Outcomes of COVID-19 in Patients With Cancer: Report From the National COVID Cohort Collaborative (N3C)

Efficacy and safety of interim oncology treatments introduced for solid cancers during the COVID-19 pandemic in England: a retrospective evidence-based analysis

Background

The COVID-19 global pandemic placed unprecedented pressure on cancer services, requiring new interim Systemic Anti-Cancer Treatments (SACT) options to mitigate risks to patients and maintain cancer services. In this study we analyse interim COVID-19 SACT therapy options recommended in England, evaluating the evidence supporting inclusion and delineating how these have been integrated into routine cancer care.

Methods

We performed a retrospective analysis of interim Systemic Anti-Cancer Treatments endorsed by NHS England during the COVID-19 pandemic. Interim therapy options were compared to baseline (replacement) therapies by comparing data from the key pivotal trial(s) in terms of clinical efficacy and potential benefits (e.g., reduced immunosuppression or improved adverse effect profile) within the context of the pandemic. Furthermore, we evaluated the evolution of these interim SACT options, exploring if these have been integrated into current treatment pathways or are no longer accessible at the pandemic end.

Findings

31 interim oncology treatment options, across 36 indications, for solid cancers were endorsed by NHS England between March 2020 and August 2021. Interim therapies focused on the metastatic setting (83%; 30/36), allowing greater utilisation of immune checkpoint inhibitors (45%; 14/31) and targeted therapies (26%; 8/31), in place of cytotoxic chemotherapy. Overall, 36% (13/36) of therapies could not have efficacy compared with baseline treatments due to a paucity of evidence. For those which could, 39% (9/23) had superior efficacy (e.g., overall survival), 26% (6/23) had equivocal efficacy and 35% (8/23) lower efficacy. 53% (19/36) of interim therapies had better or equivocal toxicity profiles (when assessable), and/or were associated with reduced immunosuppression. Almost half (47%; 17/36) of interim therapies did not have UK market authorisation, being classified as 'off label' use. Analysing access to interim options at the end of the pandemic (May 2023) identified 19 (53% 19/36) interim options were fully available, and a further four (11% 4/36) therapies were partially available.

Interpretation

Interim SACT options, introduced in England, across a range of solid cancers supported delivery of cancer services during the pandemic. Most interim therapies did not demonstrate superior efficacy, but provided other important benefits (e.g., reduced immunosuppression) in the context of the pandemic.

Funding

None.

Impact of Hyponatremia on COVID-19-Related Outcomes: A Retrospective Analysis

BACKGROUND

Sodium disturbances are observed in one-third of patients with COVID-19 and result from multifaceted mechanisms. Notably, hyponatremia is associated with disease progression and mortality.

AIM

We aimed to analyze the impact of hyponatremia on COVID-19 outcomes and its correlation with clinical and laboratory parameters during the first wave.

METHODS

We evaluated the sodium levels of 558 patients with COVID-19 between 21 March 2020, and 31 July 2020, at a single center. We performed linear regression analyses to explore the correlation of sodium levels with COVID-19-related outcomes, demographic data, signs and symptoms, and laboratory parameters. Next, we conducted Pearson correlation analyses. A p-value < 0.05 was considered significant.

RESULTS

Hyponatremia was found in 35.3% of hospitalized patients with COVID-19. This was associated with the need for intensive care transfer (B = -1.210, p = 0.009) and invasive mechanical ventilation (B = -1.063, p = 0.032). Hyponatremia was frequently found in oncologic patients (p = 0.002) and solid organ transplant recipients (p < 0.001). Sodium was positively associated with diastolic blood pressure (p = 0.041) and productive cough (p = 0.022) and negatively associated with dry cough (p = 0.032), anorexia (p = 0.004), and nausea/vomiting (p = 0.007). Regarding the correlation of sodium levels with other laboratory parameters, we observed a positive correlation with hematocrit (p = 0.011), lymphocytes (p = 0.010), pCO2 (p < 0.0001), bicarbonate (p = 0.0001), and base excess (p = 0.008) and a negative correlation with the neutrophil-to-lymphocyte ratio (p = 0.009), the platelet-to-lymphocyte ratio (p = 0.033), and arterial blood glucose (p = 0.016).

