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Background: COVID-19 can have a particularly detrimental effect on patients with cancer, but no studies to date have examined if the presence, or site, of metastatic cancer is related to COVID-19 outcomes., Methods: Using the COVID-19 and Cancer Consortium (CCC19) registry, the authors identified 10,065 patients with COVID-19 and cancer (2325 with and 7740 without metastasis at the time of COVID-19 diagnosis). The primary ordinal outcome was COVID-19 severity: not hospitalized, hospitalized but did not receive supplemental O 2 , hospitalized and received supplemental O 2 , admitted to an intensive care unit, received mechanical ventilation, or died from any cause. The authors used ordinal logistic regression models to compare COVID-19 severity by presence and specific site of metastatic cancer. They used logistic regression models to assess 30-day all-cause mortality., Results: Compared to patients without metastasis, patients with metastases have increased hospitalization rates (59% vs. 49%) and higher 30 day mortality (18% vs. 9%). Patients with metastasis to bone, lung, liver, lymph nodes, and brain have significantly higher COVID-19 severity (adjusted odds ratios [ORs], 1.38, 1.59, 1.38, 1.00, and 2.21) compared to patients without metastases at those sites. Patients with metastasis to the lung have significantly higher odds of 30-day mortality (adjusted OR, 1.53; 95% confidence interval, 1.17-2.00) when adjusting for COVID-19 severity., Conclusions: Patients with metastatic cancer, especially with metastasis to the brain, are more likely to have severe outcomes after COVID-19 whereas patients with metastasis to the lung, compared to patients with cancer metastasis to other sites, have the highest 30-day mortality after COVID-19., (© 2024 American Cancer Society.)

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., Competing Interests: GN, SV, AK, TS, NK, DA, JA, JA, ZB, NB, TB, BB, SB, MB, PB, SB, BB, HB, CC, HC, JD, AD, NE, LF, DF, CF, MG, CG, PG, SG, MH, HH, DH, CH, CJ, SJ, MJ, VK, EK, NK, VK, AK, DK, CL, PL, KL, ML, XL, GL, GL, DM, AM, MM, SM, RM, IM, VM, RN, SN, RN, TN, TO, OP, KP, JP, KP, JP, HP, MP, YR, PR, SR, JR, DR, MR, SR, AR, LS, PS, MS, LS, MS, DS, MS, LT, MT, ST, LW, GW, MW, EW, SM, BF, JW, ML, MA, DS No competing interests declared

Importance: Systematic data on the association between anticancer therapies and thromboembolic events (TEEs) in patients with COVID-19 are lacking., Objective: To 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 Participants: This 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., Exposure: Treatments 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 Measures: Main 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., Results: Of 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 Relevance: In 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.

Background: Data regarding outcomes among patients with cancer and co-morbid cardiovascular disease (CVD)/cardiovascular risk factors (CVRF) after SARS-CoV-2 infection are limited., Objectives: To compare Coronavirus disease 2019 (COVID-19) related complications among cancer patients with and without co-morbid CVD/CVRF., Methods: Retrospective cohort study of patients with cancer and laboratory-confirmed SARS-CoV-2, reported to the COVID-19 and Cancer Consortium (CCC19) registry from 03/17/2020 to 12/31/2021. CVD/CVRF was defined as established CVD or no established CVD, male ≥ 55 or female ≥ 60 years, and one additional CVRF. The primary endpoint was an ordinal COVID-19 severity outcome including need for hospitalization, supplemental oxygen, intensive care unit (ICU), mechanical ventilation, ICU or mechanical ventilation plus vasopressors, and death. Secondary endpoints included incident adverse CV events. Ordinal logistic regression models estimated associations of CVD/CVRF with COVID-19 severity. Effect modification by recent cancer therapy was evaluated., Results: Among 10,876 SARS-CoV-2 infected patients with cancer (median age 65 [IQR 54-74] years, 53% female, 52% White), 6253 patients (57%) had co-morbid CVD/CVRF. Co-morbid CVD/CVRF was associated with higher COVID-19 severity (adjusted OR: 1.25 [95% CI 1.11-1.40]). Adverse CV events were significantly higher in patients with CVD/CVRF (all p <0.001). CVD/CVRF was associated with worse COVID-19 severity in patients who had not received recent cancer therapy, but not in those undergoing active cancer therapy (OR 1.51 [95% CI 1.31-1.74] vs. OR 1.04 [95% CI 0.90-1.20], p interaction <0.001)., Conclusions: Co-morbid CVD/CVRF is associated with higher COVID-19 severity among patients with cancer, particularly those not receiving active cancer therapy. While infrequent, COVID-19 related CV complications were higher in patients with comorbid CVD/CVRF. (COVID-19 and Cancer Consortium Registry [CCC19]; NCT04354701)., Competing Interests: R.M reports research funding from Bayer, Pfizer, and Tempus; and 18 personal fees from AstraZeneca, Bayer, Bristol Myers Squibb, Calithera, 19 Caris, Dendreon, Exelixis, Janssen, Johnson and Johnson, Merck & Co, Myovant, Novartis, Pfizer, Sanofi, Sorrento Therapeutics, Tempus, and Vividion. A.N. reports consulting fees from AstraZeneca, Takeda Oncology and Bantam Pharmaceuticals. B.B. reports research support to institution from Amgen, Bicycle Therapeutics, Boehringer Ingelheim, Ikena Oncology, Kahr Medical, Merck, Syros, Tarveda Therapeutics. Z.B. receives research support from 10.13039/100004328Genentech/imCORE and Bristol Myers Squibb. Personal fees from UpToDate. L.A.F reports clinical trial funding from BMS, EMDserono, Pfizer, Merck, Array, Kartos, Incyte, personal fees from Elsevier, ViaOncology, outside the submitted work. J.L.W. reports research funding from NIH/NCI during the conduct of the work, research funding from AACR, consulting fees from Westat, Roche, Flatiron Health, Melax Tech, other from HemOnc.org LLC (ownership), outside the submitted work. C.H reports stock holdings in Johnson and Johnson; research funding to institution from Merck, Bausch Health, Genentech, Bayer, and AstraZeneca, consultant fees from Tempus, Genzyme, and EMD Sorono, speaking fees from OncLive/MJH Life Sciences, travel fees from Merck, all outside the submitted work. The remaining authors have nothing to disclose., (© 2023 Published by Elsevier Inc.)

Background: Breakthrough SARS-CoV-2 infections following vaccination against COVID-19 are of international concern. Patients with cancer have been observed to have worse outcomes associated with COVID-19 during the pandemic. We sought to evaluate the clinical characteristics and outcomes of patients with cancer who developed breakthrough SARS-CoV-2 infections after 2 or 3 doses of mRNA vaccines., Methods: We evaluated the clinical characteristics of patients with cancer who developed breakthrough infections using data from the multi-institutional COVID-19 and Cancer Consortium (CCC19; NCT04354701). Analysis was restricted to patients with laboratory-confirmed SARS-CoV-2 diagnosed in 2021 or 2022, to allow for a contemporary unvaccinated control population; potential differences were evaluated using a multivariable logistic regression model after inverse probability of treatment weighting to adjust for potential baseline confounding variables. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) are reported. The primary endpoint was 30-day mortality, with key secondary endpoints of hospitalization and ICU and/or mechanical ventilation (ICU/MV)., Findings: The analysis included 2486 patients, of which 564 and 385 had received 2 or 3 doses of an mRNA vaccine prior to infection, respectively. Hematologic malignancies and recent receipt of systemic anti-neoplastic therapy were more frequent among vaccinated patients. Vaccination was associated with improved outcomes: in the primary analysis, 2 doses (aOR: 0.62, 95% CI: 0.44-0.88) and 3 doses (aOR: 0.20, 95% CI: 0.11-0.36) were associated with decreased 30-day mortality. There were similar findings for the key secondary endpoints of ICU/MV (aOR: 0.60, 95% CI: 0.45-0.82 and 0.37, 95% CI: 0.24-0.58) and hospitalization (aOR: 0.60, 95% CI: 0.48-0.75 and 0.35, 95% CI: 0.26-0.46) for 2 and 3 doses, respectively. Importantly, Black patients had higher rates of hospitalization (aOR: 1.47, 95% CI: 1.12-1.92), and Hispanic patients presented with higher rates of ICU/MV (aOR: 1.61, 95% CI: 1.06-2.44)., Interpretation: Vaccination against COVID-19, especially with additional doses, is a fundamental strategy in the prevention of adverse outcomes including death, among patients with cancer., Funding: This study was partly supported by grants from the National Cancer Institute grant number P30 CA068485 to C-YH, YS, SM, JLW; T32-CA236621 and P30-CA046592 to C.R.F; CTSA 2UL1TR001425-05A1 to TMW-D; ACS/FHI Real-World Data Impact Award, P50 MD017341-01, R21 CA242044-01A1, Susan G. Komen Leadership Grant Hunt to MKA. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH)., Competing Interests: TKC reports grants, personal fees and non-financial support from Merck, BMS, Exelixis, Astra Zeneca, Eli Lilly, Eisai, Novartis, GSK, Pfizer, EMD Serono; stocks in Pionyr, Tempest, outside the submitted work; In addition, TKC reports patent: pending International Patent Application No. PCT/US2018/12209, entitled “PBRM1 Biomarkers Predictive of Anti-Immune Checkpoint Response,” filed January 3, 2018, claiming priority to U.S. Provisional Patent Application No. 62/445,094, filed January 11, 2017; pending International Patent Application No. PCT/US2018/058430, entitled “Biomarkers of Clinical Response and Benefit to Immune Checkpoint Inhibitor Therapy,” filed October 31, 2018, claiming priority to U.S. Provisional Patent Application No. 62/581,175, filed November 3, 2017; TKC sits on National Comprehensive Cancer Network kidney panel. CL reports grants from Genentech/ImCore. ZB reports non-financial support from Bristol Myers Squibb, grants from Genentech/ImCore, personal fees from UpToDate, outside the submitted work. ALS reports non-financial support from Astellas and Pfizer outside the submitted work. GdLL reports personal fees from Boehringer Ingelheim, Pfizer, AstraZeneca; grants from AstraZeneca, Merck Sharp & Dohme, EMD Serono, AstraZeneca, Blueprint Medicines, Tesaro, Bavarian Nordic, Novartis, G1 Therapeutics, Adaptimmune, BMS, GSK, Abbvie, Rgenix, Pfizer, Roche, Genentech, Eli Lilly, Janssen; personal fees from Boehringer Ingelheim, Pfizer, E.R. Squibb Sons, LLC, Janssen; all outside the submitted work. CH reports grants from Merck, Bayer, Genentech, AstraZeneca, Bausch Health; Consulting fees from Tempus, Genzyme, EMD Sorono, payment or honoraria from OncLive/MJH Life Sciences, support for attending meetings and/or travel from Merck, participation on a data safety monitoring or advisory board of Henry Ford Cancer Institute, Hoosier Cancer Research Network; Leadership or fiduciary role in Wayne County Medical Society of Southeast Michigan; Stock or stock options in Johnson and Johnson, all outside the submitted work. EAG reports Consulting fees from Alexion Inc, Picnic Health, AbbVie, CTI Biopharma, Genentech Inc., Novartis, Celgene/Bristol Myers-Squibb, Takeda oncology, Taiho Oncology and Research Funding from Genentech Inc, Astex Pharmaceuticals, and BluePrint Medicines, outside the submitted work. SH reports grants/research supports from ASCO TAPUR, Astellas; honoraria or consultation fees from Sanofi, Aveo Oncology, outside the submitted work. SB reports Consulting fees from BMS, Exelexis, Eisai, Pfizer, Myovant, SeaGen; Payment or honoraria from Exelexis, Eisai, BMS; Participation on a Data Safety Monitoring Board or Advisory Board from SeaGen, Pfizer, Myovant; Stock or stock options in Natera; outside the submitted work. MJ reports grants from AstraZeneca, Pfizer; Eisai, personal fees from Seagen, Sanofi, outside the submitted work. NTNG reports personal fees from Novocure, outside the submitted work. RRM reports Advisory board/consultant—Aveo, AstraZeneca, Bayer, Bristol Myers Squib, Calithera, Caris, Dendreon, Exelixis, Janssen, Merck, Myovant, Novartis, Pfizer, Sanofi, Sorrento therapeutics, Pfizer, Tempus, Vividion, unrelated to this work. SMR reports advisory for Roche, Janssen, Sanofi, and EUSA Pharma, unrelated to this work. PV reports institutional research funding from Sanofi; stocks or stock options in Novavax, Biontech. HAZ acknowledges support from Georgia NCORP. CRF reports grants from Merck Foundation, grants from NCCN/Pfizer, grants from National Cancer Institute, other from National Cancer Institute, other from Patient-Centered Outcomes Research Institute, outside the submitted work. SM reports support from National Cancer Institute, and Intl Assoc. for the Study of Lung Cancer during the conduct of the study; and personal fees from National Geographic outside the submitted work. DF reports Grants or contracts from Merck, Viracor, Astellas; Support for attending meetings and/or travel from Viracor; outside the submitted work. JLW reports grants from NIH during the conduct of the study; personal fees from Roche, Westat, Flatiron Health, Melax Tech, IBM Watson Health, ownership of HemOnc.org LLC, grants from AACR; outside the submitted work. TMW-D reports grants from BMS, Merck & Co, GSK/Tesaro, Janssen; personal fees from Exicure, Shattuck Labs, SITC, Merck & Co, Caris Life Sciences, outside the submitted work. C-YH, SRKS, CJ, LBW, UW, TEO'C, OAP, EJK, HS, RN, TKN, RQ, MP, BHM, SADP, KR, BF, DYR, MKA, HS, DRR, YS, and SB have nothing to disclose. The content is solely the responsibility of the authors and does not necessarily represent the US Food and Drug Administration official views or policies., (© 2023 The Author(s).)

