Defining the true impact of coronavirus disease 2019 in the at-risk population of patients with cancer

Does COVID-19 pandemic impact cancer outcomes in metastatic setting? A comparative cohort study among metastatic patients treated at day care hospital

INTRODUCTION

COVID-19 outbreak rapidly spread since early 2020 leading to the implementation of nationwide lockdowns. To cope with this sudden change, management guidelines were quickly published to adapt oncological care, with potential impact on cancer outcomes.

METHODS

We conducted a retrospective comparative cohort study to assess the impact of the COVID-19 outbreak in 2020 on cancer outcomes in metastatic patients. Two cohorts of metastatic patients receiving intravenous (iv) therapy in a French oncological day care hospital were assessed: a 2020 cohort during the first French lockdown, and a 2018 historical cohort before the COVID-19 pandemic. We performed a propensity score analysis to match patients from the two cohorts. After one-year follow-up, we compared progression-free survival (PFS) and overall survival (OS) between cohorts. Adaptations of medical oncological treatments in 2020 were also analysed.

RESULTS

The 376 patients of the 2020 cohort were matched with 376 of the 2018 cohort. No SARS-CoV-2 infection was observed in the 2020 cohort. The adjusted PFS was significantly shorter in 2020 compared to 2018 (HR = 1.23; 95% CI: 1.03-1.46), as well as among patients without treatment adaptation compared to matched patients of the 2018 cohort (HR = 1.33; 95% CI: 1.10-1.61). We did not observe any significant difference of PFS among the group with treatment adaptations. OS was not significantly different.

CONCLUSION

Metastatic cancer patients treated during the first lockdown had a higher risk of disease progression 1 year after COVID-19 outbreak. However, oncological treatment adaptations or SARS-CoV-2 infections do not explain these results. A longer follow-up is needed to observe the impact on OS.

SARS-CoV-2 Neutralizing Antibodies Kinetics Postvaccination in Cancer Patients under Treatment with Immune Checkpoint Inhibition

Simple Summary

Solid tumor patients under active anticancer treatment are peculiarly affected by COVID-19 infection, given not only its ominous outcomes but also the need of disruptions of their rather strict therapeutic scheme. Thus, they have been globally prioritized for both primary and booster vaccinations. The existing data with respect to the seroconversion rate of neutralizing antibodies (NAbs) among them, after vaccination, remain nevertheless obscure. Therefore, we prospectively evaluated the long-term humoral immunity dynamics for up to one month after the third dose in patients with solid malignancies receiving immunotherapy. Further research is required to assess the incremental benefit of booster doses and to optimize the vaccination schedule across different types of cancer and diverse systemic therapies.

Abstract

Considering that COVID-19 could adversely affect cancer patients, several countries have prioritized this highly susceptible population for vaccination. Thus, rapidly generating evidence on the efficacy of SARS-CoV-2 vaccination in the subset of patients with cancer under active therapy is of paramount importance. From this perspective, we launched the present prospective observational study to comprehensively address the longitudinal dynamics of immunogenicity of both messenger RNA (mRNA) and viral vector-based vaccines in 85 patients treated with immune checkpoint inhibitors (ICIs) for a broad range of solid tumors. Despite the relatively poor humoral responses following the priming vaccine inoculum, the seroconversion rates significantly increased after the second dose. Waning vaccine-based immunity was observed over the following six months, yet the administration of a third booster dose remarkably optimized antibody responses. Larger cohort studies providing real-world data with regard to vaccines effectiveness and durability of their protection among cancer patients receiving immunotherapy are an increasing priority.

Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis synthesized the evidence on the impacts of demographics and comorbidities on the clinical outcomes of COVID-19, as well as the sources of the heterogeneity and publication bias of the relevant studies. Two authors independently searched the literature from PubMed, Embase, Cochrane library, and CINAHL on 18 May 2021; removed duplicates; screened the titles, abstracts, and full texts by using criteria; and extracted data from the eligible articles. The variations among the studies were examined by using Cochrane, Q.; I2, and meta-regression. Out of 11,975 articles that were obtained from the databases and screened, 559 studies were abstracted, and then, where appropriate, were analyzed by meta-analysis (n = 542). COVID-19-related severe illness, admission to the ICU, and death were significantly correlated with comorbidities, male sex, and an age older than 60 or 65 years, although high heterogeneity was present in the pooled estimates. The study design, the study country, the sample size, and the year of publication contributed to this. There was publication bias among the studies that compared the odds of COVID-19-related deaths, severe illness, and admission to the ICU on the basis of the comorbidity status. While an older age and chronic diseases were shown to increase the risk of developing severe illness, admission to the ICU, and death among the COVID-19 patients in our analysis, a marked heterogeneity was present when linking the specific risks with the outcomes.

