Citations

PURPOSE GBM AGILE (ClinicalTrials.gov identifier: NCT03970447 ) is a phase II/III Bayesian adaptive platform registration trial testing multiple arms against a common control; the primary end point is overall survival (OS). Regorafenib, a multikinase inhibitor, showed OS benefit in recurrent (RD) glioblastoma in the phase II REGOMA trial and entered GBM AGILE as the first investigational arm. METHODS Patient subtypes included in the regorafenib arm of GBM AGILE were newly diagnosed unmethylated (NDU) and RD glioblastoma. Prospective defined sets of subtypes, or arm signatures, were NDU, RD, and all (NDU + RD). As the first investigational arm in GBM AGILE, regorafenib was equally randomized to the control arm. Treatment in the control arm is temozolomide + radiotherapy (in newly diagnosed) or lomustine (in RD). Efficacy was assessed by OS hazard ratio (HR), arm/control, and demonstrated when the Bayesian probability of benefit (HR <1.00) was ≥98%. Analysis was performed monthly for limited efficacy, which occurs when the Bayesian predictive power is <25% for all signatures, and determines stopping enrollment. Follow-up continued for 12 months after accrual stopped. RESULTS When the predictive power was <25% in all predefined signatures for regorafenib, accrual stopped for limited efficacy. The final analysis did not demonstrate OS improvement in the regorafenib arm in RD nor NDU glioblastoma. Median HRs were 1.05 (NDU), 1.07 (RD), and 1.07 (all) with final probabilities of benefit (HR <1.00) of 0.421 (NDU), 0.312 (RD), and 0.296 (all). Regorafenib was associated with increased toxicity relative to control. CONCLUSION GBM AGILE did not show superiority of regorafenib over control in RD (lomustine) or NDU (temozolomide + radiotherapy) glioblastoma, yet caused increased toxicities. Regorafenib has been removed from National Comprehensive Cancer Network guidelines as a treatment option for RD.

Effective translation relies on high performance teams integrating diverse disciplines to bring new drugs, medical devices, diagnostics or behavioral interventions into improved health. Despite substantial advancements informed by the Science of Team Science (SciTS), challenges remain in effective translational team (TT) operations, while limited institutional, scholarly, and practitioner legitimacy of team science expertise constrains efforts to address them. Here, we describe an essential member of the TT, the Team Science Professional (TSP). Serving as a team educator and facilitator of team interventions, the TSP plays a pivotal role in facilitating effective team performance. Current challenges faced by this nascent profession are defining career pathways and establishing competencies needed for expert performance. To address these challenges, the authors, representing a spectrum of academic universities organized as a special interest group (SIG) of the Association of Clinical and Translational Science (ACTS), propose a suite of individualized, standardized and pathway-selective micro-credentials (digital badges). Digital badges in “Team Science (TS) Fundamentals,” “TS Practitioner,” “TT Trainer” and “TT Intervention Expert” are described, along with preliminary feasibility and usability evaluations of the submission process. These stackable credentials provide a customizable, portable recognition of skills and help advance career pathways for TSPs. In so doing, the Digital Badge Initiative will enhance the capacity of translational science “Hubs” such as those supported by Clinical and Translational Science Awards to conduct effective and rigorous translation. Moving forward, the ACTS TSP SIG will be examining the impact of digital badging on standardization and its effect on career recognition and retention.

Background/Objectives: Machine learning (ML) models can predict hospital admission from emergency department (ED) triage data with areas under the receiver operating characteristic curve (AUC) exceeding 0.85. Whether incorporating the assigned provider’s identity—as a proxy for unmeasured practice variation—improves prediction has not been systematically studied. We aimed to compare 10 supervised ML classifiers for predicting hospital admission at ED triage, with and without provider identity, and to characterize model reasoning using SHapley Additive exPlanations (SHAP). Methods: We conducted a retrospective cohort study of 186,094 ED visits (2020–2023, training) and 58,151 visits (2024, temporal holdout test) at one academic tertiary-care ED. Ten classifiers spanning linear, distance-based, tree-based, ensemble, probabilistic, and neural network families were each trained in two conditions: baseline (23 triage features) and with provider identity appended. SHAP TreeExplainer was applied to the top-performing models (CatBoost and XGBoost). Results: The admission rate was 31.3% (training) and 31.7% (test). CatBoost achieved the highest baseline AUC of 0.8906 (0.8878–0.8933). Adding provider identity produced negligible AUC changes across all models (ΔAUC range: −0.0029 to +0.0015; all DeLong p > 0.05). SHAP analysis identified ESI level, respiratory rate, temperature, complaint category, and age as the dominant predictors, with clinically intuitive directionality. Conclusions: Provider identity does not meaningfully improve ML prediction of hospital admission beyond standard triage variables. The observed 28-percentage-point variation in provider admission rates is explained by patient case-mix differences than with independent practice pattern effects on prediction. SHAP provides transparent, clinically interpretable explanations suitable for bedside decision support.

