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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.)

The focus of present study was to find out the effect of non-genetic factors on linear type traits in Karan Fries and Sahiwal cows reared at an organized farm of northern India. The present study was conducted on Lactating Karan Fries ( N  = 123) and Sahiwal ( N  = 133) cows maintained at Livestock Research Center of ICAR- National Dairy Research Institute, Karnal, India during the period of 2017-2019. Total eight udder morphometric traits and seven teat morphometric traits were measured. The linear model including fixed effects of season, parity and stage of lactation was used for the analysis. In Karan Fries cows, linear type traits were significantly affected by parity and stage of lactation, while in Sahiwal cows linear type traits were significantly affected by season, parity and stage of lactation. Udder depth (UD) and udder circumference (UC) were significantly ( p  < 0.05) affected by season, parity and stage of lactation in Sahiwal cattle, while in Karan Fries cattle udder length (UL) and shortest distance from rear teat ends to floor (SDR) were significantly ( p  < 0.01) affected by parity and stage of lactation. The results pertaining to present study indicated that season, parity and stages of lactation were important sources of variation for most of linear type traits. Adjustment of data for these effects is necessary to reduce known differences between animals and to obtain reliable estimates of the traits.

Purpose: Prime childbearing years occur during medical training and early career, leaving physicians with tough choices between family planning and career growth. Restrictive workplace parental leave (PL) policies may negatively affect physician well-being. We evaluate existing PL and lactation policies, as well as return-to-work experiences, among oncology trainees and early-career faculty., Methods: An anonymous 43-question cross-sectional survey was distributed via e-mail and social media channels between May and June 2021 to oncology trainees and physicians within 5 years of terminal training in the United States. The survey was administered through SurveyMonkey. Descriptive statistics were used to analyze data. Two hundred seventy-five participants were recruited via social media and outreach to program directors and coordinators in adult hematology/oncology and radiation oncology program directors., Results: The average duration of PL was <6 weeks for most participants. Among those who used PL, 50% felt pressured to work while on PL, 60% felt guilty asking coworkers for help, and 79% were overwhelmed with demands of work and home, whereas only 27% had resources available at workplace to assist with transition back to work. Among those who breastfed at return to work, 31% did not have access to a lactation room, 56% did not have adequate pumping breaks, and 66% did not have pumping breaks mandated in contract., Conclusion: Our findings underline the immense magnitude of problems surrounding inadequate PL and support for lactating mothers among trainees and early-career physicians in oncology subspecialities. Policies and practices around PL and lactation should be restructured to meet the needs of the evolving oncology workforce.

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.

Introduction: COVID-19 particularly impacted patients with co-morbid conditions, including cancer. Patients with melanoma have not been specifically studied in large numbers. Here, we sought to identify factors that associated with COVID-19 severity among patients with melanoma, particularly assessing outcomes of patients on active targeted or immune therapy., Methods: Using the COVID-19 and Cancer Consortium (CCC19) registry, we identified 307 patients with melanoma diagnosed with COVID-19. We used multivariable models to assess demographic, cancer-related, and treatment-related factors associated with COVID-19 severity on a 6-level ordinal severity scale. We assessed whether treatment was associated with increased cardiac or pulmonary dysfunction among hospitalized patients and assessed mortality among patients with a history of melanoma compared with other cancer survivors., Results: Of 307 patients, 52 received immunotherapy (17%), and 32 targeted therapy (10%) in the previous 3 months. Using multivariable analyses, these treatments were not associated with COVID-19 severity (immunotherapy OR 0.51, 95% CI 0.19 - 1.39; targeted therapy OR 1.89, 95% CI 0.64 - 5.55). Among hospitalized patients, no signals of increased cardiac or pulmonary organ dysfunction, as measured by troponin, brain natriuretic peptide, and oxygenation were noted. Patients with a history of melanoma had similar 90-day mortality compared with other cancer survivors (OR 1.21, 95% CI 0.62 - 2.35)., Conclusions: Melanoma therapies did not appear to be associated with increased severity of COVID-19 or worsening organ dysfunction. Patients with history of melanoma had similar 90-day survival following COVID-19 compared with other cancer survivors., (© 2023. The Author(s).)

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).)