Differences in Outcomes and Factors Associated With Mortality Among Patients With SARS-CoV-2 Infection and Cancer Compared With Those Without Cancer: A Systematic Review and Meta-analysis

Importance

SARS-CoV-2 infection has been associated with more severe disease and death in patients with cancer. However, the implications of certain tumor types, treatments, and the age and sex of patients with cancer for the outcomes of COVID-19 remain unclear.

Objective

To assess the differences in clinical outcomes between patients with cancer and SARS-CoV-2 infection and patients without cancer but with SARS-CoV-2 infection, and to identify patients with cancer at particularly high risk for a poor outcome.

Data Sources

PubMed, Web of Science, and Scopus databases were searched for articles published in English until June 14, 2021. References in these articles were reviewed for additional studies.

Study Selection

All case-control or cohort studies were included that involved 10 or more patients with malignant disease and SARS-CoV-2 infection with or without a control group (defined as patients without cancer but with SARS-CoV-2 infection). Studies were excluded if they involved fewer than 10 patients, were conference papers or abstracts, were preprint reports, had no full text, or had data that could not be obtained from the corresponding author.

Data Extraction and Synthesis

Two investigators independently performed data extraction using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Meta-analysis was performed using a random-effects model.

Main Outcomes and Measures

The difference in mortality between patients with cancer and SARS-CoV-2 infection and control patients as well as the difference in outcomes for various tumor types and cancer treatments. Pooled case fatality rates, a random-effects model, and random-effects meta-regressions were used.

Results

A total of 81 studies were included, involving 61 532 patients with cancer. Among 58 849 patients with available data, 30 557 male individuals (52%) were included and median age ranged from 35 to 74 years. The relative risk (RR) of mortality from COVID-19 among patients with vs without cancer when age and sex were matched was 1.69 (95% CI, 1.46-1.95; P < .001; I2 = 51.0%). The RR of mortality in patients with cancer vs control patients was associated with decreasing age (exp [b], 0.96; 95% CI, 0.92-0.99; P = .03). Compared with other cancers, lung cancer (RR, 1.68; 95% CI, 1.45-1.94; P < .001; I2 = 32.9%), and hematologic cancer (RR, 1.42; 95% CI, 1.31-1.54; P < .001; I2 = 6.8%) were associated with a higher risk of death. Although a higher point estimate was found for genitourinary cancer (RR, 1.11; 95% CI, 1.00-1.24; P = .06; I2 = 21.5%), the finding was not statistically significant. Breast cancer (RR, 0.51; 95% CI, 0.36-0.71; P < .001; I2 = 86.2%) and gynecological cancer (RR, 0.76; 95% CI, 0.62-0.93; P = .009; I2 = 0%) were associated with a lower risk of death. Chemotherapy was associated with the highest overall pooled case fatality rate of 30% (95% CI, 25%-36%; I2 = 86.97%; range, 10%-100%), and endocrine therapy was associated with the lowest at 11% (95% CI, 6%-16%; I2 = 70.68%; range, 0%-27%).

Conclusions and Relevance

Results of this study suggest that patients with cancer and SARS-CoV-2 infection had a higher risk of death than patients without cancer. Younger age, lung cancer, and hematologic cancer were also risk factors associated with poor outcomes from COVID-19.

Comprehensive adjusted outcome data are needed to assess the impact of immune checkpoint inhibitors in cancer patients with COVID-19: Results of a systematic review and meta-analysis

Background

Determining how prior immune checkpoint inhibitor (ICI) therapy influences outcomes in cancer patients presenting with COVID‐19 is essential for patient management but must account for confounding variables.

Methods

We performed a systematic review and meta‐analysis of studies reporting adjusted effects of ICIs on survival, severe events, or hospitalisation in cancer patients with COVID‐19 based on variables including age, gender, diabetes mellitus, hypertension (HTN), chronic obstructive pulmonary disease, and other comorbidities. When adjusted effects were unavailable, unadjusted data were analysed.

