Cancer history is an independent risk factor for mortality in hospitalized COVID-19 patients: a propensity score-matched analysis

COVID-19 vaccine updates for people under different conditions

SARS-CoV-2 has caused global waves of infection since December 2019 and continues to persist today. The emergence of SARS-CoV-2 variants with strong immune evasion capabilities has compromised the effectiveness of existing vaccines against breakthrough infections. Therefore, it is important to determine the best utilization strategies for different demographic groups given the variety of vaccine options available. In this review, we will discuss the protective efficacy of vaccines during different stages of the epidemic and emphasize the importance of timely updates to target prevalent variants, which can significantly improve immune protection. While it is recognized that vaccine effectiveness may be lower in certain populations such as the elderly, individuals with chronic comorbidities (e.g., diabetes with poor blood glucose control, those on maintenance dialysis), or those who are immunocompromised compared to the general population, administering multiple doses can result in a strong protective immune response that outweighs potential risks. However, caution should be exercised when considering vaccines that might trigger an intense immune response in populations prone to inflammatory flare or other complications. In conclusion, individuals with special conditions require enhanced and more effective immunization strategies to prevent infection or reinfection, as well as to avoid the potential development of long COVID.

Predictors for cause-specific and timing of deaths in patients with COVID-19: a cohort study in Taiwan

BACKGROUND

This cohort study determines the predictors for cause-specific and timing of deaths in patients with COVID-19 in Taiwan.

METHODS

Patients with laboratory-confirmed COVID-19 admitted to Taipei City Hospital from January 1 to July 31, 2022, were recruited in this cohort. All patients were followed up until death, discharge from the hospital, or August 31, 2022. Early deaths within the first 2 weeks were recorded, and the cause of death was confirmed by the death certificate database of Taiwan. Predictors of cause-specific and timing of deaths of patients with COVID-19 were determined using multinomial Cox proportional hazards regression analysis.

RESULTS

Of the 195 (8.0%) patients who died during hospitalization, 147 (84.0%) had COVID-19-specific deaths. Moreover, 54.9% of the deceased patients had early death. After controlling for other covariates, patients aged ≥ 65 years had a higher risk of COVID-19-specific, non-COVID-19-specific, early, and late deaths [adjusted hazards ratio (AHR): 3.85, 6.45, 3.33, and 6.57; 95% confidence interval (CI): 1.91-7.78, 1.17-35.68, 1.51-7.36, and 2.18-19.76, respectively]. Fully vaccinated patients had a lower risk of COVID-19-specific (AHR: 0.68; 95% CI: 0.47-0.98) and early deaths (AHR: 0.54; 95% CI: 0.35-0.84), whereas comorbid patients with chronic obstructive pulmonary disease had a higher risk of non-COVID-19-specific deaths (AHR: 5.43; 95% CI: 1.73-17.03).

CONCLUSIONS

This study suggests that prioritizing COVID-19 vaccination and carefully monitoring comorbid patients during hospitalization can reduce the risk of COVID-19-specific and early deaths and non-COVID-19-specific mortalities, respectively.

Predictors of 2-year mortality in geriatric patients hospitalized with COVID-19 in Türkiye: a retrospective cohort study

Aim: To reveal factors affecting 2-year mortality in geriatric patients hospitalized with COVID-19.Methods: Demographic characteristics, clinical and laboratory data, thorax computed tomography (CT) images, second-year survival status, and causes of death were analyzed.Results: The 2-year post-discharge mortality rate of 605 patients was 21.9%. Mean age of patients in the deceased group was 76.8 ± 8.1 years, which was shorter than the life expectancy at birth in Türkiye. Older age (≥85), delirium, some co-morbidities, and atypical thorax CT involvement were associated with a significant increase in 2-year mortality (p < 0.05).Conclusion: This is the first study to evaluate factors associated with 2-year mortality in older COVID-19 patients. Identifying risk factors for long-term mortality in geriatric COVID-19 patients is important.

Breast cancer (BC) and severe COVID-19 (C-19) outcomes: a matched analysis

PURPOSE

Patients with cancer receiving anticancer treatment have a higher risk of severe COVID-19 (C-19) outcomes. We examine the association between breast cancer (BC), recent treatment (systemic therapy, surgery, radiation), and C-19 outcomes.

METHODS

Retrospective matched cohort study using the Optum® de-identified C-19 Electronic Health Record dataset (2007-2022). Patients with C-19 were categorized into: no cancer, BC with recent treatment, and BC without recent treatment and matched based on age, C-19 diagnosis date, and comorbidity score. We evaluated 30-day mortality, mechanical ventilation, intensive care unit (ICU) stay, and hospitalization. A composite outcome including all outcomes was analyzed. Multivariable logistic regression models were used.

RESULTS

2200 matched triplets (1:1:10) of patients with BC recently treated, BC not recently treated, and no cancer were included. Rates of adverse outcomes improved in 2021 compared to 2020. Compared to patients without cancer, those with BC recently treated had a similar risk of adverse outcomes, while patients with BC not recently treated had a lower risk of ICU stay and hospitalization. Using the composite variable, BC recently treated had similar outcomes (OR = 1.02; 95%CI 0.93-1.11) to patients without cancer, while BC patients not recently treated had better outcomes (OR = 0.66; 95%CI 0.59-0.74). Among patients with BC, chemotherapy within 3 months was associated with a higher risk of hospitalization (OR = 2.30; 95%CI 1.76-2.99) and composite outcome (OR = 2.11; 95%CI 1.64-2.72).

CONCLUSION

Patients with BC have a similar risk of adverse C-19 outcomes compared to patients without cancer. Among patients with BC, recent chemotherapy was associated with a higher risk of hospitalization.

ACE2: the node connecting the lung cancer and COVID-19

Angiotensin-converting Enzyme 2 (ACE2) collaborates with Angiotensin (Ang) 1-7 and Mas receptors to establish the ACE2-Ang (1-7)-Mas receptor axis. ACE2 impacts lung function and can cause lung injury due to its inflammatory effects. Additionally, ACE2 contributes to pulmonary vasculature dysfunction, resulting in pulmonary hypertension. In addition, ACE2 is a receptor for coronavirus entry into host cells, leading to coronavirus infection. Lung cancer, one of the most common respiratory diseases worldwide, has a high rate of infection. Elevated levels of ACE2 in lung cancer patients, which increase the risk of SARS-CoV-2 infection and severe disease, have been demonstrated in clinical studies and by molecular mechanisms. The association between lung cancer and SARS-CoV-2 is closely linked to ACE2. This review examines the basic pathophysiological role of ACE2 in the lung, the long-term effects of SARS-CoV-2 infection on lung function, the development of pulmonary fibrosis, chronic inflammation in long-term COVID patients, and the clinical research and mechanisms underlying the increased susceptibility of lung cancer patients to the virus. Possible mechanisms of lung cancer in SARS-CoV-2-infected individuals and the potential role of ACE2 in this process are also explored in this review. The role of ACE2 as a therapeutic target in the novel coronavirus infection process is also summarized. This will help to inform prevention and treatment of long-term pulmonary complications in patients.

A challenging issue in COVID-19 infection: The relationship between PA1-1 and TAFI levels in patients with coagulation disorder: A retrospective and observational study

COVID-19 disrupts the balance between coagulation and fibrinolysis. Especially in the clinical course of serious disease, plasminogen activator inhibitor-1 (PAI-1), thrombin activatable fibrinolysis inhibitor (TAFI), and tissue plasminogen activator levels increase in association with hypercoagulable state and hypofibrinolysis. This explains the increased incidence of thrombosis seen in COVID-19 infection. In this study, we aimed to examine the changes in PAI-1 and TAFI levels of COVID-19 patients. Department of Infectious Diseases and Clinical Microbiology, University of Health Sciences, Dişkapi Yildirim Beyazit Training and Research Hospital-Ankara Turkey, between April 1 and May 7, 2021. Patients who were diagnosed with COVID-19 were included in this retrospective study. TAFI and PAI-1 levels were analyzed from the samples that had been stored at -80 °C formerly. One hundred thirty-five patients diagnosed with COVID-19 and followed up in the service or intensive care unit were included in the study. Thirty-four (25.2%) patients required follow-up in the intensive care unit. Mortality rate was 10.4%, the coagulation tests of these patients were also compared. PA1-1 levels were found to be statistically significantly higher in intensive care unit patients (median: 133 pg/mL vs 31 pg/mL; P < .001), and there was no significant difference in TAFI levels (median:7.31 ng/mL vs 9.80 ng/mL; P = .171) between the 2 groups. TAFI levels were found to be higher in patients who died. In COVID-19 infection, as the severity of the disease increases, the coagulation balance deteriorates and eventually a hypercoagulable state occurs with an increase in PAI-1 and TAFI levels. Markers such as PAI and TAFI can be illuminating in further studies in determining prognosis and mortality and developing new treatment options.

Improved interpretable machine learning emergency department triage tool addressing class imbalance

Objective

The Score for Emergency Risk Prediction (SERP) is a novel mortality risk prediction score which leverages machine learning in supporting triage decisions. In its derivation study, SERP-2d, SERP-7d and SERP-30d demonstrated good predictive performance for 2-day, 7-day and 30-day mortality. However, the dataset used had significant class imbalance. This study aimed to determine if addressing class imbalance can improve SERP's performance, ultimately improving triage accuracy.