Agriculture in India accounts for 18% of greenhouse gas (GHG) emissions and uses significant land and water. Various socioeconomic factors and food subsidies influence diets in India. Indian food systems face the challenge of sustainably nourishing the 1.3 billion population. However, existing studies focus on a few food system components, and holistic analysis is still missing. We identify Indian food systems covering six food system components: food consumption, production, processing, policy, environmental footprints, and socioeconomic factors from the latest Indian household consumer expenditure survey. We identify 10 Indian food systems using k-means cluster analysis on 15 food system indicators belonging to the six components. Based on the major source of calorie intake, we classify the ten food systems into production-based (3), subsidy-based (3), and market-based (4) food systems. Home-produced and subsidized food contribute up to 2000 kcal/consumer unit (CU)/day and 1651 kcal/CU/day, respectively, in these food systems. The calorie intake of 2158 to 3530 kcal/CU/day in the food systems reveals issues of malnutrition in India. Environmental footprints are commensurate with calorie intake in the food systems. Embodied GHG, land footprint, and water footprint estimates range from 1.30 to 2.19 kg CO2eq/CU/day, 3.89 to 6.04 m2/CU/day, and 2.02 to 3.16 m3/CU/day, respectively. Our study provides a holistic understanding of Indian food systems for targeted nutritional interventions on household malnutrition in India while also protecting planetary health., Competing Interests: The authors declare no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

Importance: Non-Hispanic Black individuals experience a higher burden of COVID-19 than the general population; hence, there is an urgent need to characterize the unique clinical course and outcomes of COVID-19 in Black patients with cancer., Objective: To investigate racial disparities in severity of COVID-19 presentation, clinical complications, and outcomes between Black patients and non-Hispanic White patients with cancer and COVID-19., Design, Setting, and Participants: This retrospective cohort study used data from the COVID-19 and Cancer Consortium registry from March 17, 2020, to November 18, 2020, to examine the clinical characteristics and outcomes of COVID-19 in Black patients with cancer. Data analysis was performed from December 2020 to February 2021., Exposures: Black and White race recorded in patient's electronic health record., Main Outcomes and Measures: An a priori 5-level ordinal scale including hospitalization intensive care unit admission, mechanical ventilation, and all-cause death., Results: Among 3506 included patients (1768 women [50%]; median [IQR] age, 67 [58-77] years), 1068 (30%) were Black and 2438 (70%) were White. Black patients had higher rates of preexisting comorbidities compared with White patients, including obesity (480 Black patients [45%] vs 925 White patients [38%]), diabetes (411 Black patients [38%] vs 574 White patients [24%]), and kidney disease (248 Black patients [23%] vs 392 White patients [16%]). Despite the similar distribution of cancer type, cancer status, and anticancer therapy at the time of COVID-19 diagnosis, Black patients presented with worse illness and had significantly worse COVID-19 severity (unweighted odds ratio, 1.34 [95% CI, 1.15-1.58]; weighted odds ratio, 1.21 [95% CI, 1.11-1.33])., Conclusions and Relevance: These findings suggest that Black patients with cancer experience worse COVID-19 outcomes compared with White patients. Understanding and addressing racial inequities within the causal framework of structural racism is essential to reduce the disproportionate burden of diseases, such as COVID-19 and cancer, in Black patients.

Importance: The COVID-19 pandemic has had a distinct spatiotemporal pattern in the United States. Patients with cancer are at higher risk of severe complications from COVID-19, but it is not well known whether COVID-19 outcomes in this patient population were associated with geography., Objective: To quantify spatiotemporal variation in COVID-19 outcomes among patients with cancer., Design, Setting, and Participants: This registry-based retrospective cohort study included patients with a historical diagnosis of invasive malignant neoplasm and laboratory-confirmed SARS-CoV-2 infection between March and November 2020. Data were collected from cancer care delivery centers in the United States., Exposures: Patient residence was categorized into 9 US census divisions. Cancer center characteristics included academic or community classification, rural-urban continuum code (RUCC), and social vulnerability index., Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. The secondary composite outcome consisted of receipt of mechanical ventilation, intensive care unit admission, and all-cause death. Multilevel mixed-effects models estimated associations of center-level and census division-level exposures with outcomes after adjustment for patient-level risk factors and quantified variation in adjusted outcomes across centers, census divisions, and calendar time., Results: Data for 4749 patients (median [IQR] age, 66 [56-76] years; 2439 [51.4%] female individuals, 1079 [22.7%] non-Hispanic Black individuals, and 690 [14.5%] Hispanic individuals) were reported from 83 centers in the Northeast (1564 patients [32.9%]), Midwest (1638 [34.5%]), South (894 [18.8%]), and West (653 [13.8%]). After adjustment for patient characteristics, including month of COVID-19 diagnosis, estimated 30-day mortality rates ranged from 5.2% to 26.6% across centers. Patients from centers located in metropolitan areas with population less than 250 000 (RUCC 3) had lower odds of 30-day mortality compared with patients from centers in metropolitan areas with population at least 1 million (RUCC 1) (adjusted odds ratio [aOR], 0.31; 95% CI, 0.11-0.84). The type of center was not significantly associated with primary or secondary outcomes. There were no statistically significant differences in outcome rates across the 9 census divisions, but adjusted mortality rates significantly improved over time (eg, September to November vs March to May: aOR, 0.32; 95% CI, 0.17-0.58)., Conclusions and Relevance: In this registry-based cohort study, significant differences in COVID-19 outcomes across US census divisions were not observed. However, substantial heterogeneity in COVID-19 outcomes across cancer care delivery centers was found. Attention to implementing standardized guidelines for the care of patients with cancer and COVID-19 could improve outcomes for these vulnerable patients.

Background: Cardiopulmonary arrest is known to have a poor prognosis, further worsened by preexisting comorbidities. With improved treatment, the prevalence of metastatic cancers is rapidly increasing; however, the outcomes of in-hospital cardiopulmonary resuscitation (ICPR) remain to be well described. This study examines the epidemiology, associations, and outcomes of ICPR in these patients., Methods: This is a retrospective cohort analysis of the Nationwide Inpatient Sample database (2012-2014) including patients aged ≥18 years with metastatic cancers. Primary outcome was inpatient mortality following ICPR. Factors associated with the primary outcome were analyzed using univariate/multivariate logistic regression analysis., Results: Among all admissions with metastatic cancers (n = 5,500,684), 0.47% (n = 26,070) received ICPR. Inpatient mortality was 81.77% (n = 8905) versus 68.90% among those without metastatic solid cancers and receiving ICPR. Inpatient palliative care encounter was documented in 18.95% of patients with metastatic cancer who received ICPR. On multivariate logistic regression, some of the notable factors associated with higher mortality included being of African American or Hispanic race and hospital admission over the weekend. Factors associated with lower mortality included female sex, elective admission, and head and neck as the primary site. Admissions with ICPR were associated with higher mean total charge of hospitalization (by $48,670) compared with admissions without ICPR. Of those who survived ICPR, 43.82% were transferred to another facility after discharge., Conclusions: Among adult patients with metastatic solid cancers having ICPR, 81.8% died within the same hospital admission. Race and admission type predicted mortality. Despite known poor prognosis, only a minority had palliative care., Lay Summary: Cardiopulmonary resuscitation during hospitalization for patients who have metastatic cancer has a very poor outcome with a mortality rate of 81.77%. Inpatient cardiopulmonary resuscitation in these patients is also associated with a significantly higher cost of care, longer length of stay, and high rate of transfer to a different health care facility upon discharge. Knowledge of these outcomes is helpful in discussing the pros and cons of pursuing aggressive resuscitative interventions with patients and families., (© 2021 American Cancer Society.)

Background: Patients with cancer may be at high risk of adverse outcomes from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed a cohort of patients with cancer and coronavirus 2019 (COVID-19) reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anticancer therapies., Patients and Methods: Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between 17 March and 18 November 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anticancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients)., Results: A total of 4966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic black race, Hispanic ethnicity, worse Eastern Cooperative Oncology Group performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count; high absolute neutrophil count; low platelet count; abnormal creatinine; troponin; lactate dehydrogenase; and C-reactive protein were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anticancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality., Conclusions: Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anticancer therapies., Clinical Trial Identifier: NCT04354701., Competing Interests: Disclosure JDA reports research funding to the institution from Tesaro, outside the submitted work. ZB reports nonfinancial support from Bristol Myers Squibb and grants from Genentech/imCORE, outside the submitted work. BB reports research funding to the institution from Boehringer Ingelheim, Bicycle Therapeutics, Syros Pharmaceuticals, and Ikena Oncology, all outside the submitted work. TB-S reports research funding to the institution from Agios, Arys, Boston Biomedical, Bayer, Amgen, Merck, Celgene, Lilly, Ipsen, Clovis, Seattle Genetics, Array Biopharma, Genentech, Novartis, Mirati, Merus, AbGenomics, Incyte, Pfizer, BMS; consulting (to institution) for Ipsen, Array Biopharma, Pfizer, Seattle Genetics, Bayer, Genentech, Incyte, and Merck; consulting (to self) for AbbVie, Boehringer Ingelheim, Janssen, Eisai, Daiichi Sankyo, Natera, Treos Bio, Celularity, Exact Science, Sobi, BeiGene, Xilis, Astra Zeneca, and Foundation Medicine; serving on Independent Data Monitoring Committee/Data and Safety Monitoring Board (to self) for AstraZeneca, Exelixis, Lilly, PanCAN, and 1Globe; positions on Scientific Advisory Board for Imugene, Immuneering, and Sun Biopharma; and inventions/patents (WO/2018/183488 and WO/2019/055687), all outside the submitted work. SB reports being on advisory boards for Bristol Meyers Squibb and Seattle Genetics. MAB reports personal fees from Exelixis, Bristol-Myers Squibb, Bayer, Eisai, Pfizer, AstraZeneca, Janssen, Genomic Health, Nektar, and Sanofi; grants from Xencor, Bayer, Bristol-Myers Squibb, Genentech/Roche, Seattle Genetics, Incyte, Nektar, AstraZeneca, Tricon Pharmaceuticals, Peloton Therapeutics, and Pfizer, outside the submitted work. NB reports honoraria from Novartis, Pfizer, Roche, and Lilly, outside the submitted work. DWB reports research funding to the institution from Exelixis, Ayala, Merck, and Elevar, all outside the submitted work. DDC declares consulting or advisory role with Exelixis, outside the submitted work. TKC reports institutional and personal research support from Alexion, Analysis Group, AstraZeneca, Aveo, Bayer, Bristol Myers-Squibb/ER Squibb and sons LLC, Calithera, Cerulean, Corvus, Eisai, Exelixis, F. Hoffmann-La Roche, Foundation Medicine Inc., Genentech, GlaxoSmithKline, Ipsen, Lilly, Merck, Novartis, Peloton, Pfizer, Prometheus Labs, Roche, Roche Products Limited, Sanofi/Aventis, Takeda, Tracon; consulting/honoraria or advisory role with Alexion, Analysis Group, AstraZeneca, Aveo, Bayer, Bristol Myers-Squibb/ER Squibb and sons LLC, Cerulean, Corvus, Eisai, EMD Serono, Exelixis, Foundation Medicine Inc., Genentech, GlaxoSmithKline, Heron Therapeutics, Infinity Pharma, Ipsen, Jansen Oncology, IQVIA, Lilly, Merck, NCCN, Novartis, Peloton, Pfizer, Pionyr, Prometheus Labs, Roche, Sanofi/Aventis, Surface Oncology, Tempest, Up-to-Date; CME-related events (e.g. OncLive, PVI, MJH Life Sciences); stock ownership in Pionyr, Tempest; patents filed, royalties, or other intellectual properties related to biomarkers of immune checkpoint blockers; fees for travel, accommodations, expenses, medical writing in relation to consulting, advisory roles, or honoraria; and no speaker's bureau; also supported in part by the Dana-Farber/Harvard Cancer Center Kidney SPORE and Program, the Kohlberg Chair at Harvard Medical School and the Trust Family, Michael Brigham, and Loker Pinard Funds for Kidney Cancer Research at DFCI. DBD reports consulting for Ipsen, Boehringer Ingelheim; ASCO Young Investigator Award from Conquer Cancer Foundation, outside the submitted work. AE reports grant support from AstraZeneca, outside the submitted work. DF reports research funding to the institution from Viracor-Eurofins and Astellas, all outside the submitted work. LAF reports clinical trial funding to the institution from BMS, EMD Serono, Pfizer, Merck KGaA, Array, Kartos, Merck, and Incyte, ECOG-ACRIN study funding from Array; and personal fees from Elsevier and Via Oncology, outside the submitted work. DBF reports honoraria from Castle Biosciences. SMG reports Honoraria from AstraZeneca, Merck, Genentech/Roche; consulting or advisory role with Genentech/Roche, AstraZeneca, Bristol-Myers Squibb, Takeda, Xcovery, Boehringer Ingelheim, Novocure, Daiichi Sankyo, Novartis, Jazz Pharmaceuticals, Blueprint Medicines, Eli Lilly, Pfizer, Janssen Oncology; research funding (to self) from Merck, AstraZeneca; research funding (to institution) from Genentech/Roche, Merck, Blueprint Medicines, ARIAD/Takeda, Astellas Pharma, Lycera, Daiichi Sankyo, IMAB, Nektar, AstraZeneca, Pfizer, Amgen; travel, accommodations, expenses from Genentech/Roche, Merck; and other relationship from AstraZeneca, all outside the submitted work. MDG reports personal fees from Genentech, Pfizer, Astra Zeneca, Merck, Bristol Myers Squib, Dragonfly, Dracen, Seattle Genetics, and Astellas, outside the submitted work. PG reports consulting fees from AstraZeneca, Bayer, Bristol-Myers Squibb, Clovis Oncology, Dyania Health, Driver, EMD Serono, Exelixis, Foundation Medicine, Genentech/Roche, Genzyme, GlaxoSmithKline, Heron Therapeutics, Immunomedics, Infinity Pharmaceuticals, Janssen, Merck, Mirati Therapeutics, Pfizer, Seattle Genetics, QED Therapeutics; research funding to institution from Merck, Mirati Therapeutics, Pfizer, Clovis Oncology, Bavarian Nordic, Immunomedics, Debiopharm, Bristol-Myers Squibb, QED Therapeutics, GlaxoSmithKline, and Kure It Cancer Research, all outside the submitted work. SG reports research funding to the institution from AstraZeneca and consulting/advisory role with Puma Biotechnology. SG reports consultancy fees from BMS, Merck, AstraZeneca, Seattle Genetics, Pfizer; and speaker fees from Seattle Genetics and Janssen, all outside the submitted work. TRH reports consulting or advisory role with Curium, ScioScientific, TERUMO, Lexicon, Ipsen, Advanced Accelerator; research funding from Ipsen, ArQule, Agios, Thermo Fisher Scientific, Basilea. BH reports research funding to the institution from Amgen, AbbVie, BI, Mirati, Merck, Eli-Lilly, AstraZeneca, BMS, Novartis, GSK, Pfizer, Advaxis, and Guardant Health; consulting/advisory role with Merck, BMS, Genentech, AstraZeneca, Amgen, Novartis, TPT, VI, Guardant Health; and honoraria from PER and OncLive, all outside the submitted work. JEH reports research funding from Regeneron and Dendreon; and travel, accommodations, and expenses from Genzyme. CH reports funding from the Henry Ford Cancer Institute supporting the current work; research funding to institution from Merck, Exelixis, Bayer, AstraZeneca, Genentech, Dendreon and Bausch; personal fees from Sanofi/Genzyme, Dendreon, Exelixis, Bristol Myers Squibb, Astellas, Medivation, Bayer, and Janssen Scientific, all outside the submitted work; and stock ownership by an immediate family member in Johnson and Johnson. DBJ reports advisory board participation for Array Biopharma, BMS, Catalyst Biopharma, Iovance, Jansen, Merck, Novartis, and OncoSec, and receives research funding from BMS and Incyte, all outside the submitted work. AK reports support to his institution from TESARO, Halozyme, Geistlich Pharma, Astellas Pharma, and Rafael Pharmaceuticals; and honoraria from OncLive, outside the submitted work. ARK (or an immediate family member) has currently or during the past 2 years owned stock or held an ownership interest in Merck, Sanofi, and BMS. VSK reports personal fees from Pfizer, Janssen, Dendreon, AstraZeneca, Seattle Genetics, and Clovis; grants (for institution) from Nektar, Novartis/Endocyte, Janssen, Clovis, and Prostate Cancer Foundation, all outside the submitted work. NMK reports personal fees from G1 Therapeutics, Invitae, Beyond Spring, Spectrum, BMS, Janssen, and Total Health, all outside the submitted work. PEL reports consulting/advisory role with Pfizer, Merck, Teva, BI, and Astra Zeneca, all outside the submitted work. AL-B reports personal fees from PSI CRO, Bayer, Blueprint, Astra-Zeneca, Medidata, Taiho, QED, Cardinal Health, BrightInsight, The Lynx Group, Boston Biomedical, Amgen, Bayer, Guardant, Natera, Eisai, Ipsen, and Merck; and stock options from Massive Bio, outside the submitted work. GdLL reports honoraria from Boehringer Ingelheim; consulting or advisory role for Pfizer and AstraZeneca; research funding from AstraZeneca; funding to his institution from Merck Sharp & Dohme, EMD Serono, AstraZeneca, Blueprint Medicines, Tesaro, Bavarian Nordic, NOVARTIS, G1 Therapeutics, Adaptimmune, BMS, GSK, AbbVie, Rgenix, Pfizer, Roche, Genentech, Lilly, and Janssen; travel, accommodations, and expenses from Boehringer Ingelheim, Pfizer, E.R. Squibb Sons, LLC, Janssen. GHL reports grants from AMGEN (institution); personal fees from G1 Therapeutics, TEVA, Samsung Bioepis, Beyond Spring, and Merck, outside the