Results

Of 42 observational studies (38 retrospective), 7 reported adjusted outcomes for ICIs and 2 provided sufficient individual patient data to calculate adjusted outcomes. In eight studies, adjusted outcomes were based on ≤7 variables. Over all studies, only one included >100 ICI patients while 26 included <10. ICIs did not alter the odds ratio (95%CI) (OR) of death significantly (random effects model), across adjusted (n = 8) [1.31 (0.58–2.95) p = 0.46; I² = 42%, p = 0.10], unadjusted (n = 30) [1.06 (0.85–1.32) p = 0.58; I² = 0%, p = 0.76] or combined [1.09 (0.88;1.36) p = 0.41; I² = 0%, p = 0.5)] studies. Similarly, ICIs did not alter severe events significantly across adjusted (n = 5) [1.20 (0.30–4.74) p = 0.73; I² = 52%, p = 0.08], unadjusted (n = 19) [(1.23 (0.87–1.75) p = 0.23; I² = 16%, p = 0.26] or combined [1.26 (0.90–1.77) p = 0.16; I² = 25%, p = 0.14] studies. Two studies provided adjusted hospitalisation data and when combined with 13 unadjusted studies, ICIs did not alter hospitalisation significantly [1.19 (0.85–1.68) p = 029; I² = 5%, p = 0.40]. Results of sensitivity analyses examining ICI effects based on 5 variables were inconclusive. Certainty of evidence was very low.

Conclusions

Across studies with adjusted and unadjusted results, ICIs did not alter outcomes significantly. But studies with comprehensive adjusted outcome data controlling for confounding variables are necessary to determine whether ICIs impact COVID‐19 outcomes in cancer patients.

Should routine risk reduction procedures for the prevention and control of pandemics become a standard in all oncological outpatient clinics? The prospective COVID-19 cohort study: protect-CoV

Limited knowledge exists on the effectiveness of preventive preparedness plans for the care of outpatient cancer patients during epidemics or pandemics. To ensure adequate, timely and continuous clinical care for this highly vulnerable population, we propose the establishment of preventive standard safety protocols providing effective early phase identification of outbreaks at outpatient cancer facilities and communicating adapted standards of care. The prospective cohort study Protect-CoV conducted at the LMU Klinikum from mid-March to June 2020 investigated the effectiveness of a rapid, proactive and methodical response to protect patients and interrupt SARS-CoV-2 transmission chains during the first pandemic wave. The implemented measures reduced the risk of infection of individual cancer patients and ensured safe adjunctive infusion therapy in an outpatient setting during the early COVID-19 pandemic. In addition to the immediate implementation of standard hygiene procedures, our results underscore the importance of routine PCR testing for the identification of asymptomatic or pre-symptomatic COVID-19 cases and immediate tracing of positive cases and their contacts. While more prospective controlled studies are needed to confirm these results, our study illustrates the importance of including preventative testing and tracing measures in the standard risk reduction procedures at all out patient cancer centers.

Cancer and the risk of coronavirus disease 2019 diagnosis, hospitalisation and death: A population-based multistate cohort study including 4 618 377 adults in Catalonia, Spain

The relationship between cancer and coronavirus disease 2019 (COVID-19) infection and severity remains poorly understood. We conducted a population-based cohort study between 1 March and 6 May 2020 describing the associations between cancer and risk of COVID-19 diagnosis, hospitalisation and COVID-19-related death. Data were obtained from the Information System for Research in Primary Care (SIDIAP) database, including primary care electronic health records from ~80% of the population in Catalonia, Spain. Cancer was defined as any primary invasive malignancy excluding non-melanoma skin cancer. We estimated adjusted hazard ratios (aHRs) for the risk of COVID-19 (outpatient) clinical diagnosis, hospitalisation (with or without a prior COVID-19 diagnosis) and COVID-19-related death using Cox proportional hazard regressions. Models were estimated for the overall cancer population and by years since cancer diagnosis (<1 year, 1-5 years and ≥5 years), sex, age and cancer type; and adjusted for age, sex, smoking status, deprivation and comorbidities. We included 4 618 377 adults, of which 260 667 (5.6%) had a history of cancer. A total of 98 951 individuals (5.5% with cancer) were diagnosed, and 6355 (16.4% with cancer) were directly hospitalised with COVID-19. Of those diagnosed, 6851 were subsequently hospitalised (10.7% with cancer), and 3227 died without being hospitalised (18.5% with cancer). Among those hospitalised, 1963 (22.5% with cancer) died. Cancer was associated with an increased risk of COVID-19 diagnosis (aHR: 1.08; 95% confidence interval [1.05-1.11]), direct COVID-19 hospitalisation (1.33 [1.24-1.43]) and death following hospitalisation (1.12 [1.01-1.25]). These associations were stronger for patients recently diagnosed with cancer, aged <70 years, and with haematological cancers. These patients should be prioritised in COVID-19 vaccination campaigns and continued non-pharmaceutical interventions.

