6520 Background: Increased patient engagement in decision making may mitigate disparities in breast cancer surgical care. Socioeconomically disadvantaged patients disproportionately experience barriers to engagement. Decision aids (DA) increase engagement by providing information, establishing role expectations during the consult, and increasing confidence in surgeon interactions. The objective was to test the effectiveness of a surgical web-based DA in increasing engagement among breast cancer patients in clinics that care for a high proportion of socioeconomically disadvantaged patients. Methods: A stepped wedge trial was conducted with 10 NCI Community Oncology Research Program clinics (Alliance for Clinical Trials in Oncology Research Base, 6/19-12/21). Clinics were randomized to time of transition from usual care (UC) to delivery of a web-based DA. Patients with stage 0-3 breast cancer eligible for surgery provided consent prior to a surgical consult. Socioeconomic disadvantage was assessed with the Area Deprivation Index measured at the zip+4 level and dichotomized. Patient engagement was measured by Patient’s Self-Efficacy in Patient-Physician Interactions (PEPPI-5, follow-up survey) and count of Active Patient Behaviors (Street protocol, audio recorded consult). Intervention effects were tested with linear mixed-effects models, accounting for surgeon and clinic-level clustering, time, and enrollment post-COVID. Heterogeneity of treatment effect by socioeconomic disadvantage was assessed with an interaction term. Results: 573 patients enrolled. 44% (136/309) reviewed the DA. No significant difference in engagement was observed comparing DA and UC for PEPPI-5 (-0.80 [95% CI -2.13, 0.54], p = 0.24) or Active Patient Behaviors (2.52 [CI -4.11, 9.15], p = 0.46). Enrollment post-COVID was associated with increased Active Patient Behaviors (9.59 [CI 1.76, 17.43], p = 0.02) but no change in PEPPI-5 (-1.31 [CI -2.88, 0.26], p = 0.10). No heterogeneity of treatment effect was observed. Conclusions: In this trial conducted in clinics that serve diverse populations, no significant relationship was observed between a web-based DA and patient engagement. Conducting this stepped wedge trial during the pandemic was challenging. Future analyses will explore the impact of COVID on outcomes and effect of the decision aid for patients who reviewed it. UG1 CA189823; AHRQ R01HS025194; https://acknowledgments.alliancefound.org . Clinical trial information: NCT03766009 . [Table: see text]
Surgical care and outcomes in older patients with cancer through implementation of a pre-surgical toolkit (OPTI-Surg): Interim results of a phase III cluster randomized trial (Alliance A231601CD).
1541 Background: Frailty is common in older adults undergoing major cancer surgery. Mounting evidence indicates multimodal interventions to optimize patient functional status by addressing vulnerabilities associated with frailty before surgery result in decreased complications and enhanced functional recovery. This study tested the effectiveness of OPTI-Surg, a surgical prehabilitation toolkit for improving surgical care and outcomes in older patients undergoing major cancer surgery. Here, we report results from the planned futility interim analysis (IA). Methods: Thoracic (T), gastrointestinal (GI), and urologic (GU) oncological surgery practices affiliated with NCI’s Community Oncology Research Program were randomized 1:1:1, stratified by practice type, to usual care (control), OPTI-Surg toolkit, or OPTI-Surg with an implementation coach. The toolkit was implemented at the practice level. It consisted of the 12-item Edmonton Frail Scale and guided recommendations for interventions directed at identified vulnerabilities. Eligible patients were adults ≥70 years old undergoing curative intent surgery for lung, gastrointestinal, or urologic cancers. Primary outcome was 8-week post-operative function (weekly caloric expenditure) derived from the validated Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire. A linear mixed model was used to compare usual care to the 2 OPTI-Surg arms combined, controlling for baseline function. Results: From July 2019 to October 2021, 225 patients, 50% of the total accrual goal, were enrolled from 29 practices, triggering the IA. Study was suspended to new patient accrual March to June 2020 due to the COVID-19 pandemic. There were no differences in demographics by arm (mean age 76.2 years; 46.4% women; 79.6% white; 20.4% lung resection, 69.8% major GI surgery, 9.8% total cystectomy). Of the 225 patients, 140 (47 Usual Care, 93 OPTI-Surg) were evaluable for the IA. There was no significant difference in post-operative function between OPTI-Surg and usual care (mean decrease of 0.59 kCal/week for OPTI-Surg patients and 0.19 kCal/week for usual care patients, p = 0.762, intraclass correlation = 0.033). Based on the futility analysis, the DSMB recommended closure of recruitment on September 16, 2022. Conclusions: Implementation of the OPTI-Surg toolkit did not significantly improve functional outcomes 8 weeks after surgery for patients aged 70 and older undergoing major cancer surgery compared to usual care. Future analysis of implementation and ethnographic data may identify reasons why significant differences between the intervention and usual care arms were not observed, potentially including disruptions due to the COVID-19 pandemic. Clinical trial information: NCT03857620 .