submitted work. RRM reports research funding from Bayer, Pfizer, Tempus; serves on Advisory Board for AstraZeneca, Bayer, Bristol Myers Squibb, Calithera, Exelixis, Janssen, Merck, Novartis, Pfizer, Sanofi, Tempus; is a consultant for Dendreon, Vividion; and serves on the molecular tumor board at Caris. RAM grants from Incyte, CTI, AbbVie, and Celgene; personal fees from Novartis, Genentech, Sierra Oncology, La Jolla, and Samus, outside the submitted work. VM has currently or during the past 2 years employment and stock or other ownership interest with Johnson & Johnson, all outside the submitted work. GN reports research funding to the institution from Novartis, all outside the submitted work. JN reports personal fees from AstraZeneca, Clovis Oncology; all outside the submitted work. CAP (or an immediate family member) has currently or during the past 2 years owned stock or held an ownership interest in Pfizer, Epizyme, Inovio, OPKO Health Inc, Roche. JMP reports grant from Dana-Farber/Harvard Cancer Center Breast SPORE Program, outside the submitted work. PP reports receiving payment for speakers' bureau from Novartis, Daichi Sankyo, Genentech, Seattle Genetics, and Pfizer, all outside the submitted work. NAP reports personal fees from Eli Lilly, Merck, BMS, Genentech, AstraZeneca, Inivata, and Regeneron, outside the submitted work. SP reports personal fees from AbbVie, Amgen, AstraZeneca, Bayer, Biocartis, Boehringer-Ingelheim, Bristol-Myers Squibb, Clovis, Daiichi Sankyo, Debiopharm, Eli Lilly, F. Hoffmann-La Roche, Foundation Medicine, Illumina, Janssen, Merck Sharp and Dohme, Merck Serono, Merrimack, Novartis, Pharma Mar, Pfizer, Regeneron, Sanofi, Seattle Genetics and Takeda, AstraZeneca, Boehringer-Ingelheim, Bristol-Myers Squibb, Eli Lilly, F. Hoffmann-La Roche, Merck Sharp and Dohme, Novartis, Pfizer, and Takeda; nonfinancial support from Amgen, AstraZeneca, Boehringer-Ingelheim, Bristol-Meyers Squibb, Clovis, F. Hoffmann-La Roche, Illumina, Merck Sharp and Dohme, Merck Serono, Novartis, Pfizer, and Sanofi; and personal fees from BioInvent (all fees to institution), outside the submitted work. DYR reports consulting/advisory role with and coverage of travel/accommodation expenses by Castle Biosciences, all outside the submitted work. BIR reports grants, personal fees, and nonfinancial support from Merck; grants and personal fees from BMS, Pfizer, Aveo, and Genentech; grants from Astra Zeneca; personal fees from Synthorx, 3D Medicines, Aravive, Surface Oncology, and Arrowhead Therapeutics; and other from PTC Therapeutics, outside the submitted work. RPR reports research grants to her institution from BMS and Janssen and has worked as a consultant/advisor and received honoraria from BMS and Janssen, all of which are outside the scope of submitted work. ALS reports travel support provided by Pfizer and Astellas. GKS reports personal fees from Apexigen, Array, Epizyme, GenCirq, Daiichi Sankyo, Fortress, Iovance Biotherapeutics, Bayer Pharmaceuticals, Pfizer Oncology, Array Advisory Board, Oncogenuity, Puretech, PTC Therapeutics, Ellipses Pharma, Concarlo; advisory board for Bionaut; grants from Astex; stock ownership in Pfizer, all outside the submitted work. SS reports stock and other ownership interests in Grand Rounds, Janssen, and Natera. YS reports honoraria from Boehringer Ingelheim, AstraZeneca, Novartis, and Eisai; consulting or advisory role with Pfizer, AstraZeneca, Novartis, Roche, Genentech, and Janssen, all outside the submitted work. MAT reports travel support from Syapse, Royalties from UpToDate, Connect MDS/AML Registry in Celgene (now owned by BMS), Myeloma Registry in Takeda; stock ownership in Doximity; personal fees from VIA Oncology (now owned by Elsevier ClinicalPath), Adaptive Advisory Board, and GSK; he is the local PI for Clinical Trials in AbbVie, BMS, CRAB CTC, Denovo, Research Network, Eli Lilly, LynxBio, Strata Oncology, and TG Therapeutics, all outside the submitted work. AKV reports research funding to the institution from BMS, MedPacto, Prelude, iOnctura, and Janssen; honoraria from Acceleron and