Concomitant infections in patients with cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) study

Background: COVID-19 has been associated with immune modulation that may predispose infected patients to bacterial, viral, or fungal coinfections. Due to critical illness, > 70% of patients with severe COVID-19 receive empiric antibacterial or antifungal therapy, along with standard anti-COVID-19 treatments. However, the frequency of proven or probable secondary infections is < 10%. To our knowledge, there are no studies evaluating co-infections in patients with cancer and COVID-19, a vulnerable group with multiple risk factors for co-infections. We aim to describe the prevalence of bacterial, viral, and fungal co-infections, identify risk factors for coinfection, and investigate the potential impact of co-infections on mortality, in patients with a history of cancer and COVID-19. Methods: The CCC19 registry (NCT04354701) includes patients with active or prior hematologic or invasive solid malignancies reported across academic and community sites. We captured bacterial, fungal, or viral coinfections diagnosed within ±2 weeks from diagnosis of COVID-19, identified factors associated with an increased risk of having a coinfection, and evaluated the association of coinfections with 30-day all-cause mortality. Results: We examined 6732 patients with a history of cancer and a laboratory-confirmed diagnosis of SARS-CoV-2 reported to CCC19 by 82 sites between March 17, 2020 and February 3, 2021, with complete data on coinfection status. Median age was 65 (interquartile range: 55-75) years with 48% male, 52% non-Hispanic white, 19% non-Hispanic black, and 16% Hispanic. 5448 (81%) had solid tumors and 1466 (22%) had hematologic malignancies. Bacterial infections were reported in 823 patients (12%), including 296 Gram+ and 245 Gram- bacterial events. Documented viral (176 patients, 3%) and fungal (59 patients, 0.9%) co-infections were rare. The risk for co-infections increased with age, and they were more frequent among men, older patients, and those with diabetes, pulmonary or renal comorbid conditions, active progressive cancer, or hematologic malignancies (unadjusted P< 0.01). The frequency of reported co-infections decreased over the study period (divided into quartiles, Mantel-Haenszel P< 0.01). All-cause mortality rates were higher among those with bacterial (24% vs. 10%), viral (22% vs. 12%), and fungal (37% vs. 12%) coinfections compared to those without (unadjusted P< 0.01). Conclusions: The frequency of bacterial infections in patients with cancer and COVID-19 is relatively low. Viral and fungal co-infections are uncommon. Coinfections are associated with higher mortality rates. Several patient and tumor factors can be used for risk stratification and guide early empiric antimicrobial agent selection, which may improve clinical outcomes. These data could inform antimicrobial stewardship interventions in this tenuous patient population.

Racial and ethnic disparities among patients with breast cancer and COVID-19

Background: Racial/ethnic minorities have disproportionately increased risk of contracting COVID-19 and experiencing severe illness;they also have worse breast cancer (BC) outcomes. COVID-19 outcomes among racial/ethnic minorities with BC are currently unknown. We sought to compare clinicopathologic characteristics and COVID-19 outcomes stratified by race/ethnicity. Methods: The COVID-19 and Cancer Consortium registry (NCT04354701) was used to identify patients with invasive BC and laboratory-confirmed SARS-CoV-2 diagnosed in the U.S. between 2020-03-06 and 2021-02-04. The primary analysis was restricted to women who selfidentified as non-Hispanic White (NHW), nonHispanic Black (NHB), or Hispanic (H). Demographic, cancer characteristics, and COVID-19 outcomes were evaluated. COVID-19 outcomes included: hospital admission, intensive care unit (ICU) admission, mechanical ventilation, death within 30 days of COVID-19 diagnosis and death from any cause during follow-up. Descriptive statistics were used to compare clinicopathologic characteristics and Fisher exact tests were used to compare COVID19 outcomes across the 3 racial/ethnic groups. Results: A total of 1133 patients were identified of which 1111 (98%) were women;of which 575 (52%) NHW, 243 (22%) NHB, 183 (16%) H, and 110 (10%) other/unknown. Baseline characteristics differed among racial/ethnic groups. H were younger (median age: NHW 63y;NHB 62y;H 54y) and more likely to be never smokers (NHW 62%;NHB 62%;H 78%). NHB had higher rates of obesity (NHW 40%;NHB 54%;H 46%), diabetes (NHW 16 %;NHB 32%;H 20%) and combined moderate and severe baseline COVID-19 at presentation (NHW 28%;NHB 42%;H 28%). Cancer characteristics are as shown (Table). Significant differences were observed in outcomes across racial/ethnic groups including higher rates of hospital admission (NHW 34%;NHB 49%;H 34%;P <0.001), mechanical ventilation (NHW 3%;NHB 9%;H 5%;P=0.002), 30-day mortality (NHW 6%;NHB 9%;H 4%;P=0.043) and total mortality (NHW 8%;NHB 12%;H 5%;P=0.05) among NHB compared to NHW and H. Conclusions: This is the largest study to show significant differences in COVID-19 outcomes by racial/ethnic groups of women with BC. The adverse outcomes in NHB could be due to higher moderate to severe COVID-19 at presentation and preexisting comorbidities. H did not have worse outcomes despite having more active disease and recent anti-cancer therapy, including with cytotoxic chemotherapy - potentially due to younger age and nonsmoking status. (Table Presented).