Outcomes of Older Adults With AML Treated in Community Versus Academic Centers: An Analysis of Alliance Trials
PURPOSE: Clinical trials are important for managing older patients with AML. We investigated differences in outcomes of older patients with AML on the basis of whether patients participated in intensive chemotherapy trials at community versus academic cancer centers. METHODS: We used data from the Alliance for Clinical Trials in Oncology phase III trials that enrolled patients age ≥ 60 years with newly diagnosed AML between 1998 and 2002 in the Cancer and Leukemia Group B (CALGB) 9720 trial and between 2004 and 2006 in the CALGB 10201 trial. Centers funded by the NCI Community Oncology Research Program were identified as community cancer centers; others were designated as academic cancer centers. Logistic regression models and Cox proportional hazards models were used to compare 1-month mortality and overall survival (OS) by center type. RESULTS: Seventeen percent of the 1,170 patients were enrolled in clinical trials in community cancer centers. The study results demonstrated comparable rates of grade ≥3 adverse events (97% v 93%), 1-month mortality (19.1% v 16.1%), and OS (43.9% v 35.7% at 1 year) between community versus academic cancer centers, respectively. After adjusting for covariates, 1-month mortality (odds ratio, 1.40; 95% CI, 0.92 to 2.12; P = .11) and OS (hazard ratio, 1.04; 95% CI, 0.88 to 1.22; P = .67) were not statistically different among patients treated in community versus academic cancer centers. CONCLUSION: An older patient population, who have complex health care needs, can be successfully treated on intensive chemotherapy trials in select community cancer centers with outcomes comparable with that achieved at academic cancer centers.
Lessons learned from conducting the first cancer care delivery trial in the Alliance for Clinical Trials in Oncology (Alliance A191402CD)
Introduction: Testing healthcare delivery interventions in rigorous clinical trials is a critical step in improving patient care, but conducting multisite randomized clinical trials to test the effect of care delivery interventions has unique challenges and requires foresight and planning. Methods: We conducted the first care delivery trial (A191402CD) in the Alliance for Clinical Trials in Oncology, a National Cancer Institute Community Oncology Research Program research base, which tested the effectiveness of two different decision aids for supporting shared decision-making about prostate cancer treatment. Our experience illustrates the kind of challenges that confront care delivery researchers as they seek to test interventions to improve the experiences of patients. Results: Lessons learned include the following: cluster-randomized designs introduce complexity; workflow disruption can discourage site participation; evidence-based methods may not always be sufficient. Conclusion: We conclude with the following recommendations: assessing feasibility requires special rigor; relationships and interpersonal dynamics must be leveraged. Our experiences may inform future care delivery research.
Increasing socioeconomically disadvantaged patients’ engagement in breast cancer surgery decision-making through a shared decision-making intervention (A231701CD): protocol for a cluster randomised clinical trial
Introduction Socioeconomic disparities for breast cancer surgical care exist. Although the aetiology of the observed socioeconomic disparities is likely multifactorial, patient engagement during the surgical consult is critical. Shared decision-making may reduce health disparities by addressing barriers to patient engagement in decision-making that disproportionately impact socioeconomically disadvantaged patients. In this trial, we test the impact of a decision aid on increasing socioeconomically disadvantaged patients’ engagement in breast cancer surgery decision-making. Methods and analysis This multisite randomised trial is conducted through 10 surgical clinics within the National Cancer Institute Community Oncology Research Program (NCORP). We plan a stepped-wedge design with clinics randomised to the time of transition from usual care to the decision aid arm. Study participants are female patients, aged ≥18 years, with newly diagnosed stage 0–III breast cancer who are planning breast surgery. Data collection includes a baseline surgeon survey, baseline patient survey, audio-recording of the surgeon–patient consultation, a follow-up patient survey and medical record data review. Interviews and focus groups are conducted with a subset of patients, surgeons and clinic stakeholders. The effectiveness of the decision aid at increasing patient engagement (primary outcome) is evaluated using generalised linear mixed-effects models. The extent to which the effect of the decision aid intervention on patient engagement is mediated through the mitigation of barriers is tested in joint linear structural equation models. Qualitative interviews explore how barriers impact engagement, especially for socioeconomically disadvantaged women. Ethics and dissemination This protocol has been approved by the National Cancer Institute Central Institutional Review Board, and Certificate of Confidentiality has been obtained. We plan to disseminate the findings through journal publications and national meetings, including the NCORP network. Our findings will advance the science of medical decision-making with the potential to reduce socioeconomic health disparities. Trial registration number ClinicalTrials.gov Registry (NCT03766009).