Novartis; consulting/advisory role with Stelexis and Janssen; stock or other ownership in Stelexis; and an immediate family member with employment/leadership with CereXis, all outside the submitted work. DCV reports honoraria and speakers' bureau fees from CSL Behring, Merck Canada, Novartis Canada, Takeda, and UCB Biosciences GmbH, and travel accommodations from CSL Behring, and Avir Pharma, all outside the submitted work. He is supported by the Fonds de la recherche en santé du Québec (FRQS) Clinician-Scientist Junior 2 program. JLW reports grants from the National Cancer Institute during the conduct of the study; personal fees from Westat and IBM Watson Health; and other from HemOnc.org LLC, outside the submitted work. TMW-D reports stock and other ownership interests in High Enroll; honoraria from Physicians' Education Resource; consulting or advisory roles with Shattuck Labs, Rakuten Medical, Exicure; research funding from Merck, AstraZeneca/MedImmune, Bristol-Myers Squibb, GlaxoSmithKline, Caris Life Sciences, GlaxoSmithKline; travel, accommodations, expenses from Merck, Bristol-Myers Squibb, Bexion, AstraZeneca/MedImmune, Caris Life Sciences, Lilly, and Tesaro, all outside the submitted work. EW-B reports work in a consultant/advisor role for Astellas and BMS; funding support from Pfizer Global Medical Grants; other for Exelixis; and an immediate family member with stock ownership in Immunomedics and Nektar, all outside the submitted work. TZ reports research funding (to Duke) from Pfizer, Janssen, Acerta, AbbVie, Novartis, Merrimack, OmniSeq, PGDx, Merck, Mirati, Astellas, and Regeneron; consulting/speaking role with Genentech Roche, Exelixis, Genomic Health, and Sanofi Aventis; and serves on the consulting/advisory board for AstraZeneca, Bayer, Pfizer, Foundation Medicine, Janssen, Amgen, BMS, Calithera, Dendreon, and MJH Associates; stock ownership/employment (spouse) from Capio Biosciences, Archimmune Therapeutics, and Nanorobotics. AYZ has currently or during the past 2 years owned stock or held an ownership interest in Gilead Sciences. LZ reports personal fees from MERCK, outside the submitted work. All others have declared no conflicts of interest., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The incidence of invasive melanoma is rising, and approval for the first immune checkpoint inhibitor (ICI) to treat metastatic melanoma occurred in 2011. We aim to describe the epidemiology and outcomes in recent years, sociodemographic factors associated with the presence of metastasis at diagnosis, and the real-world impact of ICI approval on survival based on melanoma subtype and race. Methods: This is a retrospective analysis of the National Cancer Database (NCDB) from the years 2004-2015. The primary outcome was the overall survival of metastatic melanoma by subtype. Secondary outcomes included sociodemographic factors associated with the presence of metastasis at diagnosis and the impact of treatment facility type and ICI approval on the survival of metastatic melanoma. Results: Of the 419,773 invasive melanoma cases, 93.80% were cutaneous, and 4.92% were metastatic at presentation. The odds of presenting with metastatic disease were higher in African Americans (AA) compared to Caucasians (OR 2.37; 95% CI 2.11-2.66, p < 0.001). Treatment of metastatic melanoma at an academic/research facility was associated with lower mortality versus community cancer programs (OR 0.75, 95 % CI 0.69-0.81, p -value < 0.001). Improvement in survival of metastatic melanoma was noted for Caucasians after the introduction of ICI (adjusted HR 0.80, 95% CI 0.78-0.83, p < 0.001); however, this was not statistically significant for AA (adjusted HR 0.80, 95% CI 0.62-1.02, p -value = 0.073) or ocular cases (HR 1.03, 95% CI 0.81-1.31, p -value = 0.797). Conclusion: Real-world data suggest a 20% improvement in survival of metastatic melanoma since the introduction of ICI. The disproportionately high odds of metastatic disease at presentation in AA patients with melanoma suggest the need for a better understanding of the disease and improvement in care delivery.

We describe a case of haemophagocytic lymphohistiocytosis (HLH) secondary to disseminated histoplasmosis, which was treated with chemotherapy in addition to standard antifungal therapy. While HLH in the setting of infections is very well described, its treatment in this setting is controversial, with some physicians treating only the underlying infection, whereas others using immune suppression in addition to antimicrobials. To the best of our knowledge, this is the first report documenting the successful treatment of an adult patient with HLH due to disseminated histoplasmosis using etoposide chemotherapy after initial antifungal therapy failed to show improvement., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Lung cancer screening (LCS) with annual low-dose computed tomography in high-risk groups decreases the mortality related to lung cancer. Its implementation rate has been low, and knowledge relating to LCS has not been assessed in providers treating underserved populations., Materials and Methods: An institutional review board-approved anonymous survey was sent to primary care physicians of the Cook County Health system, a safety-net healthcare system. The survey assessed the knowledge pertaining to LCS guidelines, providers' experience with LCS, and their recommendations for quality improvement using 24 questions. The predictors of LCS within the previous 6 months were identified using logistic regression analysis., Results: Of the 152 survey responses, 43% were from nontrainees with diverse training backgrounds. Adequate knowledge of LCS was demonstrated by 72% of the respondents, and pretest counseling was the domain most often answered incorrectly in the questionnaire. LCS had been ordered in the previous 6 months by 57% of the respondents. However, 88% estimated that they had screened < 50% of eligible patients. Higher patient volume, more experience, and family medicine training predicted for ordering LCS in the previous 6 months. In addition, 82.2% indicated that prompts in the electronic medical records would increase LCS, and 78.3% reported that receiving statistics about their LCS practice would increase LCS performance., Conclusions: Primary care physicians in the hospital healthcare system had reasonable knowledge of LCS, but the implementation rate was low. We have identified areas for improvement relating to LCS implementation., (Copyright © 2020 Elsevier Inc. All rights reserved.)

(1) Background: Outcomes with coronavirus disease 2019 (COVID-19) have been worse in those with comorbidities and amongst minorities. In our study, we describe outcomes amongst cancer patients in Detroit, a major COVID-19 hotspot with a predominant inner-city population. (2) Methods: We retrospectively analyzed 85 patients with active invasive cancers who were infected with COVID-19. The primary outcome was death or transition to hospice. (3) Results: The majority were males (55.3%, n = 47), ≤70 years old (58.5%, n = 50), and African Americans (65.5%, n = 55). The most common primary site was prostate (18.8%, n = 16). Inpatient admission was documented in 85.5% (n = 73), ICU admission in 35.3% (n = 30), and primary outcome in 43.8% (n = 32) of hospitalized patients. On a multivariate analysis, factors associated with increased odds of a primary outcome included an age of >70 years versus ≤70 years (OR 4.7, p = 0.012) and of male gender (OR 4.8, p = 0.008). Recent cancer-directed therapy was administered in 66.7% (n = 20) of ICU admissions versus 39.5% (n = 17) of general floor admissions (Chi-square p -value of 0.023). (4) Conclusions: High rates of mortality/transition to hospice and ICU utilization were noted amongst our patients with active invasive cancer, following a COVID-19 infection. Men and those of >70 years of age had a greater than four-fold increase in odds of death or transition to hospice.

Heparin-induced thrombocytopenia (HIT) is an immune-mediated adverse reaction to heparin products characterized by thrombocytopenia with or without thrombosis. This study aimed to determine the incidence, morbidity, mortality and economic burden of HIT in solid-malignancy-related hospitalizations. We analyzed the National Inpatient Sample Database (NIS), the largest public database of hospital admissions in the United States, from January 2012 to September 2015. The primary outcome of the study was the incidence of HIT. Secondary outcomes included incidence of venous thrombosis (acute deep venous thrombosis and pulmonary embolism), arterial thrombosis (thrombotic stroke, myocardial infarctions and other arterial thromboembolism), mortality associated with HIT, length of stay, total hospital charges and disposition. During the study period, 7 437 049 hospitalizations had an associated diagnosis of solid malignancy. Approximately 0·08% (n = 6225) hospitalizations had a secondary diagnosis of HIT in this population. The standardized incidence of total thrombotic events was higher in the solid malignancy with HIT compared to the solid malignancy without HIT group (24·7% vs. 6·8%, P < 0·001). The standardized mortality rate was 4·8% in solid malignancy with HIT compared to 3·4% in the without HIT group (OR, 1·53; 95% CI, 1·25-1·89; P < 0·001). HIT in solid malignancy is a rare condition but associated with increased morbidity and mortality., (© 2020 British Society for Haematology and John Wiley & Sons Ltd.)