Cost-effectiveness of filgrastimsndz as primary prophylaxis (PP) versus secondary prophylaxis (SP) to prevent chemotherapyinduced febrile neutropenia (FN) in breast cancer patients at intermediate risk

Background: According to clinical practice guidelines, the threshold for routine myeloid growth factor (MGF) PP is a high risk (>20%) of developing FN. However, in response to the COVID-19 pandemic, a recent recommendation expands this threshold for using MGF PP to include patients at intermediate risk (10-20%) of developing FN, with the goal of reducing emergency room and hospital visits. Patients with breast cancer receiving potentially curative chemotherapy consisting of docetaxel or paclitaxel (every 21 days) are at an intermediate risk (10-20%) of developing FN. This study evaluates the cost-effectiveness of PP vs. SP using a biosimilar MGF, filgrastim-sndz, in earlystage breast cancer patients at intermediate risk of FN. Methods: A Markov model with a lifetime horizon was constructed to evaluate the total costs and clinical outcomes when using filgrastim-sndz as PP vs. SP in 56 year old early-stage breast cancer patients receiving adjuvant docetaxel (following doxorubicin/cyclophosphamide) every 3 weeks for 4 cycles. Patients had ≥1 FN risk factor (i.e., recent surgery) without the receipt of anti-HER2 therapy, representing a 16% baseline FN risk. Average Sales Price (ASP) calculated from the Centers for Medicare & Medicaid Services July 2020 ASP Drug Pricing File was used as the filgrastim-sndz cost. Incremental cost-effectiveness ratios (ICERs) were calculated for cost per FN event avoided, life-year saved (LYS), and quality-adjusted life-year (QALY) gained from a United States payer perspective. Deterministic and probabilistic sensitivity analyses (PSA) were conducted. Results: Filgrastim-sndz as PP vs. SP provided an additional 0.102 FN events avoided, 0.065 LYS, and 0.056 QALYs at an incremental cost of $2,106. The ICERs were $20,656, $32,624 and $37,333 for cost per FN event avoided, cost per LYS, and cost per QALY gained, respectively. In the PSA, the likelihood of cost-effectiveness at a willingnessto-pay (WTP) threshold of $50,000 per QALY gained was 71.3%. Conclusions: For early-stage breast cancer patients at intermediate risk of FN receiving adjuvant docetaxel with 1 or more risk factors, PP with filgrastim-sndz compared to SP is cost-effective based on a WTP threshold of $50,000/QALY.

Supportive care in patients with cancer during the COVID-19 pandemic.

Cancer care has been profoundly impacted by the global pandemic of severe acute respiratory syndrome coronavirus 2 disease (coronavirus disease 2019, COVID-19), resulting in unprecedented challenges. Supportive care is an essential component of cancer treatment, seeking to prevent and manage chemotherapy complications such as febrile neutropenia, anaemia, thrombocytopenia/bleeding, thromboembolic events and nausea/vomiting, all of which are common causes of hospitalisation. These adverse events are an essential consideration under routine patient management, but particularly so during a pandemic, a setting in which clinicians aim to minimise patients' risk of infection and need for hospital visits. Professional medical oncology societies have been providing updated guidelines to support health care professionals with the management, treatment and supportive care needs of their patients with cancer under the threat of COVID-19. This paper aims to review the recommendations made by the most prominent medical oncology societies for devising and modifying supportive care strategies during the pandemic.

Clinical impact of COVID-19 on patients with cancer: Data from the COVID-19 and Cancer Consortium (CCC19)

Background: There are limited data on COVID-19 in patients with cancer. We characterize the outcomes of patients with cancer and COVID-19 and identify potential prognostic factors. Methods: The COVID- 19 and Cancer Consortium (CCC19) cohort study includes patients with active or prior hematologic or invasive solid malignancies reported across academic and community sites. Results: We included 1,018 cases accrued March-April 2020. Median age was 66 years (range, 18-90). Breast (20%) and prostate (16%) cancers were most prevalent;43% of patients were on active anti-cancer treatment. At time of data analysis, 106 patients (10.4%) have died and 26% met the composite outcome of death, severe illness requiring hospitalization, and/or mechanical ventilation. In multivariable logistic regression analysis, independent factors associated with increased 30- day mortality were age, male sex, former smoking, ECOG performance status (2 versus 0/1: partially adjusted odds ratio (pAOR) 2.74, 95% CI 1.31-5.7;3/4 versus 0/1: pAOR 5.34, 95% CI 2.44-11.69), active malignancy (stable/responding, pAOR 1.93, 95% CI 1.06-3.5;progressing, pAOR 3.79, 95% CI 1.78-8.08), and receipt of azithromycin and hydroxychloroquine. Tumor type, race/ethnicity, obesity, number of comorbidities, recent surgery, and type of active cancer therapy were not significant factors for mortality. Conclusions: All-cause 30-day mortality and severe illness in this cohort were significantly higher than previously reported for the general population and were associated with general risk factors as well as those unique to patients with cancer. Cancer type and treatment were not independently associated with increased 30-day mortality. Longer follow-up is needed to better understand the impact of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments.