Citations

Abstract Introduction: Pathological complete response (pCR) is a strong prognostic marker, but survival outcomes comparing treatment to control do not reliably align with treatment-control differences in pCR rates in breast cancer. A novel Bayesian hierarchical framework models treatments within trials, allowing us to predict treatment effects on distant recurrence-free survival (DRFS) from pCR with greater accuracy. Methods: We analyzed 12 neoadjuvant breast cancer trials (6,000 patients, all HR/HER2 subtypes; including I-SPY2). The framework of Burzykowski, Molenberghs & Buyse (2005) is extended to a novel arm-based hierarchical structure providing a distribution of pCR and DRFS treatment effects controlling for subtype (HR/HER2), N and T stage, grade, and calendar year. Three held-out trials (877 patients; 26 regimens; med follow-up >4 years) validate predictions of DRFS treatment benefit from pCR. All data was used to estimate treatment-effect correlation and the surrogate threshold effect (STE). Analyses were repeated for Residual Cancer Burden Index (binary RCB01, continuous RCB). Results: Predicted probability of DRFS benefit closely matched actual DRFS follow-up (mean absolute error 0.06; Pearson r = 0.9). Across all trials, pCR showed moderate surrogacy (ρ = 0.82, R2 = 0.67). A 60% increase in pCR odds achieves ≥95% probability of DRFS benefit (STE = OR of 1.60). RCB outperforms pCR across all metrics, with 92% sensitivity and 93% specificity for detecting DRFS benefit in 26 validation regimens (Table 1). Conclusion: This novel Bayesian meta-analytic framework reveals that pCR, RCB01 and continuous RCB reliably predict survival benefit across heterogeneous trials, with RCB performing the best in an external validation. This provides a statistical foundation for accelerated approval decisions using robust early biomarkers in modern neoadjuvant trial designs by accurately predicting survival at the treatment arm level. Citation Format: Keli S. Santos-Parker, Jessica R. Santos-Parker, W. Fraser Symmans, Laura J. Esserman, Christina Yau, Angie DeMichele, Laura van't Veer, Doug Yee, Fabien Reyal, Helena Earl, Jean Abraham, David Cameron, Peter Hall, Judy Boughey, Matthew Goetz, Gabe Sonke, Miguel Martín, Sara López-Tarruella, Priyanka Sharma, Rachel Freiberg, Jane Perlmutter, Aditya Bardia, Martin Eklund, Rachel Freiberg, Lajos Pusztai. A novel statistical framework for surrogate endpoint prediction of survival in neoadjuvant breast cancer trials [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 1401.

Abstract Frailty predicts adverse outcomes in multiple myeloma (MM), yet an objective frailty biomarker is lacking. Circulating senescence-associated secretory phenotype (SASP) factors correlate with frailty and adverse outcomes in chronic diseases, but their relevance in MM is unclear. In this study, we investigated the relationship between 36 plasma SASP factors, frailty, and clinical outcomes in: (1) a historical cohort using stored specimens from 59 patients with newly diagnosed MM, and (2) a prospective cohort of 36 patients initiating new MM treatment. Several SASP factors were significantly associated with frailty after adjusting for age, sex, and body mass index; GDF-15, TNF-RI, IL-6, and IL-8 showed positive correlations with both cumulative-deficit based and physical frailty indices. Additionally, significant age-adjusted associations were observed between SASP factors and treatment outcomes, including overall survival (OS), high-grade toxicity, and healthcare utilization. We developed a 5-factor SASP model that demonstrated superior predictive performance for OS compared to chronological age, R-ISS stage, and clinical frailty, and TNF-RI alone (5-year OS AUC: 0.90). These findings highlight the association between senescence biomarkers and frailty and OS, and support further investigation of SASP factors as objective frailty biomarkers in MM.

Abstract Myocardial infarction (MI) triggers a systemic neutrophil response, yet the roles of distinct neutrophil subsets in cardiac remodeling remain unclear. Studying this requires murine models that accurately mirror human neutrophil dynamics. Here, we show that a minimally invasive intact-chest MI model is more pathophysiologically relevant than the standard open-chest approach for investigating post-MI immune responses. In the open-chest model, surgical trauma disrupts bone marrow homeostasis, releases large numbers of immature neutrophils, and masks MI-specific immune mechanisms. In contrast, the intact-chest model preserves bone marrow integrity and induces only a modest rise in circulating immature neutrophils, closely reflecting MI patient profiles. We further demonstrate that accumulation of immature neutrophils in the infarcted heart exacerbates cardiac dysfunction. Beyond neutrophils, the overall cardiac immune landscape differs markedly between both models. Collectively, our findings establish the intact-chest model as superior for studying post-MI inflammation and reveal immature neutrophils as mediators of adverse cardiac remodeling.

ABSTRACT Background Sunlight has profound impacts on physical and mental health, beyond vision, including effects on circadian rhythms, alertness, mood, and sleep. A family history of any mood disorders is strongly associated with psychiatric disorders including bipolar disorder. The purpose of this study was to evaluate the association between a family history of any mood disorder in patients with bipolar I disorder and solar insolation at varied international onset locations. Methods Data for this analysis were available from 5842 patients with a diagnosis of bipolar I disorder obtained at 83 collection sites in both hemispheres. This included 4752 patients from 71 collection sites in the northern hemisphere and 1090 patients from 12 collection sites in the southern hemisphere. Patient data variables were obtained from records or interviews. Solar insolation data were obtained from The National Aeronautics and Space Administration (NASA) Power database for each onset location, and the ratio of the mean monthly minimum/mean monthly maximum solar insolation was calculated. Typically, the ratio is largest near the equator (little yearly change in solar insolation) and smallest near the poles (large yearly change in solar insolation). Results A significant relationship was found between a family history of any mood disorder, the ratio of the mean monthly minimum/mean monthly maximum solar insolation, and gender. The odds of a family history of mood disorder increased as patient location nears the poles and decreased near the equator. Female gender also increased the odds of having a family history of a mood disorder. Conclusions This study highlighted the association between family history, solar insolation, and gender in international patients with bipolar I disorder. Given the profound effects of sunlight on human health, the family of patients with bipolar disorder who live in the same location with the same solar insolation, and especially females, may be at increased risk for a mood disorder.

ABSTRACT Background Acute heart failure (AHF) exhibits marked heterogeneity in diastolic hemodynamics, yet comprehensive echocardiographic assessment of diastolic function (DF) and filling pressure (FP) is often infeasible. We evaluated whether artificial intelligence–enabled electrocardiography (AI-ECG) could provide scalable DF grading and FP estimation in hospitalized AHF patients. Methods We retrospectively studied adults hospitalized for AHF across Mayo Clinic sites (2013–2023) who received ≥1 dose of intravenous loop diuretic and had paired 12-lead ECG and TTE. The previously validated AI-ECG DF model was applied without retraining to generate four DF grades and a continuous FP probability. Clinical outcomes were all-cause mortality and heart failure rehospitalization. Associations with clinical severity markers and echocardiographic indices were examined. Kaplan–Meier survival analysis and adjusted multivariable Cox proportional hazards models were performed. Exploratory analyses examine the kinetics of change in FP probability and impact on mortality. Results Among 11,513 patients (median age 75 years, 39% female), AI-ECG DF grading was feasible in 100%, whereas echocardiographic DF was indeterminate in 44% of clinically eligible patients. In 2,582 patients with determinate echocardiographic DF, AI-ECG FP probability discriminated TTE Grade 2–3 dysfunction with AUC 0.85 (95% CI 0.83 – 0.86). Higher AI-ECG DF grades were associated with higher