Methods

The Singapore General Hospital (SGH) emergency department (ED) dataset was used, which contains 1,833,908 ED records between 2008 and 2020. Records between 2008 and 2017 were randomly split into a training set (80%) and validation set (20%). The 2019 and 2020 records were used as test sets. To address class imbalance, we used random oversampling and random undersampling in the AutoScore-Imbalance framework to develop SERP+-2d, SERP+-7d, and SERP+-30d scores. The performance of SERP+, SERP, and the commonly used triage risk scores was compared.

Results

The developed SERP+ scores had five to six variables. The AUC of SERP+ scores (0.874 to 0.905) was higher than that of the corresponding SERP scores (0.859 to 0.894) on both test sets. This superior performance was statistically significant for SERP+-7d (2019: Z = -5.843, p < 0.001, 2020: Z = -4.548, p < 0.001) and SERP+-30d (2019: Z = -3.063, p = 0.002, 2020: Z = -3.256, p = 0.001). SERP+ outperformed SERP marginally on sensitivity, specificity, balanced accuracy, and positive predictive value measures. Negative predictive value was the same for SERP+ and SERP. Additionally, SERP+ showed better performance compared to the commonly used triage risk scores.

Conclusions

Accounting for class imbalance during training improved score performance for SERP+. Better stratification of even a small number of patients can be meaningful in the context of the ED triage. Our findings reiterate the potential of machine learning-based scores like SERP+ in supporting accurate, data-driven triage decisions at the ED.

Clinical Characteristics and Outcomes in Hospitalized Patients with COVID-19 and Cancer History: A Multicenter Cross-Sectional Study in Southwestern Iran

Background: Cancer patients are more exposed to opportunistic infections, such as COVID-19, due to their poor health status. This study aimed to identify the clinical characteristics of cancer and non-cancer patients with COVID-19 that may lead to death, intubation, and ICU admission. Materials and Methods: A Multicenter Cross-Sectional study was conducted on confirmed COVID-19 adult patients with and without a history of cancer from March 2019 to March 2021. Demographic and clinical features, ICU admission, intubation, and discharge status have been extracted from patients' medical records. Chi-square, odds ratio, Mann-Whitney test, and logistic regression were used to analyze the data. Results: The death rate in 1332 cancer patients was 28% compared to the 91464 noncancer patients which was 9% with an odds ratio of 3.94 and p<0.001. ICU admission rates among the cancer group were 43%, while in the noncancer group, it was 17.9% (p<0.001). Moreover, intubation was done for 20.9% of cancer patients and 7.4% of non-cancer patients (p<0.001). However, no significant difference was observed between the two groups in terms of length of stay in the hospital. Multivariable logistic regression analysis showed that age, level of consciousness, SPO2, and autoimmune disorders were associated with mortality in cancer patients with COVID-19. Conclusion: This study showed that older age, loss of consciousness, low oxygen saturation, and suffering from autoimmune disorders were the predictors of death in cancer patients with COVID-19. These results can have important implications for the management and care of cancer patients with COVID-19.

Breast Cancer (BC) and Severe COVID-19 (C-19) Outcomes: A Matched Analysis

Purpose

Patients with cancer receiving anticancer treatment have a higher risk of severe COVID-19 (C-19) outcomes. We examine the association between breast cancer (BC), recent treatment (systemic therapy, surgery, radiation), and C-19 outcomes.

Methods

Retrospective matched cohort study using the Optum® de-identified COVID-19 Electronic Health Record dataset (2007-2022). Patients with C-19 were categorized into: No cancer, BC with recent treatment, and BC without recent treatment and matched based on age, C-19 diagnosis date, and comorbidity score. We evaluated 30-day mortality, mechanical ventilation, intensive care unit (ICU) stay, and hospitalization. A composite outcome including all outcomes was analyzed. Multivariable logistic regression models were used.

Results

2200 matched triplets (1:1:10) of patients with BC recently treated, BC not recently treated, and no cancer were included. Rates of adverse outcomes improved in 2021 compared to 2020. Compared to patients without cancer, those with BC recently treated had a similar risk of adverse outcomes, while patients with BC not recently treated had a lower risk of ICU stay and hospitalization. Using the composite variable, BC recently treated had similar outcomes (OR = 1.02; 95%CI 0.93-1.11) to patients without cancer, while BC patients not recently treated had better outcomes (OR = 0.66; 95%CI 0.59-0.74). Among patients with BC, chemotherapy within 3-months was associated with a higher risk of hospitalization (OR = 2.30; 95%CI 1.76-2.99) and composite outcome (OR = 2.11; 95%CI 1.64-2.72).

Conclusion

Patients with BC have a similar risk of adverse C-19 outcomes compared to patients without cancer. Among patients with BC, recent chemotherapy was associated with a higher risk of hospitalization.

Mortality of COVID-19 in patients with hematological malignancies versus solid tumors: a systematic literature review and meta-analysis

Cancer patients are more vulnerable to COVID-19 compared to the general population, but it remains unclear which types of cancer have the highest risk of COVID-19-related mortality. This study examines mortality rates for those with hematological malignancies (Hem) versus solid tumors (Tumor). PubMed and Embase were systematically searched for relevant articles using Nested Knowledge software (Nested Knowledge, St Paul, MN). Articles were eligible for inclusion if they reported mortality for Hem or Tumor patients with COVID-19. Articles were excluded if they were not published in English, non-clinical studies, had insufficient population/outcomes reporting, or were irrelevant. Baseline characteristics collected included age, sex, and comorbidities. Primary outcomes were all-cause and COVID-19-related in-hospital mortality. Secondary outcomes included rates of invasive mechanical ventilation (IMV) and intensive care unit (ICU) admission. Effect sizes from each study were computed as logarithmically transformed odds ratios (ORs) with random-effects, Mantel-Haenszel weighting. The between-study variance component of random-effects models was computed using restricted effects maximum likelihood estimation, and 95% confidence intervals (CIs) around pooled effect sizes were calculated using Hartung-Knapp adjustments. In total, 12,057 patients were included in the analysis, with 2,714 (22.5%) patients in the Hem group and 9,343 (77.5%) patients in the Tumor group. The overall unadjusted odds of all-cause mortality were 1.64 times higher in the Hem group compared to the Tumor group (95% CI: 1.30-2.09). This finding was consistent with multivariable models presented in moderate- and high-quality cohort studies, suggestive of a causal effect of cancer type on in-hospital mortality. Additionally, the Hem group had increased odds of COVID-19-related mortality compared to the Tumor group (OR = 1.86 [95% CI: 1.38-2.49]). There was no significant difference in odds of IMV or ICU admission between cancer groups (OR = 1.13 [95% CI: 0.64-2.00] and OR = 1.59 [95% CI: 0.95-2.66], respectively). Cancer is a serious comorbidity associated with severe outcomes in COVID-19 patients, with especially alarming mortality rates in patients with hematological malignancies, which are typically higher compared to patients with solid tumors. A meta-analysis of individual patient data is needed to better assess the impact of specific cancer types on patient outcomes and to identify optimal treatment strategies.

The Association of Hypertension with Increased Mortality Rate During the COVID-19 Pandemic: An Update with Meta-analysis

BACKGROUND AND AIM

The impact of multiple risk factors on COVID-19 mortality has been previously reported in multiple systematic reviews and meta-analyses. The aim of this review is to provide a comprehensive update on the association between hypertension (HTN) and mortality in patients with COVID-19.

METHODS

A systematic review and meta-analysis were performed and followed the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. A search was achieved using PubMed, Scopus, and Cochrane Databases for research publications on hypertension, COVID-19, and mortality published between December 2019 and August 2022.

RESULTS

A total of 23 observational studies involving 611,522 patients from 5 countries (China, Korea, the UK, Australia, and the USA) were included in our study. The confirmed number of COVID-19 with HTN cases in each study ranged from 5 to 9964. The mortality ranged from 0.17% to 31% in different studies. Pooled results show that the mortality rate of COVID-19 among the included studies ranges from a minimum of 0.39 (95% CI 0.13-1.12) to a maximum of 5.74 (95% CI 3.77-8.74). Out of the 611,522 patients, 3119 died which resulted in an overall mortality prevalence of 0.5%. Subgroup analyses indicated that patients with COVID-19 who have hypertension and male patients had slightly less risk of mortality than female patients [the percentage of men > 50%; OR 1.33: 95% CI (1.01, 1.76); the percentage of men ≤ 50%: OR 2.26; and 95% CI (1.15, 4.48)]. Meta-regression analysis results also showed a statistically significant association between hypertension and COVID-19 mortality.

CONCLUSION

This systematic review and meta-analysis suggest that hypertension may not be the only risk factor associated with the increased mortality rate during the COVID-19 pandemic. In addition, a combination of other comorbidities and old age appears to increase the risk of mortality from COVID-19. The impact of hypertension on mortality rate among COVID-19 patients.

Comparison of characteristics and laboratory tests of COVID-19 hematological patients from France and Brazil during the pre-vaccination period: identification of prognostic profiles for survival

INTRODUCTION

COVID-19 disease presentation is heterogeneous, from asymptomatic up to severe life-threatening forms. Getting further insights into patients with specific diseases is of particular interest. We aimed to identify profiles of hematology patients hospitalized with COVID-19 that would be associated with survival and to assess the differences between cohorts METHODS: A binational cohort of 263 patients with COVID-19 and hematological disease was studied in Paris, France and São Paulo, Brazil. Patient profiles were based on age, comorbidities, biological measurements, COVID-19 symptoms and hematological disease characteristics. A semi-supervised learning method with a survival endpoint was first used, following which, a classifier was identified to allow the classification of patients using only baseline information MAIN RESULTS: Two profiles of patients were identified, one being young patients with few comorbidities and low C-reactive protein (CRP), D-dimers, lactate dehydrogenase (LDH) and creatinine levels, and the other, older patients, with several comorbidities and high levels of the 4 biology markers. The profiles were strongly associated with survival (p < 0.0001), even after adjusting for age (p = 0.0002). The 30-day survival rate was 77.1% in the first profiles, versus 46.7% in the second. The Brazilian analysis emphasized the importance of age, while the French focused on the comorbidities CONCLUSION: This analysis showed the importance of CRP, LHD and creatinine in the COVID-19 presentation and prognosis, whatever the geographic origin of the patients.

Characteristics and Outcomes of COVID-19 Cancer Patients Admitted to a Portuguese Intensive Care Unit: A Case-Control Study

Cancer patients appear to be a vulnerable group in the COVID-19 pandemic. This study aims to compare clinical characteristics and outcomes of cancer and non-cancer patients with COVID-19 admitted to the ICU. All COVID-19 cancer patients (cases) admitted to a Portuguese ICU between March 2020 and January 2021 were included and matched on age, sex and comorbidities with COVID-19 non-cancer patients (controls); 29 cases and 29 controls were enrolled. Initial symptoms were similar between the two groups. Anemia was significantly superior among cases (76% vs. 45%; p = 0.031). Invasive mechanical ventilation (IMV) need at ICU admission was significantly higher among cases (48% vs. 7%; odds ratio (OR) = 12.600, 95% CI: 2.517-63.063, p = 0.002), but there were no differences for global need for IMV during all-length of ICU stay and mortality rates. In a multivariate model of logistic regression, the risk of IMV need at ICU admission among cases remained statistically significant (adjusted OR = 14.036, 95% CI: 1.337-153.111, p = 0.028). Therefore, compared to critical non-cancer patients, critical cancer patients with COVID-19 had an increased risk for IMV need at the moment of ICU admission, however, not for IMV need during all-length of ICU stay or death.

Impact of COVID-19 pandemic on older cancer patients: Proposed solution by the International Geriatric Radiotherapy Group

Older cancer patients are disproportionally affected by the Coronavirus 19 (COVID-19) pandemic. A higher rate of death among the elderly and the potential for long-term disability have led to fear of contracting the virus in these patients. This fear can, paradoxically, cause delay in diagnosis and treatment that may lead to a poor outcome that could have been prevented. Thus, physicians should devise a policy that both supports the needs of older patients during cancer treatment, and serves to help them overcome their fear so they seek out to cancer diagnosis and treatment early. A combination of telemedicine and a holistic approach, involving prayers for older cancer patients with a high level of spirituality, may improve vaccination rates as well as quality of life during treatment. Collaboration between health care workers, social workers, faith-based leaders, and cancer survivors may be crucial to achieve this goal. Social media may be an important component, providing a means of sending the positive message to older cancer patients that chronological age is not an impediment to treatment.

Impact of coronavirus disease 2019 on lung cancer patients: A meta-analysis

Background

The coronavirus disease 2019 (COVID-19) pandemic poses a great challenge to the treatment of lung cancer patients.

Materials and methods

The PubMed, Embase, and Web of Science databases were searched for studies published before March 15, 2022, and Stata 14.0 software was used to perform a meta-analysis with a random-effects model. The odds ratio (OR) along with the corresponding 95% confidence interval (CI) was reported.

Results

Our meta-analysis included 80 articles with 318,352 patients involved. The proportion of lung cancer patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was 2.4% (95% CI: 0.02-0.03) prior to the Omicron variant outbreak. Among COVID-19 patients, those with lung cancer showed a higher mortality rate than those with other types of malignant solid tumors (OR = 1.82, 95% CI: 1.61-2.06) and non-cancer patients (OR = 4.67, 95% CI: 3.61-6.05); however, no significant difference was observed in the mortality rate between patients with lung cancer and those with hematologic malignancies (OR = 1.07, 95% CI: 0.85-1.33). SARS-CoV-2 infection significantly increased the mortality rate in lung cancer patients (OR = 8.94, 95% CI: 6.50-12.31). By contrast, the all-cause mortality rate in lung cancer patients (OR = 1.04, 95% CI: 0.69-1.57) and the proportion of patients diagnosed with advanced lung cancer (OR = 1.04, 95% CI: 0.85-1.27) did not significantly change before and after the pandemic.

Conclusions

More attention should be paid on improving the health of lung cancer patients during the COVID-19 pandemic.

Prognostic value of procalcitonin in cancer patients with coronavirus disease 2019

OBJECTIVES

Many biomarkers have been studied to assist in the risk stratification and prognostication of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Procalcitonin (PCT), a circulating precursor of the hormone calcitonin, has been studied with mixed results as a predictor of severe coronavirus disease 2019 (COVID-19) in the general population; however, to date, no studies have focused on the utility of PCT in predicting disease severity and death from COVID-19 in the cancer population.

METHODS

We conducted a retrospective study of cancer patients hospitalized with COVID-19 at a comprehensive cancer center over a 10-month period who had PCT recorded on admission. We assessed associations between variables of clinical interest and the primary outcomes of progression of COVID-19 and death during or within 30 days of hospitalization using univariable and multivariable logistic regression.

RESULTS

The study included 209 unique patients. In the univariate analysis, elevated PCT on admission was associated with higher odds of progression of COVID-19 or death (Odds ratio [OR] 1.40, 95% CI 1.08-1.93) and mortality alone (OR 1.53, 95% CI 1.17-2.11). In multivariate regression, PCT remained significantly associated with progression or death after holding chronic kidney disease (CKD) status constant (OR 1.40, 95% CI: 1.08, 1.93, p=0.003). Similarly, the association of PCT and death remained significant after adjusting for age (OR 1.54, 95% CI: 1.17-2.15).

CONCLUSIONS

In hospitalized COVID-19 patients with underlying cancer, initial PCT levels on admission may be associated with prognosis, involving higher odds of progression of COVID-19 and/or mortality.

Efficacy and safety of COVID-19 vaccines for patients with spinal tumors receiving denosumab treatment: An initial real-clinical experience study

Background

Even if COVID-19 vaccine has gradually been adopted in the world, information of side effects and crosstalk in patients with spinal tumors is absent due to the exclusion from clinical research. In this research, we aimed to investigate the efficacy and safety for the patients with spinal tumors treated by denosumab.

Methods

In this retrospective research, 400 patients under treatment of denosumab against spinal tumors in real-clinical experience were grouped into two cohorts according to the treatment of COVID-19 vaccine. And linked hospital data, serum samples and unsolicited related adverse events had been collected from January 22nd 2021 to June 1st 2021 respectively.

Results

233 patients of all participants who received regular treatment of denosumab were vaccinated by mRNA or inactivated vaccine. Patients of metastatic disease and primary osseous spinal tumor showed similar distribution in both two groups. Over the study period, within 176 patients tested the status of serologic response of vaccine, 88(81.48%) and 41(87.23%) individuals injected one or two inactivated vaccines had effective antibody against SARS-CoV-2 infections. As 21 patients (85.71%) treated by mRNA vaccine did. Considering of the safety of vaccine, most common systemic adverse events were nausea or vomiting (45 events vs 23events). Interestingly, fewer participants in the vaccine group were statistically recorded in local adverse events than in the placebo group (16 events vs 33 events).

Conclusions

Our initial real-clinical experience suggests that COVID-19 vaccines are likely safe and effective in in patients with spinal tumors receiving denosumab treatment.

Classification of Extracellular Vesicles Based on Surface Glycan Structures by Spongy-like Separation Media

Extracellular vesicles (EVs) are lipid bilayer vesicles that enclose various biomolecules. EVs hold promise as sensitive biomarkers to detect and monitor various diseases. However, they have heterogeneous molecular compositions. The compositions of EVs from identical donor cells obtained using the same purification methods may differ, which is a significant obstacle for elucidating objective biological functions. Herein, the potential of a novel lectin-based affinity chromatography (LAC) method to classify EVs based on their glycan structures is demonstrated. The proposed method utilizes a spongy-like monolithic polymer (spongy monolith, SPM), which consists of poly(ethylene-co-glycidyl methacrylate) with continuous micropores and allows an efficient in situ protein reaction with epoxy groups. Two distinct lectins with different specificities, Sambucus sieboldiana agglutinin and concanavalin A, are effectively immobilized on SPM without impacting the binding activity. Moreover, high recovery rates of liposomal nanoparticles as a model of EVs are achieved due to the large flow-through pores (>10 μm) of SPM compared to a typical agarose gel. Finally, lectin-immobilized SPMs are employed to classify EVs based on the surface glycan structures and demonstrate different subpopulations by proteome profiling. This is the first approach to clarify the variation of protein contents in EVs by the difference of surface glycans via lectin immobilized media.

A year of experience with COVID-19 in patients with cancer: A nationwide study

BACKGROUND

Cancer is a major public health problem and comorbidity associated with COVID-19 infection. According to previous studies, a higher mortality rate of COVID-19 in cancer patients has been reported.