OUP accepted manuscript

Purpose

Provide real-world data regarding the risk for SARS-CoV-2 infection and mortality in breast cancer (BC) patients on active cancer treatment.

Methods

Clinical data were abstracted from the 3778 BC patients seen at a multisite cancer center in New York between February 1, 2020 and May 1, 2020, including patient demographics, tumor histology, cancer treatment, and SARS-CoV-2 testing results. Incidence of SARS-CoV-2 infection by treatment type (chemotherapy [CT] vs endocrine and/or HER2 directed therapy [E/H]) was compared by Inverse Probability of Treatment Weighting. In those diagnosed with SARS-CoV-2 infection, Mann–Whitney test was used to a assess risk factors for severe disease and mortality.

Results

Three thousand sixty-two patients met study inclusion criteria with 641 patients tested for SARS-COV-2 by RT-PCR or serology. Overall, 64 patients (2.1%) were diagnosed with SARS-CoV-2 infection by either serology, RT-PCR, or documented clinical diagnosis. Comparing matched patients who received chemotherapy (n = 379) with those who received non-cytotoxic therapies (n = 2343) the incidence of SARS-CoV-2 did not differ between treatment groups (weighted risk; 3.5% CT vs 2.7% E/H, P = .523). Twenty-seven patients (0.9%) expired over follow-up, with 10 deaths attributed to SARS-CoV-2 infection. Chemotherapy was not associated with increased risk for death following SARS-CoV-2 infection (weighted risk; 0.7% CT vs 0.1% E/H, P = .246). Advanced disease (stage IV), age, BMI, and Charlson’s Comorbidity Index score were associated with increased mortality following SARS-CoV-2 infection (P ≤ .05).

Conclusion

BC treatment, including chemotherapy, can be safely administered in the context of enhanced infectious precautions, and should not be withheld particularly when given for curative intent.

Functional antibody and T cell immunity following SARS-CoV-2 infection, including by variants of concern, in patients with cancer: the CAPTURE study

Patients with cancer have higher COVID-19 morbidity and mortality. Here we present the prospective CAPTURE study, integrating longitudinal immune profiling with clinical annotation. Of 357 patients with cancer, 118 were SARS-CoV-2 positive, 94 were symptomatic and 2 died of COVID-19. In this cohort, 83% patients had S1-reactive antibodies and 82% had neutralizing antibodies against wild type SARS-CoV-2, whereas neutralizing antibody titers against the Alpha, Beta and Delta variants were substantially reduced. S1-reactive antibody levels decreased in 13% of patients, whereas neutralizing antibody titers remained stable for up to 329 days. Patients also had detectable SARS-CoV-2-specific T cells and CD4+ responses correlating with S1-reactive antibody levels, although patients with hematological malignancies had impaired immune responses that were disease and treatment specific, but presented compensatory cellular responses, further supported by clinical recovery in all but one patient. Overall, these findings advance the understanding of the nature and duration of the immune response to SARS-CoV-2 in patients with cancer.

Early mortality following COVID-19 infection among cancer patients who received radiotherapy: A meta-analysis

Introduction:

Identifying the patients at higher risk for poor outcomes after radiotherapy (RT) during coronavirus disease 19 (COVID-19) era is an unmet clinical need.

