Le‐Rademacher, Jennifer

Importance Decentralized clinical trials (DCTs) aim to increase trial access for underrepresented populations (URP) and ensure study outcomes, conclusions, and policy-related decisions are applicable to diverse populations. Objective To assess trends in the percentage of accrued participants from more than 120 miles from the research site upon DCT program implementation. Design, Setting, and Participants This descriptive quality improvement study was conducted from January 2024 to March 2025 at Mayo Clinic, a US multiregional, academic medical center (AMC) comprising 3 sites and an affiliated, community-based health care system. All individuals who consented and/or accrued to an institutional review board–approved clinical trial were included. Exposure DCTs are defined as trials with at least 1 decentralized capability beyond remote consent. DCT program development began July 2022. By January 2024, remote consent, video telehealth visits, remote phlebotomy, and device services were implemented across all sites and departments. Remote monitoring and oral medication delivery were available on a limited basis. Prospective automated program and DCT participant data collection and quarterly reporting began in January 2024. Main Outcomes and Measures Percentage of all DCT accrued participants with a residential zip code more than 120 miles from 1 of 3 AMC sites. Results There were 7469 participants (median [IQR] age, 62 [51-70] years; 3594 [48.1%] female; 241 [3.2%] Asian, 391 [5.2%] Black or African American, and 6347 [85.0%] White individuals) accrued to 765 DCTs. During the study period, the percentage of DCT participants residing more than 120 miles from an AMC site ranged from 18.9% in the first quarter (Q1) of 2024 (383 of 2032 participants) to 29.6% in Q1 of 2025 (346 of 1170 participants). Of those accrued, 1147 (15.4%) were of a racial or ethnic URP, ranging from 12.5% in Q1 of 2024 (253 participants) to 17.4% in Q1 of 2025 (204 participants). There were 1554 (20.8%) participants from a rural location, ranging from 16.6% in Q1 of 2024 (338 participants) to 24.9% in Q1 of 2025 (291 participants). Additionally, by geospatial distance from an AMC site, the male-to-female ratio was nearly 50:50, and the age distribution appeared similar. Conclusions and Relevance In this quality improvement study of a DCT program implementation, DCT accruals trended favorably among those residing more than 120 miles from an AMC site and those of rural or URP populations. While these findings cannot be directly attributed to program implementation, they are reassuring that this strategy may address some barriers to clinical trial access. Future studies should assess the sustained effectiveness and scalability of DCT models in improving equitable trial access.

Abstract Background Older adults remain underrepresented in prospective trials of immunotherapy for advanced lung cancer. To estimate pembrolizumab adverse events, we conducted a multicenter, nonrandomized, open-label phase 2 trial of oncologist-choice first-line pembrolizumab with or without chemotherapy for older adults with advanced lung adenocarcinoma. Methods Alliance for Clinical Trials in Oncology A171901 enrolled patients aged 70 years and older with stage IV or recurrent lung adenocarcinoma starting oncologist’s choice of first-line pembrolizumab with or without carboplatin and pemetrexed. The primary endpoint was the proportion of patients experiencing a solicited grade 3 or greater adverse event within 6 months. Secondary endpoints included overall survival, quality of life, and association of a geriatric assessment toxicity risk score with severe adverse events. Results Among 95 evaluable patients, 43 (45.3%) received pembrolizumab and 52 (54.7%) received pembrolizumab plus chemotherapy. Median age was 77 years (range = 70-92 years); 11.6% had an E Performance Status of 2 or higher. During 6 months of treatment, 25.6% (95% CI = 13.5% to 41.2%) experienced a solicited grade 3 or greater adverse event in the monotherapy group and 42.3% (95% CI = 28.7% to 56.8%) in the combination group. Median overall survival was 16.4 months (95% CI = 10.1 to not estimable) with monotherapy and 29.9 months (95% CI = 16.4 to not estimable) with combination therapy. Quality of life worsened during treatment. The geriatric assessment toxicity risk score was not associated with severe adverse events with pembrolizumab with or without chemotherapy. Conclusions Older adults with advanced lung adenocarcinoma receiving pembrolizumab with or without chemotherapy had comparable adverse event rates to those in prior registration trials that excluded medically frail patients. These findings can inform shared decision making and support inclusion of older adults in future trials. Clinical Trial NCT04533451 (https://clinicaltrials.gov/study/NCT04533451)

