphoma 2 (BCL-2) inhibitor, in patients with relapsed or refractory chronic lymphocytic leukemia or small lymphocytic lymphoma (R/R CLL/SLL) and other hematologic malignancies (HMs). Patients and Methods: Maximum tolerated dose (MTD) and recommended phase II dose were evaluated. Outcome measures were safety and tolerability (primary) and pharmacokinetic variables and antitumor effects (secondary). Pharmacodynamics in patient tumor cells were explored. Results: Among 52 patients receiving lisaftoclax, MTD was not reached. Treatment-emergent adverse events (TEAEs) included diarrhea (48.1%), fatigue (34.6%), nausea (30.8%), anemia and thrombocytopenia (28.8% each), neutropenia (26.9%), constipation (25.0%), vomiting (23.1%), headache (21.2%), peripheral edema and hypokalemia (17.3% each), and arthralgia (15.4%). Grade ≥ 3 hematologic TEAEs included neutropenia (21.2%), thrombocytopenia (13.5%), and anemia (9.6%), none resulting in treatment discontinuation. Clinical pharmacokinetic and pharmacodynamic results demonstrated that lisaftoclax had a limited plasma residence and systemic exposure and elicited rapid clearance of malignant cells. With a median treatment of 15 (range, 6–43) cycles, 14 of 22 efficacy-evaluable patients with R/R CLL/SLL experienced partial responses, for an objective response rate of 63.6% and median time to response of 2 (range, 2–8) cycles. Conclusions: Lisaftoclax was well tolerated, with no evidence of tumor lysis syndrome. Dose-limiting toxicity was not reached at the highest dose level. Lisaftoclax has a unique pharmacokinetic profile compatible with a potentially more convenient daily (vs. weekly) dose ramp-up schedule and induced rapid clinical responses in patients with CLL/SLL, warranting continued clinical investigation.