Elsaid, Mohamed I

Abstract Background: Metformin may impact tumorigenesis directly, through effects on AMP kinase, and indirectly, through reduction in circulating growth factors such as insulin. To examine the potential preventive effects of metformin, we analyzed MD, a known risk factor for breast cancer, in participants enrolled in the NCIC MA.32 trial, a randomized, placebo-controlled trial investigating the effects of 5 years of metformin on invasive disease-free survival in women with early breast cancer. The primary aim of this companion to MA.32 (Alliance A211201) was to examine the effects of 1 year of metformin vs placebo on MD in women treated for estrogen receptor negative (ER-) breast cancer. Methods: Eligible women were enrolled on MA.32, had ER- breast cancer, had >25% MD at baseline, and had an unaffected contralateral breast. MD was calculated on the contralateral breast using Cumulus software and analyzed at baseline, 1 and 2 years. The aim was to achieve a sample size of 274 (137 per arm), which would have at least 85% power to detect a 4% difference between study arms, i.e., 5% change from baseline to one year of treatment for metformin vs. 1% for placebo, using a two-sided two-sample t-test at a significance level of 5%. The current study was activated in the United States on 8/22/2012. Enrollment was halted on 10/13/2017 with 177 participants enrolled. Results: 146 women were evaluable (66 on metformin and 80 on placebo). The mean age of evaluable women was 53.6 years (standard deviation [SD] 9.4), 88.4% were white, 31.5% had a body mass index greater than or equal to 30 kg/m2, 99.3% of participants received chemotherapy. The proportions of white women and HER2+ participants in the metformin group were higher compared to placebo ([white 92.4% vs. 85.0%] and [HER2+ 21.2% vs. 11.3%], respectively). The mean MD at baseline was 22.7% (SD 14.1%) for the group as a whole (24.5% (SD 14.5%) for the metformin group and 21.2% (SD 13.6%) for the placebo group. This is lower than the eligibility criteria (>25%MD), due to difference in methods of calculation of MD (BIRADs for eligibility and Cumulus for study analysis). At 1 year, MD decreased by 0.7% (SD 7.6%) in the metformin group and 0.2% (SD 7.3%) in the placebo group (p = 0.58). At 2 years, MD decreased by 0.7% (SD 8.0%) in the metformin group and 0.8% (SD 7.1%) in the placebo group (p=0.60). Conclusions: In a cohort of women with early ER- breast cancer, there was no significant difference in the change in MD in women treated with metformin vs. placebo. There was a non-significant trend toward decreased MD while on metformin after 1 year of treatment. The arms were well balanced, though with more white and HER2+ participants in the metformin arm. The sample size for this study was about half of what was intended thus limiting power to detect a significant difference. Additional limitations include low mean MD, which may have limited our ability to detect the benefit in those at the highest risk, and further, the Cumulus method of MD determination can be imprecise. Interestingly, trends toward decreased MD with metformin were seen in Alliance A211102, and it might be reasonable to consider further study of metformin in a select population (highest MD or atypical hyperplasia). Support: UG1CA189823, U10CA180863, CCS 707213; https://acknowledgments.alliancefound.org.Clinicaltrials.gov ID: NCT01666171. Citation Format: M. Wood, M. I. Elsaid, L. J. Grimm, H. Liu, C. Oswold, C. S. Kuzma, I. Bedrosian, J. Ligibel, P. J. Goodwin. Change in mammographic density (MD) with metformin use: Alliance A211201, A companion study to NCIC study MA.32 [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 PS3-01-30.

Abstract Immune checkpoint inhibitor–associated immune thrombocytopenia (ICI-ITP) has been described in case reports and small case series, but comprehensive data on its incidence, risk factors, clinical features, treatment, and outcomes are lacking. We reviewed medical records of all adults initiating ICI therapy between 2016 and 2023 at 29 US hospitals across 7 major cancer centers to identify patients with ICI-ITP. Multivariable logistic regression was used to identify risk factors, and Cox modeling was performed to assess the association between ICI-ITP, its severity, and mortality. Among 86 467 patients, ICI-ITP occurred in 214 (0.25%). Independent risk factors included lower baseline platelet count, combination ICI therapy, stage IV cancer, and additional immune-related adverse events. ICI-ITP occurred at a median of 8 weeks (interquartile range [IQR], 4-18) after ICI initiation, with a median nadir platelet count of 41 × 109/L (IQR, 17 × 109/L to 64 × 109/L). Patients were treated with glucocorticoids (n = 106 [49.5%]), immune globulin (n = 39 [18.2%]), and thrombopoietin receptor agonists (n = 29 [13.6%]). Recovery occurred in 161 patients (75.2%) at a median of 2.3 weeks (IQR, 1.0-5.3). Of 76 patients rechallenged with ICIs, 23 (30.3%) developed recurrent ICI-ITP. ICI-ITP and its severity were associated with higher all-cause mortality, with a nearly threefold increase in risk among patients with severe ICI-ITP than those without ICI-ITP (adjusted hazard ratio, 2.96 [95% confidence interval, 2.14-4.08]). These findings establish ICI-ITP as a rare but clinically significant complication of ICI therapy, provide, to our knowledge, the first large-scale description of its risk factors and clinical course, and underscore the importance of timely recognition and management.