Abstract Background: Adhering to 2018 World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) Cancer Prevention Recommendations is reportedly associated with better survival among long-term colon cancer survivors (likely affected by immortal time bias). Thus, it is important to validate survival benefits by assessing adherence shortly after diagnosis, and further investigation is needed to examine its association with chemotherapy outcomes. Methods: Using an NCI-sponsored adjuvant chemotherapy trial conducted in patients with stage III colon cancer (CALGB/SWOG 80702; NCT01150045), we included 1,666 patients who returned valid Willett food frequency questionnaires (FFQ) at chemotherapy initiation and derived WCRF/AICR scores accordingly (higher score suggesting higher adherence). The primary outcome was disease-free survival (time from FFQ completion to recurrence or death), and secondary outcomes were reduced relative dose intensity (RDI; &lt;85% suggesting worse completion) and severe toxicities (grade ≥3 for any chemotherapy-related toxicity). To estimate the associations of WCRF/AICR scores (quartiles) with survival and chemotherapy outcomes, we conducted multivariable Cox proportional hazards regression for disease-free survival and multivariable logistic regression for reduced RDI and severe toxicities. Results: Compared to those in the lowest quartile of the WCRF/AICR score, patients in the highest quartile had significantly better disease-free survival (hazard ratio: 0.75 [0.58, 0.98], Ptrend = 0.02) and lower risk of reduced RDI (odds ratio [OR]: 0.74 [0.54, 1.00], Ptrend = 0.03), but not for severe toxicities (OR: 1.24 [0.93, 1.67], Ptrend = 0.11). Conclusions: In patients with stage III colon cancer, higher adherence to WCRF/AICR recommendations was associated with better survival and chemotherapy completion, but not for severe toxicities. Funding: https://acknowledgments.alliancefound.org Citation Format: En Cheng, Chao Ma, Qian Shi, Anthony F. Shields, Peter T. Campbell, Ardaman P. Shergill, Katherine A. Guthrie, Felix Couture, Philip Kuebler, Pankaj Kumar, Benjamin Tan, Smitha S. Krishnamurthi, Kimmie Ng, Eileen M. O'Reilly, Justin C. Brown, Philip A. Philip, Jeffrey A. Meyerhardt. Associations of WCRF/AICR recommendations with survival and chemotherapy outcomes in colon cancer: CALGB/SWOG 80702 (Alliance) [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 5038.