CONCLUSIONS

Hyponatremia is a risk factor for adverse outcomes in COVID-19 patients. It is associated with demographic data and clinical and laboratory parameters. Therefore, hyponatremia is an important tool for risk stratification in COVID-19 patients.

A retrospective single institutional analysis of outpatient chemotherapy in patients with cancer during the COVID-19 pandemic

Providing treatment to patients with cancer, even during the coronavirus disease (COVID-19) pandemic, is essential. In collaboration with infectious disease specialists, we established guidelines for the management of patients with cancer receiving ambulatory treatment during the pandemic on April 8, 2020. This study examined the practice and management of ambulatory chemotherapy under emergency conditions. Following the guidelines, our Breast and Medical oncology department developed a chemotherapy strategy for the phases. Additionally, to distinguish fever during chemotherapy, we developed a flow chart for fever. As part of a fact-finding survey, the status of outpatient chemotherapy was investigated: (1) whether there was any change in the number of chemotherapies before and after the declaration of a state of emergency by the Tokyo Metropolitan Government and (2) the frequency and severity of febrile neutropenia (FN) cases. Compared to before the first declaration of the state of emergency, the number of chemotherapies decreased except after the declaration, but no decrease was observed during the rest of the period; no difference was observed in the frequency or severity of FN outbreaks or in the use of pegfilgrastim for primary prevention before and after the epidemic. With appropriate treatment guidelines, routine chemotherapy can be performed in an outpatient setting during an outbreak.

A population-based study of COVID-19 mortality risk in US cancer patients

BACKGROUND

In this study, we provide the largest analysis to date of a US-based cancer cohort to characterize death from COVID-19.

METHODS

A total of 4 020 669 patients across 15 subtypes living with cancer in 2020 and included in the National Cancer Institute's Surveillance, Epidemiology, and End Results database were abstracted. We investigated prognostic factors for death due to COVID-19 using a Cox proportional hazards model and calculated hazard ratios (HRs). Standardized mortality ratios were calculated using observed mortality counts from Surveillance, Epidemiology, and End Results and expected mortality based on US mortality rates.

RESULTS

A total of 291 323 patients died, with 14 821 (5.1%) deaths attributed to COVID-19 infection. The COVID-19 disease-specific mortality rate was 11.81/10 000-persons years, and the standardized mortality ratio of COVID-19 was 2.30 (95% confidence interval [CI] = 2.26 to 2.34; P < .0001). COVID-19 ranked as the second leading cause of death following ischemic heart disease (5.2%) among 26 noncancer causes of death. Patients who are older (80 years and older vs 49 years and younger: HR = 21.47, 95% CI = 19.34 to 23.83), male (vs female: HR = 1.46, 95% CI = 1.40 to 1.51), unmarried (vs married: HR = 1.47, 95% CI = 1.42 to 1.53), and Hispanic or non-Hispanic African American (vs non-Hispanic White: HR = 2.04, 95% CI = 1.94 to 2.14 and HR = 2.03, 95% CI = 1.94 to 2.14, respectively) were at greatest risk of COVID-19 mortality.

CONCLUSIONS

We observed that people living with cancer are at 2 times greater risk of dying from COVID-19 compared with the general US population. This work may be used by physicians and public health officials in the creation of survivorship programs that mitigate the risk of COVID-19 mortality.