Abstract INTRODUCTION Immune checkpoint inhibitors (ICIs) have emerged as a cornerstone of cancer therapy. However, despite their efficacy, ICIs can cause a unique spectrum of autoimmune toxicities known as immune-related adverse events (irAEs). In contrast to irAEs involving other organ systems, hematologic irAEs such as ICI-associated immune thrombocytopenia (ICI-ITP) are less common. As a result, existing data on ICI-ITP are largely confined to isolated case reports, single-center case series, and pharmacovigilance databases lacking granular clinical data. To address this key knowledge gap, we sought to comprehensively characterize the incidence, risk factors, clinical features, treatments, and outcomes associated with ICI-ITP. METHODS We performed a multicenter cohort study of adult patients who initiated ICI therapy at 29 hospitals across 7 major cancer centers in 11 geographically diverse states in the US between 2016-2023. ICI-ITP was defined as a decline in platelet count to <100 x109/L in the absence of an alternative more plausible etiology of thrombocytopenia. Patients with hematologic malignancies were excluded, as were those who received cytotoxic chemotherapy within 30 days prior to thrombocytopenia onset. For each patient identified as having ICI-ITP, we collected data on demographics, comorbidities, medications, laboratory values, treatments, and outcomes. All data were extracted by manual chart review. To identify risk factors for ICI-ITP and to examine its association with death, for each case of ICI-ITP we also collected data on two control patients who initiated ICI therapy at the same site and in the same year but without development of ICI-ITP. We used multivariable logistic regression to identify independent risk factors for ICI-ITP and its recovery (the latter defined according to criteria established by the ITP International Working Group). We used a multivariable Cox model to examine the association between ICI-ITP and its severity with all-cause mortality. RESULTS We identified a total of 214 patients who developed ICI-ITP among 86,648 examined (0.25%). The incidence was highly consistent across sites (range, 0.15–0.30%). Risk factors for ICI-ITP included simultaneous receipt of two different classes of ICIs, additional irAEs, and a lower baseline platelet count. ICI-ITP developed at a median of 8 weeks (IQR, 4–18) following ICI initiation. The median nadir platelet count was 41 x109/L (IQR, 17–64). Six out of 214 patients (2.8%) developed a major bleed, and 16 patients (7.5%) developed a clinically relevant non-major bleed. Cell-bound anti-platelet antibody testing was positive in 6 of 8 patients (75.0%) for whom it was assessed, and median circulating thrombopoietin levels (201 pg/mL [IQR, 178–295]) were similar to those seen in primary ITP. Treatments used included glucocorticoids (49.5%), immune globulin (18.2%), and thrombopoietin receptor agonists (13.6%). Overall, 161 patients (75.2%) recovered from ICI-ITP at a median of 2 weeks (IQR, 1–5) following ICI-ITP onset. Predictors of recovery included additional irAEs and a higher nadir platelet count. Treatment response was observed in 57.0%, 56.4%, and 58.3% of patients within 60 days following initiation of glucocorticoids, immune globulin, and thrombopoietin receptor agonists, respectively. Of 76 patients rechallenged with an ICI, 23 (30.3%) developed recurrent ICI-ITP at a median of 9 weeks (IQR, 2–15); 17 of these 23 patients (73.9%) recovered. Finally, ICI-ITP and its severity were monotonically associated with a higher risk of death (adjusted hazard ratio 2.96 [95% CI, 2.14–4.08] for those with severe ICI-ITP compared to those without ICI-ITP). CONCLUSION In this multicenter study involving patients treated with ICIs at 29 hospitals across the US, we identified 214 patients with ICI-ITP. For the first time, we characterize in detail the incidence, risk factors, clinical features, treatments, and outcomes of ICI-ITP, a relatively novel disease entity. We found that more than half of patients responded to conventional ITP-directed therapies, and that most patients rechallenged did not develop recurrent ICI-ITP. We also found that ICI-ITP was independently associated with an increased risk of death, including a nearly 3-fold increased risk in those with severe ICI-ITP. These findings highlight ICI-ITP as a rare but clinically significant complication of ICI therapy that hematologists must be equipped to recognize and manage.

Abstract Prevention trials in oncology are some of the most important cancer clinical trials that can be designed, implemented, analyzed, and interpreted. They are pivotal in the goal of stopping the development of cancer before it starts. Prevention trials are unique in that they not only have some of the same requirements and challenges as treatment trials but also have challenges that may make their design more complex. This paper aims to discuss some types of prevention trials and highlight their most common design challenges, including large sample size requirements, slow accrual rates with long accrual duration, extended follow-up periods with trial adherence issues and missing data, endpoints that require extended follow-up or have a high level of confounding, and problems with optimizing study design. This article provides real study examples and suggestions for designing prevention clinical trials while mitigating the known issues they face.

Abstract Interpreting cancer clinical trial results often depends on addressing issues of multiplicity. When testing multiple hypotheses, unreliable findings can occur by chance due to the inflation of the type I error rate, the probability of mistakenly rejecting the null hypothesis when the null hypothesis is true. In this setting, researchers may often set the type I error rate (or the alpha level) low to limit false positive findings and the interpretation of a causal relationship where none exists. Conversely, overly conservative type I error control may result in declaring findings, that do not meet multiplicity-adjusted alpha levels, as false when they are actually true, reducing opportunities for new discovery. This presentation focuses on multiplicity adjustment in the context of clinical trials conducted within the NCI’s Community Oncology Research Program (NCORP). Because federally sponsored trials often require long-term participation from patients and represent a substantial investment by taxpayers, striking the right balance between optimizing what is learned from these trials, while avoiding false positive results, should be a priority.

TPS4196 Background: Advanced BTC patients have poor prognosis. Up to 40% of BTCs have KRAS mutations and are associated with worse overall survival (OS). With a median OS of 7.7 months in KRAS wild-type compared to 1.7 months in KRAS mutated disease, these alterations are independent poor prognostic factors in BTC. Gemcitabine and cisplatin (GC) with or without immunotherapy are often used as 1st-line therapies. However, there is a lack of data on best 2nd-line regimens. mFOLFOX6 (5-fluorouracil [5-FU], leucovorin [LV], oxaliplatin) or liposomal irinotecan+5-FU+LV are options when no biomarkers are found (e.g., MSI-H, BRAFV600E, FGFR-fusions, IDH1-mutation, HER2-overexpression). Prior studies do not demonstrate benefit with MEK inhibitors (MEKi), but none of the studies had biomarker selection. Pre-clinical studies in BTC cell lines suggest synergy between MEKi and 5-FU. Thymidylate synthase (TS )levels induced by 5-FU are downregulated by addition of binimetinib. Early clinical studies show safety and tolerance of this combination. In this study, we will evaluate if the combination of mFOLFOX6+binimetinib improves OS for patients with BTC and MAPK mutations compared to mFOLFOX6 alone in 2nd-line therapy. Methods: EAY191-A6 is a treatment study arm of the NCI ComboMATCH master registration trial EAY191. The A6 trial has a randomized phase II design, enrolling a maximum of 66 patients. Patients with any MAPK pathway mutations except those with available therapies will be eligible. Patient must first enroll to the EAY191 master trial. Local molecular results may be used for enrollment. Submission of tissue at baseline is mandatory. Eligible patients will be randomized 1:1 to mFOLFOX6 vs mFOLFOX6 + binimetinib (45 mg oral twice a day every 14 days). Stratification factors include location and stage of disease. Primary efficacy analysis will compare OS in the intent-to-treat population. If the observed hazard ratio (HR) of experimental arm vs standard of care is < 0.545 (corresponding to an observed increase in OS by 5 months or longer), experimental treatment will be considered superior. An interim futility analysis at 50% of expected events will be conducted. If the observed HR is ≥ 1, experimental treatment will not be considered superior, and accrual maybe suspended. Secondary endpoints include progression-free survival, objective response rate, duration of response, disease control rate and toxicity of treatments. Exploratory objectives include prognostic modeling, correlations of genomic alterations with response or resistance and use of machine learning for outcome prediction. This study is active and open to accrual. Clinical trial information: NCT05564403 .