Citations

TPS8604 Background: Chemoimmunotherapy followed by durvalumab maintenance yields a median overall survival of 12.9 months in patients with extensive stage Small Cell Lung Cancer (ES SCLC), which is an improvement over chemotherapy alone. However, 90% of these patients will have progressive disease. While topotecan and lurbinectedin have established modest activity in the second line, it is unknown whether continuing immunotherapy in this setting confers additional benefit. In preclinical studies lurbinectedin, a DNA minor groove binder, used with immune checkpoint inhibitors has synergistic effects. Methods: This phase 2 trial is enrolling patients with ES SCLC who have progressed on platinum based chemoimmunotherapy, to three treatment groups. Group 1 includes patients with platinum sensitive SCLC who will receive durvalumab (1500 mg given as an intravenous [IV] infusion once every 3 weeks) and topotecan (1.25 mg/m2/day IV for 5 consecutive days every 3 weeks). In Groups 2A and 2B, patients with platinum sensitive and platinum resistant disease respectively, receive durvalumab and lurbinectedin (3.2 mg/m2 IV on Day 1 of every 21-day cycle). Patients with platinum sensitive disease are assigned to Groups 1 or 2A based on the preferences of the treating physician and the patient. Patients with treated/stable CNS metastases are eligible. The primary endpoint is the proportion of patients who are alive at 6 months (6OS) for Group 1 and the proportion of patients who are alive and progression-free at 6 months (6PFS) in Groups 2A and 2B. Secondary endpoints include safety, adverse event profile, response rate, PFS, and OS. The sample size is based on a 2-stage Simon Optimal Design. For Treatment Group 1, with 22 eligible patients there is 80% power to detect a true 6-month OS rate (6OS) of 75%, with 10% alpha under the null hypothesis that the true 6OS is at most 50%. For Treatment Group 2A, with 20 eligible patients this design has 80% power to detect a true 6-month PFS rate (6PFS) of 65%, with 10% alpha under the null hypothesis that the true 6PFS is at most 40%. For Treatment Group 2B, with 22 eligible patients this design has 80% power to detect a true 6-month PFS rate (6PFS) of 40%, with 10% alpha under the null hypothesis that the true 6PFS is at most 19%. To account for possible drop-outs, accrual targets will be 24, 22, and 24 patients to Groups 1, 2A, and 2B respectively. For the safety analyses, 6 patients will be enrolled at the starting dose level for each treatment group (1, 2) and then briefly closed to accrual to assess adverse events. If we observe 2+ DLTs in these 6 treated patients during Cycle 1 within a treatment group (1 vs. 2), we will declare the combination treatment too toxic and lower the starting dose of chemotherapy for the next 6 patients. The study was open for all 3 groups as of January 2022 and has accrued 2 patients. Clinical trial information: NCT04607954.

TPS2670 Background: Tumor necrosis factor receptor-2 (TNFR2) is expressed on effector CD8+ T cells, CD4+ T cells, T regulatory cells, natural killer cells, and myeloid cells. Targeting TNFR2 is anticipated to yield effective anti-tumor immunity by stimulating T-cell and NK-cell activation and proliferation in the tumor microenvironment. HFB200301 is a first-in-class anti-TNFR2 agonistic monoclonal antibody that triggers both innate and adaptive immune stimulation by binding to a specific epitope on TNFR2. HFB200301 has demonstrated dose-dependent anti-tumor activity in human TNFR2 knock-in mice bearing MC38 and Hepa1-6 syngeneic tumors. Methods: HFB200301 is being evaluated in a first-in-human, open-label, multi-center, dose escalation and expansion study in adult patients with advanced solid tumors. A single-cell immune profiling platform, DIS, was deployed to identify unique tumor-infiltrating T cell signatures that could help optimize patient selection for HFB200301 treatment. It is hypothesized that the presence of an effector T cell subpopulation that express both TNFR2 and CD8A in solid tumors may represent a tumor microenvironment favorable to TNFR2 agonism. The following cancer indications have been identified based on the prevalence of a TNFR2 high/CD8 high signature: Epstein-Barr Virus positive (EBV+) gastric cancer, clear cell renal cell carcinoma (ccRCC), cutaneous melanoma, testicular germ cell tumor (TGCT), soft tissue sarcoma (STS), and PD-L1+ cancers: cervical cancer, pleural mesothelioma, lung adenocarcinoma, and head and neck squamous cell carcinoma (HNSCC). The escalation portion of the study explores increasing doses in cohorts of up to six patients, utilizing mTPI-2 design to determine recommended dose(s) for expansion (RDE(s)). Based on pharmacokinetic modeling to maximize HFB200301 activity, 60-minute intravenous infusions of HFB200301 are administered every 4 weeks. Once RDE(s) is determined, expansion into three indication-specific cohorts is planned to determine the recommended phase 2 dose (RP2D). Key eligibility criteria include histologically documented advanced or metastatic solid tumors in the above listed indications. Patient enrollment opened in February 2022 in the USA, with plans for additional clinical sites in Spain and China. The primary objective is to identify the RDE, characterize safety and tolerability of HFB200301, and determine RP2D. Secondary objectives include pharmacokinetic parameters, preliminary evidence of anti-tumor efficacy (e.g., ORR, DCR, DOR) and pharmacodynamic evaluation (e.g., T cell subsets) in the blood and in the tumor. Furthermore, a potential predictive biomarker signature derived based on the DIS single-cell immune profiling approach will be investigated retrospectively. Clinical trial information: NCT05238883.

512 Background: The role of immune checkpoint inhibitors (ICIs) in the treatment of extrapulmonary neuroendocrine carcinoma (EP-NEC) has yet to be established. While objective responses have been observed, it is still unknown which patients are likely to derive benefit. We investigated the genomic profiles of patients who did and did not benefit from ICIs. Methods: Previously we reported the objective responses to ICI in a retrospective series of patients with EP-NEC. RECIST 1.1 criteria were used to categorize patients as achieving disease control (DC = CR, PR, or SD) vs progressive disease (PD). The EMR was reviewed to identify patients who had genomic panels performed, and results were extracted for analysis. Results: Of 31 patients eligible for RECIST assessment, 19 had genomic panels available (9 with DC: 4 SD, 5 PR vs 10 with PD). Of those with NEC histology specified, 9 were small cell, 1 combined large and small cell, 3 were large cell. All tumors were microsatellite-stable. All but one (with TMB = 25) of 16 tumors with TMB status available were < 10 m/MB. Of those with disease control, 67% had both TP53 and RB1 alterations, compared with only 10% in those with progressive disease; this was statistically significant ( p = 0.0198, Fisher exact). Of 7 tumors with TP53 + RB1 alterations, 4 were specified as small cell carcinoma. Half of those with PD showed alterations in β-catenin pathway genes CTNNB1 or APC, compared to only one of the DC group, but this did not reach significance ( p = 0.1409, Fisher exact). In an analysis of all Mayo patients (not just those treated with ICI) with NGS data available (Tempus and FoundationOne), concurrent TP53 + RB1 alteration was significantly more common in SCLC than in EP-NEC (Table). Conclusions: In this small series of patients with EP-NEC treated with ICIs, the SCLC-like genomic signature of concurrent TP53 + RB1 alterations was significantly more common in those with disease control than in those with progressive disease. An analysis of all patients with NGS data (not just on ICI) showed that the dual alteration was more common in SCLC, and SCLC also had more TMB-high tumors. This may explain why ICIs are more effective in SCLC than in EP-NEC. Further study is warranted to determine whether TP53 + RB1 mutations predict response to ICI in NEC.[Table: see text]

PURPOSE: The benefit of routine pre-emptive screening for severe acute respiratory syndrome coronavirus 2 infections in patients with cancer before cancer-directed therapies is unclear. Herein, we characterize the outcomes of a cohort of patients with cancer who were diagnosed with COVID-19 by routine screening (RS) in comparison with those diagnosed on the basis of clinical suspicion or exposure history (nonroutine screening [NRS]). METHODS: A multisite prospective observational study was conducted at three major and five satellite campuses of the Mayo Clinic Cancer Center between March 18 and July 31, 2020. The primary outcome was COVID-19–related hospital admission. Secondary outcomes included intensive care unit admissions and all-cause mortality. RESULTS: Five thousand four hundred fifty-two patients underwent RS in the outpatient setting only, and 44 (0.81%) were diagnosed with COVID-19. RS detected 19 additional patients from the scheduled inpatient admissions for surgical or interventional procedures or inpatient chemotherapy. One hundred sixty-one patients were diagnosed with COVID-19 on the basis of NRS. COVID-19–related hospitalization rate (17.5% v 26.7%; P = .14), intensive care unit admission (1.6% v 5.6%; P = .19), and mortality (4.8% v 3.7%; P = .72) were not significantly different between the RS and NRS groups. In the multivariable analysis, age ≥ 60 years (odds ratio, 4.4; P = .023) and an absolute lymphocyte count ≤ 1.4 × 109/L (odds ratio, 9.2; P = .002) were independent predictors of COVID-19–related hospital admission. CONCLUSION: The COVID-19 positivity rate was low on the basis of RS. Comparing the hospital admission and mortality outcomes with the NRS cohort, there were no significant differences. The value of routine pre-emptive screening of asymptomatic patients with cancer for COVID-19 remains low.

PURPOSE: The goal of this study was to assess the impact of an interdisciplinary remote patient monitoring (RPM) program on clinical outcomes and acute care utilization in cancer patients with COVID-19. METHODS: This is a cross-sectional analysis following a prospective observational study performed at Mayo Clinic Cancer Center. Adult patients receiving cancer-directed therapy or in recent remission on active surveillance with polymerase chain reaction–confirmed SARS-CoV-2 infection between March 18 and July 31, 2020, were included. RPM was composed of in-home technology to assess symptoms and physiologic data with centralized nursing and physician oversight. RESULTS: During the study timeframe, 224 patients with cancer were diagnosed with COVID-19. Of the 187 patients (83%) initially managed in the outpatient setting, those who did not receive RPM were significantly more likely to experience hospitalization than those receiving RPM. Following balancing of patient characteristics by inverse propensity score weighting, rates of hospitalization for RPM and non-RPM patients were 2.8% and 13%, respectively, implying that the use of RPM was associated with a 78% relative risk reduction in hospital admission rate (95% CI, 54 to 102; P = .002). Furthermore, when hospitalized, these patients experienced a shorter length of stay and fewer prolonged hospitalizations, intensive care unit admissions, and deaths, although these trends did not reach statistical significance. CONCLUSION: The use of RPM and a centralized virtual care team was associated with a reduction in hospital admission rate and lower overall acute care resource utilization among cancer patients with COVID-19.

e20554 Background: The paradigm for locally advanced non-small cell lung cancer has been markedly altered to include maintenance durvalumab (D) post completion of definitive chemoradiation (CRT) following the publication of the Pacific trial in 2018. The toxicity of this treatment has not been well evaluated in the real-world setting. Methods: We identified 42 patients (pts) with Stage IIB-IIIC NSCLC treated at Mayo Clinic Rochester between 6/1/2018 and 10/1/2020 who received definitive CRT followed by maintenance D. Data were abstracted by retrospective chart review under an IRB approved protocol. Results: Median age was 66 yrs (range 47-90) and 62% were women. Primary lung cancer histology included 19 adenocarcinoma, 20 squamous cell, and 3 adenosquamous. The distribution of stages was: IIB (4/42), IIIA (15/42), IIIB (19/42), IIIC (4/42). Approximately half of patients had PDL1 expression > 25% (20/42). With a median follow up of 12.2 months (calculated from first cycle of D; range 4.2-30.5 months), 14 had completed one year of maintenance D, 16 were receiving ongoing D, and 10 stopped D early with 6/12 discontinuing due to disease progression (4/6 local progression, 2/6 distant progression). Other reasons for discontinuation (5/10) included grade 3 colitis, grade 2 hepatitis, aspergillus lung infection, and flare of autoimmune disorders. One quarter of patients experienced grade 2 radiation pneumonitis (RP; 10/42) with median time to development of RP 78 days from end of CRT and 45 days from start of D. RP was determined by multidisciplinary review of imaging and treatment fields. 17/42 patients developed immune related adverse events (see Table for details). There was minimal overlap between the patients who experienced pneumonitis and immune related toxicity; 2/17 had both pneumonitis and immune related toxicity (hepatitis, thyroiditis). Conclusions: In our early experience with the Pacific regimen, 29% of patients did not complete D due to either toxicity or progression during D administration. Pneumonitis was common (10/42 patients) although there were no grade 3 events. Nearly half of the patients developed an immune-related adverse event. Further analysis is needed to evaluate the real-world toxicity of this treatment as well as oncologic outcomes.[Table: see text]

1503 Background: Patients with cancer and COVID-19 are at risk for poor clinical outcomes. An established multi-site remote patient monitoring (RPM) service was rapidly adapted to support a novel, interdisciplinary COVID-19 program for outpatient management of patients at high-risk for severe illness. The goal of this study was to assess the impact of the RPM program on clinical outcomes and acute care utilization in cancer patients diagnosed with COVID-19. Methods: This is a cross-sectional analysis following a multi-site prospective observational study performed at Mayo Clinic Cancer Center (MCCC). All adult patients with active cancer – defined as currently receiving cancer-directed therapy or in recent remission on active surveillance – and PCR-confirmed SARS-CoV-2 infection between March 18 and July 31, 2020 were included. RPM was comprised of in-home technology to assess symptoms and physiologic data with centralized nurse and physician oversight. Results: During the study timeframe 224 cancer patients were diagnosed with COVID-19 at MCCC. Initial management included urgent hospitalization (within 48 hours of diagnosis) in 34 patients (15%). Of the remaining 190 patients (85%) initially managed in the outpatient setting, those who did not receive RPM were significantly more likely to experience hospitalization than those receiving RPM (OR 3.6, 95% CI 1.036 to 12.01, P = 0.044). Following balancing of patient characteristics by inverse propensity weighting, rates of hospital admission for RPM and non-RPM patients were 3.1% and 11% respectively, implying that RPM was associated with an 8% reduction in hospital admission rate (-0.077; 95% CI: -0.315 to -0.019, P = 0.009). Use of RPM was also associated with lower rates of prolonged hospitalization, ICU admission, and mortality, though these trends did not reach statistical significance. Conclusions: In the midst of a global pandemic associated with inpatient bed, ventilator, and PPE shortages, the RPM program provided an effective strategy for outpatient clinical management and was associated with decreased rates of hospitalization, ICU admission, and mortality in cancer patients with COVID-19. This care model enabled simultaneous opportunity to mitigate the increased risks of exposure, transmission, and resource utilization associated with conventional care.

Abstract Abstract Importance: The benefit of routine screening for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in patients with cancer before cancer-directed therapies is unclear. Herein, we characterize the outcomes of a cohort of cancer patients diagnosed with Coronavirus Disease 2019 (COVID-19) by routine screening in comparison with those diagnosed based on clinical suspicion or exposure history (non-routine screening). Objective: To describe and compare the outcomes of cancer patients diagnosed with COVID-19 on routine screening vs. non-routine screening at a multi-site tertiary cancer center. To identify risk factors for COVID-19-related hospital admission. Design: A multi-site prospective observational study was conducted between March 18 and July 31, 2020. Setting: Three major and 5 satellite campuses of the Mayo Clinic Cancer Center. Participants: Adult patients diagnosed with active cancer within the past five years and confirmed SARS-CoV-2 infection were included. Primary Outcomes and Measures: Clinical and laboratory data were assessed as independent variables. The primary outcome was COVID-19-related hospital admission. Secondary outcomes included intensive care unit (ICU) admissions and all-cause mortality. Results: Between March 18 and July 31, 2020, 5452 patients underwent routine screening in the outpatient setting, 44 (0.81%) were diagnosed with COVID-19. Routine screening detected additional 19 patients from inpatient and pre-procedural settings; 161 patients were diagnosed with COVID-19 based on non-routine screening. The median age of the entire cohort at diagnosis was 54 years, and 95 patients (42.2%) were female. COVID-19 related-hospitalization rate (17.5% vs. 26.7%, p=0.14), ICU admission (1.6% vs. 5.6%, p=0.19), and mortality (4.8% vs. 3.7%, p=0.72) were not significantly different between routine screening and non-routine screening groups. In the multivariable analysis, age ≥ 60 years (odds ratio: 4.4, p=0.023) and an absolute lymphocyte count ≤1.4 × 109/L (odds ratio: 9.2, p=0.002) were independent predictors of COVID-19-related hospital admission. Conclusions and Relevance: The COVID-19 positivity rate was low based on routine screening. Comparing the outcome with the non-routine screening cohort, there was no significant difference. These results led to an important practice change at our cancer center. We currently follow a testing strategy based on symptoms, exposure, risk factors, and clinical judgment. Citation Format: Zhuoer Xie, Antoine N. Saliba, Jithma Abeykoon, Umair Majeed, Daniel Almquist, Julia Wiedmeier-Nutor, Evandro Bezerra, Xavier Andrade-Gonzalez, Ashley Hickman, Karl Sorenson, Sagar Rakshit, Christopher Wee, Sri Tella, Anuhya Kommalapati, Nadine Abdallah, Joshua Pritchett, Mariza De Andrade, Dipesh Uprety, Andrew Badley, Joleen Hubbard, Naseema Gangat, Carrie A. Thompson, Thomas Witzig, Robert R. McWilliams, Konstantinos Leventakos, Thorvardur R. Halfdanarson. Outcomes of COVID-19 in patients with cancer: Results of a prospective observational comparison of routine screening strategy versus testing based on clinical suspicion [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2021 Feb 3-5. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(6_Suppl):Abstract nr S06-03.

Abstract Objectives: Cognitive computing has the potential to improve efficiency and accuracy of clinical trial enrollment using artificial intelligence. The cognitive computing clinical trial matching (CTM) system used for this study utilizes natural language processing to derive patient and tumor attributes from structured and unstructured electronic medical record (EMR) data. The attributes are matched to complex eligibility criteria in trial protocols. This CTM system has been implemented in our gynecologic oncology practice, for which there is lower representation of ethnic minorities, elderly, and uninsured in National Cancer Institute-sponsored trials. Methods: A clinical research coordinator (CRC) used the CTM system to screen patients for potential clinical trials one day prior to their clinic visit. Trial matches were shared with gynecologic oncology clinicians to raise awareness for study opportunities and assist in treatment decisions. Clinicians were surveyed regarding their experience with the CTM system prepared matches. The identical patients were evaluated by a clinician using the traditional manual screening method. Results: Seventeen patients with new diagnosis, recent resection, or restaging scans were screened for 41 potential gynecologic, phase I, and supportive care clinical trials. Trial screening by the CRC using the CTM system resulted in a total of 119 matched trials (mean: 7 trials/patient) compared to the clinician-generated list of 271 matched trials (mean: 16 trials/patient). The CRC using the CTM system spent an average of 18 minutes/patient (range: 7 to 40 minutes) compared to the clinician average of 22 minutes/patient (range: 7 to 37 minutes). A survey of 8 gynecologic oncology clinicians reported they were willing to spend an average of 8 minutes/patient (range: 1 to 15 minutes) to screen patients for trial eligibility. On independent review, discrepancies occurred when the clinician identified trials that the CRC excluded due to inclusion/exclusion criteria or were unknowingly closed to accrual. In addition, the CRC identified trials that were inadvertently missing from the clinician’s list of active protocols. Consistent with these observations, 100% of surveyed clinicians (8 of 8) agreed that “The CTM system has helped to include and exclude trials prior to discussion with patients.” Conclusions: Use of the CTM system by a CRC was superior to a clinician alone for the accuracy and efficiency of screening clinical trial eligibility. This process improved the identification of trials that a clinician might otherwise miss and the exclusion of trials that were not available or appropriate for patients. The CTM system can reduce the burden of clinicians and research staff to screen patients. Additional research is needed to determine if the process can improve clinical trial enrollment in gynecologic cancers. Citation Format: Thanh P. Ho, Jane M. Helgeson, Angela L. Andring, Jennifer C. Reed, Venessa L. Boyle, Nigar Sofiyeva, Konstantinos Leventakos, Tufia C. Haddad, Andrea E. Wahner Hendrickson, Saravut (John) Weroha. Implementation of cognitive computing to match clinical trials in gynecologic cancers: A single-institution experience [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr 01.