Abstract Introduction: COE has become the gold standard in addressing health disparities. COE’s value is emphasized by NIH and leading cancer-related organizations e.g., AACR. The Alliance for COE (The Alliance) mission is to advance the art, science, and impact of COE; promote community health and wellness; and reduce cancer burden and disparities. Methods: This abstract builds on the Alliance’s Science of Community Outreach and Engagement (SoCOE) Conference a NCI R13 funded series. SoCOE Conference is organized by 10 NCI-designated Cancer Centers to provide a platform for COE academic-clinical-policy-community stakeholders to share best practices for solution-focused community responsive cancer prevention, diagnostics, therapeutics and survivorship research and practice. Results: &gt; 500 researchers, clinicians, policymakers, healthcare administrators, with &gt;12% being survivors and/or advocates, participated in our SoCOE Conferences. The delegates’ recommendations are: Decentralize who/entities that hold all the power in science and clinical research (trials). Communities hold valuable, necessary wisdom and resources to inform and guide science Include multisectoral partners early and always Community capacity building and compensation with gratitude Mentoring of junior COE researchers, clinicians, policymakers, healthcare administrators, survivors and advocates with humility is a must Develop virtual communities to share best practices across cancer centers and within regions Develop working groups to identify and explore commonalities across COE work in rural/urban, diverse/homogenous spaces Publish Science of COE papers on various topics related to COE Frameworks and evidenced-solutions Provide community reports on best practice guide that can be widely available to be shared locally and in-person, and digitally Partner and learn from COE teams working with other cultural/ethnic groups Attend to, measure and remedy societal/social drivers of health disparities that mirror barriers to care, and research engagement and participation. Discussion: Informed by our community advisory boards and the findings for our SoCOE Conferences, we present the pillars of the Alliance to tackle population cancer burden and disparities: Training future COE leaders/advocates, Advocating for public health policies/guidelines, Increasing access to cancer prevention and care that will also increase access to studies, Engaging and partnering with multisectoral stakeholders and communities, Building community capacity, Advancing COE science through catchment-relevant research, and Leading bi-directional communication and information and resource sharing between catchment area communities and cancer centers. The expectation and impact of COE can only be achieved if COE teams are valued, supported cancer center members with community advisory boards and community as cancer centers’ priority population. Citation Format: Kimlin Ashing, CHARNITA ZEIGLER-JOHNSON, Hayley S. Thompson, Kim Rhoads, Nadine Barrett, Lisa Carter Bawa, Timiya S. Nolan, Monica Baskin, Vanessa B. Sheppard, Marvella E. Ford, Erica Phillips, Lorna H. McNeill, Folakemi T. Odedina. Advancing the science, practice and impact of COE [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 7577.

Abstract Background S0221 investigated weekly vs every 2 weeks dosing of doxorubicin (A) and cyclophosphamide (C) followed by paclitaxel in patients with high-risk early breast cancer. After an interim analysis, random assignment to the 2 AC arms was stopped for futility, and the trial was modified to study only the paclitaxel schedules. Methods Between December 2003 and November 2010, a total of 2716 patients were randomly assigned in a 2 × 2 factorial design to 15 weeks of weekly A and daily C vs 6 cycles of every 2 weeks AC; and weekly paclitaxel for 12 weeks vs 6 cycles of every 2 weeks paclitaxel. Between January 2011 and January 2012, an additional 578 patients were assigned to 4 cycles of every 2 weeks AC and randomly assigned to weekly vs every 2 weeks paclitaxel. Updated survival was assessed using log-rank tests and Cox regression models. We compared outcomes by breast cancer subtype as well. Results At a median follow-up of 12.1 years, there were no statistically significant differences among the 4 treatment arms in disease-free survival (DFS) (P = .91) or overall survival (P = .34) in the original protocol. Among the 578 patients assigned AC for 4 cycles and randomly assigned to paclitaxel weekly vs every 2 weeks paclitaxel, there were no overall differences in DFS (P = .32) or overall survival (P = .42). Conclusion As there were no statistically significant outcome differences in DFS or overall survival between the studied schedules of AC and paclitaxel with extended follow-up in the original or revised protocol, either paclitaxel schedule may be recommended, with selection based on toxicity, cost, or patient preference.

Functional neurological disorder (FND) is a prevalent neurologic condition, yet existing treatment approaches yield inconsistent outcomes. We propose a unifying framework that conceptualizes FND as a disorder triggered and perpetuated by individuals lacking targeted tools to reconcile the cumulative impact of intolerance of uncertainty (IU) and multidimensional allostatic overload. Expanding upon predictive coding and IU theories from neuroscience and psychology research, we argue that during times of uncertainty, individuals with FND exhibit a higher rate of prediction error but lack the energy, resources, and adaptive capacity to respond. This sustained hyperactivation of the brain and body trigger and perpetuate FND. We propose that FND treatment requires a strategic and progressively tiered behavioral approach. First, the individual with FND must be taught behavioral skills to gain immediate symptom control and shift automatic, hyperactive processes into conscious awareness. Only then, can practices from Acceptance and Commitment Therapy, Dialectical Behavioral Therapy, and Mindfulness Therapy be leveraged. These practices help explicitly identify sources of uncertainty and teach how to effectively respond to hyperactive processes with skills that optimize function, commitment to values, and well-being. This framework offers testable hypotheses and a pathway to more effective, individualized care for FND.