Adolescents and young adults with cancer: the clinical course of COVID-19 infections

Adolescents and young adults (ie, individuals aged 15-39 years, known as AYAs) with cancer face unique vulnerabilities yet remain underrepresented in clinical trials, including adult registries of COVID-19 in cancer (AYAs: 8%-12%). We used the Pediatric Oncology COVID-19 Case Report to examine the clinical course of COVID-19 among AYAs with cancer. The Pediatric Oncology COVID-19 Case Report collects deidentified clinical and sociodemographic data regarding individuals aged from birth to 39 years with cancer (37%) and COVID-19 from more than 100 institutions. Between April 1, 2020, and November 28, 2023, 191 older AYAs (individuals 22-39 years of age) and 640 younger AYAs (individuals 15-21 years of age) were captured. Older AYAs were less often hospitalized (P < .001), admitted to the intensive care unit (P = .02), and required respiratory support (P = .057). In multivariable analyses, older AYAs faced 80% lower odds of intensive care unit admission but 2.3-times greater odds of changes to cancer-directed therapy. Unvaccinated patients had 5.4-times higher odds of intensive care unit admission. Among AYAs with cancer, the COVID-19 course varies by age. These findings can inform oncology teams directing COVID-19 management and prevention in AYA patients with cancer.

Managing and treating COVID-19 in patients with hematological malignancies: a narrative review and expert insights

Patients with hematologic malignancies (HMs) are at a significantly higher risk of contracting COVID-19 and experiencing severe outcomes compared to individuals without HMs. This heightened risk is influenced by various factors, including the underlying malignancy, immunosuppressive treatments, and patient-related factors. Notably, immunosuppressive regimens commonly used for HM treatment can lead to the depletion of B cells and T cells, which is associated with increased COVID-19-related complications and mortality in these patients. As the pandemic transitions into an endemic state, it remains crucial to acknowledge and address the ongoing risk for individuals with HMs. In this review, we aim to summarize the current evidence to enhance our understanding of the impact of HMs on COVID-19 risks and outcomes, identify particularly vulnerable individuals, and emphasize the need for specialized clinical attention and management. Furthermore, the impaired immune response to COVID-19 vaccination observed in these patients underscores the importance of implementing additional mitigation strategies. This may include targeted prophylaxis and treatment with antivirals and monoclonal antibodies as indicated. To provide practical guidance and considerations, we present two illustrative cases to highlight the real-life challenges faced by physicians caring for patients with HMs, emphasizing the need for individualized management based on disease severity, type, and the unique circumstances of each patient.

Changes in hospital mortality in patients with cancer during the COVID-19 pandemic (ISARIC-CCP-UK): a prospective, multicentre cohort study

BACKGROUND

Patients with cancer are at greater risk of dying from COVID-19 than many other patient groups. However, how this risk evolved during the pandemic remains unclear. We aimed to determine, on the basis of the UK national pandemic protocol, how factors influencing hospital mortality from COVID-19 could differentially affect patients undergoing cancer treatment. We also examined changes in hospital mortality and escalation of care in patients on cancer treatment during the first 2 years of the COVID-19 pandemic in the UK.

METHODS

We conducted a prospective cohort study of patients aged older than 19 years and admitted to 306 health-care facilities in the UK with confirmed SARS-CoV-2 infection, who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol (CCP) across the UK from April 23, 2020, to Feb 28, 2022; this analysis included all patients in the complete dataset when the study closed. The primary outcome was 30-day in-hospital mortality, comparing patients on cancer treatment and those without cancer. The study was approved by the South Central-Oxford C Research Ethics Committee in England (Ref: 13/SC/0149) and the Scotland A Research Ethics Committee (Ref 20/SS/0028), and is registered on the ISRCTN Registry (ISRCTN66726260).

