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A concerted commitment across research stakeholders is necessary to increase equity, diversity, and inclusion (EDI) and address barriers to cancer clinical trial recruitment and participation. Racial and ethnic diversity among trial participants is key to understanding intrinsic and extrinsic factors that may affect patient response to cancer treatments. This ASCO and Association of Community Cancer Centers (ACCC) Research Statement presents specific recommendations and strategies for the research community to improve EDI in cancer clinical trials. There are six overarching recommendations: (1) clinical trials are an integral component of high-quality cancer care, and every person with cancer should have the opportunity to participate; (2) trial sponsors and investigators should design and implement trials with a focus on reducing barriers and enhancing EDI, and work with sites to conduct trials in ways that increase participation of under-represented populations; (3) trial sponsors, researchers, and sites should form long-standing partnerships with patients, patient advocacy groups, and community leaders and groups; (4) anyone designing or conducting trials should complete recurring education, training, and evaluation to demonstrate and maintain cross-cultural competencies, mitigation of bias, effective communication, and a commitment to achieving EDI; (5) research stakeholders should invest in programs and policies that increase EDI in trials and in the research workforce; and (6) research stakeholders should collect and publish aggregate data on racial and ethnic diversity of trial participants when reporting results of trials, programs, and interventions to increase EDI. The recommendations are intended to serve as a guide for the research community to improve participation rates among people from racial and ethnic minority populations historically under-represented in cancer clinical trials. ASCO and ACCC will work at all levels to advance the recommendations in this publication.

PURPOSE: Patients' concerns regarding clinical trial (CT) participation include apprehension about side effects, quality of life (QoL), financial burden, and quality of care. METHODS: We prospectively evaluated the experience of patients with multiple myeloma or lymphoma who were treated on CTs (CT group, n = 35) versus patients treated with standard approaches (non-CT group, n = 88) focusing on QoL, financial burden of care, and patients' perception of quality of care over a 1-year period. RESULTS: There were no significant differences in any of the patient-reported outcomes in CT versus non-CT groups. We observed an initial decline in overall QoL in the first 3 months across both groups, driven primarily by physical and functional well-being. QoL gradually improved and was above baseline by month 12. Patients reported highest improvement in the functional well-being subdomain. Patients in both groups reported high satisfaction with the quality of care received, and there were no differences in overall satisfaction, communication with team, or access to care. At baseline, 16%-19% of patients reported financial burden, which increased to a peak of 33% in the CT group and to 49% in the non-CT group over the course of 1 year. There was no significant difference in financial burden in the two groups overall. Most of the patients reported getting all the care that was deemed medically necessary in both groups. However, a significant proportion of patients reported having to make other kinds of financial sacrifices because of their cancer (CT group: 33% of patients at baseline and 21%-40% over 1 year; non-CT group: 19% at baseline and 25%-36% over 1 year). CONCLUSION: Patients treated on CTs reported comparable QoL and quality of care with the non-CT group. A high proportion of patients reported financial burden over time in both groups. Our findings can serve as a guide to educate patients regarding CT participation and highlight the need to address the significant financial burden experienced by patients with cancer.

Background: Patients with peripheral artery disease (PAD) are at increased risk for major adverse limb and cardiac events including mortality. Developing screening tools capable of accurate PAD identification is a necessary first step for strategies of adverse outcome prevention. This study aimed to determine whether machine analysis of a resting Doppler waveform using deep neural networks can accurately identify patients with PAD. Methods: Consecutive patients (4/8/2015 – 12/31/2020) undergoing rest and postexercise ankle–brachial index (ABI) testing were included. Patients were randomly allocated to training, validation, and testing subsets (70%/15%/15%). Deep neural networks were trained on resting posterior tibial arterial Doppler waveforms to predict normal (> 0.9) or PAD (⩽ 0.9) using rest and postexercise ABI. A separate dataset of 151 patients who underwent testing during a period after the model had been created and validated (1/1/2021 – 3/31/2021) was used for secondary validation. Area under the receiver operating characteristic curves (AUC) were constructed to evaluate test performance. Results: Among 11,748 total patients, 3432 patients met study criteria: 1941 with PAD (mean age 69 ± 12 years) and 1491 without PAD (64 ± 14 years). The predictive model with highest performance identified PAD with an AUC 0.94 (CI = 0.92–0.96), sensitivity 0.83, specificity 0.88, accuracy 0.85, and positive predictive value (PPV) 0.90. Results were similar for the validation dataset: AUC 0.94 (CI = 0.91–0.98), sensitivity 0.91, specificity 0.85, accuracy 0.89, and PPV 0.89 (postexercise ABI comparison). Conclusion: An artificial intelligence-enabled analysis of a resting Doppler arterial waveform permits identification of PAD at a clinically relevant performance level.