comorbidity burden, worse NYHA class, elevated NT-proBNP, higher MAGGIC scores, elevated PCWP, and more advanced structural remodeling. After multivariable adjustment, AI-ECG DF remained independently associated with mortality (hazard ratio [HR] 1.25, 95% CI 1.16–1.35 for Grade 2; HR 1.44, 95% CI 1.33–1.56 for Grade 3 versus Normal/Grade 1). Combining AI-ECG DF with MAGGIC scores yielded ordered risk gradients, with highest mortality in patients with both high MAGGIC and Grade 2–3 DF. Among patients with serial ECGs, improvement in FP probability was independently associated with lower mortality (HR 0.85, 95% CI 0.79–0.91), whereas worsening did not show a consistent adverse gradient beyond baseline DF. Conclusions In a large, geographically diverse AHF cohort, AI-ECG DF grading was universally feasible, correlated with established hemodynamic severity markers, and provided independent prognostic information beyond established risk factors, supporting its role as a pragmatic, scalable diastolic biomarker in AHF. CLINICAL PERSPECTIVE What Is New? In 11,513 hospitalized acute heart failure (HF) patients, artificial intelligence-enabled electrocardiography provided diastolic function grading in 100% of patients from a single 12-lead ECG without requiring additional clinical variables, compared with 56% feasibility for guideline-based echocardiography grading. AI-ECG diastolic function grades correlated with established marker of severity (NYHA functional class, NT-proBNP, MAGGIC risk scores, and pulmonary capillary wedge pressure) and remained independently associated with both mortality and HF rehospitalization after multivariable adjustment. Serial AI-ECG measurements identified post-discharge filling pressure trajectories, with improvement independently associated with 15% lower mortality, a first demonstration that longitudinal ECG assessment can track post-discharge hemodynamic recovery. What Are the Clinical Implications? AI-ECG transforms the universally obtained 12-lead ECG into an actionable hemodynamic biomarker that addresses the critical gap when echocardiographic diastolic function assessment is indeterminate or unavailable in acute HF patients. Despite markedly different hemodynamic severity and long-term outcomes across AI-ECG diastolic function grades, hospitalization length of stay did not differ, suggesting advanced diastolic dysfunction represents occult risk not easily recognized during routine acute care and highlighting the need for improved post-discharge risk stratification. The continuous filling pressure probability metric enables longitudinal monitoring of post-discharge hemodynamic status using serial routine ECGs, potentially identifying patients requiring intensified follow-up or specialist referral.

703 Background: The association of circulating tumor DNA (ctDNA) reduction with treatment response has been investigated across multiple malignancies. This study aims to assess the impact of ctDNA response on survival outcomes in patients receiving enfortumab-pembrolizumab (EV-P). Methods: We identified 32 patients with advanced urothelial carcinoma who received EV-P and had ≥2 ctDNA assessments with ≥1 detectable level. Deep molecular response was defined as >2-log reduction from highest ctDNA detection. Radiographic progression was determined from radiology reports documenting progression by RECIST criteria. Kaplan Meier analyses were performed to compute Hazard Ratios (HR) with 95% confidence intervals (CI) for radiographic progression free survival (rPFS), defined as time from treatment start to radiographic progression or death and overall survival (OS) defined as time from treatment start to death were computed. Log-rank tests were performed to compare PFS and OS in patients with deep molecular response to those without response. A p-value <0.05 indicated a statistically significant association with response. Results: Thirty-two patients were included (median age 71 years; range 39–90). Median follow-up was 10.6 months. At cutoff (10/1/2025), 26 patients were alive and 6 had died. Seventeen (53%) achieved a ≥2-log ctDNA reduction (responders), while 15 (47%) did not (non-responders). Progression-free survival was significantly longer in responders (log-rank P < 0.001); median PFS was 5.9 months (95% CI 2.4–NR) in non-responders and not reached in responders (HR 0.09, 95% CI 0.02–0.44; P = 0.0026). Median overall survival was 12.7 months (95% CI 10.0–NR) in non-responders versus not reached in responders (log-rank P = 0.011; HR 0.11, 95% CI 0.01–0.88; P = 0.037). At cutoff, 94% of responders and 67% of non-responders were alive. Conclusions: Achieving a >2-log decrease in ctDNA during EV + Pembrolizumab therapy was significantly associated with improved progression free and overall survival. These findings support ctDNA kinetics as a potential early biomarker of response warranting prospective validation. Clinical outcomes by >2-log ctDNA reduction status. Endpoint > 2-log drop (n = 17 ≤ 2-log drop (n = 15) Log-rank p Median (mo) ≤ 2-log > 2-log HR (95% CI) P C-index PFS 2 events (12%) 10 events (67%) 0.0002 5.9 (2.4–NA) NR 0.09 (0.02–0.44) 0.0026 0.77 OS 1 event (6%) 6 events (40%) 0.011 12.7 (10.0–NA) NR 0.11 (0.01–0.88) 0.037 0.73