Methods:

The Ovid MEDLINE, Ovid Embase, Clarivate Analytics Web of Science, PubMed and Wiley-Blackwell Cochrane Library databases were searched. Eligible studies were required to address the outcomes of cancer patients who underwent RT during the COVID-19 era. The primary outcome was early mortality, while secondary outcomes included length of hospital stay, hospital admission, intensive care unit (ICU) admission and use of mechanical ventilation. Pooled event rates were calculated, and meta-regression and ‘leave-one-out’ sensitivity analyses were performed.

Results:

Twelve eligible studies were included out of 928. The prevalence of early mortality after COVID-19 infection was 21·0%. The prevalence of hospital admission, ICU admission and mechanical ventilation was 78·1, 15·4 and 20·0%, respectively. Meta-regression showed that older age was significantly and positively associated with early mortality (β = 0·0765 ± 0·0349, p = 0·0284), while breast cancer was negatively associated with early mortality (β = −1·2754 ± 0·6373, p = 0·0454).

Conclusions:

Older age adversely impacts the early mortality rate in cancer patients during COVID-19 era. The risks of interruption/delay of cancer treatment should be weighed against the risk of increased morbidity and mortality from the infection. A global registry is needed to establish international oncologic guidelines during the COVID-19 era.

Predictors and microbiology of respiratory and bloodstream bacterial infection in patients with COVID-19: living rapid review update and meta-regression

Background

The prevalence of bacterial infection in patients with COVID-19 is low, however, empiric antibiotic use is high. Risk stratification may be needed to minimize unnecessary empiric antibiotic use.

Objective

To identify risk factors and microbiology associated with respiratory and bloodstream bacterial infection in patients with COVID-19.

Data sources

We searched MEDLINE, OVID Epub and EMBASE for published literature up to 5 February 2021.

Study eligibility criteria

Studies including at least 50 patients with COVID-19 in any healthcare setting.

Methods

We used a validated ten-item risk of bias tool for disease prevalence. The main outcome of interest was the proportion of COVID-19 patients with bloodstream and/or respiratory bacterial co-infection and secondary infection. We performed meta-regression to identify study population factors associated with bacterial infection including healthcare setting, age, comorbidities and COVID-19 medication.

Results

Out of 33 345 studies screened, 171 were included in the final analysis. Bacterial infection data were available from 171 262 patients. The prevalence of co-infection was 5.1% (95% CI 3.6–7.1%) and secondary infection was 13.1% (95% CI 9.8–17.2%). There was a higher odds of bacterial infection in studies with a higher proportion of patients in the intensive care unit (ICU) (adjusted OR 18.8, 95% CI 6.5–54.8). Female sex was associated with a lower odds of secondary infection (adjusted OR 0.73, 95% CI 0.55–0.97) but not co-infection (adjusted OR 1.05, 95% CI 0.80–1.37). The most common organisms isolated included Staphylococcus aureus, coagulase-negative staphylococci and Klebsiella species.

Conclusions

While the odds of respiratory and bloodstream bacterial infection are low in patients with COVID-19, meta-regression revealed potential risk factors for infection, including ICU setting and mechanical ventilation. The risk for secondary infection is substantially greater than the risk for co-infection in patients with COVID-19. Understanding predictors of co-infection and secondary infection may help to support improved antibiotic stewardship in patients with COVID-19.

Risk stratification by anamnesis increases SARS-CoV-2 test efficiency in cancer patients

Purpose

To evaluate the impact of testing asymptomatic cancer patients, we analyzed all tests for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) before and during radiotherapy at a tertiary cancer center throughout the second wave of the pandemic in Germany.

Methods

Results of all real-time polymerase chain reaction (RT-PCR) tests for SARS-CoV‑2 performed at our radio-oncology department between 13 October 2020 and 11 March 2021 were included. Clinical data and anamnestic information at the time of testing were documented and examined for (i) the presence of COVID-19-related symptoms and (ii) virus-related anamnesis (high-risk [prior positive test or contact to a positive tested person within the last 14 days] or low-risk [inconspicuous anamnesis within the last 14 days]).

Results

A total of 1056 SARS-CoV‑2 tests in 543 patients were analyzed. Of those, 1015 tests were performed in asymptomatic patients and 41 tests in patients with COVID-19-associated symptoms. Two of 940 (0.2%) tests in asymptomatic patients with low-risk anamnesis and three of 75 (4.0%) tests in asymptomatic patients with high-risk anamnesis showed a positive result. For symptomatic patients, SARS-CoV‑2 was detected in three of 36 (8.3%) low-risk and three of five (60.0%) high-risk tests.