Abstract A recent systematic review reported that trials involving patients with marginal zone lymphoma (MZL) show marked heterogeneity both in the choice and definitions of primary and secondary endpoints, thus hampering comparability between trials. The main objective of this study was to reach consensus, through a Delphi process, on the definitions of four time‐to‐event endpoints in MZL trials, by surveying clinicians and methodologists involved in the conduct of clinical trials including patients with MZL. We polled a panel of leading international experts involved in MZL trials by means of self‐administered sequential questionnaires in 2021. Of these 105 experts, 62 responded to the Round 1 questionnaire regarding the definitions of progression‐free survival (PFS), event‐free survival (EFS), time‐to‐failure (TTF), and time‐to‐next‐treatment (TTNT). Afterward, we therefore focused the Round 2 and 3 questionnaires among principal investigators, coinvestigators, and trial methodologists. Consensus was reached when there was a >80% agreement on all potential events (11 choices) of each endpoint. Participants in our survey reached consensus on three of the four time‐to‐event endpoints definitions. Consensus was reached on the definitions of PFS and TTNT after Round 1, of TTF after Round 2, and was not reached for EFS after Round 3. The disagreement concerned the event “treatment discontinuation” in EFS definition. The main interest of our study was to elicit investigator's interest in the importance of consistently defining endpoints in MZL trials and to highlight that composite endpoints should not be encouraged. Fifteen years after the last consensus statement on time‐to‐event endpoints definitions issued in Lugano (2007), both the review of literature and survey of international investigators agree on the inconsistency of endpoints definitions used within the MZL community. Hopefully, revised standardized definitions of endpoints shall be provided at the upcoming International Conference on Malignant Lymphoma in 2023.

Abstract Purpose: To report on the first-in-human phase I study of VIP152 (NCT02635672), a potent and highly selective cyclin-dependent kinase 9 (CDK9) inhibitor. Patients and Methods: Adults with solid tumors or aggressive non–Hodgkin lymphoma who were refractory to or had exhausted all available therapies received VIP152 monotherapy as a 30-minute intravenous, once-weekly infusion, as escalating doses (5, 10, 15, 22.5, or 30 mg in 21-day cycles) until the MTD was determined. Results: Thirty-seven patients received ≥ 1 VIP152 dose, with 30 mg identified as the MTD based on dose-limiting toxicity of grade 3/4 neutropenia. The most common adverse events were nausea and vomiting (75.7% and 56.8%, respectively), all of grade 1/2 severity. Of the most common events, grade 3/4 events occurring in > 1 patient were neutropenia (22%), anemia (11%), abdominal pain (8%), increased alkaline phosphatase (8%), and hyponatremia (8%). Day 1 exposure for the MTD exceeded the predicted minimum therapeutic exposure and reproducibly achieved maximal pathway modulation; no accumulation occurred after multiple doses. Seven of 30 patients with solid tumors had stable disease (including 9.5 and 16.8 months in individual patients with pancreatic cancer and salivary gland cancer, respectively), and 2 of 7 patients with high-grade B-cell lymphoma with MYC and BCL2/BCL6 translocations (HGL) achieved durable complete metabolic remission (ongoing at study discontinuation, after 3.7 and 2.3 years of treatment). Conclusions: VIP152 monotherapy, administered intravenously once weekly, demonstrated a favorable safety profile and evidence of clinical benefit in patients with advanced HGL and solid tumors.

AbstractErdheim–Chester disease (ECD) is a histiocytic neoplasm that predominantly harbors mitogen‐activated protein kinase (MAPK) pathway variants. MAPK inhibitors typically are effective treatments, but mutations outside the MAPK pathway, such as CSF1R variants, may cause refractory ECD. We describe a patient with a novel somatic mutation in CSF1R (CSF1RR549_E554delinsQ) that resulted in refractory ECD affecting the central nervous system. Cell model studies, RNA sequencing analysis, and in silico protein modeling suggested that she had a gain‐of‐function mutation occurring in a region critical for autoinhibition. The patient was treated with pexidartinib, a CSF1R inhibitor, and has had a complete clinical and metabolic response lasting more than 1.5 years to date. To our knowledge, this is the first report to describe successful treatment of a patient with ECD by using an agent that specifically targets CSF1R. This case also highlights the critical role of individualized molecular profiling to identify novel therapeutic targets in ECD.

