Citations

Purpose: This letter addresses a recent paper by Mailend et al. (2025) that expressed concerns about the Apraxia of Speech Rating Scale (ASRS) and offered guidelines and definitions regarding its principles, scale labels, item definitions, and scoring procedures, including the addition of new items to the scale. The primary purpose of this letter is to clarify the uncertainty that other users of the scale may have about whether the current ASRS version (ASRS 3.5; Duffy et al., 2023) should be altered to include the numerous proposed revisions. It provides examples of proposed revisions that, in our judgment, are helpful, redundant, questionable or premature, or are misaligned with the primary purposes of the scale. Conclusions: Some of the proposed revisions to the ASRS are helpful and likely to improve reliability by reducing user uncertainty about ratings. Others are questionable or premature without supporting data or are not aligned with the primary purposes of the scale.

Abstract Background: Black men carry a disproportionate prostate cancer (CaP) burden and often experience significant psychosocial distress at the point of prostate cancer diagnosis (PPCD). Many report emotional shock, uncertainty, and limited access to culturally competent guidance, which can negatively affect treatment decisions and long-term survivorship. To address these needs, we developed the PPCD Virtual Reality Assistant (ViRA), an immersive, AI-enabled intervention co-designed with Black CaP survivors. ViRA delivers tailored psycho-oncology support, emotional guidance, and navigation of social determinants of health (SDOH) within virtual reality environments. This study evaluated the feasibility, acceptability, and usability of the PPCD ViRA (NCT06535802). Methods: ViRA was developed through a structured, seven-step co-design process with survivors, integrating mobile immersive technologies, SDOH navigation, and culturally grounded psycho-oncology content. Personalization was enabled through AI-driven predictive analytics and a recommendation engine. Alpha testing assessed initial usability and acceptability among 10 participants (seven team members and three Black CaP survivors). Beta testing with 24 Black men in Florida examined feasibility and preliminary efficacy. Results: A demonstration of ViRA is available (https://www.youtube.com/watch?v=1mI-HS5R6sk). Alpha testing indicated strong usability, positive emotional engagement, and clear promise for enhancing support at the PPCD. In Beta testing, participants varied in age; most were married (58.3%), held a bachelor’s degree (45.8%), were retired (45.8%), and had a family history of cancer (83.3%). ViRA use was associated with increased engagement and reduced distress across participants. Overall, 74% rated ViRA as “excellent,” while the remainder rated it as “good” or “very good.” More than 90% reported being “very satisfied,” with the rest indicating satisfaction. Conclusions: Findings demonstrate high feasibility, acceptability, and cultural relevance of the PPCD ViRA for supporting Black men at diagnosis. Lessons learned highlight the need for culturally embedded design, emotional timing, community co-creation, flexible delivery formats, and strong community partnerships to advance digital health equity. The refinement and larger-scale validation to establish clinical utility and readiness for implementation is ongoing (NCT07126548). Citation Format: Folakemi T. Odedina, Che Ngufor, Christopher Williams, Mary Ellen Young, Floyd Willis, Adam M. Kase, Arnold Merriweather, Emelina Asto-Flores, Dee M. Glaser-Boivin, Jada Melton, Monica L. Albertie, Michelle Fudge, Quincy Wimberly, Inclusive Cancer Care Research Equity (iCCaRE) Consortium, Prostate Cancer Transatlantic Consortium (CaPTC). Novel application of the iCCaRE consortium virtual reality assistant (ViRA) to support Black men at the point of prostate cancer diagnosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6306.