Abstract Introduction Cancer clinical trials have historically faced challenges in achieving fully representative trial population, particularly in terms of including patients from diverse ethnic and racial groups, those with low socioeconomic status, and those living in rural regions. This has contributed to inequities in access to novel therapeutic options. Background The I-SPY adaptive platform trials have prioritized diversity since inception, consistently enrolling in &gt;10% of trial patients being Black and/or Hispanic individuals. The majority of participating institutions in the I-SPY 2.2 study are academic or large well-resourced health systems. In 2023, the I-SPY ACCESS (Achieving Cancer Clinical Trial Equity in Socioeconomically Diverse Sites) Initiative was launched to enhance representation by engaging and involving nontraditional trial sites- such as safety-net hospitals, community cancer centers, and rural cancer centers- that serve historically excluded patient populations. Methods The I-SPY ACCESS Initiative offers customized and personalized tailored support to under-resourced sites. This includes comprehensive feasibility and readiness assessments, onboarding guidance, enhanced site-specific training, centralized institutional review board (IRB) navigation, site peer mentorship, and educational materials for both patient and provider. Additionally, patients gain access to I-SPY advocate peer trial navigators. Sites are provided culturally responsive patient education tools- including multilingual brochures, a dedicated patient website, and content co-developed with community partners. A Clinical Trial Navigator supports both patients and sites, helping to locate logistical, social, and trial specific resources.Tools such as virtual Clinical Research Coordinators (vCRC's) and OneSource technology are deployed strategically based on assessed site need and resource availability. OneSource is an innovative platform that enables direct extraction of clinical data from electronic health records into trial databases, reducing site workload and improving data quality. Funding models are currently being explored to extend OneSource and vCRC services across more ACCESS sites. In the future, there are plans to pilot financial navigation services and integrative care resources for all patients enrolled in I-SPY with particular focus on those enrolled at ACCESS sites. Results and Progress As of June 2025, seven sites have been assessed as ACCESS sites for I-SPY 2.2, with two sites having successfully completed activation and currently enrolling participants. Beginning in mid-2024, one DCIS RECAST ACCESS site has been activated and 11 additional sites are in the onboarding process. The modest pace of I-SPY 2.2 activation reflects the complexity and operational demands associated with resource-intensive platform trial. In contrast, the DCIS RECAST protocol was designed with a lower burden, facilitating easier implementation by under-resourced sites, reflected by increased interest in the study among ACCESS sites. The ACCESS framework is being explored for potential future application in the Pre I-SPY Phase 1 platform trial, particularly considering the historical underrepresentation of such sites in the early-phase clinical research. Conclusion and Future Goals The I-SPY ACCESS initiative demonstrates that investing in thoughtful, innovative, and effective means for trial delivery, as well as incorporating community-based support, can strengthen representation in complex, adaptive breast cancer trials. The initiative offers a flexible, equity-driven framework that is impactful now and scalable for future innovation in oncology research. Citation Format: S. L. Horton, D. A. Idossa, K. C. Hewitt, J. Perlmutter, L. Van't Veer, N. Hylton, A. Borowsky, F. Symmans, D. Yee, C. Yau, P. Pohlmann, J. Boughey, L. Esserman. Expanding Diversity through Innovation: Development of the I-SPY ACCESS Initiative for the I-SPY2.2 and DCIS RECAST Clinical Trials [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-09-08.