Abstract Background Ceftriaxone-resistant Escherichia coli infections are increasingly common, partially because of the emergence of E. coli sequence type 131 (ST131), including its subclade C2/H30Rx, which produce extended-spectrum β-lactamases. Methods A prospective cohort including 14 US sites, which enrolled monomicrobial ceftriaxone-resistant and susceptible E. coli bloodstream infection (BSI) cases in a 1:1 ratio, was used to compare ST131 versus non-ST131 E. coli BSI, with specific attention to E. coli ST131 C2/H30Rx. Desirability of outcome ranking was determined at 30 days after infection onset. Results This analysis included 282 patients with E. coli BSI; 43% (121/282) were E. coli ST131 and 23% (66/282) belonged to the C2/H30Rx subclade. Resistance to ceftriaxone was present in 79% (96/121) ST131, 86% (57/66) E. coli ST131 C2/H30Rx, and 27% (43/161) E. coli non-ST131. Compared to patients with non-ST131 E. coli BSI, patients with ST131 BSI were older (median 70 years, [Q1 62, Q3 76] years vs 65 years, [51, 74]; P = .005) and more often admitted from long-term care facilities (21/121 [17%] vs 7/161 [4%], P &lt; .001). Overall and empiric carbapenem use was more frequent in the treatment of patients with ST131 BSI compared with non-ST131 BSI (overall 89/121 [74%] vs 50/161 [31%]; empiric: 58/121 [48%] vs 31/161 [19%], P &lt; .001). Desirability of outcome ranking outcomes were similar between groups. Conclusions Most ceftriaxone-resistant E. coli from US patients with E. coli BSI belong to ST131, particularly E. coli ST131 C2/H30Rx, serving as an important driver of carbapenem use.

369 Background: MRI-guided transurethral ultrasound ablation (TULSA) uses MRI to target, monitor, and control thermal ablation of prostate tissue with high intensity directional ultrasound, demonstrating favorable histologic control and preservation of genitourinary function in single-arm studies [1,2]. CAPTAIN (NCT05027477) is a post-market, multi-center randomized controlled trial (RCT) of TULSA vs RARP for intermediate-risk prostate cancer, and is the first such study to meet its enrolment target. Here we compare baseline patient characteristics, treatment parameters, and periprocedural outcomes. Methods: CAPTAIN enrolled men with treatment-naïve, organ-confined, Grade Group 2 or 3 prostate cancer at 23 centers including academic and private clinics in the USA (20), Canada (2), and Finland (1). Patients were randomized 2:1 to TULSA or RARP, without crossover. Endpoints include pad-free urinary continence (EPIC) and erections sufficient for penetration (IIEF Q2) at 1 year, salvage treatment at 3 years, and survival to 10 years. Periprocedural metrics include length of stay, blood loss, catheter time, and 30-day patient diary (EQ-5D-5L, NRS pain score). Results: 211 patients were treated from Jan 2022 to Aug 2025 (70% TULSA, 30% RARP), surpassing the enrolment target of 201. Arms had similar baseline characteristics: median (IQR) age for TULSA vs. RARP was 63 (58–68) vs 65 (60–69) years (p=0.12), PSA was 6.5 (4.9–9.6) vs 7.2 (5.6–9.7) ng/mL (p=0.63), Grade Group 2/3 proportions were 76%/24% vs 77%/23% (p=0.88). RARP involved bilateral, unilateral, or no nerve sparing in 89%, 5.7%, and 5.7% of cases. TULSA ablation plans included whole-gland (68%) and ≥hemi-ablation (32%). Median (IQR) blood loss was lower during TULSA vs RARP: 0 (0–0) vs 100 (100–200) mL (p<0.001). Hospital stay was shorter for TULSA: 0.29 (0.27–0.32) vs 1.24 (1.12–1.36) days (p<0.001). Catheter duration was longer post-TULSA: 13 (11–15) vs 8 (8–10) days (p<0.001). Patients reported lower NRS pain scores after TULSA to post-operative day 6, and less decline in overall health on the EQ-5D-5L 0-100 visual analog scale over 30 days (p<0.05). Fewer patients reported extreme inability on EQ-5D-5L after TULSA vs RARP over the first month for mobility (0% vs 15%), self-care (1% vs 18%), and usual activities (18% vs 38%) (all p<0.05). Conclusions: CAPTAIN is the first multicenter RCT comparing ablation to radical prostate cancer treatment to meet its enrollment target. Early perioperative results from CAPTAIN demonstrate that TULSA had no blood loss or overnight hospitalization, reduced post-procedural pain, and faster return to baseline activities and overall health. Data collection to 1 and 3 years post-treatment continues to readout of the primary safety and oncological outcomes. [1] Klotz et al 2021, JUrol 205(3):769-779. [2] Eggener et al 2024, UrolOnc 42:S83. Clinical trial information: NCT05027477 .

