ABSTRACT
Background: Comprehensive real-world evidence of the virulence of COVID-19 Omicron, Delta, and Alpha variants as well as the effectiveness of booster vaccinations in patients with cancer are lacking. We aimed to fill in these gaps for cancer patients and provide essential insights on the management of the fast-evolving pandemic by leveraging the nationally-representative electronic medical records from the National COVID Cohort Collaborative (N3C) registry. Methods: The virulence of COVID-19 variants was examined according to severe outcomes of infected patients with cancer, compared with non-cancer patients, using the N3C data between 12/01/2020 and 02/03/2022. Variants were inferred according to the time periods of variant dominance at > 95% accuracy. The Cox proportional hazards model was employed to evaluate the effects of COVID-19 variants, adjusting for age, gender, race/ethnicity, geographic regions, vaccination status, cancer types, smoking status, cancer treatments, and adjusted Charlson Comorbidity Index (CCI). Results: Our study cohort included 114,195 COVID-19 patients with cancer and 160,493 without cancer as control. Among them, 52,539 (21%) were infected by Omicron, 82,579 (33%) by Delta, and 115,200 (46%) by Alpha variants. Prior to the COVID-19 breakthrough infection, 7%, 22%, 3%, and 69% were vaccinated with 1 dose, 2 doses, a booster, or unvaccinated respectively. The proportions of hospitalization and death among patients with vs without cancer were 40% and 7% vs 18% and 0.4%, respectively. Characteristics of the cancer subcohort are summarized in the Table. Our analysis showed dramatically lower risks of severe outcomes for patients who were infected by Omicron (HR 0.42, 95%CI: 0.38 - 0.46) and slightly lower risks for Delta (HR 0.93, 95%CI: 0.89 - 0.98) compared with those infected by Alpha, after adjusting for other demographic clinical risk factors, and vaccination status. This trend remained similar in subgroups of patients with solid tumors, hematologic malignancies, or without cancer. Similar associations were observed when virulence was evaluated in association with mortality. The effectiveness of booster vaccinations varied across sub-cohorts stratified by variants and cancer types. Booster shots reduced the risk of severe outcomes for patients with solid tumors infected by Omicron variant or hematologic malignancies infected by Delta variants. Conclusions: Our work provides up-to-date and comprehensive real-world evidence of the virulence of COVID-19 variants in patients with cancer. Omicron variant showed significantly reduced virulence for different cancer types.
ABSTRACT
Background: Patient portals support patient access, engagement, and care coordination, yet could also widen the digital divide and exacerbate disparities among vulnerable populations. There is emerging evidence that racial/ethnic minority patients are less likely to use portals, yet prior research has not examined potential rural differences. We identified sociodemographic factors associated with portal enrollment and use among a racially and geographically diverse population of cancer patients. Methods: We retrospectively examined portal enrollment and use at an NCI-designated comprehensive cancer center from January 2015 until February 2022 among patients 18+ years old with a neoplastic disease diagnosis (ICD-10-CM C00-D49). Potential predictors included gender, race/ethnicity, marital status, age, rural (Rural-Urban Continuum Codes [RUCC] 4-9) vs nonrural (RUCC 1-3) residence, residential distance from the cancer center, and time since diagnosis. We used multivariable logistic regression to generate odds ratios (ORs) for portal enrollment and having ever sent a portal message, and Poisson regression to determine incidence rate ratios (IRRs) for number of logins and number of healthcare team interactions (portal messages or appointment requests), controlling for ICD-10 diagnosis (SAS 9.4). Results: We identified 11,333 patients (average age 67 years, 59% female, 24% rural, 10% Non-Hispanic Black, 1% Hispanic, 20% non-melanoma skin cancer, 14% breast cancer, 9% lung cancer). 36% of patients had enrolled in the portal, and of these, 80% had sent at least one message. Patients logged in a median of 203.5 times and had a median of 19 portal interactions. Rural residents were less likely to enroll in the portal than urban patients (28% vs 38%, p < 0.0001). Non-Hispanic Black patients and Hispanic/Latinx patients were less likely to enroll in the portal compared with non-Hispanic White patients (22% and 27%, respectively, vs 38.5%, p < 0.0001). Women, younger patients, more recently diagnosed cancer patients, and patients who were married/ partnered were significantly more likely to enroll. In multivariable analysis controlling for cancer type, rural patients were half as likely to enroll in the portal (OR: 0.48 [0.43-0.54]). Among those enrolled, rural residents were 25% less likely to have ever sent a portal message (OR: 0.75 [(0.62-0.92]), and had nearly half the login and interaction rates (IRR: 0.66 [0.66-0.67];IRR: 0.58 [0.58-0.59], respectively). Patients who were Non-Hispanic Black, Hispanic, or unmarried were also significantly less likely to enroll or engage in the portal. Conclusions: Patient portals remain underutilized among cancer patients, despite an increased reliance on virtual communications in the COVID era. Interventions to support portal engagement among rural residents and racial/ethnic minority patients are needed to avoid potentially exacerbating health disparities.