Importance: Cytokine 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., Objective: To 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 Participants: This 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., Exposures: Immunosuppression due to therapy; systemic anticancer therapy (IO or non-IO)., Main Outcomes and Measures: The 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., Results: The 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 Relevance: This 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 Registration: ClinicalTrials.gov Identifier: NCT04354701.

Background: The frequency of coinfections and their association with outcomes have not been adequately studied among patients with cancer and coronavirus disease 2019 (COVID-19), a high-risk group for coinfection., Methods: We included adult (≥18 years) patients with active or prior hematologic or invasive solid malignancies and laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection, using data from the COVID-19 and Cancer Consortium (CCC19, NCT04354701). We captured coinfections within ±2 weeks from diagnosis of COVID-19, identified factors cross-sectionally associated with risk of coinfection, and quantified the association of coinfections with 30-day mortality., Results: Among 8765 patients (hospitalized or not; median age, 65 years; 47.4% male), 16.6% developed coinfections: 12.1% bacterial, 2.1% viral, 0.9% fungal. An additional 6.4% only had clinical diagnosis of a coinfection. The adjusted risk of any coinfection was positively associated with age >50 years, male sex, cardiovascular, pulmonary, and renal comorbidities, diabetes, hematologic malignancy, multiple malignancies, Eastern Cooperative Oncology Group Performance Status, progressing cancer, recent cytotoxic chemotherapy, and baseline corticosteroids; the adjusted risk of superinfection was positively associated with tocilizumab administration. Among hospitalized patients, high neutrophil count and C-reactive protein were positively associated with bacterial coinfection risk, and high or low neutrophil count with fungal coinfection risk. Adjusted mortality rates were significantly higher among patients with bacterial (odds ratio [OR], 1.61; 95% CI, 1.33-1.95) and fungal (OR, 2.20; 95% CI, 1.28-3.76) coinfections., Conclusions: Viral and fungal coinfections are infrequent among patients with cancer and COVID-19, with the latter associated with very high mortality rates. Clinical and laboratory parameters can be used to guide early empiric antimicrobial therapy, which may improve clinical outcomes., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background: Data on patients with COVID-19 who have cancer are lacking. Here we characterise the outcomes of a cohort of patients with cancer and COVID-19 and identify potential prognostic factors for mortality and severe illness., Methods: In this cohort study, we collected de-identified data on patients with active or previous malignancy, aged 18 years and older, with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from the USA, Canada, and Spain from the COVID-19 and Cancer Consortium (CCC19) database for whom baseline data were added between March 17 and April 16, 2020. We collected data on baseline clinical conditions, medications, cancer diagnosis and treatment, and COVID-19 disease course. The primary endpoint was all-cause mortality within 30 days of diagnosis of COVID-19. We assessed the association between the outcome and potential prognostic variables using logistic regression analyses, partially adjusted for age, sex, smoking status, and obesity. This study is registered with ClinicalTrials.gov, NCT04354701, and is ongoing., Findings: Of 1035 records entered into the CCC19 database during the study period, 928 patients met inclusion criteria for our analysis. Median age was 66 years (IQR 57-76), 279 (30%) were aged 75 years or older, and 468 (50%) patients were male. The most prevalent malignancies were breast (191 [21%]) and prostate (152 [16%]). 