Factors Associated with SARS-CoV-2 Infection and Outcome in Patients with Solid Tumors or Hematological Malignancies: A Single-Center Study

Context Immunocompromised cancer patients are presumed to be at high risk of developing COVID-19 infection. Objective Predisposing factors to contracting COVID-19 and to severe outcomes have been described in registries but were not compared between solid tumors and hematological malignancies. Design This retrospective study included patients from March 10 to May 18, 2020. Setting The study took place in a single oncologic tertiary center in Belgium. Patients or Other Participants 212 adult patients with solid tumors or hematological malignancies referred to testing by naso-pharyngeal swab for a SARS-CoV-2 RT-PCR were included in the study. Interventions We collected data on demographics, symptoms, comorbidities, performance status, type and stage of cancer, anti-cancer treatment, blood work, imaging and outcome. Main Outcomes Meausres The primary endpoint was the incidence of COVID-19 among patients with concordant symptoms, close contact with a confirmed case or concordant imaging among patients with solid tumors or hematological malignancies. Results Among the 212 patients included in the study, 45 (21%) tested positive with SARS-CoV-2. The univariate analysis with positive SARS-CoV-2 PCR as a dependent variable reveals significant Odds Ratios (ORs) for age with a mean of 62.5 years - (OR: 1.05, 95% CI: 1.02-1.08), performance status ≥2 (OR: 2.38, 95% CI: 1.22-4.70), inpatient status (OR: 2.36, 95% CI: 1.11-4.91) and hematological malignancies (OR: 2.48, 95% CI: 1.23-4.96). In contrast, OR for solid tumors reveals a negative association (OR: 0.40, 95% CI: 0.20-0.81). When integrating severe outcome (ICU admission or COVID-19 related death) as a dependent variable, the univariate logistic regression model shows significant ORs for pre-existing lymphopenia (OR: 4.0, 95% CI: 1.17-15.04), hematological malignancies (OR: 3.73, 95% CI: 1.09-13.80), and a negative association for solid tumors (OR: 0.27;95% CI: 0.07-0.92). Conclusions In patients referred for SARS-CoV-2 testing, hematological malignancies were associated with a higher risk of COVID-19 infection and severe outcomes. Other factors were age, active chemotherapy treatment and inpatient status.

Factors associated with SARS-CoV-2 infection and outcome in patients with solid tumors or hematological malignancies: a single-center study.

BACKGROUND: Immunocompromised cancer patients are presumed to be at high risk of developing COVID-19 infection. Predisposing factors to contracting COVID-19 and to severe outcomes have been described in registries but were not compared between solid tumors and hematological malignancies. METHOD: This retrospective single oncologic center study included adults with solid tumors or hematological malignancies referred to testing by naso-pharyngeal swab for a SARS-CoV-2 RT-PCR from March 10 to May 18, 2020. RESULTS: A total of 212 patients were included in the study. Forty-five (21%) were tested positive with SARS-CoV-2. The univariate analysis with positive SARS-CoV-2 PCR as a dependent variable reveals significant odds ratios (ORs) for age-with a mean of 62.5 years-(OR: 1.05, 95% CI: 1.02-1.08), performance status ≥2 (OR: 2.38, 95% CI: 1.22-4.70), inpatient status (OR: 2.36, 95%CI: 1.11-4.91), and hematological malignancies (OR: 2.48, 95% CI: 1.23-4.96). In contrast, OR for solid tumors reveals a negative association (OR: 0.40, 95% CI: 0.20-0.81). When integrating severe outcome (ICU admission or COVID-19-related death) as a dependent variable, the univariate logistic regression model shows significant ORs for pre-existing lymphopenia (OR: 4.0, 95% CI: 1.17-15.04), hematological malignancies (OR: 3.73, 95% CI: 1.09-13.80), and a negative association for solid tumors (OR: 0.27; 95% CI: 0.07-0.92). CONCLUSION: In patients referred for SARS-CoV-2 testing, hematological malignancies were associated with a higher risk of COVID-19 infection and severe outcomes. Other factors were age and inpatient status.

A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.

The COVID-19 pandemic has worldwide individual and socioeconomic consequences. Chest computed tomography has been found to support diagnostics and disease monitoring. A standardized approach to generate, collect, analyze, and share clinical and imaging information in the highest quality possible is urgently needed. We developed systematic, computer-assisted and context-guided electronic data capture on the FDA-approved mint LesionTM software platform to enable cloud-based data collection and real-time analysis. The acquisition and annotation include radiological findings and radiomics performed directly on primary imaging data together with information from the patient history and clinical data. As proof of concept, anonymized data of 283 patients with either suspected or confirmed SARS-CoV-2 infection from eight European medical centers were aggregated in data analysis dashboards. Aggregated data were compared to key findings of landmark research literature. This concept has been chosen for use in the national COVID-19 response of the radiological departments of all university hospitals in Germany.

Predictors of Mortality in Hospitalized COVID-19 Patients in Athens, Greece

Background: The epidemic of COVID-19 has rapidly spread worldwide, with millions of confirmed cases and related deaths. Numerous efforts are being made to clarify how the infection progresses and potential factors associated with disease severity and mortality. We investigated the mortality in Greek hospitalized COVID-19 patients and also the predictors of this mortality. Objective: Most importantly, it may assist in the implementation of efficient protective measures and public healthcare policies. Methodology: Study population included 512 COVID-19 patients admitted to the hospitals of the Attica region of Greece. Patients' demographic characteristics, comorbidities, allergies, previous vaccination for seasonal influenza virus, admission to ICU, intubation, and death were recorded. Potential predictors of in-hospital mortality were identified by regression analysis. Results: The mean age of hospitalized patients was 60.4 years, and was higher in patients who deceased. The most common comorbidities were respiratory diseases, hypertension, gastrointestinal disorders, dyslipidemia, mental health diseases, asthma, diabetes mellitus and cardiovascular diseases. The need for ICU care and intubation was significantly higher among patients who died. The mortality rate was 15.8% (81 out of 512). Age >65 years, cancer, chronic kidney disease, endocrine diseases, central nervous system disorders, anemia, and intubation were independently associated with increased in-hospital mortality, while allergies and previous influenza vaccination were associated with decreased in-hospital mortality. Conclusion: Our finding of a beneficial effect of allergies and influenza vaccination against COVID-19 infection merits further investigation, as it may shed light in the mechanisms underlying disease progression and severity.