Abstract Background: Advances in oncology, particularly the adoption of immunotherapies and antibody-drug conjugates, are transforming the nature and frequency of adverse events (AEs). These AEs come with both short and long-term symptoms that significantly impact patient quality of life. Monitoring for early onset of symptoms could optimize personalized therapy, maximizing potential efficacy while mitigating toxicity. It is also possible that some toxicities are directly associated with drug sensitivity. We sought to identify symptoms associated with pathologic complete response (pCR) using patient-reported outcomes (PROs) in early-stage high-risk breast cancer patients. Methods: Our study population included 288 stage II/III high-risk breast cancer patients enrolled on the I-SPY2 trial from 2021-2024, who received IO and ADC neoadjuvant therapies ± standard paclitaxel. pCR was defined as tumor absent in breast and nodes at surgery following neoadjuvant treatment. Patients (n = 288) were sent electronic PROs. 33 patient-reported AEs were measured using NCI's Patient Reported Outcomes - Common Terminology Criteria for Adverse Events (PRO-CTCAE). Each symptom was evaluated using severity, frequency, and interference on a Likert Scale. Presence of early PRO symptoms (cycles 1-3 of treatment) were categorized (at least one of moderate or greater), and odds ratios were computed with pCR as outcome. To assess whether higher grade AEs were enriched in patients that achieved a pCR, we also performed the Wilcoxan Rank Sum test using maximum (worst) symptom severity. Breast tumor volume was measured by MRI at baseline and again at cycle 3 (∼day 21 from treatment start). Functional tumor volume (FTV) was computed from MR images by using enhancement thresholds. and percent change from baseline (ΔFTV) was calculated. Reduction in FTV was defined as a positive change. The Benjamini-Hochberg method was used to adjust for multiple hypothesis testing. Results: Of 288 patients included in our analysis (median age = 48 years, range = 20-78, pCR rate = 29%), 203 (70.5%) were White, 17 (5.9%) were Asian, 33 (11.5%) were Black or African American, and 35 (12.2%) were Hispanic and 89% were administered immunotherapy, 11% ADC. The pCR rate was 29%. PRO analysis revealed that patients that had moderate to severe muscle pain (27% vs 10% OR = 3.15, P &lt; 0.05), joint pain (22% vs 8% OR = 3.23, P &lt; 0.05), headache (27% vs 12.5% OR = 2.59, P &lt; 0.05), or mouth/throat sores (16% vs 5% OR = 3.56, p &lt; 0.05) within weeks 1-3 had higher odds of achieving a pCR. Maximum severity between weeks 1-3 was associated with pCR. Patients that achieved a PCR had higher grade muscle pain (P &lt; 0.05), heart rates of palpitations (P &lt; 0.05), and significantly lower grade numbness and tingling (p = 0.002). Additionally, of the symptoms assessed, frequency, interference, and severity of arm or leg swelling was significantly correlated with reduction in tumor volume (FTV) during weeks 1-3 treatment (Bonferroni corrected P&lt;0.01). Beyond 6 weeks, associations were weak or insignificant. Conclusion: Our study utilizes a computational framework that defined sentinel symptoms such as muscle and joint pain, mouth/throat sores, headache, and swelling, as early as weeks 1-3 that were associated with a favorable tumor response. This may suggest an early immune reaction in patients that eventually respond favorably to treatment, and prioritization to continue these patients on treatment may be warranted. Our work can help provide earlier proactive monitoring to mitigate toxicities, to enhance treatment response, and a potential symptom-based early understanding to personalize treatment efficacy. Citation Format: A. Basu, S. Umashankar, C. Yau, K. J. Ruddy, A. H. Blaes, D. M. Wolf, A. DeMichele, J. Perlmutter, D. Yee, A. B. Olshen, L. J. van't Veer, R. A. Shatsky, C. Isaacs, R. Nanda, H. S. Rugo, M. E. Melisko, N. Hylton, L. J. Esserman, D. L. Hershman, I-SPY Trial Investigators and Patient Advocates.. Early Adverse Symptoms Predict Response to Treatment Among Patients in the I-SPY Trial [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr RF1-04.