Background/Objectives. Decades of research have failed to uncover effective approaches to prevent chemotherapy-induced peripheral neuropathy (CIPN), a common side effect of neurotoxic chemotherapy. Increased interest in placebo response as a potentially under-recognized confounder in CIPN trials was recently sparked by the results of a multisite NCI-funded phase II-III CIPN prevention study of duloxetine, a promising serotonin–norepinephrine reuptake inhibitor that enhances pain-inhibitory mechanisms within the central nervous system. Study findings revealed high and nearly equivalent response rates in three randomized treatment groups—little to no CIPN was reported by 65.2%, 66.0%, and 68.0% of study participants who received duloxetine 30 mg, 60 mg, or placebo treatment, respectively. Methods. We performed a meta-analysis of placebo response rates from seven randomized, double-blinded, placebo-controlled trials conducted over the past 20 years and comprising 191 placebo participants that were specifically testing interventions for oxaliplatin- and paclitaxel-induced peripheral neuropathy and that serially collected patient responses on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire for Chemotherapy-Induced Neuropathy questionnaire. Additionally, we sought to identify trial- and patient-specific factors that predicted higher placebo response rates from a participant-level pooled analysis. Results. The placebo response rate was 10.0% [95% CI: 5.8%, 16.6%] when response was defined more conservatively as patients reporting no neuropathy at all. When the placebo response was defined more broadly based on patients reporting no or a little neuropathy, the placebo response rate was higher (39.6% [95% CI: 27.4%, 53.2%]). Male participants, receipt of oxaliplatin, and a 2:1 randomization ratio favoring the intervention arm were individually associated with a higher placebo response. Conclusions. High placebo response rates can threaten scientific progress toward identifying effective treatments for cancer treatment-associated side effects, like CIPN. Careful attention to study design factors, participant eligibility, and patient and research staff expectations may help to minimize placebo response rates in future CIPN intervention studies.

Abstract Background: Despite the decline in overall mortality and incidence of cancer in the US population, the burden of cancer is still high, especially in underserved and under-researched populations. A major contributor to poor cancer outcomes is the absence of dedicated efforts utilizing scientifically rigorous approaches and implementation strategies to optimize participant enrollment and accrual in clinical trials. The Connecting Patient Populations to Clinical Trials (CP2CT) program implements innovative multilevel interventions to enhance clinical trial awareness and optimize referral pathways that facilitate patient enrollment. The CP2CT Data, Evaluation, and Coordinating Center (DECC) supports its data and evaluation activities, and coordinates a learning collaborative towards mitigating the key barriers of cancer burden in all populations. Methods: Using an implementation science-informed approach, the DECC deployed coordinated strategies over three years: (1) administrative structuring through streamlined governance, centralized reporting, and stakeholder integration; (2) data standardization via Common Data Elements (CDEs), a cross-network REDCap system, and a multi-institution Data Transfer Agreement (DTA); (3) evaluation infrastructure through a Network Logic Model, evaluation plan, standardized constructs, and a Process Evaluation Plan with tools; (4) learning supports through an internal website and expanded Speaker Series; and (5) site-level implementation facilitation through structured visits. Results: In collaboration with the CP2CT Network and NCI, the DECC’s achievements span four domains: (1) Administrative: built infrastructure, deployed centralized reporting platforms, coordinated key meetings, and strengthened community integration. (2) Data: standardized collection, secured network-wide data sharing through the DTA, enabled harmonized multi-site reporting, and advanced groundwork for interoperability and scientific value. (3) Program Evaluation: linked CP2CT activities to measurable outcomes through a Network-wide Logic Model, guided evaluation, established shared evaluation language, and launched a transferable Process Evaluation framework. (4) Learning Collaborative: developed a centralized resource hub, expanded the Speaker Series, and advanced authorship transparency with the CP2CT Publication Policy. < Conclusion: The CP2CT DECC has established a sustainable, scalable infrastructure that integrates administrative coordination, standardized data collection, robust program evaluation, and a collaborative learning environment. These efforts enhance clinical trial awareness, optimize referral pathways, and provide a transferable model for improving participant enrollment and scientific rigor across national research networks, ultimately addressing disparities in cancer outcomes. Citation Format: Laura E. Lectora, Cristina J. Orozco, Holly A. Thorson, Timethia Bonner, Robert R. Freimuth, Jennifer G. Le-Rademacher, Folakemi T. Odedina. Building a national network coordination center for clinical trials: Early implementation outcomes from the CP2CT DECC [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 899.