Conclusion

To the best of our knowledge, this is the first study evaluating the correlation between individual risk factors and positivity rates of SARS-CoV‑2 tests in cancer patients. The data demonstrate that clinical and anamnestic assessment is a simple and effective measure to distinctly increase SARS-CoV‑2 test efficiency. This might enable cancer centers to adjust test strategies in asymptomatic patients, especially when test resources are scarce.

Supplementary Information

The online version of this article (10.1007/s00066-021-01853-7) contains supplementary material, which is available to authorized users.

Functional antibody and T-cell immunity following SARS-CoV-2 infection, including by variants of concern, in patients with cancer: the CAPTURE study

Patients with cancer have higher COVID-19 morbidity and mortality. Here we present the prospective CAPTURE study (NCT03226886) integrating longitudinal immune profiling with clinical annotation. Of 357 patients with cancer, 118 were SARS-CoV-2-positive, 94 were symptomatic and 2 patients died of COVID-19. In this cohort, 83% patients had S1-reactive antibodies, 82% had neutralizing antibodies against WT, whereas neutralizing antibody titers (NAbT) against the Alpha, Beta, and Delta variants were substantially reduced. Whereas S1-reactive antibody levels decreased in 13% of patients, NAbT remained stable up to 329 days. Patients also had detectable SARS-CoV-2-specific T cells and CD4+ responses correlating with S1-reactive antibody levels, although patients with hematological malignancies had impaired immune responses that were disease and treatment-specific, but presented compensatory cellular responses, further supported by clinical. Overall, these findings advance the understanding of the nature and duration of immune response to SARS-CoV-2 in patients with cancer.

Mortality in adult patients with solid or hematological malignancies and SARS-CoV-2 infection with a specific focus on lung and breast cancers: A systematic review and meta-analysis

BACKGROUND

A systematic review and meta-analysis was performed to estimate mortality in adult patients with solid or hematological malignancies and SARS-CoV-2 infection.

METHODS

A systematic search of PubMed, up to 31 January 2021, identified publications reporting the case-fatality rate (CFR) among adult patients with solid or hematological malignancies and SARS-CoV-2 infection. The CFR, defined as the rate of death in this population, was assessed with a random effect model; 95% confidence intervals (CI) were calculated.

RESULTS

Among 135 selected studies (N = 33,879 patients), the CFR was 25.4% (95% CI 22.9%-28.2%). At a sensitivity analysis including studies with at least 100 patients, the CFR was 21.9% (95% CI 19.1%-25.1%). Among COVID-19 patients with lung (N = 1,135) and breast (N = 1,296) cancers, CFR were 32.4% (95% CI 26.5%-39.6%) and 14.2% (95% CI 9.3%-21.8%), respectively.

CONCLUSIONS

Patients with solid or hematological malignancies and SARS-CoV-2 infection have a high probability of mortality, with comparatively higher and lower CFRs in patients with lung and breast cancers, respectively.

Descriptive and retrospective analysis of diffuse glioma patients with symptomatic SARS-CoV2 infection during the first wave of the pandemic

Background

Little is known about diffuse glioma patients infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2).

Methods

We performed a descriptive and retrospective analysis of 41 diffuse glioma patients with symptomatic SARS-CoV2 infection during the first wave of the COVID-19 pandemic.

Results

Confusion with or without fever was the most common neurological symptom (32%) supporting SARS-CoV2 testing in glioma patients with acute and unexplained confusion. Sixteen patients (39%) died after a median delay of 13 days. While multiple clinical, biological, and pathological features, COVID-19- or diffuse glioma-related, at hospital admission appeared to have a pejorative prognostic impact, none was significantly associated with death. Oncological treatments were interrupted at COVID-19 diagnosis and re-initiated with a median delay of 30 days after the end of COVID-19 symptoms.

Conclusions

Interestingly, our retrospective study describes for the first time the characteristics of a cohort of diffuse glioma patients with symptomatic COVID-19. Diffuse glioma patients with poorly symptomatic COVID-19 did not come to the attention of physicians and were not enrolled in the study skewing the denominator for prognostic analysis. Further studies are warranted to specify prognosis of overall population of diffuse glioma patients with COVID-19, including asymptomatic patients, and interactions of prognostic factors of both COVID-19 and diffuse gliomas.