AIMS

This study was undertaken to determine associated risk factors and epidemiological characteristics of hospitalized COVID-19 patients with cancer using a nationwide COVID-19 hospital data registry in Iran for the first time.

METHODS

In this retrospective study, we used a national data registry of hospitalized patients with Severe Acute Respiratory Syndrome (SARS) symptoms and patients with confirmed positive COVID-19 PCR between 18 February 2020 and 18 November 2020. The patients were classified into two groups patients with/without malignancy. Logistic regression model was utilized to analyze demographic factors, clinical features, comorbidities, and their associations with the disease outcomes.

RESULTS

In this study, 11 068 and 645 186 in-patients with SARS symptoms with and without malignancy were included, respectively. About 1.11% of our RT-PCR-positive patients had cancer. In patients with malignancy and COVID-19, older ages than 60 (OR: 1.88, 95% CI: 1.29-2.74, p-value: .001), male gender (OR: 1.43, 95% CI: 1.16-1.77, p-value: .001), concomitant chronic pulmonary diseases (CPD) (OR: 1.75, 95% CI: 1.14-2.68, p-value: .009), and presence of dyspnea (OR; 2.00, 95% CI: 1.60-2.48, p-value: <.001) were associated with increased mortality rate.

CONCLUSION

Given the immunocompromised state of patients with malignancy and their vulnerability to Covid-19 complications, collecting data on the comorbidities and their effects on the disease outcome can build on a better clinical view and help clinicians make decisions to manage these cases better; for example, determining special clinical care, especially in the shortage of health services.

Clinical outcomes in patients with COVID-19 and gynecologic cancer: A society of gynecologic oncology COVID-19 and gynecologic cancer registry study

OBJECTIVES

Patients with gynecologic malignancies may have varied responses to COVID-19 infection. We aimed to describe clinical courses, treatment changes, and short-term clinical outcomes for gynecologic oncology patients with concurrent COVID-19 in the United States.

METHODS

The Society of Gynecologic Oncology COVID-19 and Gynecologic Cancer Registry was created to capture clinical courses of gynecologic oncology patients with COVID-19. Logistic regression models were employed to evaluate factors for an association with hospitalization and death, respectively, within 30 days of COVID-19 diagnosis.

RESULTS

Data were available for 348 patients across 7 institutions. At COVID-19 diagnosis, 125 patients (36%) had active malignancy. Delay (n = 88) or discontinuation (n = 10) of treatment due to COVID-19 infection occurred in 28% with those on chemotherapy (53/88) or recently receiving surgery (32/88) most frequently delayed. In addition to age, performance status, diabetes, and specific COVID symptoms, both non-White race (adjusted odds ratio (aOR) = 3.93, 95% CI 2.06-7.50) and active malignancy (aOR = 2.34, 95% CI 1.30-4.20) were associated with an increased odds of hospitalization. Eight percent of hospitalized patients (8/101) died of COVID-19 complications and 5% (17/348) of the entire cohort died within 30 days after diagnosis.

CONCLUSIONS

Gynecologic oncology patients diagnosed with COVID-19 are at risk for hospitalization, delay of anti-cancer treatments, and death. One in 20 gynecologic oncology patients with COVID-19 died within 30 days after diagnosis. Racial disparities exist in patient hospitalizations for COVID-19, a surrogate of disease severity. Additional studies are needed to determine long-term outcomes and the impact of race.

SARS-CoV-2 infection and lytic reactivation of herpesviruses: A potential threat in the postpandemic era?

The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative pathogen for the coronavirus disease 2019 (COVID-19) pandemic, has greatly stressed our healthcare system. In addition to severe respiratory and systematic symptoms, several comorbidities increase the risk of fatal disease outcomes, including chronic viral infections. Increasing cases of lytic reactivation of human herpesviruses in COVID-19 patients and vaccinated people have been reported recently. SARS-CoV2 coinfection, COVID-19 treatments, and vaccination may aggravate those herpesvirus-associated diseases by reactivating the viruses in latently infected host cells. In this review, we summarize recent clinical findings and limited mechanistic studies regarding the relationship between SARS-CoV-2 and different human herpesviruses that suggest an ongoing potential threat to human health in the postpandemic era.

The Effect of Dexamethasone Treatment on COVID-19 Prognosis in Cancer Patients

Background: Dexamethasone is used to treat cancer, relieve chemotherapy-induced nausea and vomiting, enhance cancer patients’ appetites, and treat COVID-19 patients. There is little evidence of the impact of a dexamethasone treatment plan on the severity of COVID-19 infections in cancer patients. This study explores whether dexamethasone treatment plan influences the severity of COVID-19 in dexamethasone-treated cancer patients. Methods: The medical records of 108 cancer patients receiving dexamethasone at King Hussein Cancer Center with a COVID-19 infection and 343 without corticosteroid treatment were reviewed. Patients on dexamethasone within seven days before infection, after infection, or both were included. Ventilation support, hospitalization, and mortality within 28 days of a COVID-19 diagnosis were key severity factors. Results: We found that dexamethasone before a COVID-19 infection increased the risk of requiring ventilation assistance and mortality within 28 days by a factor of 5.8 (2.8−12.0) relative to control (p < 0.005). Continuing dexamethasone treatment after a COVID-19 infection, or starting it after infection, had a risk factor equivalent to control. Conclusion: Our data showed that dexamethasone therapy protocol affected COVID-19 prognoses in cancer patients, and it is preferable to not discontinue therapy after infection. A rigorous prospective comparison between early and late dexamethasone dosing is needed to determine the best protocol for treatment.

Prevalence and Assessment of Factors Associated with COVID-19 Vaccine Hesitancy in an Ethnic Minority Oncology Patient Population

BACKGROUND

Complicating the COVID-19 pandemic are the healthcare disparities experienced by ethnic minorities, especially those with comorbidities including cancer. The introduction of COVID-19 vaccines has been instrumental in blunting the morbidity and mortality from the pandemic; however, vaccine hesitancy, particularly among ethnic minorities, has been a major concern. Thus, we sought to evaluate the knowledge and perspectives of COVID-19 and vaccines among our ethnic minority cancer patient population.

METHODS

Following an IRB approved protocol, questionnaires were completed by patients in a predominantly ethnic minority population at a single institution between 1 February and 30 June 2021. Included were any adult cancer patients with either a solid or hematologic malignancy.

RESULTS

Among the 84 patients that were offered the questionnaires, 52 patients responded, with a median age of 63.5 years. Overall, 36% were non-Hispanic Blacks and 30% were Hispanics; 65% were receiving active treatment for their cancer. Seventy-nine percent believed COVID-19 to be dangerous or harmful to them, 61% were concerned about the side effects, yet 65% considered COVID-19 vaccines as safe. Among the seven patients that refused the vaccine, (71%, n = 5) cited side effects and/or (57%, n = 4) believed that the vaccine was not needed. Overall, there was a significantly higher chance of being vaccinated if patients were receiving active cancer treatment, believed COVID-19 was harmful, or that the vaccine was safe, and knew COVID-19 was a virus.

CONCLUSIONS

This exploratory study demonstrates that most ethnic minority cancer patients are receptive to vaccines, with a majority being vaccinated. However, we also discovered various reasons why this group of patients may not want be vaccinated, including concerns about side effects and perception that COVID-19 is not harmful. These findings can help us further understand the complex nature of vaccine hesitancy in ethnic minority cancer patients, and aid in developing future vaccine awareness strategies as the COVID-19 pandemic continues to evolve.

Clinical Characteristics and Risk Factors among Patients with Positive COVID-19 Test Admitted to ICU

Background

Studies that show common characteristics among ICU-admitted patients due to COVID-19 are available on the net, but such studies in Saudi Arabia are limited.

Methods

A descriptive cross-sectional study establishing common comorbidities and risk factors among critically ill patients who tested positive for COVID-19 at the National Guard Hospital from March 2, 2020, to March 20, 2021. The data were obtained from the BEST Care System of King Abdulaziz Medical City, computed, and analyzed using SPSS.

Results

Three hundred eighty-five COVID-19 patients admitted to the intensive care unit (ICU) were included in this study. The mean age was 60.85 ± 20.46, 60.85% were males, and 39.2% were females. There was statistically significant positive relationship between severity of the symptoms and age (P = 0.002). The mean duration of hospital stay in the sample was 21.85 ± 28.47. More than one-third (37.4%) of cases admitted to the hospital died while about two-thirds of the cases were discharged after complete recovery. Two hundred ninety (75.3%) of the patients who were admitted to the National Guard Health Affairs (Riyadh, Saudi Arabia) had respiratory disease. Two hundred twelve patients (55.1%) had diabetes mellitus, while the number of hypertensive patients was 203 (52.7%). There was a significant positive relation among patients with gastrointestinal tract infection (GIT) risk factors and the severity of the symptoms of COVID-19 (P = 0.000). In addition, there was a strong significant relation between hypertension patients and the severity of the COVID-19 symptoms (P = 0.017).

Conclusion

COVID-19 patients who have GIT and hypertension have been found to be at an increased risk of COVID-19 symptom severity. Old age was also found to have an increased risk for COVID-19 symptom severity.