476 Background: Lack of standardized reporting and collection of patient-reported outcomes (PROs) limits cross-trial comparisons of first-line IO-based regimens for mRCC. Prospectively collected real world data may fill this important knowledge gap. Pts with stable/improved QoL at 3 mo versus baseline have longer median OS than pts with worse/unobserved HRQoL versus baseline (Cella, 2024). Methods: ODYSSEY is a multi-site, prospective observational study of 468 US pts with mRCC. Pts must have mRCC (any histology), no prior systemic therapy (ST), and follow up at a PCORnet study site. Exclusion criteria include treatment for cancer except mRCC. Descriptive statistics are used to show PRO score changes from baseline. We evaluate longitudinal change from baseline in PRO scores using least squares mean (LSM). Minimally important differences (MID) are 3 points for FKSI-19 total score, 1 point for the FKSI-Disease Related Symptoms (DRS) subscale and 7 points for FACT-G. Higher score indicates better QOL. The primary objective is to determine patterns of change in QOL and symptom burden of pts with mRCC. Results: As of 10/1/25, 360 pts were managed with ST, including 266 pts on IO-based combinations: 35 cabozantinib + nivolumab (C+N), 49 lenvatinib + pembrolizumab (L+P), 40 axitinib + pembrolizumab (A+P), and 142 ipilimumab + nivolumab (I+N). Overall median follow-up is 12.1 mos (IQR 6, 24). Age, sex and race were similar across regimens. Prior nephrectomy (50%) was lower than in trials. C+N and L+P pts had less clear cell (56 and 65%) versus A+P and I+N pts (94 and 82%). A+P pts had more favorable IMDC risk (19%) and less poor risk (14%). Baseline QOL was variable across regimens, with L+P generally the lowest. Absolute changes in PROs from enrollment to mo 3 (early change) by regimen are shown in the Table. LSM change from baseline in FKSI-19 and FKSI-DRS favored IO-IO versus IO-TKI at 3 mos but not at 6 mos (not shown). Conclusions: While early change in PROs did not meet the MID threshold between the IO-TKI and I+N cohorts, different patterns of early change are apparent among specific IO-TKI regimens. IO-TKI regimens exhibited higher variation in early PRO change vs I+N. As the data matures, we will associate baseline PROs and early PRO changes with early death and other outcomes. Clinical trial information: NCT04919122 . 3 month change. Instrument C+N (N=35) L+P (N=49) A+P (N=40) All IO-TKI(N=124) I+N(N=142) FKSI-19, N (%) 26 (74) 33 (67) 33 (83) 92 (74) 104 (73) Mean (SD) -0.3 (11) 2.8 (13) -3.2 (12) -0.2 (12) 0.7 (10) Median (IQR) 1.4 (-7, 6) 5.0 (-7, 11) -1.0 (-14, 5) 1.4 (-10, 8) -0.3 (-5, 6) FKSI-DRS, N (%) 26 (74) 33 (67) 33 (83) 92 (74) 104 (73) Mean (SD) -0.8 (5) 1.5 (7) -1.8 (6) -0.3 (6) 0.8 (5) Median (IQR) -0.5 (-5, 3) 2.0 (-5, 5) -1.0 (-5, 3) 0.0 (-5, 4) 0.0 (-2, 4) FACT-G, N (%) 27 (77) 32 (65) 29 (73) 88 (71) 102 (72) Mean (SD) 2.1 (14) 5.2 (16) -3.5 (15) 1.4 (15) 0.3 (13) Median (IQR) 4.0 (-4, 10) 1.2 (-6, 13) -6.4 (-11, 4) 1.6 (-8, 10) 1.6 (-7, 8)