Abstract Background: Black men across the African Diaspora experience a disproportionate burden of prostate cancer (CaP). The Inclusive Cancer Care Research Equity (iCCaRE) Consortium aims to eliminate CaP burden through global scientific collaboration, innovative research, community-engaged interventions, and next-generation workforce development. The primary objective for this Consortium was to optimize CaP diagnosis, treatment, and survivorship through research, research training and education, community engagement and community outreach. The Consortium integrates digital health technologies, community navigation, precision communication and precision science. Methods: Five full projects and one pilot project were launched across partner institutions in North America and Africa. Supported by multiple cores and services, the research activities included (1) implementation of a Point of Prostate Cancer Diagnosis Virtual Robot Assistant (PPCD-ViRA); (3) initiation of a cancer care at home trial; (4) migrant health studies of Caribbean and Sub-Saharan African immigrants; (5) expansion of genomic and metabolomic research; and (6) digital, psychosocial, and survivorship intervention development. Training and dissemination activities were deployed through iCCaRE TV, webinars, and community engagement programs including the Global Prostate Health Dialogue (Glo-PHD). Results: In one year, accomplishments included 45 presentations, 17 publications, 16 grant submissions, and 3 awards. The consortium delivered 408 live webinar engagements and reached more than 400 men globally through Glo-PHD. PPCD-ViRA was fully developed and prepared for clinical deployment (see https://www.youtube.com/watch?v=1mI-HS5R6sk). The African cohort expansion for genomic and metabolomic profiling was activated across several countries, with biospecimen collection underway. Media dissemination generated more than 15,000 views across platforms, including high-impact educational videos (see: www.youtube.com/@iCCaREConsortium). Training achievements included 13 early-career investigators and 7 trained prostate cancer advocates. Conclusions: In just one year, the iCCaRE Consortium Phase 2 made substantial progress toward transforming CaP equity globally. Through multidisciplinary science, digital innovation, and community partnerships, the consortium is building scalable infrastructure to address diagnosis experiences, treatment quality, and survivorship among Black men. Ongoing efforts will continue to advance precision medicine, culturally grounded interventions, and global capacity building. Citation Format: Folakemi T. Odedina, Arnold Merriweather, Roxana S. Dronca, Ernest T. Kaninjing, Solomon Rotimi, Gerardo Colon-Otero, Kimlin Ashing, Ademola A. Popoola, Gladys Asiedu, Opeyemi Bolajoko, Ewan COBRAN, Emelina Asto-Flores, Floyd Willis, Christopher Williams, Monica L. Albertie, Michelle Fudge, Oluwaseyi Toye, Collisa Mahin, Jada Melton, Inclusive Cancer Care Research Equity (iCCaRE) Consortium, Prostate Cancer Transatlantic Consortium (CaPTC). Achieving prostate cancer equity globally: Multinational advances from the iCCaRE consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2382.

Abstract Introduction Revascularization to prevent limb loss is not feasible or represents a very high risk in a significant proportion of patients with chronic limb-threatening ischaemia (CLTI). No standard definition currently exists to define this population of patients. The aim of this study was to develop a consensus-based, multidomain definition to improve clinical assessment and reporting of studies in people with ‘no option’ (NO) or ‘poor option’ (PO) CLTI. Methods A modified Delphi process was conducted with 164 specialists from 30 countries. Two iterative survey rounds were used to reach consensus, defined as ≥70% agreement with a score of ≥7 on a nine-point scale. Results Some 164 international vascular specialists participated in the study, averaging 19 years of experience. A multidomain framework including arterial disease anatomy, biology, risk, function, and context (ABRFC) achieved 83% consensus. A ‘desert foot’ was defined as the absence of distal arterial revascularization targets on advanced non-invasive imaging, invasive digital subtraction angiography, and at least one failed endovascular revascularization attempt (81.6% agreement). Inadequate autogenous bypass conduit was defined as the lack of usable autologous vein across all four limbs (85% agreement). Patients were classified as NO for revascularization if they present with ‘desert foot’, prohibitive medical risk, a non-functional limb, or in those patients who refused arterial revascularization. PO revascularization patients combined factors such as severe infection, lack of autologous vein, or treatment non-compliance (72.1% agreement). Conclusion This consensus study established a structured, expert-validated definition of no option or poor option for revascularisation of patients with CLTI. The multidomain ABRFC framework provides a foundation for standardized clinical assessment, trial design, and future guideline development.

Abstract Background: The Alaska Tribal Health System is working to increase colorectal cancer (CRC) screening among Alaska Native peoples. It is unknown why people who initially agree to screening might not follow through to complete their screening. Methods: As part of a larger intervention investigating multi-target stool DNA (mt-sDNA) test use in rural Alaska communities, we interviewed Alaska Native people who had agreed to scheduling a colonoscopy or having a mt-sDNA kit sent to their home but who did not complete their selected test. Results: Of 531 Alaska Native people who initially agreed but did not complete screening, 299 (56%) were able to be contacted for a follow-up survey. Of those, 256 (86%) answered the survey; 187/224 (83%) who had chosen mt-sDNA, and 69/75 (93%) who had chosen colonoscopy. Reported reasons for non-completion of stool DNA test kits included being busy or forgetting, being uncomfortable doing a stool test, and not knowing how to do the test or concerns over how to return the kit for processing. Reasons for non-completion of colonoscopy included scheduling issues, physical health issues, travel, and housing barriers, as well as cost, fear, and being too busy. Of note, many respondents in both groups indicated they would still be interested in CRC screening in the future or were currently pursuing screening. Conclusions: This was the first exploration of reasons for non-adherence to CRC screening after initial test request by Alaska Native people. Many of the identified themes are amenable to health care system changes for future interventions to improve screening outreach and uptake. Citation Format: Diana Redwood, Christie A. Flanagan, Lauren Jeffries, Melissa Toffolon, Joseph Klejka, Lila J. Finney Rutten, Judith S. Kaur, John B. Kisiel. Non-completion of colorectal cancer screening among Alaska Native people in an intervention trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2474.

Abstract Large Language Models (LLM) are being widely adopted into the medical field for their impressive ability to analyze and summarize large amounts of text data. These models enable clinicians and researchers to extract meaningful insights from complex datasets and may assist with decision making. Here we present our workflows and application of LLM for the interpretation and summarization of clinical data related to CAR-T cell therapy. Using an LLM (Gemini 2.5 pro) in the Google Cloud Computing (GCP) environment, two applications were developed to analyze CAR-T cell therapy clinical data: 1) extracting and summarizing CRS and ICANS event-related data to streamline the compliance team workflow, and 2) identifying features available at time of CAR-T infusion able to classify patients into high- or low-monitoring needs 14 days post CAR-T. Patient data (vitals, labs, hematology notes, and EKGs) were extracted from the electronic medical record (EMR) using Google BigQuery into SQL tables in GCP. For each application, relevant data fields were retrieved, formatted into JSON objects, and embedded in the LLM prompt for context-aware processing. Both applications have undergone iterative prompt engineering after analyzing the LLM output against ground truth data in the EMR. For the application extracting and summarizing CRS and ICANS events, the LLM was optimized on Mayo Clinic Rochester data. When compared to the IEC compliance database, the LLM achieved 100% accuracy and F1 score for CRS events, and 96% accuracy and 82% F1 score for ICANS events. The match rate for CRS and ICANS grades were 83% and 89% respectively. We applied the same LLM to Mayo Clinic Arizona (MCA) and Mayo Clinic Florida (MCF) cases, who document clinical notes and toxicity flowsheet differently, and achieved an accuracy (MCA: 93%, MCF:93%) and F1 score (MCA: 96%, MCF: 96%) for CRS and accuracy (MCA: 81%, MCF:82%) and F1 score (MCA: 76%, MCF: 75%) for ICANS. LLM was able to capture events missed by manual reviews. For most of the discrepancies where compliance team final adjudication is needed, LLM will be updated to flag discrepancies for review by the compliance team. For the application related to the monitoring needs 14 days post CAR-T, the LLM identified 5 categories predictive of high or low monitoring needs post CAR-T infusion (disease status, inflammatory and tumor burden markers, hematologic status, renal function and performance status). Our model achieved a sensitivity of 85.7%, specificity of 23.8%, and F1 score of 65.5% for our first cohort, compared with data extracted by the LLM from the EMR. For our second cohort, with demographics statistically similar to cohort 1 and using the same 5 categories, the LLM achieved a sensitivity of 83.3%, a specificity of 28.6%, and F1 score of 65.4%. Our workflow and applications of LLM’s provide examples and guidance to others interested in applying LLM’s for clinical and research applications. Citation Format: Emmanuel Contreras Guzman, Matthew Jankowski, Andre De Menezes Silva Corraes, Malvika Gupta, Monica L. Shaw, Madiha Iqbal, Talal Hilal, Saurabh Chhabra, Ricardo Daniel Parrondo, Jody K. Mclean, Kim R. Riester, Kayla Joseph, Melinda Tan, Holly Ross, Cleyonia Barnett, Sylvia Carter, Semy Girmay, Rachel Wolan, Milana Ramsey, Christian Downhour, Kristy Morgan, Shae Sibley, Erica Rushing, Lucy Holmes, Allison Burgstahler, Stephen M. Ansell, Hassan Alkhateeb, Matthew Hathcock, Ramona Bruno, Allison C. Rosenthal, Hemant Murthy, Patrick B. Johnston, Jonas Paludo, Yi Lin. Applications of large language models to CAR-T cell therapy clinical data using Google cloud computing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2740.

Abstract Background: Melanoma brain metastases (MBM) represent a biologically distinct and clinically aggressive subset of melanoma. Comprehensive molecular characterization focused on intracranial disease remains limited. We aimed to define the genomic landscape of MBM and compare these findings with public melanoma datasets. Methods: We retrospectively identified 166 patients with histologically confirmed MBM across Mayo Clinic tri-sites (2011-2025). Molecular testing was performed in 123 patients (74.1%). Comprehensive next-generation sequencing (NGS; ≥300-gene platforms including Tempus, FoundationOne, Caris, NeoGenomics, and MayoComplete Solid Tumor Panel) was available in 41 patients (24.7%). Intermediate-depth profiling using the MayoComplete Melanoma Panel (17 genes) was performed in 21 patients (12.7%), and a targeted 5-gene melanoma driver panel (BRAF, NRAS, KIT, GNAQ, GNA11) in 52 patients (31.3%). cfDNA-based NGS was available in 12 patients (7.2%). Genomic alterations were summarized and benchmarked against TCGA-SKCM and MSK-IMPACT datasets via cBioPortal. We considered assay heterogeneity, as Mayo panels varied in sequencing depth and CNV coverage, and hybrid-capture platforms often under-detect TERT promoter hotspots. Results: Patients had a median age of 67 years, and 63% were male. BRAF mutations occurred in 48.8% (BRAF V600E/K 41.6%; non-V600 7.2%). Additional MAPK alterations included NRAS (17.5%), KIT (5.4%), GNAQ (1.2%), and GNA11 (0.6%). In the comprehensive NGS subset, tumor-suppressor alterations included CDKN2A (17.5%), PTEN (7.8%), NF1 (9.0%), TP53 (8.4%), and TERT promoter mutations (22.9%). Median TMB was 11.55 mut/Mb (IQR 5.0-25.5). Co-alterations included BRAF+CDKN2A (7.2%), BRAF+PTEN (4.2%), NRAS+CDKN2A (4.2%), NRAS+PTEN (1.2%), and CDKN2A+PTEN (3.6%); overall, 18.1% harbored MAPK driver + tumor-suppressor co-alterations. Compared with TCGA and MSK cohorts, MBM showed similar MAPK driver frequencies but fewer MAPK + tumor-suppressor co-alterations and lower CDKN2A, PTEN, and TP53 disruption, alongside a more prevalent of TERT promoter mutations (22.9% vs 7% and 2.1%), which may partly reflect coverage differences. Conclusion: MBM exhibit a distinct genomic profile characterized by reduced tumor-suppressor loss, fewer MAPK-tumor-suppressor co-alterations, and higher prevalence of TERT promoter mutations. While assay heterogeneity limits direct cross-cohort comparisons, these patterns suggest potentially distinct biological features of intracranial melanoma and underscore the need for harmonized, MBM-specific molecular studies to guide therapeutic development. Citation Format: Dina Elantably, Joseph B. Parker, Jakob Hamilton, Ahmed Abdelhakeem, Oluwatayo Adeoye, Saivaishnavi Kamatham, Winston Tan, Arkadiusz Z. Dudek, Anastasios Dimou, Matthew S. Block, Robert McWilliams, Svetomir Markovic, Mahesh Seetharam, Roxana Dronca, Ruqin Chen. Genomic landscape of melanoma brain metastases: Real-world analysis and comparison with public melanoma cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2107.