COVID-19 Diagnosis and Risk of Death Among Adults With Cancer in Indiana: Retrospective Cohort Study

BACKGROUND

Prior studies, generally conducted at single centers with small sample sizes, found that individuals with cancer experience more severe outcomes due to COVID-19, caused by SARS-CoV-2 infection. Although early examinations revealed greater risk of severe outcomes for patients with cancer, the magnitude of the increased risk remains unclear. Furthermore, prior studies were not typically performed using population-level data, especially those in the United States. Given robust prevention measures (eg, vaccines) are available for populations, examining the increased risk of patients with cancer due to SARS-CoV-2 infection using robust population-level analyses of electronic medical records is warranted.

OBJECTIVE

The aim of this paper is to evaluate the association between SARS-CoV-2 infection and all-cause mortality among recently diagnosed adults with cancer.

METHODS

We conducted a retrospective cohort study of newly diagnosed adults with cancer between January 1, 2019, and December 31, 2020, using electronic health records linked to a statewide SARS-CoV-2 testing database. The primary outcome was all-cause mortality. We used the Kaplan-Meier estimator to estimate survival during the COVID-19 period (January 15, 2020, to December 31, 2020). We further modeled SARS-CoV-2 infection as a time-dependent exposure (immortal time bias) in a multivariable Cox proportional hazards model adjusting for clinical and demographic variables to estimate the hazard ratios (HRs) among newly diagnosed adults with cancer. Sensitivity analyses were conducted using the above methods among individuals with cancer-staging information.

RESULTS

During the study period, 41,924 adults were identified with newly diagnosed cancer, of which 2894 (6.9%) tested positive for SARS-CoV-2. The population consisted of White (n=32,867, 78.4%), Black (n=2671, 6.4%), Hispanic (n=832, 2.0%), and other (n=5554, 13.2%) racial backgrounds, with both male (n=21,354, 50.9%) and female (n=20,570, 49.1%) individuals. In the COVID-19 period analysis, after adjusting for age, sex, race or ethnicity, comorbidities, cancer type, and region, the risk of death increased by 91% (adjusted HR 1.91; 95% CI 1.76-2.09) compared to the pre-COVID-19 period (January 1, 2019, to January 14, 2020) after adjusting for other covariates. In the adjusted time-dependent analysis, SARS-CoV-2 infection was associated with an increase in all-cause mortality (adjusted HR 6.91; 95% CI 6.06-7.89). Mortality increased 2.5 times among adults aged 65 years and older (adjusted HR 2.74; 95% CI 2.26-3.31) compared to adults 18-44 years old, among male (adjusted HR 1.23; 95% CI 1.14-1.32) compared to female individuals, and those with ≥2 chronic conditions (adjusted HR 2.12; 95% CI 1.94-2.31) compared to those with no comorbidities. Risk of mortality was 9% higher in the rural population (adjusted HR 1.09; 95% CI 1.01-1.18) compared to adult urban residents.

CONCLUSIONS

The findings highlight increased risk of death is associated with SARS-CoV-2 infection among patients with a recent diagnosis of cancer. Elevated risk underscores the importance of adhering to social distancing, mask adherence, vaccination, and regular testing among the adult cancer population.

Are patients with cancer at higher risk of COVID-19-related death? A systematic review and critical appraisal of the early evidence

BACKGROUND

Early reports suggested that COVID-19 patients with cancer were at higher risk of COVID-19-related death. We conducted a systematic review with risk of bias assessment and synthesis of the early evidence on the risk of COVID-19-related death for COVID-19 patients with and without cancer.

METHODS AND FINDINGS

We searched Medline/Embase/BioRxiv/MedRxiv/SSRN databases to 1 July 2020. We included cohort or case-control studies published in English that reported on the risk of dying after developing COVID-19 for people with a pre-existing diagnosis of any cancer, lung cancer, or haematological cancers. We assessed risk of bias using tools adapted from the Newcastle-Ottawa Scale. We used the generic inverse-variance random-effects method for meta-analysis. Pooled odds ratios (ORs) and hazard ratios (HRs) were calculated separately. Of 96 included studies, 54 had sufficient non-overlapping data to be included in meta-analyses (>500,000 people with COVID-19, >8000 with cancer; 52 studies of any cancer, three of lung and six of haematological cancers). All studies had high risk of bias. Accounting for at least age consistently led to lower estimated ORs and HRs for COVID-19-related death in cancer patients (e.g. any cancer versus no cancer; six studies, unadjusted OR=3.30,95%CI:2.59-4.20, adjusted OR=1.37,95%CI:1.16-1.61). Adjusted effect estimates were not reported for people with lung or haematological cancers. Of 18 studies that adjusted for at least age, 17 reported positive associations between pre-existing cancer diagnosis and COVID-19-related death (e.g. any cancer versus no cancer; nine studies, adjusted OR=1.66,95%CI:1.33-2.08; five studies, adjusted HR=1.19,95%CI:1.02-1.38).

CONCLUSIONS

The initial evidence (published to 1 July 2020) on COVID-19-related death in people with cancer is characterised by multiple sources of bias and substantial overlap between data included in different studies. Pooled analyses of non-overlapping early data with adjustment for at least age indicated a significantly increased risk of COVID-19-related death for those with a pre-existing cancer diagnosis.

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.

Methodological Considerations on COVID-19 Mortality in Cancer Patients: A Systematic Review and Meta-Analysis

BACKGROUND

Patients with cancer are at risk for severe COVID-19. Previous studies examining mortality in cancer patients with COVID-19 have produced inconclusive results. Several published meta-analyses have aimed to estimate this association; however, because of methodological limitations in study selection and data aggregation, these studies do not reliably estimate the independent association between cancer and COVID-19 mortality. We conducted this systematic review and meta-analysis to determine whether cancer is an independent risk factor for COVID-19 mortality.

METHODS

A literature search was performed in PubMed to identify studies that compared COVID-19 mortality in adult patients with and without cancer. Selection criteria included polymerase chain reaction-confirmed COVID-19, multivariate adjustment and/or matching for mortality risk estimates, and inclusion of hospitalized noncancer controls. Adjusted odds ratios and/or hazard ratios for mortality based on cancer status were extracted. Odds ratio and hazard ratio estimates were pooled using a random effects model.

RESULTS

The analysis included 42 studies comprising 129 840 patients: 8612 cancer patients and 121 228 noncancer patients. Of these studies, 18 showed a null difference in survival between cancer and noncancer patients with COVID-19, and 24 studies showed statistically significantly worse survival in cancer patients with COVID-19. Meta-analysis revealed an increased risk of mortality in patients with cancer compared with noncancer patients with COVID-19 (odds ratio = 1.93, 95% confidence interval = 1.55 to 2.41; hazard ratio = 1.54, 95% confidence interval = 1.29 to 1.84).

CONCLUSION

We conclude that cancer is an independent risk factor for mortality in unvaccinated patients admitted for or diagnosed with COVID-19 during hospitalization.

Association between short-term exposure to air pollution and COVID-19 mortality in all German districts: the importance of confounders

BACKGROUND

The focus of many studies is to estimate the effect of risk factors on outcomes, yet results may be dependent on the choice of other risk factors or potential confounders to include in a statistical model. For complex and unexplored systems, such as the COVID-19 spreading process, where a priori knowledge of potential confounders is lacking, data-driven empirical variable selection methods may be primarily utilized. Published studies often lack a sensitivity analysis as to how results depend on the choice of confounders in the model. This study showed variability in associations of short-term air pollution with COVID-19 mortality in Germany under multiple approaches accounting for confounders in statistical models.

METHODS

Associations between air pollution variables PM_2.5, PM₁₀, CO, NO, NO₂, and O₃ and cumulative COVID-19 deaths in 400 German districts were assessed via negative binomial models for two time periods, March 2020-February 2021 and March 2021-February 2022. Prevalent methods for adjustment of confounders were identified after a literature search, including change-in-estimate and information criteria approaches. The methods were compared to assess the impact on the association estimates of air pollution and COVID-19 mortality considering 37 potential confounders.

RESULTS

Univariate analyses showed significant negative associations with COVID-19 mortality for CO, NO, and NO₂, and positive associations, at least for the first time period, for O₃ and PM_2.5. However, these associations became non-significant when other risk factors were accounted for in the model, in particular after adjustment for mobility, political orientation, and age. Model estimates from most selection methods were similar to models including all risk factors.

CONCLUSION

Results highlight the importance of adequately accounting for high-impact confounders when analyzing associations of air pollution with COVID-19 and show that it can be of help to compare multiple selection approaches. This study showed how model selection processes can be performed using different methods in the context of high-dimensional and correlated covariates, when important confounders are not known a priori. Apparent associations between air pollution and COVID-19 mortality failed to reach significance when leading selection methods were used.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s12302-022-00657-5.

Quality of Life and Its Associated Factors Among Cancer Patients Receiving Chemotherapy at Oncology Hospitals in Vietnam After the Third Wave of the COVID-19 Pandemic

Purpose

This study aimed to evaluate the health-related quality of life (HRQOL) of cancer patients receiving chemotherapy and identify associated factors affecting the HRQOL after the third wave of the COVID-19 pandemic in Vietnam.

Patients and Methods

Patients with solid cancers receiving chemotherapy at two oncology hospitals in Vietnam during April and May 2021 were included. The European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire version 3 was used to measure the HRQOL. Three questions were asked to explore patients’ concern levels about contracting COVID-19, delaying chemotherapy, or not controlling cancer well. One question was used to explore whether patients were concerned about cancer progression or COVID-19 infection more, or equally, or had no concern about both. Multiple regression models were conducted to examine factors associated with the global health status (GHS) score.