Abstract Background: Multidisciplinary research networks often face challenges in harmonizing metrics and measures across participating sites, limiting the ability to aggregate data and generate generalizable insights. To address this barrier within the Connecting Patient Populations to Clinical Trials (CP2CT) Network, the Data, Evaluation, and Coordinating Center (DECC) coordinated the establishment of a unified framework that supports comparable evaluation and enhances the scientific impact of network-wide activities. Methods: Consensus was developed through a structured, iterative, and collaborative process: (1) drafting initial constructs, metrics, measures, and benchmarks informed by Network site materials and relevant literature; (2) soliciting qualitative and quantitative feedback from Network sites via Basecamp, an innovative online collaborative workspace for construct development; (3) conducting open dialogue sessions followed by systematic review and integration of site feedback; and (4) refining all elements through repeated feedback cycles until no further modifications were requested. Each iteration strengthened the clarity, coherence, and scientific precision of the final constructs. Results: A total of seven constructs were incorporated into the consensus-development process: clinical trials referral, clinical trials accrual, participants’ awareness of clinical trials, participants’ knowledge of clinical trials, providers’ awareness of NCI-supported clinical trials, providers’ engagement with NCI-supported clinical trials, and providers’ referral to NCI-supported clinical trials. For each construct, the Network established a conceptual definition (broad description of the construct), an operational definition (specification of how the construct is measured or observed), benchmarks (standards for assessing performance), metrics (quantitative indicators of performance), and measures (tools used to quantify inputs, processes, or outcomes). Common measures were developed for two constructs—clinical trials accrual and participants’ knowledge of clinical trials. Although full consensus was not achieved across all four Network sites for every construct, at least three sites reached consensus for the remaining five constructs. Conclusion: This consensus-building initiative resulted in the development of a unified, scientifically grounded framework. By harmonizing key elements related to clinical trial referral, accrual, awareness, knowledge, and provider engagement, the Network has established foundational tools that enable cross-site data comparability and facilitate more rigorous assessment of efforts to connect diverse patient populations to clinical trials. This framework positions the Network to inform strategies that improve equitable clinical trial participation. Citation Format: Folakemi T. Odedina, Jennifer Le-Rademacher, Robert Freimuth, Cristina Orozco, Laura Lectora, Timethia Bonner, Holly Thorson, Connecting Patient Populations to Clinical Trials(CP2CT) Program Evaluation Work Group, Connecting Patient Populations to Clinical Trials(CP2CT) Steering Committee. Development of and consensus building towards shared metrics, measures and benchmarks for the connecting patient populations to clinical trials (CP2CT) [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 860.

Abstract Background: The choice of analysis method and primary endpoint can have a major impact on the results of a clinical trial. The power of these analysis methods is affected by the response patterns, response distributions, autocorrelations, missing values, and the number of times the endpoint is evaluated. Guidelines are needed to help investigators select statistical methods that give investigators the best chance of finding an intervention effect if one truly exists. Methods: Monte Carlo methods were used to determine how different endpoints are affected by changes in study assumptions. Copula simulation methods were applied to prior Alliance hot flash and CIPN studies to determine which endpoints would provide the highest power for future studies. Results: Longitudinal analyses had higher power if there was a plateau response, there were fewer missing values, responses were collected more often, and there was lower correlation between responses from the same subject. Having skewed data did not greatly affect power. Prior hot flash and CIPN studies showed skewed data, plateau response rates, and very high autocorrelations. Conclusion: Hot flash and CIPN studies are more likely to find true effects if the analysis method uses data at all of the time points and adjusts for baseline. Collecting data at more time points and reducing the missing data rates also increase study power.

PURPOSE This national study was undertaken to determine screening mammography rates among transgender and gender diverse (TGD) individuals. METHODS TGD individuals and cisgender women who qualified to receive screening mammography based on American College of Radiology guidelines were identified in the longitudinal OptumLabs Data Warehouse. The primary end point was the percentage of patients who had high rates of screening (>75% recommended screenings). Multivariable analyses were conducted in a matched population of transgender men to cisgender women to identify and adjust for factors associated with high adherence. Individuals were matched at a 1:4 ratio (transgender men: cisgender women) on age, race/ethnicity, year of enrollment in their health care plan, and duration of follow-up. RESULTS This study focused on 10,478 TGD individuals (3,778 transgender men; 1,294 transgender women; 5,406 with gender dysphoria not meeting other TGD criteria, NMOT) and 6,218,369 cisgender women. For transgender men, transgender women, individuals with gender dysphoria NMOT, and cisgender women, high mammography rates were observed in 41.1% (95% CI, 39.5 to 42.6), 7.4% (95% CI, 6.0 to 8.8), 11.9% (95% CI, 11.0 to 12.7), and 38.3% (95% CI, 38.3 to 38.4), respectively ( P < .0001). When transgender men were compared with 15,112 matched cisgender women, an age-based differential association was observed between sex and high mammography rates (interaction P = .0003); compared with cisgender women, transgender men appeared more likely to manifest high rates of screening at age 40-49 years (odds ratios [ORs], 1.38 [95% CI, 1.28 to 1.50]; P < .0001) and 50-59 years (OR, 1.57 [95% CI, 1.35 to 1.81]; P < .0001) but not in the older age groups. CONCLUSION The relatively high rates of screening mammography in cisgender women and transgender men suggest clinicians are offering mammography to individuals who are at average or high breast cancer risk, as compared with cisgender women, and not to transgender women at low risk.