Abstract Background: Event-free survival at 24 months (EFS24) is an important clinical endpoint in newly diagnosed diffuse large B-cell lymphoma and follicular lymphoma, and patients who achieve EFS24 with frontline immunochemotherapy have minimal loss of lifetime compared to age- and sex-matched general population. However, the prognostic role of EFS24 in mantle cell lymphoma (MCL) has not been well studied, possibly due to the perception of continued relapse pattern and poor survival outcome of MCL historically. A recent study from our group demonstrated evolving frontline therapy pattern from 2002-2009 ("Era 1") to 2010-2015 ("Era 2") which was associated with improved EFS and overall survival (OS) in Era 2. In the current study, we sought to explore the prognostic role of EFS24 in the two eras. Methods: Patients with newly diagnosed MCL from 9/2002 through 6/2015 were identified from Molecular Epidemiology Resource (MER), a prospective cohort study of the University of Iowa/Mayo Clinic Lymphoma SPORE. OS was defined as time from diagnosis (or the EFS24 defining event where applicable) to death from any cause and was analyzed using the Kaplan-Meier method. Expected OS accounting for age and sex was generated in R by using the general US population as the reference group. Observed versus expected OS was summarized by using standardized mortality ratio (SMR) and 95% confidence intervals (CI) of observed to expected deaths. Cumulative incidence of lymphoma-specific death was analyzed using Gray's test, with deaths from all other causes treated as competing events. Results: A total of 343 patients were included, 175 from Era 1 (median follow-up 13.0 years) and 168 from Era 2 (median follow-up 6.9 years). Age, sex and simplified MIPI score were similar between the 2 groups. Patients diagnosed in Era 2 had better OS, with a 5-year OS of 68.4% vs 59.2% (simplified MIPI-adjusted hazard ratio 0.68, 95% CI 0.50-0.93). Patients diagnosed in both eras had inferior OS compared to the general population, with an SMR of 3.26 (95% CI 2.70-3.89, P<0.001) in Era 1 and 2.63 (95% CI 2.03-3.36, P<0.001) in Era 2. Patients diagnosed in Era 1 who achieved EFS24 (n=98) still had inferior OS compared to the general population, with an SMR of 2.23 (95% CI 1.67-2.92, P<0.001) (Figure 1A). In contrast, for patients diagnosed in Era 2 who achieved EFS24 (n=99), no evidence of OS difference was found compared to the general population, with an SMR of 1.31 (95% CI 0.78-2.07, P=0.31) (Figure 1B). The primary cause of death after diagnosis was lymphoma-related for patients diagnosed in both eras. The 5-year rate of lymphoma-related death was 28.8% in Era 1 and 20.5% in Era 2. In patients who were diagnosed in Era 1 and achieved EFS24, the primary cause of death after achieving EFS24 remained to be lymphoma-related, with a 5-year rate of 19.8% compared to 6.2% for lymphoma-unrelated causes (Figure 1C). In contrast, in patients who were diagnosed in Era 2 and achieved EFS24, the rate of lymphoma-related death was no longer higher than that of lymphoma-unrelated death, with a 5-year rate of 2.1% vs 5.5%, respectively (Figure 1D). In a sensitivity analysis restricted to only patients who received standard frontline immunochemotherapy, similar results were obtained. For example, in patients who achieved EFS24, the SMR compared to the general population was 2.89 (95% CI 2.00-4.04, P<0.001) in Era 1 and 0.89 (95% CI 0.43-1.64, P=0.82) in Era 2. The 5-year rates of deaths due to lymphoma-related vs lymphoma-unrelated causes were 20.7% vs 6.2% in Era 1 and 1.3% vs 4.9% in Era 2. Conclusions: MCL survival outcome has improved for patients first diagnosed in the more recent era (2010-2015, compared to 2002-2009), likely due to improved frontline therapy as well as better salvage treatments (such as lenalidomide and BTK inhibitors). In the more recent treatment era, patients who achieved EFS24 had survival approaching the age- and sex-matched general population. In addition, these patients had a low risk of dying from lymphoma and were more likely to die from other causes. Longer follow-up (e.g., in Era 2) and external validation in other series are necessary to confirm the prognostic role of EFS24. With more efficacious salvage treatment options and likely continued improvement of OS in MCL, EFS24 may become an important clinical endpoint in frontline therapy of MCL. Figure 1 Figure 1. Disclosures Wang: TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; InnoCare: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; MorphoSys: Research Funding. Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Nanostring: Research Funding. Link: Novartis, Jannsen: Research Funding; Genentech/Roche: Consultancy, Research Funding; MEI: Consultancy. Farooq: Kite, a Gilead Company: Honoraria. Paludo: Karyopharm: Research Funding. Witzig: Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding; Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees. Habermann: Seagen: Other: Data Monitoring Committee; Tess Therapeutics: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Genentech: Research Funding. Nowakowski: Celgene, NanoString Technologies, MorphoSys: Research Funding; Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Abstract Background: While extranodal involvement by mantle cell lymphoma (MCL) is relatively common, involvement of the central nervous system (CNS) is rare (<5% of cases), with limited treatment options. We report the outcomes of 36 patients (pts) with CNS involvement compared to 72 matched control MCL pts without CNS involvement. Methods: MCL pts with CNS involvement seen at Mayo Clinic between 1/1995-9/2020 were identified using the Mayo Data Explorer tool. CNS involvement was defined by tissue biopsy confirmed CNS MCL, CSF analysis demonstrating lymphoma cells, and/or neuroimaging findings compatible with CNS involvement. A 2:1 control group of MCL pts without CNS involvement, matched by age (+/- 2 years) and year of diagnosis (+/- 1 year), was selected among all MCL cases. Medical records were reviewed for baseline characteristics, treatment modalities, and outcomes. Kaplan-Meier method was used for time to event analysis. Wilcoxon test was used to compare continuous variables and Chi square test was used for categorical variables. Results: Out of 1,753 pts with MCL, 36 (2%) had evidence of CNS involvement, including 4 pts with CNS involvement at initial MCL diagnosis. Baseline characteristics of pts with CNS involvement (CNS MCL group) and those without CNS involvement (control group) are shown in Table 1. At MCL diagnosis, non-CNS extranodal involvement was seen in 30 (83%) pts in the CNS MCL group (24 pts with 1 site and 6 pts with ≥ 2 sites), with bone marrow being the most common extranodal site of involvement (n=24, 67%). For the control group, 54 (75%) pts had extranodal involvement (44 pts with 1 site and 10 pts with ≥ 2 sites), and bone marrow was also the most common extranodal site of involvement (n=50, 69%). Notably, advanced stage disease (stage 3-4) was more commonly seen in the CNS MCL group (n=32, 97%) than in the control group (n=59, 83%) (p=0.04) at MCL diagnosis. Blastoid variant was present in a higher proportion of pts in the CNS MCL group (n=11, 31%) compared to the control group (n=8, 11%) (p=0.02). The CNS MCL group also presented with a higher median serum LDH at diagnosis (239 U/L [range 153-1901] vs. 187 U/L [range 124-588], p=0.02), and higher Ki-67 (40% [range 15-100] vs. 30% [range 10-90], p=0.04) compared to the control group. The most common frontline treatment regimen was anthracycline-based therapies (i.e. R-CHOP, Nordic regimen, R-hyperCVAD) for both groups (58% in CNS MCL group and 56% in control group). 14 (39%) pts in the CNS MCL group underwent autologous stem cell transplant in CR1 vs. 31 pts (43%) in the control group. Similar use of rituximab maintenance was seen in both groups (31% in CNS MCL group and 25% in control group). Median total lines of therapy from initial MCL diagnosis was 3 (range 1-9) in CNS MCL group and 2 (range 1-9) in the control group. The median follow-up from MCL diagnosis was 134 months (95% CI:119-163) for the entire cohort. Median OS from MCL diagnosis was 50.3 months (95% CI: 20.9-71.1) for the CNS MCL group compared to 97.1 months (95% CI: 82.6-192.7; p=<0.001) for the control group (Figure 1). Median time from MCL diagnosis to CNS involvement was 25 months (range 0-167). Median OS from CNS involvement was 4.7 months (95% CI: 2.3-6.7). At last follow up, 31 (86%) pts were deceased from the CNS MCL group, compared to 38 (52%) pts in the control group. For the CNS MCL group, the causes of death were CNS lymphoma in 10 (32%) pts, systemic lymphoma in 9 (29%) pts, treatment-related complication in 7 (23%) pts, and other/unknown in 5 (16%) pts. For the control group, the causes of death were systemic lymphoma in 15 (39%) pts, treatment-related in 2 (5%) pts, and other/unknown in 21 (55%) pts. Conclusion: In pts with MCL, CNS involvement is associated with worse outcomes as evident by a shorter median OS from initial MCL diagnosis (50 months vs. 97 months). Involvement of the CNS by lymphoma is an important contributor for the shorter OS as suggested by the median OS of only 5 months from CNS involvement. Advanced stage, blastoid variant, elevated LDH, and elevated Ki67 at MCL diagnosis were features more commonly seen in the CNS MCL cohort. Validation of risk factors at initial MCL diagnosis associated with CNS involvement and exploring the role of CNS prophylaxis are important topics for further investigation. Figure 1 Figure 1. Disclosures Paludo: Karyopharm: Research Funding. Wang: Novartis: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; InnoCare: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding. Bennani: Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board; Verastem: Other: Advisory Board. Nowakowski: Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, NanoString Technologies, MorphoSys: Research Funding. Witzig: Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding. Habermann: Seagen: Other: Data Monitoring Committee; Tess Therapeutics: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding.