Namburi, Swathi

Background: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. Methods: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. Results: 1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32–1.67]); Black patients (aOR 1.74; 95 CI 1.24–2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70–6.79) and Other (aOR 2.97; 95 CI 1.71–5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83–12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63–3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20–2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66–3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89–22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status. Conclusions: Using one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients. Funding: This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. Clinical trial number: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701 .

ImportanceSystematic data on the association between anticancer therapies and thromboembolic events (TEEs) in patients with COVID-19 are lacking.ObjectiveTo assess the association between anticancer therapy exposure within 3 months prior to COVID-19 and TEEs following COVID-19 diagnosis in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included patients who were hospitalized and had active cancer and laboratory-confirmed SARS-CoV-2 infection. Data were accrued from March 2020 to December 2021 and analyzed from December 2021 to October 2022.ExposureTreatments of interest (TOIs) (endocrine therapy, vascular endothelial growth factor inhibitors/tyrosine kinase inhibitors [VEGFis/TKIs], immunomodulators [IMiDs], immune checkpoint inhibitors [ICIs], chemotherapy) vs reference (no systemic therapy) in 3 months prior to COVID-19.Main Outcomes and MeasuresMain outcomes were (1) venous thromboembolism (VTE) and (2) arterial thromboembolism (ATE). Secondary outcome was severity of COVID-19 (rates of intensive care unit admission, mechanical ventilation, 30-day all-cause mortality following TEEs in TOI vs reference group) at 30-day follow-up.ResultsOf 4988 hospitalized patients with cancer (median [IQR] age, 69 [59-78] years; 2608 [52%] male), 1869 had received 1 or more TOIs. Incidence of VTE was higher in all TOI groups: endocrine therapy, 7%; VEGFis/TKIs, 10%; IMiDs, 8%; ICIs, 12%; and chemotherapy, 10%, compared with patients not receiving systemic therapies (6%). In multivariable log-binomial regression analyses, relative risk of VTE (adjusted risk ratio [aRR], 1.33; 95% CI, 1.04-1.69) but not ATE (aRR, 0.81; 95% CI, 0.56-1.16) was significantly higher in those exposed to all TOIs pooled together vs those with no exposure. Among individual drugs, ICIs were significantly associated with VTE (aRR, 1.45; 95% CI, 1.01-2.07). Also noted were significant associations between VTE and active and progressing cancer (aRR, 1.43; 95% CI, 1.01-2.03), history of VTE (aRR, 3.10; 95% CI, 2.38-4.04), and high-risk site of cancer (aRR, 1.42; 95% CI, 1.14-1.75). Black patients had a higher risk of TEEs (aRR, 1.24; 95% CI, 1.03-1.50) than White patients. Patients with TEEs had high intensive care unit admission (46%) and mechanical ventilation (31%) rates. Relative risk of death in patients with TEEs was higher in those exposed to TOIs vs not (aRR, 1.12; 95% CI, 0.91-1.38) and was significantly associated with poor performance status (aRR, 1.77; 95% CI, 1.30-2.40) and active/progressing cancer (aRR, 1.55; 95% CI, 1.13-2.13).Conclusions and RelevanceIn this cohort study, relative risk of developing VTE was high among patients receiving TOIs and varied by the type of therapy, underlying risk factors, and demographics, such as race and ethnicity. These findings highlight the need for close monitoring and perhaps personalized thromboprophylaxis to prevent morbidity and mortality associated with COVID-19–related thromboembolism in patients with cancer.

ImportanceCytokine storm due to COVID-19 can cause high morbidity and mortality and may be more common in patients with cancer treated with immunotherapy (IO) due to immune system activation.ObjectiveTo determine the association of baseline immunosuppression and/or IO-based therapies with COVID-19 severity and cytokine storm in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included 12 046 patients reported to the COVID-19 and Cancer Consortium (CCC19) registry from March 2020 to May 2022. The CCC19 registry is a centralized international multi-institutional registry of patients with COVID-19 with a current or past diagnosis of cancer. Records analyzed included patients with active or previous cancer who had a laboratory-confirmed infection with SARS-CoV-2 by polymerase chain reaction and/or serologic findings.ExposuresImmunosuppression due to therapy; systemic anticancer therapy (IO or non-IO).Main Outcomes and MeasuresThe primary outcome was a 5-level ordinal scale of COVID-19 severity: no complications; hospitalized without requiring oxygen; hospitalized and required oxygen; intensive care unit admission and/or mechanical ventilation; death. The secondary outcome was the occurrence of cytokine storm.ResultsThe median age of the entire cohort was 65 years (interquartile range [IQR], 54-74) years and 6359 patients were female (52.8%) and 6598 (54.8%) were non-Hispanic White. A total of 599 (5.0%) patients received IO, whereas 4327 (35.9%) received non-IO systemic anticancer therapies, and 7120 (59.1%) did not receive any antineoplastic regimen within 3 months prior to COVID-19 diagnosis. Although no difference in COVID-19 severity and cytokine storm was found in the IO group compared with the untreated group in the total cohort (adjusted odds ratio [aOR], 0.80; 95% CI, 0.56-1.13, and aOR, 0.89; 95% CI, 0.41-1.93, respectively), patients with baseline immunosuppression treated with IO (vs untreated) had worse COVID-19 severity and cytokine storm (aOR, 3.33; 95% CI, 1.38-8.01, and aOR, 4.41; 95% CI, 1.71-11.38, respectively). Patients with immunosuppression receiving non-IO therapies (vs untreated) also had worse COVID-19 severity (aOR, 1.79; 95% CI, 1.36-2.35) and cytokine storm (aOR, 2.32; 95% CI, 1.42-3.79).Conclusions and RelevanceThis cohort study found that in patients with cancer and COVID-19, administration of systemic anticancer therapies, especially IO, in the context of baseline immunosuppression was associated with severe clinical outcomes and the development of cytokine storm.Trial RegistrationClinicalTrials.gov Identifier: NCT04354701

Background: Here we describe an online network of patients with cancer, clinicians and researchers, layered on top of a comprehensive real world database of treatments and outcomes, continuously updated in near real time, and initially focused on multiple myeloma. Methods: Patients with multiple myeloma register at www.all4cure.com and sign HIPAA release forms to provide access to all of their medical records from all of the institutions from which they have received care. From the medical records, a structured dataset of treatments and lab results is extracted by a myeloma-dedicated team for display on each patient's de-identified, personalized dashboard. A discussion panel allows more than 1200 participating patients, clinicians and researchers to post comments or questions regarding each patient's specific circumstances. For each patient, lines of therapy and responses are determined according to IMWG and published criteria (Blood [2015] 126: 921-922). Here we report initial results from the treatments and responses among patients with multiple myeloma and plasma cell leukemia. Results: A total of 493 patients includes 26 with monoclonal gammopathy of undetermined significance (MGUS), 51 with smoldering myeloma, 408 with multiple myeloma, and 8 with primary plasma cell leukemia. Among patients with multiple myeloma, 42 (10.3%) had antecedent MGUS and/or smoldering myeloma. The average age is 65.6 (+/- 9.7). 50.9% are male and 49.1% are female. 42 states in the U.S. and 8 other countries are represented. Two patients with multiple myeloma had not started treatment by the time of this report. The remaining 414 patients with multiple myeloma or plasma cell leukemia received 1 to 16 lines of therapy. Among the 414 patients that received at least one line of therapy, a remarkable 89 distinct first line therapies were administered. The most common first line therapies were lenalidomide, bortezomib, dexamethasone (n=92), cyclophosphamide, bortezomib, dexamethasone (n=50), lenalidomide, bortezomib, dexamethasone + autologous stem cell transplant + lenalidomide maintenance (n=41), lenalidomide and dexamethasone (n=29), and bortezomib and dexamethasone (n=22). 62 patients received a first line therapy that was not received by any other patient in our database. This variation was attributable to participation in clinical trials, variation in the availability of drugs over time and different geographic locations, and the very large number of distinct combinations associated with multi-agent regimens. Seventy six percent of patients with multiple myeloma or plasma cell leukemia received a second line of therapy, 52% received a third line of therapy, 34% received a fourth line of therapy, 23% received a fifth line of therapy, and 18% received a sixth line of therapy. We observed a trend toward a decline in favorable responses with successive lines of therapy (Table 1) consistent with previous reports, with a correlation coefficient between the line of therapy and overall response rate of -0.74. Among the 76 patients who received 6 or more lines of therapy (247 lines of therapy in total), only 7 achieved stringent complete responses (sCRs), of which 5 were associated with a CAR-T therapy. Table 1 also shows a trend toward more rapid changes in treatment associated with later lines of therapy. 57 of 493 patients (12%) are deceased. Conclusions: Our findings reveal remarkable variation in the treatment of myeloma and provide a potentially valuable resource of up to date and current clinical features, prognosis, treatments, side effects, and outcomes of patients with myeloma in the real world. Table 1. Summary of lines of therapy and outcomes across 414 patients with multiple myeloma and plasma cell leukemia. The percentages of patients achieving sCR, ≥ PR (overall response rate - ORR), and ≥MR (clinical benefit rate - CBR) are shown for each line of therapy. Also depicted is the interval mortality and the mean and median number of days between the beginning of a line therapy and the beginning of the next line of therapy. Table Disclosures Richter: Janssen: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi: Consultancy; X4 pharmaceuticals: Consultancy; Oncopeptides: Consultancy; Adaptive biotechnologies: Consultancy; Secura bio: Consultancy; Astra Zeneca: Consultancy; BMS: Consultancy; Karyopharm: Consultancy; Antengene: Consultancy. Chhun:All4Cure: Current Employment. Zheng:All4Cure: Current Employment. Piboonvaranggoon:All4Cure: Current Employment. Mallick:All4Cure: Current Employment. Wren:All4Cure: Current Employment. Nam:All4Cure: Current Employment. Lopez Barquilla:All4Cure: Current equity holder in private company. Blau:All4Cure: Current equity holder in private company. Cowan:Janssen: Consultancy, Research Funding; Abbvie: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy; Bristol Myers Squibb: Research Funding. Bensinger:BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau; Regeneron: Consultancy, Honoraria, Research Funding, Speakers Bureau. Kumar:Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Genecentrix: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Adaptive Biotechnologies: Consultancy; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Cellectar: Other; Sanofi: Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding. Richardson:Celgene/BMS, Oncopeptides, Takeda, Karyopharm: Research Funding. Anderson:Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees. Blau:All4Cure: Current Employment, Current equity holder in private company.