Results

Of 270 included patients, mean (Standard deviation [SD]) GHS was 56.7 (20.8). Among the functional statuses, social functioning (SF) had the lowest score of 63.6 (29.2). The symptoms with the highest means were insomnia and fatigue, obtaining the score of 38.5 (31.7) and 37.3 (29.2), respectively. The mean of financial difficulties was 54.1 (32.2). In univariate analysis, high concerns about contracting COVID-19, delaying chemotherapy, not controlling cancer well, or more concern about either cancer or COVID-19 over the other were associated with worse GHS, physical functioning, emotional functioning, and SF. In multivariate analysis, those concerns and no income were significantly related to lower GHS scores besides the non-modifiable factors, such as female gender and some cancer types.

Conclusion

Patients at the high concern levels, or with more concern about either cancer or COVID-19 over the other had poorer HRQOL. Interventions to address the concerns are required to improve their HRQOL, particularly for women, those without income, or with some specific cancers.

Risk factors of SARS-CoV-2 infection in cancer patients pre- and post-vaccination

Background

Severe complications from COVID-19 and poor responses to SARS-CoV-2 vaccination were commonly reported in cancer patients compared to those without cancer. Therefore, the identification of predisposing factors to SARS-CoV-2 infection in cancer patients would assist in the prevention of COVID-19 and improve vaccination strategies. The literature lacks reports on this topic from the Kingdom of Saudi Arabia (KSA). Therefore, we studied clinical and laboratory data of 139 cancer patients from King Abdulaziz Medical City, Riyadh, KSA.

Methods

The cancer patients fall into three categories; (i) uninfected with SARS-CoV-2 pre-vaccination and remained uninfected post-vaccination (control group; n = 114; 81%), (ii) pre-vaccination infected group (n = 16; 11%), or (iii) post-vaccination infected group (n = 9; 6%). Next, the clinical and lab data of the three groups of patients were investigated.

Results

Comorbidity factors like diabetes and hemodialysis were associated with the risk of infection in cancer patients before the vaccination (p<0.05). In contrast to breast cancer, papillary thyroid cancer was more prevalent in the infected patients pre- and post-vaccination (p<0.05). Pre-vaccination infected group had earlier cancer stages compared with the control group (p = 0.01). On the other hand, combined therapy was less commonly administrated to the infected groups versus the control group (p<0.05). Neutrophil to lymphocyte ratio was lower in the post-vaccination infected group compared to the control group (p = 0.01).

Conclusion

Collectively, this is the first study from KSA to report potential risk factors of SARS-CoV-2 infection in cancer patients pre- and post-vaccination. Further investigations on these risk factors in a larger cohort are worthwhile to draw a definitive conclusion about their roles in predisposing cancer patients to the infection.

A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received

Vaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-risk patients and maximize lives saved. We used electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until 30 November 2021, in a national healthcare organization in Israel to build logistic models estimating the probability of subsequent hospitalization and death of newly infected patients based on a few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and the presence of hypertension, pulmonary disease, and malignancy) and the number of BNT162b2 mRNA vaccine doses received. The model’s performance was assessed by 10-fold cross-validation: the area under the curve was 0.889 for predicting hospitalization and 0.967 for predicting mortality. A total of 50%, 80%, and 90% of death events could be predicted with respective specificities of 98.6%, 95.2%, and 91.2%. These models enable the rapid identification of individuals at high risk for hospitalization and death when infected, and they can be used to prioritize patients to receive scarce medications or booster vaccination. The calculator is available online.

PARIS score for evaluation of probability of SARS-CoV-2 infection in cancer patients

Control of transmissible diseases as COVID-19 needs a testing and an isolation strategy. The PARIS score developed by Torjdman et al. was aimed at improving patient selection for testing and quarantining but was derived from a general population. We performed a retrospective analysis of the validity of the PARIS score in a cancer patient population. We included 164 patients counting for 181 visits at the emergency department of the Jules Bordet Institute between March 10th and May 18th which had a SARS-CoV-2 RT-PCR test at admission. Twenty-six cases (14.3%) were tested positive with a higher proportion of positive tests among hematological patients compared to those with solid tumors (26% vs 11% p = 0.02). No clinical symptoms were associated with a positive SARS-CoV-2 PCR. No association between anticancer treatment and SARS-CoV-2 infection was found. The PARIS score failed to differentiate SARS-CoV-2-positive and SARS-CoV-2-negative groups (AUC 0.61 95% CI 0.48–0.73). The negative predictive value of a low probability PARIS score was 0.89 but this concerned only 11% of the patients. A high probability PARIS score concerned 49% patients but the positive predictive value was 0.18. CT scan had a sensitivity of 0.77, specificity 0.51, a positive predictive value of 0.24, and a negative predictive value of 0.92. The performance of the PARIS score is thus very poor in this cancer population. A low-risk score can be of some utility but this concerns a minority of patients.

Characterizing cancer and COVID-19 outcomes using electronic health records

Purpose

Patients with cancer often have compromised immune system which can lead to worse COVID-19 outcomes. The purpose of this study is to assess the association between COVID-19 outcomes and existing cancer-specific characteristics.

Patients and methods

Patients aged 18 or older with laboratory-confirmed COVID-19 between June 1, 2020, and December 31, 2020, were identified (n = 314 004) from the Optum® de-identified COVID-19 Electronic Health Record (EHR) derived from more than 700 hospitals and 7000 clinics in the United States. To allow sufficient observational time, patients with less than one year of medical history in the EHR dataset before their COVID-19 tests were excluded (n = 42 365). Assessed COVID-19 outcomes including all-cause 30-day mortality, hospitalization, ICU admission, and ventilator use, which were compared using relative risks (RRs) according to cancer status and treatments.

Results

Among 271 639 patients with COVID-19, 18 460 had at least one cancer diagnosis: 8034 with a history of cancer and 10 426 with newly diagnosed cancer within one year of COVID-19 infection. Patients with a cancer diagnosis were older and more likely to be male, white, Medicare beneficiaries, and have higher prevalences of chronic conditions. Cancer patients had higher risks for 30-day mortality (RR 1.07, 95% CI 1.01–1.14, P = 0.028) and hospitalization (RR 1.04, 95% CI 1.01–1.07, P = 0.006) but without significant differences in ICU admission and ventilator use compared to non-cancer patients. Recent cancer diagnoses were associated with higher risks for worse COVID-19 outcomes (RR for mortality 1.17, 95% CI 1.08–1.25, P<0.001 and RR for hospitalization 1.10, 95% CI 1.06–1.14, P<0.001), particularly among recent metastatic (stage IV), hematological, liver and lung cancers compared with the non-cancer group. Among COVID-19 patients with recent cancer diagnosis, mortality was associated with chemotherapy or radiation treatments within 3 months before COVID-19. Age, black patients, Medicare recipients, South geographic region, cardiovascular, diabetes, liver, and renal diseases were also associated with increased mortality.

Conclusions and relevance

Individuals with cancer had higher risks for 30-day mortality and hospitalization after SARS-CoV-2 infection compared to patients without cancer. More specifically, patients with a cancer diagnosis within 1 year and those receiving active treatment were more vulnerable to worse COVID-19 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.

Outcomes of COVID-19 and risk factors in patients with cancer

Patients with cancer are at higher risk for adverse coronavirus disease 2019 (COVID-19) outcomes. Here, we studied 1,253 patients with cancer, who were diagnosed with severe acute respiratory syndrome coronavirus 2 at a tertiary referral cancer center in India. Most patients had mild disease; in our settings, recent cancer therapies did not impact COVID-19 outcomes. Advancing age, smoking history, concurrent comorbidities and palliative intent of treatment were independently associated with severe COVID-19 or death. Thus, our study provides useful insights into cancer management during the COVID-19 pandemic.

Safety and Feasibility of Lung Cancer Surgery under the COVID-19 Circumstance

Simple Summary

The global coronavirus disease 2019 (COVID-19) pandemic has drastically changed the current practice of medicine worldwide. As more clinical data is collected and processed, we are beginning to have an understanding of which patients are more at risk for severe complications of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Preliminary data has shown that patients with lung cancer are disproportionally affected by the current COVID-19 pandemic. Furthermore, studies have shown that lung cancer patients are also significantly more likely to be admitted to the ICU and need mechanical ventilation. A specific subset of patients that are even more at risk for severe COVID-19 are those that require lung cancer surgery. To minimize the risk of SARS-CoV-2 infections in patients undergoing surgery, new treatment guidelines and preventive measures are necessary. In this review, we summarize the latest evidence regarding recommendations for patients undergoing lung cancer surgery in the COVID-19 era.

Abstract

The current coronavirus disease 2019 (COVID-19) pandemic has forced healthcare providers worldwide to adapt their practices. Our understanding of the effects of COVID-19 has increased exponentially since the beginning of the pandemic. Data from large-scale, international registries has provided more insight regarding risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and has allowed us to delineate specific subgroups of patients that have higher risks for severe complications. One particular subset of patients that have significantly higher risks of SARS-CoV-2 infection with higher morbidity and mortality rates are those that require surgical treatment for lung cancer. Earlier studies have shown that COVID-19 infections in patients that underwent lung cancer surgery is associated with higher rates of respiratory failure and mortality. However, deferral of cancer treatments is associated with increased mortality as well. This creates difficult situations in which healthcare providers are forced to weigh the benefits of surgical treatment against the possibility of SARS-CoV-2 infections. A number of oncological and surgical organizations have proposed treatment guidelines and recommendations for patients planned for lung cancer surgery. In this review, we summarize the latest data and recommendations for patients undergoing lung cancer surgery in the COVID-19 circumstance.

Bioinformatics approach to identify common gene signatures of patients with coronavirus 2019 and lung adenocarcinoma

Coronavirus disease 2019 (COVID-19) continues as a global pandemic. Patients with lung cancer infected with COVID-19 may develop severe disease or die. Treating such patients severely burdens overwhelmed healthcare systems. Here, we identified potential pathological mechanisms shared between patients with COVID-19 and lung adenocarcinoma (LUAD). Co-expressed, differentially expressed genes (DEGs) in patients with COVID-19 and LUAD were identified and used to construct a protein-protein interaction (PPI) network and to perform enrichment analysis. We used the NetworkAnalyst platform to establish a co-regulatory of the co-expressed DEGs, and we used Spearman's correlation to evaluate the significance of associations of hub genes with immune infiltration and immune checkpoints. Analysis of three datasets identified 112 shared DEGs, which were used to construct a protein-PPI network. Subsequent enrichment analysis revealed co-expressed genes related to biological process (BP), molecular function (MF), and cellular component (CC) as well as to pathways, specific organs, cells, and diseases. Ten co-expressed hub genes were employed to construct a gene-miRNA, transcription factor (TF)-gene, and TF-miRNA network. Hub genes were significantly associated with immune infiltration and immune checkpoints. Finally, methylation level of hub genes in LUAD was obtained via UALCAN database. The present multi-dimensional study reveals commonality in specific gene expression by patients with COVID-19 and LUAD. These findings provide insights into developing strategies for optimising the management and treatment of patients with LUAD with COVID-19.

Reduced Absolute Count of Monocytes in Patients Carrying Hematological Neoplasms and SARS-CoV2 Infection

Simple Summary

In hematological neoplasms associated with COVID-19, immunological dysfunction, including reduced count of non-classical monocytes, has been suggested as a primary driver of morbidity and mortality. In this work, we investigated the contribution of absolute monocyte count to clinical outcome of COVID-19 in 120 patients affected by hematological neoplasms that tested positive to SARS-CoV-2. We found that there was no statistical difference in 30-day mortality, rate of hospitalization for intensive cure and viral clearance at 14 days between fully vaccinated and unvaccinated patients. Increased 30-day mortality was associated with presence of active/progressing disease and absolute monocyte count lower than 400 cells/uL. Reduced absolute counts of monocytes should be used as an alert of increased risk of severe/critical forms of COVID-19 in patients with hematological malignancies, even when the full vaccination cycle has been completed.

Abstract

Background: Clinical course of COVID-19 depends on several patient-specific risk factors, including immune function, that is largely compromised in cancer patients. Methods: We prospectively evaluated 120 adult consecutive patients (including 34 cases of COVID-19 breakthrough after two full doses of BNT162b2 vaccine) with underlying hematological malignancies and a SARS-CoV-2 infection, in terms of patient’s clinical outcome. Results: Among fully vaccinated patients the achievement of viral clearance by day 14 was more frequent than in unvaccinated patients. Increased 30-day mortality was associated with presence of active/progressing disease and absolute monocyte count lower than 400 cells/uL. Results of multivariable analysis in unvaccinated patients showed that the pre-infection absolute count of monocytes less or equal to 400 cells/mmc, active or progressive disease of the underlying hematological malignancy, the COVID-19 severity identified by hospitalization requirement and lack of viral clearance at 14 days were independent predictors of 1-year overall survival. Conclusions: Taken together, our results indicate that absolute monocyte count determined one month before any documented SARS-CoV-2 infection could identify patients affected by hematological neoplasms with increased risk of inferior overall survival.

Effect of cancer on outcome of COVID-19 patients: a systematic review and meta-analysis of studies of unvaccinated patients

Background:

Since the beginning of the SARS-CoV-2 pandemic, cancer patients affected by COVID-19 have been reported to experience poor prognosis; however, a detailed quantification of the effect of cancer on outcome of unvaccinated COVID-19 patients has not been performed.

Methods:

To carry out a systematic review of the studies comparing the outcome of unvaccinated COVID-19 patients with and without cancer, a search string was devised which was used to identify relevant publications in PubMed up to December 31, 2020. We selected three outcomes: mortality, access to ICU, and COVID-19 severity or hospitalization. We considered results for all cancers combined as well as for specific cancers. We conducted random-effects meta-analyses of the results, overall and after stratification by region. We also performed sensitivity analyses according to quality score and assessed publication bias.

Results:

For all cancer combined, the pooled odds ratio (OR) for mortality was 2.32 (95% confidence interval [CI] 1.82–2.94, I² for heterogeneity 90.1%, 24 studies), that for ICU admission was 2.39 (95% CI 1.90–3.02, I² 0.0%, 5 studies), that for disease severity or hospitalization was 2.08 (95% CI 1.60–2.72, I² 92.1%, 15 studies). The pooled mortality OR for hematologic neoplasms was 2.14 (95% CI 1.87–2.44, I² 20.8%, 8 studies). Data were insufficient to perform a meta-analysis for other cancers. In the mortality meta-analysis for all cancers, the pooled OR was higher for studies conducted in Asia than studies conducted in Europe or North America. There was no evidence of publication bias.

Conclusions:

Our meta-analysis indicates a twofold increased risk of adverse outcomes (mortality, ICU admission, and severity of COVID-19) in unvaccinated COVID-19 patients with cancer compared to COVID-19 patients without cancer. These results should be compared with studies conducted in vaccinated patients; nonetheless, they argue for special effort to prevent SARS-CoV-2 infection in patients with cancer.

Funding:

No external funding was obtained.

Different Clinical Outcomes of COVID-19 in Two Healthcare Workers Vaccinated with BNT162b2 Vaccine, Infected with the Same Viral Variant but with Different Predisposing Conditions for the Progression of the Disease

Safe and effective vaccines are available to face the global threat of the COVID-19 pandemic. In this article, we report on the clinical cases of two healthcare workers vaccinated with two doses of BNT162b2 vaccine who were infected by the same viral clade but had different clinical outcomes.

An observational study of hospitalized COVID-19 patients with cancer in San Diego county

Aim: To delineate clinical correlates of COVID-19 infection severity in hospitalized patients with malignancy. Methods: The authors conducted a retrospective review of all hospitalized patients with a hematologic and/or solid tumor malignancy presenting to the authors' institution between 1 March 2020 and 5 January 2021, with a laboratory confirmed diagnosis of COVID-19. Univariate and multivariate logistic regression analyses were used to determine associations between specific severity outcomes and clinical characteristics. Results: Among 2771 hospitalized patients with COVID-19, 246 (8.88%) met inclusion criteria. Patients who were actively receiving treatment had an increased rate of death following admission (odds ratio [OR]: 2.7). After adjusting for significant covariates, the odds ratio increased to 4.4. Patients with cancer involvement of the lungs had a trend toward increased odds of death after adjusting for covariates (OR: 2.3). Conclusions: Among COVID-19 positive hospitalized cancer patients, systemic anti-cancer therapy was associated with significantly increased odds of mortality.

Neurosurgery at the crossroads of immunology and nanotechnology. New reality in the COVID-19 pandemic

Neurosurgery as one of the most technologically demanding medical fields rapidly adapts the newest developments from multiple scientific disciplines for treating brain tumors. Despite half a century of clinical trials, survival for brain primary tumors such as glioblastoma (GBM), the most common primary brain cancer, or rare ones including primary central nervous system lymphoma (PCNSL), is dismal. Cancer therapy and research have currently shifted toward targeted approaches, and personalized therapies. The orchestration of novel and effective blood-brain barrier (BBB) drug delivery approaches, targeting of cancer cells and regulating tumor microenvironment including the immune system are the key themes of this review. As the global pandemic due to SARS-CoV-2 virus continues, neurosurgery and neuro-oncology must wrestle with the issues related to treatment-related immune dysfunction. The selection of chemotherapeutic treatments, even rare cases of hypersensitivity reactions (HSRs) that occur among immunocompromised people, and number of vaccinations they have to get are emerging as a new chapter for modern Nano neurosurgery.

Clinical outcomes of geriatric patients with COVID-19: review of one-year data

Aims

In this study, we aimed to reveal mortality rates and factors affecting survival in geriatric patients infected with COVID-19.

Methods

This is a retrospective study of 873 geriatric patients with COVID-19 who were hospitalized between March 11, 2020 and March 11, 2021. Demographic, clinical, laboratory data, and treatment options were obtained from electronic medical records. Multivariate logistic regression was used to explore the risk factors for in-hospital death.

Results

During the specified period, 643 patients were discharged, and 230 patients died in the hospital. The mean age was 75.08 ± 7.39 years (mean ± SD) and 51.8% were males. We found that older age (≥ 85), polypharmacy, dyspnea, abnormal thorax computed tomography (CT), lower doses of anticoagulation, and high values of white blood cell, aspartate aminotransferase, C-reactive protein, lactate dehydrogenase, ferritin were associated with a significant increase in mortality (P < 0.001 for all). Although all of these values were significant in multivariate logistic regression analysis, the most important ones were dyspnea (Odds ratio (OR) 57.916, 95% confidence interval (CI) 23.439–143.104, P < 0.001), polypharmacy (OR 6.782, 95% CI 3.082–14.927, P < 0.001), and thorax CT classification (typical; OR 9.633, 95% CI 2.511–37.122, P < 0.001).

Conclusion

Older age, polypharmacy, dyspnea, and abnormal thorax CT were the most significant mortality criteria and in addition appropriate anticoagulant use was associated with reduced mortality. Identifying the risk factors to predict mortality in older adults with COVID-19 is important to treat future cases successfully.

Clinical Characteristics and Risk Factors of COVID-19 in 60 Adult Cancer Patients

BACKGROUND

During the pandemic of COVID-19, cancer patients have been considered as one high-risk group in the morbidity and mortality of COVID-19. This study aimed to describe the clinical symptoms and risk factors of COVID-19 in cancer patients.

METHOD

In a prospective cross-sectional study, during a year, all cancer patients who underwent chemotherapy and/or targeted therapy in our clinic (Kermanshah, Iran) were followed up in terms of getting COVID-19. We analyzed the effect of tumor features and demographic information on clinical manifestations, survival status, therapeutic outcomes, and severity of the disease COVID-19 in 2 categories of cancer (hematologic and solid cancers).

RESULTS

Most of the patients (68%) were in the solid tumor category, including breast cancer (24.4%), colon cancer (22%), and gastric cancer (9.8%). There was a statistically significant difference between 2 categories of cancer in the clinical manifestations: the stage of cancer and survival status (P < .05). Logistic regression analysis showed that the risk of death in cancer patients with COVID-19 along with symptoms of diarrhea (odds ratio [OR] = 12.8, P = .004), the difficulty of breath (OR = 10.73, P = .034), drop of SO2 (OR = 1.334, P = .003), thrombocytopenia (OR = 1.022, P = .02), anemia (OR = 2.72, P = .011), requiring mechanical ventilation (OR = 9.24, P = .004), pleural infusion (OR = 10.28, P = .02), and intensive care unit (ICU) admission (OR = 7.389, P = .009) increases independent of other variables. The COVID-19 mortality rate in our cancer patients was 23%.

CONCLUSIONS

Thrombocytopenia, anemia, and diarrhea are symptoms that, along with common symptoms such as lung involvement, difficulty breathing, and the need for a ventilator, increase the risk of death in cancer patients with COVID-19.

Analysis of epidemiological and clinical profile in COVID-19 deaths in a tertiary care ICU setup: a retrospective observational study

There are numerous publications describing the epidemiology and clinical outcome of patients infected with COVID-19. However, limited studies solely describing the fatalities, especially in India. In this retrospective, single-centre analysis of patients’ case records, we aim to describe and discuss the demographics, clinical, laboratory findings in 201 patients who expired as a result of SARS CoV-2 infection. Electronic medical files of all confirmed COVID-19 patients, admitted to the ICU between 1st February 2020 and 15th July 2020, were scanned retrospectively and data was collected from files of the fatalities only, without revealing patient identity at any point. The data, including demographics (age, sex, comorbidities), clinical presentation, baseline laboratory parameters, SOFA score and duration of illness was recorded and analyzed statistically. A total of 201 deceased patients were included in the study, out of which 58.2% were males. The median age was 59 years (IQR: 47.5 – 65 years) which appears to be less than a lot of studies conducted outside India. Majority of patients had classical influenza-like symptoms at presentation (74.1%), but a sizable number also had extra-pulmonary manifestations (24.9%). Eight patients had isolated neurological presentation. It was found that number of comorbidities increased, and duration of illness decreased with increasing age, and this was statistically significant (p 0.03 and 0.01, respectively). SOFA score was found to be an important marker of severity of illness in COVID patients. ARDS remained the primary cause of death in 87.1% patients, although septic shock was observed in 34.8%. Six patients expired due to a high suspicion of pulmonary thromboembolism.

Baseline clinical features of COVID-19 patients, delay of hospital admission and clinical outcome: A complex relationship

Introduction

Delay between symptom onset and access to care is essential to prevent clinical worsening for different infectious diseases. For COVID-19, this delay might be associated with the clinical prognosis, but also with the different characteristics of patients. The objective was to describe characteristics and symptoms of community-acquired (CA) COVID-19 patients at hospital admission according to the delay between symptom onset and hospital admission, and to identify determinants associated with delay of admission.

Methods

The present work was based on prospective NOSO-COR cohort data, and restricted to patients with laboratory confirmed CA SARS-CoV-2 infection admitted to Lyon hospitals between February 8 and June 30, 2020. Long delay of hospital admission was defined as ≥6 days between symptom onset and hospital admission. Determinants of the delay between symptom onset and hospital admission were identified by univariate and multiple logistic regression analysis.

Results

Data from 827 patients were analysed. Patients with a long delay between symptom onset and hospital admission were younger (p<0.01), had higher body mass index (p<0.01), and were more frequently admitted to intensive care unit (p<0.01). Their plasma levels of C-reactive protein were also significantly higher (p<0.01). The crude in-hospital fatality rate was lower in this group (13.3% versus 27.6%), p<0.01. Multiple analysis with correction for multiple testing showed that age ≥75 years was associated with a short delay between symptom onset and hospital admission (≤5 days) (aOR: 0.47 95% CI (0.34–0.66)) and CRP>100 mg/L at admission was associated with a long delay (aOR: 1.84 95% CI (1.32–2.55)).

Discussion

Delay between symptom onset and hospital admission is a major issue regarding prognosis of COVID-19 but can be related to multiple factors such as individual characteristics, organization of care and severe pathogenic processes. Age seems to play a key role in the delay of access to care and the disease prognosis.

Predicting COVID-19 severity using major risk factors and received vaccines

BACKGROUND

Vaccines are highly effective in preventing severe disease and death from COVID-19, and new medications that can reduce severity of disease have been approved. However, many countries are facing limited supply of vaccine doses and medications. A model estimating the probabilities for hospitalization and mortality according to individual risk factors and vaccine doses received could help prioritize vaccination and yet scarce medications to maximize lives saved and reduce the burden on hospitalization facilities.

METHODS

Electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until November 30, 2021 were extracted from a national healthcare organization in Israel. Logistic regression models were built to estimate the risk for subsequent hospitalization and death based on the number of BNT162b2 mRNA vaccine doses received and few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and presence of hypertension, pulmonary disease and malignancy).

RESULTS

The models built predict the outcome of newly infected individuals with remarkable accuracy: area under the curve was 0.889 for predicting hospitalization, and 0.967 for predicting mortality. Even when a breakthrough infection occurs, having received three vaccination doses significantly reduces the risk of hospitalization by 66% (OR=0.339) and of death by 78% (OR=0.223).

CONCLUSIONS

The models enable rapid identification of individuals at high risk for hospitalization and death when infected. These patients can be prioritized to receive booster vaccination and the yet scarce medications. A calculator based on these models is made publicly available on http://covidest.web.app.

OUP accepted manuscript

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has currently affected >220 million individuals worldwide. The complex interplay of immune dysfunction, active malignancy, the effect of cancer treatment on the immune system and additional comorbidities associated with cancer and COVID-19 all affect the outcomes of COVID-19 in patients with cancer. We have discussed the published findings (through the end of September 2021) on the effects of cancer on the morbidity and mortality of COVID-19, common factors between cancer and COVID-19, the interaction of cancer and COVID-19 treatments, the impact of COVID-19 on cancer clinical services, immune test findings in cancer patients with COVID-19 and the long-term effects of COVID-19 on cancer survivors.

Androgen deprivation therapy, comorbidity, cancer stage and mortality from COVID-19 in men with prostate cancer

BACKGROUND

Androgens facilitate entrance of the severe acute respiratory syndrome coronavirus 2 into respiratory epithelial cells, and male sex is associated with a higher risk of death from corona virus disease (COVID-19). Androgen deprivation therapy (ADT) could possibly improve COVID-19 outcomes.

METHODS

In a case-control study nested in the Prostate Cancer data Base Sweden (PCBaSe) RAPID 2019, we evaluated the association between ADT and COVID-19 as registered cause of death in men with prostate cancer. Each case was matched to 50 controls by region. We used conditional logistic regression to adjust for confounders and also evaluated potential impact of residual confounding.

RESULTS

We identified 474 men who died from COVID-19 in March-December 2020. In crude analyses, ADT exposure was associated with an increased risk of COVID-19 death (odds ratio [OR] 5.05, 95% CI: 4.18-6.10); however, the OR was substantially attenuated after adjustment for age, comorbidity, prostate cancer characteristics at diagnosis, recent healthcare use, and indicators of advanced cancer (adjusted OR 1.25, 95% CI: 0.95-1.65). If adjustment has accounted for at least 85% of confounding, then the true effect could be no more than a 5% reduction of the odds for COVID-19 death.

CONCLUSIONS

The increased mortality from COVID-19 in men with prostate cancer treated with ADT was mainly related to high age, comorbidity, and more advanced prostate cancer. There was no evidence to support the hypothesis that ADT is associated with improved COVID-19 outcomes.