Citations

Abstract Rural and low-socioeconomic status women face social determinants of health barriers leading to disproportionately low rates of breast cancer screening and markedly reduced participation in clinical trials. To address this gap, we developed the WeCARE (Women’s Engagement for Cancer Awareness, Resources, and Education) intervention using a community-engaged approach. This paper describes how Community Advisory Board feedback informed the development of Mayo Clinic Health System’s WeCARE intervention components. Their input was systematically analyzed using the Consolidated Framework for Implementation Research (CFIR 2.0) to identify determinants of acceptability, appropriateness, and feasibility and to guide actionable refinements to intervention content and delivery.

Background Surgeons face elevated risks of musculoskeletal disorders due to prolonged operating times, awkward postures, and repetitive tasks, which can impair performance and well-being. Microbreaks have emerged as a potential ergonomic intervention to reduce discomfort and fatigue during surgery. Objective The main goal of this study was to investigate and compare the intraoperative usability and effectiveness of two break scheduling strategies using the OR-Stretch TM Web-App. Furthermore, surgeons’ feedback on the primary barriers to implementation of the OR-Stretch Web-App was recorded. Methods This study used a randomized, within-subjects crossover design. Fourteen surgeons (eight females) performed three surgical procedures with the following microbreak schedules; (1) microbreaks every 30 min with an optional ten-minute snooze (Break-30), (2) microbreaks every 60 min with an optional ten-minute snooze (Break-60), or (3) no microbreaks (Baseline). Outcomes were measured using self-reported subjective surveys (e.g., discomfort, fatigue, workload, and usability). Results Surgeons found both Break-30 and Break-60 conditions aided physical performance, mental focus, body pain/discomfort, and level of fatigue (self-reported improvement between 28.6% and 78.6%). No significant differences were observed in surgeons’ subjective evaluations of the Break-30 and Break-60 conditions; however, the data suggest that Break-60 is preferable to the Break-30 condition. Conclusions This study provides evidence supporting the OR-Stretch Web-App as a potential surgical ergonomic intervention. However, enhancing the Web-App's user-friendliness and developing strategies to synchronize microbreaks with appropriate times during surgeries, to avoid disrupting the surgical workflow, are critical areas for future studies.

Abstract Rationale Chronic bronchitis (CB), a common phenotype of chronic obstructive pulmonary disease (COPD), is characterized by pathologic mucus hypersecretion and is associated with substantial morbidity, impaired quality of life, and progressive functional decline, with prior studies demonstrating an average worsening of approximately one point/year on the COPD Assessment Test (CAT). Bronchial rheoplasty (BR) with RheOx® combines mechanical mucous plug disimpaction with pulsed electric field (PEF) energy to ablate and restore the airway mucosa. The RheSolve study was designed to provide evidence of safety and efficacy versus mechanical disimpaction alone. Primary endpoint results have been previously reported; final 2-year outcomes are reported here. Methods RheSolve was a prospective, randomized, double-blind study enrolling 273 patients with COPD and moderate-to-severe CB across 37 centers in the United States and Europe. Participants were randomized 2:1 to BR (n = 185) or a mechanical control procedure (n = 88). Following unblinding at 12 months, 75% of control patients crossed over to BR, precluding valid randomized comparisons beyond that time point; therefore, longer-term outcomes were evaluated using within-patient changes from baseline in the BR cohort. Outcomes included CAT, St George’s Respiratory Questionnaire (SGRQ), Cough and Sputum Assessment Questionnaire (CASA-Q), and pulmonary function tests (PFTs). Results Patients in the BR group represented a moderate to severe COPD CB phenotype at baseline (FEV1 60.9% predicted, emphysema (-950 HU) 11.0%, CAT 27.2 points, SGRQ 64.4) with most patients (93%) receiving a combination of ≥ 2 long-acting medications (LABA, LAMA, inhaled corticosteroids). The BR procedure was well-tolerated with no SAEs related to the device or procedure beyond 12 months. Both groups demonstrated clinically meaningful improvements in CAT, SGRQ, and CASA-Q at 12 months (P < 0.001), which were sustained in the BR group through 24 months. Follow-up was limited to 1 year in the mechanical control group, with outcomes demonstrating a modest regression towards baseline at 12 months (Figure). PFTs were also stable to improved in the BR group (changes from baseline to 24 months: FEV1 % Predicted 0.9 (±10.8) P = 0.319, FVC % Predicted 2.8% (±14.0) P = 0.02, FEV1/FVC -0.5% (±7.2) P = 0.449). Conclusions BR with RheOx® (e.g.,mechanical mucous plug disimpaction and PEF delivery) demonstrated clinically meaningful symptom improvement that was sustained through 24 months supporting BR as a therapeutic option for patients with persistent symptoms despite appropriate medical therapy. This abstract is funded by: Galvanize Therapeutics

Context: Early palliative care can improve end-of-life outcomes, but referrals to palliative care specialists can be delayed in the primary care setting. Objective: This pilot study assessed the effect of a machine-learning algorithm on time to palliative care in a primary care population. Methods: Patients (aged ≥18 years) were eligible if they were empaneled with a primary care provider (PCP) from July 20, 2020, through May 30, 2021. The algorithm evaluated their health records and presented patients who were predicted to have the greatest need for palliative care. Records were then reviewed by palliative care specialists, and patients were randomized in a stepped-wedge fashion to have a referral notification sent to their PCPs if unmet palliative care needs were verified. Time-to-event outcomes were evaluated with Poisson regression models. Results: Of the 127,080 patients evaluated, 934 had their health records presented for review. Some patients were repeatedly presented by the algorithm (total presentations: 1592). In the intervention arm, PCPs were prompted to order a palliative care consultation for 142 patients. The time to 0.1% of the population receiving a palliative care consultation was 60.9 days for the intervention arm versus 71.8 days for the control arm (probability of a shorter time with the intervention, 0.88). Conclusion: A machine-learning algorithm to identify palliative care needs was successfully integrated into a primary care practice. More work is needed to improve the workflow.

Abstract Spatial transcriptomics has been widely applied to study the spatial distribution of cell types, cell states, and specific gene expression in tissue samples. However, we show that there is a prevalent transcript leakage problem in spatial transcriptomics data, where transcripts expressed by a cell diffuse to its neighborhood and are recurrently detected in the nearby cells. By analyzing published data sets, we show that this problem is general across data produced from different tissues and different species using different imaging-based and sequencing-based spatial transcriptomics platforms. It affects both upstream tasks such as expression quantification as well as downstream tasks such as cell-type annotation and detection of spatially-dependent gene expression. To tackle the transcript leakage problem, we propose a reference-free Bayesian model-based method, DeLeakage, which cleans up the data much more effectively than existing denoising methods. DeLeakage also improves cell-type annotation and avoids false detection of spatially dependent expression.

Abstract Background The current treatment of glioblastoma involves resection followed by radiotherapy (RT) and temozolomide. Rapid early progression (REP) of tumor in the surgery-to-radiotherapy interval (SRI) has been described using categorical or semi-quantitative assessments and is associated with inferior clinical outcomes. This study seeks to establish and validate a quantitative definition for REP and examine how REP could inform future therapy. Methods Volumes of tumor and resection cavity at 3 time points—preoperative, postoperative and RT-planning (pre-RT)—were contoured among patients who had undergone standard of care. A minimal, but clinically appreciable, threshold for defining REP based on change in tumor volume was established, validated, and subsequently used to assess actionable predictors of REP and its prognostic value. Results An increase of >2 cc in volume or a new satellite tumor between the post-operative to planning MRI was found to be a sensitive, pragmatic, and statistically significant cutoff for REP (P = .002). Actionable predictors such as SRI of 6 weeks and a > 5 cc residual immediate post-operative tumor volume were found to be statistically significant predictors of REP. REP was also found to be a statistically significant prognostic indicator for overall survival (P = .002) and progression-free survival. Conclusion These findings support that an increase in tumor volume between post-operative and pre-RT MRI of >2 cc is the ideal working definition of REP in this clinical setting. Furthermore, REP could serve as a prognostic ­biomarker to track treatment response. Additionally, 2 actionable predictors of REP, post-op residual tumor volume and SRI, are identified.

ABSTRACT Purpose To explore the opioid decision‐making process of prescribers in primary care, surgery, and subspecialty pain management. Methods This was a multistage qualitative‐qualitative study with clinicians involved in opioid prescribing and management from a single healthcare organization with locations in Minnesota, Florida, Arizona, and Wisconsin. Clinicians in this study included physicians, nurse practitioners (NPs), and physician assistants (PAs) practicing in primary care, surgery, or pain medicine. The interview guide was organized in three domains of a conceptual model for opioid use: (1) prescriber characteristics, (2) patient characteristics, and (3) practice environment characteristics. Individual interviews ( N = 20) were performed first, and data were summarized using a rapid template‐based approach. Subsequently, focus groups (FGs) ( N = 4) were conducted with an additional 21 clinicians to confirm and explore interview results. Data from interviews and FGs were analyzed using a common codebook. Results Findings were organized as decision factors into the three domains. Factors in the prescriber domain included characteristics such as formal pain management training, as well as factors that influenced knowledge and beliefs (e.g., advice from or observation of supervising clinicians and expert colleagues). Decision factors in the patient domain included patient pain etiology, comorbid medical or mental health conditions, and demographic characteristics. Clinicians' perceptions of these factors, such as viewing older age as having lesser risk for opioid misuse, influenced prescribing decisions. Clinicians also described challenges associated with “legacy patients” whose therapy was previously managed by a different clinician. Primary care clinicians, in particular, expressed difficulties managing post‐surgical or trauma‐related pain after care transition. Relevant decision factors reported by prescribers in the practice environment domain included guidelines and practice oversight. Most participants reported practicing in an environment that promoted conservative opioid use and having access to standardized institutional guidelines that reduced perceived decision‐making burden. Clinicians described how they used prescribing guidelines to help them communicate with patients about opioid use and prescribing decisions. Conclusions Intersecting prescriber, patient, and practice environment factors shape opioid analgesic prescribing decisions. Available resources in the practice environment, including peer input and institutional guidelines, may support clinician decision‐making and conversations with patients at the point of care, including in cases where patients have complex histories or personal characteristics that influence decision making.