Abstract Background: Cancer survivorship requires significant contributions from family caregivers at home. This role can be burdensome because family members play a vital role in the physical, functional, and emotional well-being of patients diagnosed with cancer. Although optimum care throughout the care continuum requires significant caregiver support at home, family caregivers' contribution to survivorship care is usually neglected. We provide the preliminary outcomes of caregivers' challenges and experiences in providing care and survivorship support to Black cancer survivors. We also identified ways to provide support for family caregivers. Methods: This qualitative study obtained information from 8 caregivers who care for Black cancer survivors who have completed treatment in the United States. The study used a phenomenological design to obtain data from participants. In-depth interviews focused on participants' lived experiences caring for Black patients with cancer. The study captured caregivers' personal stories of how they dealt with diagnosis, feelings, emotions, reactions, understanding of the disease, prognosis, and treatment options and decision process, as well as survivorship of their care recipients. All interviews were video recorded and transcribed verbatim. The transcript of each participant's interview was reviewed, analyzed, and coded, with emerging themes interpreted. Results: The major cahllenges identified were (1) lack of knowledge of cancer, the disease and treatment course before the diagnoses; (2) home care burden, which include the challenges of combining care for a sick person at home with caring for other members of the family and taking care of domestic chores; (3) patient care navigation, including identifying healthcare professional for specialist care, adequate health insurances, scheduling doctors' appointment, transportation, insurance and treatment paperwork; (4) financial challenges, especially keeping up with job, family income reduction, increase out of pocket spendings, as well as expensive drugs and treatment co-pays. Most of the caregivers agreed that they neglected their personal health while caring for their care recipient. All caregivers wished they received more information and training on how to care for a patient with cancer. Possible solutions identified were care packets providing information on cancer and how to provide care at home, patient care navigation to social determinants of health and financial support programs, counselling for mental health and emotional support, peer support groups for caregivers, health checks, and a contact to call for support. Conclusion: Caring for cancer patients at home is very challenging; having a care packet and caregiving training is important to support survivorship and reduce the caregiving burden experienced by family caregivers. Citation Format: Opeyemi Oreoluwa Bolajoko, Jada Melton, Mary Ellen Young, Folakemi T. Odedina. Perspectives on cancer survivorship: Voices of family caregivers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1248.

Abstract Introduction Detecting and estimating blood volume loss are important for the diagnosis and management of life-threatening hemorrhage. There is a direct relationship between percent blood volume loss (BVL%) and falling in stroke volume (SV); furthermore, there is a direct relationship between diminishing SV and the corrected flow time of the carotid artery (ccFT). Therefore, we hypothesized that change in ccFT (ccFTΔ) would directly relate with BVL% in a phlebotomy paradigm. Materials and Methods A prospective, convenience sample of healthy volunteers was studied. Volunteers underwent blood donation protocol in a physiology lab. A wireless, wearable Doppler ultrasound system monitored ccFT during blood donation. Traditional vital signs were also measured throughout. The relationship between traditional vital signs as well as ccFTΔ were compared to BVL% using 2 mixed linear regression models. Results Data from 20 subjects and blood donations comprising 46,123 cardiac cycles are included. On average 413.5 ± 39 mL of blood were drawn representing 8.6 ± 1.6% BVL%. There was a significant and strong linear relationship between BVL% and ccFTΔ during blood draw with the regression slope demonstrating that for every 1 ms reduction in ccFT there was a 0.4% reduction in blood volume. Conclusions In healthy subjects and when blood loss is the sole mechanism for falling SV, we estimate that for every 1 ms reduction in ccFT, there is an approximate 0.4 BVL%. Validation of these results in patients with traumatic hemorrhage is underway.

Abstract Objective Evaluate how RAG architecture, including corpus structure, retrieval strategy, and pipeline complexity, affects LLM-based medical problem solving and knowledge retrieval in sleep medicine. Materials and Methods We benchmarked four open-source LLMs (Llama-3-8B, Llama -3 -70B, Qwen 2.5-14B, and Qwen 2.5-235B) using a knowledge base of five sleep medicine textbooks. We compared performance across three dimensions: corpus structure (raw text vs table-of-contents aligned.), retrieval strategy (dense embedding vs hybrid sparse-dense), and pipeline complexity (baseline vs augmented). Evaluation metrics included board-style multiple choice question (MCQ) accuracy and clinical case vignette diagnostic ranking. Results RAG improved MCQ accuracy for all models. Llama-8B saw the largest gain of 10.6% (61.8% to 72.4%), while Qwen-235B reached 87.3%. In clinical cases, Llama-8B accuracy dropped by 7.1% when using raw text and dense retrieval due to context noise. This was corrected by using structured hybrid configurations. Hybrid retrieval consistently outperformed dense-only methods. Overall, structured corpora improved primary diagnosis accuracy by 6.1% on average, with Qwen-235B reaching a peak 10.2% increase. Discussion RAG effectiveness depends on the balance between model size and data structure. Large models handle uncurated text well, but smaller models are easily distracted by irrelevant data. Hybrid retrieval is necessary to maintain precision with specialized medical terms. A structured corpus paired with a baseline hybrid pipeline offers the best stability and speed for clinical use. Conclusion Rigorous data curation and hybrid retrieval are as essential as model scale for deploying safe, guideline-compliant AI in sleep medicine.