ABSTRACT
Background: Post-acute sequelae of SARS-CoV-2 or long COVID, is characterized by persistence of symptoms and/or emergence of new symptoms post COVID-19 infection. As evidence accumulates and national initiatives arise to address this increasingly prevalent syndrome, characterization of specific patient groups is still lacking including patients with cancer. Using a nationally representative sample of over 4.3M COVID-19 patients from the National COVID Cohort Collaborative (N3C), we aim to describe characteristics of patients with cancer and long COVID. Methods: We employed two approaches to identify long COVID patients within N3C: i) patients presenting to a long COVID clinic at four N3C sites and ii) patients diagnosed using the recently introduced ICD-10 code: U09.9 Post COVID- 19 condition, unspecified. We included patients with at least one positive COVID-19 diagnosis between 1/1/2020 and 2/3/2022. Patients had to survive at least 90 days from the date of their COVID- 19 diagnosis. Analyses were performed in the N3C Data Enclave on the Palantir platform. Results: A total of 1700 adult patients with long COVID were identified from the N3C cohort;634 (37.3%) were cancer patients and 1066 were non-cancer controls. The most common represented cancers were skin (21.9%), breast (17.7%), prostate (8.3%), lymphoma (8.0%) and leukemia (5.7%). Median age of long-COVID cancer patients was 64 years (Interquartile Range: 54-72), 48.6% were 65 years or older, 60.4% females, 76.8% non-Hispanic White, 12.3% were Black, and 3% Hispanic. A total of 41.1% were current or former smokers, 27.7% had an adjusted Charlson Comorbidity Index score of 0, 18.6% score of 1 and 11.2% score of 2. A total of 57.2% were hospitalized for their initial COVID-19 infection, the average length of stay in the hospital was 9.6 days (SD: 16.7 days), 9.1% required invasive ventilation, and 13% had acute kidney injury during hospitalization. The most common diagnosis among the non-cancer long COVID patients was asthma (26%), diabetes (17%), chronic kidney disease (12%), heart failure (9.4%), and chronic obstructive pulmonary disease (7.8%). Among long COVID patients, compared to non-cancer controls, cancer patients were more likely to be older (OR = 2.4, 95%CI: 1.1-5.4, p = 0.03), have comorbidities (OR = 4.3, 95%CI: 2.9-6.2, p < 0.0001), and to be hospitalized for COVID-19 (OR = 1.3, 95%CI: 1.0-1.7, p = 0.05), adjusting for sex, race/ethnicity, body mass index and smoking history. Conclusions: In a nationally representative sample of long COVID patients, there was a relative overrepresentation of patients with cancer. Compared to non-cancer controls, cancer patients were older, more likely to have more comorbidities and to be hospitalized for COVID-19 warranting further investigation to identify risk factors for long COVID in patients with cancer.
ABSTRACT
Background: Patients with multiple myeloma (MM), an age-dependent neoplasm of antibody-producing plasma cells, have compromised immune systems due to multiple factors that may increase the risk of severe COVID-19. The NCATS' National COVID Cohort Collaborative (N3C) is a centralized data resource representing the largest multi-center cohort of ∼12M COVID-19 cases and controls nationwide. In this study, we aim to analyze risk factors associated with COVID-19 severity and death in MM patients using the N3C database. Methods: Our cohort included MM patients within the N3C registry diagnosed with COVID-19 based on positive PCR or antigen tests or ICD-10-CM. The outcomes of interest include all-cause mortality (including discharge to hospice) during the index encounter, and clinical indicators of severity (hospitalization/ED visit, use of mechanical ventilation, or extracorporeal membrane oxygenation/ECMO). Results: As of 09/10/2021, the N3C registry included 690371 cancer patients, out of which 17791 were MM patients (4707 were COVID-19+). The mean age at diagnosis was 65.9yrs, 57.6% were >65yo, 46.4% were females, and 21.8% were Blacks. 25.6% had a Charlson Comorbidity Index (CCI) score of ≥2. 55.6% required an inpatient or ED visit, and 3.65% required invasive ventilation. 11.4% developed acute kidney injury during hospitalization. Multivariate logistic regression analysis showed histories of pulmonary disease (OR 2.2;95%CI: 1.7-2.8), renal disease (OR 1.8;95%CI: 1.4-2.4), and black race (p<0.001) were associated with higher risk of severity. Interestingly, smoking status was significantly associated with a lower risk of severity (OR 0.7;95%CI: 0.5-0.9). Further, protective association was also observed between COVID-19 severity and blood or marrow transplant (BMT) (OR 0.52;95%CI: 0.4-0.7), daratumumab therapy (OR 0.64;95%CI: 0.42- 0.99) and COVID-19 vaccination (OR 0.28;95%CI: 0.18-0.44). IMiDs were associated increase in the risk of COVID-19 severity (OR 2.1;95%CI: 1.6-2.7). 2.3% of N3C-myeloma COVID-19+ patients died within the first 10 days, while 4.95% died within 30 days of COVID-19 hospitalization. Overall, the survival probability was 90.5% across the course of the study. Multivariate cox proportional hazard model showed that CCI score ≥2 (HR 4.4;95%CI: 2.2-8.8), hypertension (HR 1.6;95%CI: 1.02- 2.4), IMiD (HR 2.6;95%CI: 1.8-3.8) and proteasome inhibitor (HR 1.6;95%CI: 1.1-2.5) therapy were associated with worse survival. COVID-19 vaccination (HR 0.195;95%CI: 0.09-0.45) and BMT (HR 0.65;95%CI: 0.4-0.995) were associated with lower risk of death. Conclusions: We have identified previously unpublished potential risk factors for COVID-19 severity and death in MM as well as validated some published ones. To the best of our knowledge, this is the largest nationwide study on multiple myeloma patients with COVID-19.
ABSTRACT
Research on pharmacological therapies for the treatment and prevention of Coronavirus Disease 2019 (COVID-19) is limited in patients with Type 2 Diabetes Mellitus (T2DM). In this case, diabetes management of a 51-year-old male patient who was followed up and treated with COVID-19 diagnosis in the pandemic clinic is presented. While metformin (2000 mg/day) oral therapy was continued, insulin glargine U100 (IGlar100) was added to the treatment subcutaneously. In addition, enoxaparin, hydroxychloroquine, azithromycin were started to be administered to the patient. During follow-up, respiratory distress and tachypnea (26 breaths/min), high fever (38.3oC), increased CRP (42 mg/dL), and decreased oxygen saturation (91%) were detected. Favipiravir was added to the treatment, and metformin was stopped due to possible lactic acidosis risk. IGlar300 treatment with more potency effect and lower risk of hypoglycaemia was initiated while IGlar100 was discontinued. In the follow-ups, titration was provided with IGlar300 to keep fasting blood glucose between 100-140 mg/dL and postprandial one between 140-180 mg/dL. In the treatment for this purpose, a maximum of 34 units/day insulin was needed. Capillary blood sugar monitoring was revised every 12 hours and then once a day. As the infection was brought under control, the required dose of IGlar300 decreased to 14 units/day. After diabetes training with a video phonecall, he was discharged with metformin and IGlar300. IGlar300 may be effective against diabetes in the COVID-19 pandemic. In addition, a significant contribution can be made both to the treatment safety of the patient in a glycemic sense and to the safety of contamination by reduced contact of health care professionals.
ABSTRACT
Background: The impact of COVID-19 has disproportionately affected every aspect of cancer care and research-from introducing new risks for patients to disrupting the delivery of treatment and continuity of research. Variation in risk of adverse clinical outcomes in COVID-19 patients by cancer type has been reported from relatively small cohorts. Gaps in understanding effects of COVID-19 on cancer patients can be addressed through the study of a well-constructed representative cohort. The NCATS' National COVID Cohort Collaborative (N3C) is a centralized data resource representing the largest multi-center cohort of COVID-19 cases and controls nationwide. We aimed to construct and characterize the cohort of cancer patients within N3C and identify risk factors for all-cause mortality from COVID-19. Methods: From the harmonized N3C clinical dataset, we used 3,295,963 patients from 39 medical US centers to construct a cancer patient cohort. We restricted analyses to adults ≥18 yo with a COVID-19 positive PCR or antigen test or ICD-10-CM diagnostic code for COVID-19 between 1/1/2020 and 2/14/2021. We followed N3C definitions where each lab-confirmed positive patient has one single index encounter. A modified WHO Clinical Progression Scale was used to determine clinical severity. All analyses were performed in the N3C Data Enclave on the Palantir platform. Results: A total of 372,883 adult patients with cancer were identified from the N3C cohort;54,642 (14.7%) were COVID-19 positive. Most common represented cancers were skin (11.5%), breast (10.2%), prostate (8%), and lung cancer (5.6%). Mean age of COVID-19 positive patients was 61.6 years (SD 16.7), 47.3% over 65yo, 53.7% females, 67.2% non-Hispanic White, 21.0% Black, and 7.7% Hispanic or Latino. A total of 14.6% were current or former smokers, 22.3% had a Charlson Comorbidity Index (CCI) score of 0, 4.6% score of 1 and 28.1% score of 2. Among hospitalized COVID-19 positive patients, average length of stay in the hospital was 6 days (SD 23.1 days), 7.0% patients had died while in their initial COVID-19 hospitalization, 4.5% required invasive ventilation, and 0.1% extracorporeal membrane oxygenation. Survival probability was 86.4% at 10 days and 63.6% at 30 days. Older age over 65yo (Hazard ratio (HR) = 6.1, 95%CI: 4.3, 8.7), male gender (HR = 1.2, 95%CI: 1.1, 1.2), a CCI score of 2 or more (HR = 1.15, 95%CI: 1.1, 1.2), and acute kidney injury during hospitalization (HR = 1.3, 95%CI: 1.2, 1.4) were associated with increased risk of all-cause mortality. Conclusions: Using the N3C cohort we assembled the largest nationally representative cohort on patients with cancer and COVID-19 to date. We identified demographic and clinical factors associated with increased all-cause mortality in cancer patients. Full characterization of the cohort will provide further insights on the effects of COVID-19 on cancer outcomes and the ability to continue specific cancer treatments.