e18026 Background: Immune checkpoint inhibitor (ICI) therapy is part of standard of care first-line therapy for recurrent or metastatic (R/M) HNSCC. However, less than 20% of patients (CPS ≥1) have an objective response to ICI monotherapy, and most tumors progress within ~3 months. We sought to improve the proportion of patients who benefit from a chemotherapy-free regimen by combining intratumoral (IT) VV1 oncolytic virus (VSV-IFNβ-NIS) injections with the anti-PD-1 antibody, cemiplimab. We report a pre-planned analysis of Simon's stage 1 results. Methods: We activated a phase 2 study testing the efficacy of first line IT VV1 plus cemiplimab in 1 st line patients with R/M HNSCC. A Simon's two-stage design was employed whereby 10 patients would be accrued in stage 1, and if 3 or more responses were observed, 12 additional patients would be accrued for stage 2. The primary endpoint was objective response rate (ORR) per investigator (RECIST 1.1). Eligible patients had untreated R/M HNSCC from primary oropharynx, oral cavity, hypopharynx, or larynx sites with CPS ≥1. Patients had to have at least one measurable lesion amenable to IT injection. Treatment comprised of IT injections to 1-5 lesions of oncolytic VV-1 virus and IV cemiplimab 350 mg on day 1, repeated every 21 days. Each lesion could be injected 3 times; a 4th injection was allowed if a partial response (PR) was achieved after 3 injections. Cemiplimab could be continued for up to 2 years until progression or unacceptable toxicity. Results: Patient and tumor characteristics, as well as efficacy and toxicity are summarized in the table below. Ten patients were treated at the time of Stage 1 analysis, with 3 showing a confirmed PR for ORR of 30%. Responder CPS scores were 45, 12 and 20%. Two of the responders subsequently showed progression after 6.2 and 9.9 months, the third has maintained PR at 7.7 months to date. Eight of 10 patients showed decrease in the sum of target lesion size (mean decrease of 16%; range -57 to 77%). One grade 2 event of ICI nephritis resolved with corticosteroid treatment. Conclusions: Three patients showed confirmed PR by RECIST 1.1 in Simon's stage 1, meeting criteria to proceed to Simon's stage 2. A total of 22 patients in the HNSCC will be enrolled. VV1 plus cemiplimab shows promise in first line R/M HNSCC based on these initial results. Clinical trial information: NCT04291105 . Patient demographics. N (treated) 10 Sex 20% female Median age (y) 60 (54 – 76) Oropharynx 7 HPV+ 7 Oral cavity 3 PD-L1 CPS median (range) 7.5 (1-45%) Locoregional injection 3 Distant injection 6 Local and distant injection 1 Best response (RECIST 1.1) PR 3 SD 5 PD 2 Adverse Events #pts any VV1/cemiplimab-related G3 AE 4 Lymphopenia 3 Elevated ALK 1

ABSTRACT Introduction Community health workers (CHWs) help patients navigate community resources. CHW programs can improve health outcomes and reduce healthcare utilization, but identifying eligible patients is challenging. We developed an electronic health record (EHR)‐based algorithm trained to predict referrals to a CHW program. Our objective was to evaluate whether an algorithm trained on historical referrals identifies a subgroup of patients that differs from the subgroup identified through questionnaire‐based health‐related social needs (HRSN) screening alone. Methods This analysis used data from Mayo Clinic primary care patients in Southeast Minnesota. We developed a gradient boosted time‐to‐event model that incorporated demographics, diagnoses, HRSN questionnaire responses, and HRSNs derived from clinical notes using natural language processing. We compared the characteristics of algorithm‐identified patients with those identified through questionnaires and assessed the variable importance of model features. Results The algorithm had AUC: 0.87 in the training and 0.92 in the hold out set. Patients flagged by the algorithm tended to use interpreter services more commonly (12.6% vs. 1.3%), have a non‐English preferred language (14.1% vs. 2.3%), and have more instances of health literacy documented (5.36 vs. 1.29) compared to patients identified by the HRSN questionnaire. Only 47.0% of patients flagged by the algorithm had responded to the HRSN questionnaire within 2 years. Variable importance was highest for health literacy and financial strain from unstructured notes. Conclusions The algorithm is a chart‐review prioritization tool for referral to the CHW program for patients that may overcome challenges to identifying patients with HRSNs, especially when questionnaire data is incomplete.