Impact of anti-cancer therapy on disease severity and mortality in cancer patients with COVID-19: a systematic review and meta-analysis

Background: Cancer patients are more vulnerable to Coronavirus disease-2019 (COVID-19) and have a higher risk of adverse outcomes than the general population. Therefore, it is necessary to evaluate whether anti-cancer therapies such as surgery, chemotherapy, immunotherapy, and targeted therapy will increase the severity and mortality of cancer patients with COVID-19.Methods: Relevant articles were retrieved from PubMed, Embase, Web of Science, Cochrane Library and China National Knowledge Infrastructure (CNKI). The search time was from December 1, 2019 to January 23, 2021. Meta-analysis was conducted using Revman 5.3 statistical software.Results: A total of 26 studies were included in this meta-analysis, involving 5571 cancer patients infected with SARS-CoV-2. Meta-analysis showed that surgery, chemotherapy, immunotherapy and targeted therapy were not associated with disease severity or mortality (107/688, OR =1.30, 95% CI[0.79, 2.13], P =0.30; 1956/2674, OR =1.27, 95% CI [0.95, 1.69], P =0.10; 342/1455, OR =1.20, 95% CI [0.90, 1.61], P =0.21; 503/1378, OR =0.92, 95% CI [0.72, 1.19], P =0.54, respectively).Conclusion: In cancer patients with COVID-19, anti-cancer therapy had no adverse effect on disease severity or mortality. Further research is necessary to determine the complex interrelationship between anti-cancer therapy, particularly chemotherapy, and COVID-19.

Patient Satisfaction with Oncological Care during the SARS-CoV-2 Virus Pandemic

Recently, the outbreak of the SARS-CoV-2 virus and the COVID-19 pandemic significantly affected the health situation of the entire society and necessitated reorganization of health care including oncology. The objective of this study was to examine the perception of medical services by cancer patients during the pandemic and to identify the key elements influencing the level of satisfaction with oncological care. Of note, 394 patients diagnosed with cancer treated in inpatient oncology wards participated in the study (Poland). The diagnostic survey method was used. A survey questionnaire developed by the authors was used and validated the EORTC IN-PATSAT32 questionnaire. The calculations were made in Statistica 10.0 (Statsoft; 2011, Dell Inc., Round Rock, TX, USA). The average general level of satisfaction with oncological care in the study group was 80.77 out of a total score of 100, representing the highest level of satisfaction. Levels of satisfaction varied according to time since diagnosis (longer time-greater satisfaction) and were lower where treatment was delayed or perceived as disorganised. Nearly half of the respondents felt the threat of the SARS-CoV-2 infection, despite the fact that most of them believed that the hospital was well prepared to diagnose and treat cancer patients during the COVID-19 pandemic. Convincing patients about the proper preparation of health care for diagnostics and therapy is an important element influencing patient satisfaction with oncological care.

Susceptibility to SARS-CoV-2 infection in patients undergoing chemotherapy and radiation therapy

The outbreak of the new coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly become a public health emergency of international concern, especially affecting the elderly people and patients with chronic disease, such as hypertension and respiratory syndromes. Patients undergoing chemotherapy treatment (e.g., bleomycin, cyclophosphamide, methotrexate, monoclonal antibodies, and paclitaxel therapy) are vulnerable to the development of respiratory syndromes induced by chemotherapeutic agents and are also more susceptible to viral infections as they are immunosuppressed. Neutropenia is an important risk factor for increased vulnerability to infections, as a respiratory syndrome involves an array of immune cells maintaining the balance between pathogen clearance and immunopathology. However, the differential diagnosis of pulmonary symptoms in cancer patients is broad, with complications being related to the malignancy itself, treatment toxicity, and infections. The risk factors depend on the specific type of cancer, chemotherapy, patient characteristics, and comorbidities. Thus, this review discusses the main events implicated in immunosuppression caused by chemotherapy and radiation therapy and the association of immunosuppression and other factors with SARS-CoV-2 infection susceptibility in cancer patients; and, importantly, how to deal with this situation in face of the current pandemic scenario.

A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020

The COVID-19 pandemic has affected all aspects of society. Researchers worldwide have been working to provide new solutions to and better understanding of this coronavirus. In this research, our goal was to perform a Bibliometric Network Analysis (BNA) to investigate the strategic themes, thematic evolution structure and trends of coronavirus during the first eight months of COVID-19 in the Web of Science (WoS) database in 2020. To do this, 14,802 articles were analyzed, with the support of the SciMAT software. This analysis highlights 24 themes, of which 11 of the more important ones were discussed in-depth. The thematic evolution structure shows how the themes are evolving over time, and the most developed and future trends of coronavirus with focus on COVID-19 were visually depicted. The results of the strategic diagram highlight 'CHLOROQUINE', 'ANXIETY', 'PREGNANCY' and 'ACUTE-RESPIRATORY-SYNDROME', among others, as the clusters with the highest number of associated citations. The thematic evolution. structure presented two thematic areas: "Damage prevention and containment of COVID-19" and "Comorbidities and diseases caused by COVID-19", which provides new perspectives and futures trends of the field. These results will form the basis for future research and guide decision-making in coronavirus focused on COVID-19 research and treatments.

Association of active oncologic treatment and risk of death in cancer patients with COVID-19: a systematic review and meta-analysis of patient data

BACKGROUND

Cancer patients suffer from worse coronavirus disease-2019 (COVID-19) outcomes. Whether active oncologic treatment is an additional risk factor in this population remains unclear. Therefore, here we have conducted a systematic review and meta-analysis to summarize the existing evidence for the effect of active oncologic treatment on COVID-19 outcomes.

METHODS

Systematic search of databases (PubMed, Embase) was conducted for studies published from inception to July 1, 2020, with a subsequent search update conducted on 10 October 2020. In addition, abstracts and presentations from major conference proceedings (ASCO, ESMO, AACR) as well as pre-print databases (medxriv, bioxriv) were searched. Retrospective and prospective studies reporting clinical outcomes in cancer patients with laboratory confirmation or clinical diagnosis of COVID-19 and details of active or recent oncologic treatment were selected. Random-effects model was applied throughout meta-analyses. Summary outcome measure was the pooled odds ratio (OR) of death for active cancer therapy versus no active cancer therapy for each of the following modalities: recent surgery, chemotherapy, targeted therapy, immunotherapy, or chemoimmunotherapy.

RESULTS

Sixteen retrospective and prospective studies (3558 patients) were included in the meta-analysis. Active chemotherapy was associated with higher risk of death compared to no active chemotherapy (OR, 1.60, 95% CI, 1.14-2.23). No significant association with risk of death was identified for active targeted therapy, immunotherapy, chemoimmunotherapy, or recent surgery. Meta-analysis of multivariate adjusted OR of death for active chemotherapy was consistently associated with higher risk of death compared to no active chemotherapy (OR, 1.42, 95% CI, 1.01-2.01).

CONCLUSIONS

Active chemotherapy appears to be associated with higher risk of death in cancer patients with COVID-19. Further research is necessary to characterize the complex interactions between active cancer treatment and COVID-19.

Mortality in patients with cancer and coronavirus disease 2019: A systematic review and pooled analysis of 52 studies

Background

Patients with coronavirus disease 2019 (COVID-19) who have underlying malignancy have a higher mortality rate compared with those without cancer, although the magnitude of such excess risk is not clearly defined. We performed a systematic review and pooled analysis to provide precise estimates of the mortality rate among patients with both cancer and COVID-19.

Methods

A systematic literature search involving peer-reviewed publications, preprints and conference proceedings up to July 16, 2020, was performed. The primary end-point was the case fatality rate (CFR), defined as the rate of death among patients with cancer and COVID-19. The CFR was assessed with a random effects model, which was used to derive a pooled CFR and its 95% confidence interval (CI).

Results

Fifty-two studies, involving a total of 18,650 patients with both COVID-19 and cancer, were selected for the pooled analysis. A total of 4243 deaths were recorded in this population. The probability of death was 25.6% (95% CI: 22.0%–29.5%; I² = 48.9%) in this patient population.

Conclusions

Patients with cancer who develop COVID-19 have high probability of mortality. Appropriate and aggressive preventive measures must be taken to reduce the risk of COVID-19 in patients with cancer and to optimally manage those who do contract the infection.