366 (39%) patients were on active anticancer treatment, and 396 (43%) had active (measurable) cancer. At analysis (May 7, 2020), 121 (13%) patients had died. In logistic regression analysis, independent factors associated with increased 30-day mortality, after partial adjustment, were: increased age (per 10 years; partially adjusted odds ratio 1·84, 95% CI 1·53-2·21), male sex (1·63, 1·07-2·48), smoking status (former smoker vs never smoked: 1·60, 1·03-2·47), number of comorbidities (two vs none: 4·50, 1·33-15·28), Eastern Cooperative Oncology Group performance status of 2 or higher (status of 2 vs 0 or 1: 3·89, 2·11-7·18), active cancer (progressing vs remission: 5·20, 2·77-9·77), and receipt of azithromycin plus hydroxychloroquine (vs treatment with neither: 2·93, 1·79-4·79; confounding by indication cannot be excluded). Compared with residence in the US-Northeast, residence in Canada (0·24, 0·07-0·84) or the US-Midwest (0·50, 0·28-0·90) were associated with decreased 30-day all-cause mortality. Race and ethnicity, obesity status, cancer type, type of anticancer therapy, and recent surgery were not associated with mortality., Interpretation: Among patients with cancer and COVID-19, 30-day all-cause mortality was high and associated with general risk factors and risk factors unique to patients with cancer. Longer follow-up is needed to better understand the effect of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments., Funding: American Cancer Society, National Institutes of Health, and Hope Foundation for Cancer Research., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Purpose: Asbestos exposure is the major known risk factor for mesothelioma, but several case reports have suggested a link between radiation therapy and subsequent development of malignant mesothelioma. This report explores a possible association between radiation therapy for Hodgkin's disease and mesothelioma., Patients and Methods: Four cases of malignant mesothelioma were observed following Hodgkin's disease at the Mesothelioma Clinic of the Dana-Farber Cancer Institute. A fifth such patient was found after a review of the literature., Results: In all five cases, the mesothelioma arose in the field of prior radiotherapy. No history of asbestos exposure was elicited by careful questioning or by review of chest radiographs. Examination of lung tissue in one patient showed 250 ferruginous bodies per gram of lung tissue, consistent with no significant prior exposure. The mean interval between radiation treatment for Hodgkin's disease and development of mesothelioma was 15 years, which emphasizes the need for continued follow-up and evaluation of these patients and supports a causal relationship., Conclusion: Mesothelioma may need to be added to the list of second malignancies that arise following radiation therapy for Hodgkin's disease. Further support is given to a causal link between radiation exposure and mesothelioma.

It is predicted that up to 80,000 cases of mesothelioma will occur in the next 20 years, and thus it is increasingly important to better understand this disease. There is much controversy over the best treatment, which ranges from supportive care alone to aggressive debulking surgery combined with radiation and chemotherapy. This article summarizes the results with these various regimens to date, and discusses promising new options for therapy that may ultimately lead to increased survival.

Transamidase (i.e., "transglutaminase") activity of human erythrocytes, lysed by a single freezing and thawing to 37 degrees, was measured by a method of incorporating [14C]putrescine into N,N'-dimethylcasein. In the absence of added calcium ions, virtually no enzyme activity could be detected. An increase in concentration of the cation to about 0.5 mM, however, turned on the enzyme to appreciable levels of activity. Simultaneously, Ca2+ produced formation of high molecular weight, nondisulfied bonded protein polymers either directly in the lysate or in fresh cells when the cation was added together with the A23187 ionophore. The polymers could be readily identified in the isolated cell ghosts by means of disc gel electrophoresis. If the Ca2+-promoted formation of polymers was allowed to take place in the presence of 14C-putrescine, then this tracer became incorporated into the polymeric material. The incorporation indicated that polymerization occurred through gamma-glutamyl-epsilon-lysine bridtes. It is suggested that the intrinsic transamidase mediates protein crosslinking of the erythrocyte membrane whenever there is an increase in intracellular Ca2+ concentration. The presence of suitable transglutaminase substrates, e.g. histamine, inhibited crosslinking when the cells were incubated with Ca2+ and ionophore.