Allogeneic Hematopoietic Cell Transplantation (HCT) Vs. Non-HCT Consolidation Therapies in Acute Myeloid Leukemia (AML) Patients 60-75 Years of Age in First Complete Remission (CR1): An Alliance (A151509), SWOG, ECOG-ACRIN and CIBMTR Study
Abstract Introduction: The preferred post-remission therapy for older patients (pts) with AML remains uncertain. We compared outcomes for older AML pts in CR1 receiving HCT reported to the CIBMTR to older AML pts achieving CR1 on National Clinical Trials Network induction and non-HCT consolidation therapy (CT) trials. Methods: This study focused on pts 60-75 years of age treated between 2004 to 2013. CT pts (n=211) underwent induction and consolidation on Alliance for Clinical Trials in Oncology, ECOG-ACRIN or SWOG clinical trials for initial therapy for newly diagnosed AML; the CIBMTR provided data for HCT pts (n=431). CT patients received at least one cycle of CT on study and were excluded if HCT occurred at any time. Time to event started at CR1 and pts entered at CT or HCT, respectively, using left-truncation to account for differential entry times. Results: For the CT cohort, first consolidation included standard therapy (e.g., cytarabine or a hypomethylating agent) and additional study drug (e.g., bortezomib, dasatinib, sorafenib, and Zosuquidar, gemtuzumab) or tipifarnib alone. Among HCT pts, the donor was a HLA-matched sibling or unrelated donor (URD) in 66% and the others were partially HLA-matched/mismatched URD (10%) or cord blood (24%). HCT pts were younger and more frequently had high-risk AML (high WBC, secondary AML and unfavorable cytogenetics) (Table). The median time from CR1 to HCT and CT was 3.2 and 0.5 months, respectively. Allogeneic HCT showed worse overall survival (OS) (HR=1.52, p=0.02) prior to 9 months and better OS thereafter (HR= 0.53, p <0.0001) relative to CT (figure 1A). Treatment-related mortality (TRM) was worse after HCT in the first 9 months (HR=2.8, CI: 1.5 -5.2, p=.0009), while relapse was less frequent beyond 9 months after treatment (HR = 0.42, CI: 0.29 to 0.61, p<.0001). Despite higher early TRM, HCT recipients went on to manifest superior OS [5 year OS: HCT 29% (24-34%), CT 13.8% (9 -22%)] (Figure 1A). The benefit of HCT for survival after 9 months was more prominent in those with unfavorable cytogenetics (Figure 1B). Multivariate analysis for OS showed no statistically significant effect of age or performance status, while unfavorable cytogenetics were detrimental (HR=1.74, p<.0001). Conclusions. Allogeneic HCT led to heightened early risks from TRM, but resulted in superior long-term survival in older AML pts receiving HCT relative to CT by reducing relapse. Efforts to attenuate early TRM after allogeneic HCT may further improve HCT outcomes for older pts. Disclosures Ustun: novartis: Speakers Bureau. Attar:Agios: Employment, Equity Ownership. Larson:Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding; Ariad/Takeda: Consultancy, Research Funding. Roboz:Roche/Genentech: Consultancy; Eisai: Consultancy; Cellectis: Research Funding; Aphivena Therapeutics: Consultancy; Sandoz: Consultancy; Janssen Pharmaceuticals: Consultancy; Otsuka: Consultancy; Jazz Pharmaceuticals: Consultancy; Sandoz: Consultancy; AbbVie: Consultancy; Celltrion: Consultancy; Cellectis: Research Funding; Eisai: Consultancy; Astex Pharmaceuticals: Consultancy; Argenx: Consultancy; Pfizer: Consultancy; Celgene Corporation: Consultancy; Novartis: Consultancy; Jazz Pharmaceuticals: Consultancy; Bayer: Consultancy; Bayer: Consultancy; Roche/Genentech: Consultancy; Orsenix: Consultancy; Astex Pharmaceuticals: Consultancy; Celgene Corporation: Consultancy; Daiichi Sankyo: Consultancy; Pfizer: Consultancy; Janssen Pharmaceuticals: Consultancy; Otsuka: Consultancy; Orsenix: Consultancy; Daiichi Sankyo: Consultancy; Celltrion: Consultancy; Novartis: Consultancy; Aphivena Therapeutics: Consultancy; Argenx: Consultancy; AbbVie: Consultancy. Uy:GlycoMimetics: Consultancy; Curis: Consultancy. Stone:Fujifilm: Consultancy; Ono: Consultancy; Orsenix: Consultancy; Otsuka: Consultancy; Agios: Consultancy, Research Funding; AbbVie: Consultancy; Argenx: Other: Data and Safety Monitoring Board; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee; Arog: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Jazz: Consultancy; Astellas: Consultancy; Merck: Consultancy; Pfizer: Consultancy; Sumitomo: Consultancy; Amgen: Consultancy; Cornerstone: Consultancy. Foran:Agios: Research Funding; Xencor, Inc.: Research Funding. Weisdorf:Seattle Genetics: Consultancy; Equillium: Consultancy; FATE: Consultancy; SL Behring: Consultancy; Pharmacyclics: Consultancy.