Background/Objectives: Results from a well-designed trial provide evidence to support approval of truly effective treatments or discontinuation of ineffective treatments. However, the information available at the time of trial design may be limited which may lead to underpowered trials. This work aims to evaluate the impact of design assumption misspecifications on the statistical power of randomized trials with survival outcomes. Methods: The impact of the design assumption misspecifications on statistical power of four different statistical methods was investigated in a simulation study. The methods include the log-rank test, MaxCombo test, the test of difference in survival probability, and test of difference in restricted mean survival time (RMST). The deviations considered include the survival rate in the control arm, the expected treatment effect in terms of magnitude and pattern, accrual rate, and drop-out rate. Results: Deviations in the control arm’s survival distribution have no impact on the power of the log-rank and MaxCombo tests but it affects the trial duration since trials designed with these tests require the total number of events to be met before the final analysis can be conducted. Misspecified treatment effect has similar effect on the statistical power of all four methods. When the proportional hazards assumption is misspecified, the RMST is more robust with a larger early treatment effect, while the survival probability and the MaxCombo tests are more robust with a larger late treatment effect and crossing hazards. Conclusions: Selecting the appropriate statistical tests to design a trial depends on the goal of the trial, the mechanism of action of the experimental treatment, the survival quantity of clinical interest, and the pattern of the expected treatment effect. The final design should be based on assumptions that are as accurate as possible, and the potential impacts of deviations from these assumptions on the trial’s statistical power should be carefully considered.

1530 Background: Regular breast cancer screening reduces mortality. The American College of Radiology (ACR) recommends annual screening mammography for asymptomatic, average risk 1) transgender and gender diverse (TGD) men (individuals assigned female sex at birth but identify as men) age 40+ and with residual breast tissue and 2) TGD women (individuals assigned male sex at birth but identify as women) age 40+ and on gender-affirming hormone therapy for 5+ years. This nationwide study investigated screening mammography in TGD individuals. Methods: Four cohorts were identified with complex algorithms of medical and pharmacy data in the OptumLabs Data Warehouse, a longitudinal, administrative insurance claims database that includes patients with commercial insurance and Medicare Advantage: 1) TGD men, 2) TGD women, 3) individuals with gender dysphoria not meeting other TGD criteria (NMOT), and 4) cisgender women -- all of whom met ACR screening criteria. The primary endpoint was the percentage of individuals with high adherence, defined as completing >75% of recommended screenings; comparisons were made across the cohorts (Chi-square test). Multivariable logistic regression was used to compare adherence between TGD men and cisgender women with adjustment for demographics and with 1:4 matching (on race/ethnicity, age group, year of healthcare plan enrollment, and duration of follow-up). Results: 10,478 TGD individuals (3,778 TGD men; 1,294 TGD women; and 5,406 with gender dysphoria NMOT) and 6,218,369 cisgender women were identified. For TGD men, TGD women, individuals with gender dysphoria NMOT, and cisgender women, high adherence was observed in 41.1% (95% confidence interval (CI): 39.5, 42.6%); 7.4% (95% CI: 6.0, 8.8%); 11.9% (95% CI: 11.0, 12.7%); and 38.3% (95% CI: 38.3, 38.4%), respectively, p < 0.0001. No screening ever in these same populations was observed in 23.6% (95% CI: 22.2, 24.9%); 81.3% (95% CI: 79.2, 83.4%), 72.8% (95% CI: 71.6, 74%), and 35.9% (95% CI: 35.8, 35.9%), respectively, p < 0.0001. When TGD men were matched and compared to 15,112 cisgender women, a differential association was observed between gender and high adherence by age group (p < 0.0001); compared to cisgender women, the likelihood of high adherence in TGD men ages 40-49 (n = 2,472), 50-59 (n = 852), 60-69 (n = 320), and 70+ (n = 134) were as follows: odds ratios (OR‘s): 1.38 (95% CI: 1.28, 1.50), p < 0.0001; 1.57 (95% CI: 1.35, 1.81), p < 0.0001; 0.812 (95% CI: 0.619, 1.065), p = 0.1316; and 1.277 (95% CI 0.835, 1.951), p = 0.2595, respectively. Conclusions: This study found that TGD men manifest relatively high adherence to screening mammography, whereas TGD women and individuals with gender dysphoria NMOT manifest low adherence. Future research should focus on improving breast cancer screening in these underserved populations.