Abstract Background: Breast cancer (BC) chemoprevention with selective estrogen receptor modulators (SERMs) and aromatase inhibitors (AIs) remains underutilized among high-risk women. Improving knowledge about BC risk and chemoprevention among high-risk patients and their healthcare providers may enhance informed decision-making about this BC risk reduction strategy. Methods: We conducted a cluster randomized controlled trial to evaluate the effectiveness of web-based patient and provider decision support, RealRisks and BNAV, to improve chemoprevention informed choice among women with atypical hyperplasia (AH) or lobular carcinoma in situ (LCIS). Thirty-one sites, including academic and community practices across the U.S., were randomized to standard patient educational materials alone or combined with RealRisks and BNAV. A total of 412 patients and 210 healthcare providers were enrolled. Patient surveys were administered at baseline, 6 and 12 months. The primary outcome at 6 months was chemoprevention informed choice, defined as adequate chemoprevention knowledge and attitudes congruent with decision. Secondary endpoints included BC risk perceptions, worry, chemoprevention knowledge, decision conflict and chemoprevention decision. Assuming 10% loss to follow up (LTFU), roughly equal accrual across sites, and an intraclass coefficient (ICC) of 0.02, we had 90% power to detect a 15% absolute difference in informed choice if the event rate in the control arm was 10%. Results: Among 24 evaluable sites, 14 were randomized to the intervention arm and 10 to the control arm. Among 210 enrolled providers, median age was 46 (range, 28-83) and 78% were female; 75% physicians and 25% advanced practice providers/nurses; 53% medical oncologists, 29% surgeons, and 10% gynecologists/family practitioners/internists; and 83% had previously prescribed chemoprevention. Among 412 enrolled patients, median age was 53 (range, 35-74), including 77% White, 8% Black, and 10% Asian race, and 14% Hispanic ethnicity. In terms of BC risk factors, 77% had AH and 23% LCIS, 34% had a first-degree family history of BC, and 65% had heterogeneously or extremely dense breasts on mammography. Thirty percent were unevaluable for the primary endpoint (1% ineligible, 26% LTFU, 3% missing data). Among 288 evaluable patients (148 at intervention sites, 140 at control sites), the proportion of patients exercising informed choice at 6 months in the intervention and control arms was 35% vs. 27%, respectively (odds ratio [OR]=1.44, 95% confidence interval [CI]=0.84-2.46, p=0.19; observed ICC=0.006). Compared to patients in the control arm at 6 months, those in the intervention arm were more likely to have accurate BC risk perceptions (OR=1.80, 95% CI=1.11-2.91) and adequate chemoprevention knowledge (OR=1.62, 95% CI=1.00-2.61). We observed no significant differences in BC worry, decision conflict, or chemoprevention decision between study arms. At 6 months, 49% of women in the control arm and 51% in the intervention arm decided to take a SERM or AI for BC chemoprevention (p=0.58), a rate higher than anticipated. Conclusions: We did not observe a significant increase in informed choice among patients and providers assigned to chemoprevention decision support compared to standard educational materials alone. Among women with AH or LCIS seen mainly by breast specialists who prescribed chemoprevention, about half decided to take a SERM or AI. Therefore, relatively high chemoprevention uptake may be achieved among women with high-risk breast lesions managed by breast specialists. Chemoprevention decision support may improve decision antecedents, such as accurate BC risk perceptions and chemoprevention knowledge, but may have a limited role in changing health behaviors. Citation Format: K. D. Crew, G. L. Anderson, K. B. Arnold, A. Michel, M. T. DeLucie, C. W. Law, S. Pruthi, A. C. Sandoval Leon, R. Shirley, M. T. Grosse Perdekamp, S. V. Colonna, S. L. Krisher, T. King, L. D. Yee, T. J. Ballinger, C. Braun-Inglis, D. A. Mangino, K. B. Wisinski, C. A. DeYoung, M. Ross, J. D. Floyd, A. Kaster, L. VanderWalde, T. Saphner, C. Zarwan, S. Lo, C. Graham, A. K. Conlin, K. J. Yost, D. M. Agnese, C. Jernigan, D. L. Hershman, M. L. Neuhouser, J. A. Zell, B. Arun, R. Kukafka. Making informed choices on incorporating chemoprevention into care (MiCHOICE): Cluster randomized controlled trial of decision support for breast cancer chemoprevention, SWOG 1904 [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-01-15.