FINDINGS

177 871 eligible adult patients either with no history of cancer (n=171 303) or on cancer treatment (n=6568) were enrolled; 93 205 (52·4%) were male, 84 418 (47·5%) were female, and in 248 (13·9%) sex or gender details were not specified or data were missing. Patients were followed up for a median of 13 (IQR 6-21) days. Of the 6568 patients receiving cancer treatment, 2080 (31·7%) died at 30 days, compared with 30 901 (18·0%) of 171 303 patients without cancer. Patients aged younger than 50 years on cancer treatment had the highest age-adjusted relative risk (hazard ratio [HR] 5·2 [95% CI 4·0-6·6], p<0·0001; vs 50-69 years 2·4 [2·2-2·6], p<0·0001; 70-79 years 1·8 [1·6-2·0], p<0·0001; and >80 years 1·5 [1·3-1·6], p<0·0001) but a lower absolute risk (51 [6·7%] of 763 patients <50 years died compared with 459 [30·2%] of 1522 patients aged >80 years). In-hospital mortality decreased for all patients during the pandemic but was higher for patients on cancer treatment than for those without cancer throughout the study period.

INTERPRETATION

People with cancer have a higher risk of mortality from COVID-19 than those without cancer. Patients younger than 50 years with cancer treatment have the highest relative risk of death. Continued action is needed to mitigate the poor outcomes in patients with cancer, such as through optimising vaccination, long-acting passive immunisation, and early access to therapeutics. These findings underscore the importance of the ISARIC-WHO pandemic preparedness initiative.

FUNDING

National Institute for Health Research and the Medical Research Council.

Risk of COVID-19 death for people with a pre-existing cancer diagnosis prior to COVID-19-vaccination: A systematic review and meta-analysis

While previous reviews found a positive association between pre-existing cancer diagnosis and COVID-19-related death, most early studies did not distinguish long-term cancer survivors from those recently diagnosed/treated, nor adjust for important confounders including age. We aimed to consolidate higher-quality evidence on risk of COVID-19-related death for people with recent/active cancer (compared to people without) in the pre-COVID-19-vaccination period. We searched the WHO COVID-19 Global Research Database (20 December 2021), and Medline and Embase (10 May 2023). We included studies adjusting for age and sex, and providing details of cancer status. Risk-of-bias assessment was based on the Newcastle-Ottawa Scale. Pooled adjusted odds or risk ratios (aORs, aRRs) or hazard ratios (aHRs) and 95% confidence intervals (95% CIs) were calculated using generic inverse-variance random-effects models. Random-effects meta-regressions were used to assess associations between effect estimates and time since cancer diagnosis/treatment. Of 23 773 unique title/abstract records, 39 studies were eligible for inclusion (2 low, 17 moderate, 20 high risk of bias). Risk of COVID-19-related death was higher for people with active or recently diagnosed/treated cancer (general population: aOR = 1.48, 95% CI: 1.36-1.61, I2  = 0; people with COVID-19: aOR = 1.58, 95% CI: 1.41-1.77, I2  = 0.58; inpatients with COVID-19: aOR = 1.66, 95% CI: 1.34-2.06, I2  = 0.98). Risks were more elevated for lung (general population: aOR = 3.4, 95% CI: 2.4-4.7) and hematological cancers (general population: aOR = 2.13, 95% CI: 1.68-2.68, I2  = 0.43), and for metastatic cancers. Meta-regression suggested risk of COVID-19-related death decreased with time since diagnosis/treatment, for example, for any/solid cancers, fitted aOR = 1.55 (95% CI: 1.37-1.75) at 1 year and aOR = 0.98 (95% CI: 0.80-1.20) at 5 years post-cancer diagnosis/treatment. In conclusion, before COVID-19-vaccination, risk of COVID-19-related death was higher for people with recent cancer, with risk depending on cancer type and time since diagnosis/treatment.

Analysis of the impact of radiotherapy and surgical treatment regimens based on the SEER database on the survival outcomes of rectal cancer patients over 70 years

OBJECTIVE

This study evaluates the impact of different combinations of treatment regimens, such as additional radiation, chemotherapy, and surgical treatments, on the survival of elderly rectal cancer patients ≥ 70 years of age to support physicians' clinical decision-making.

METHODS

Data from a sample of elderly rectal cancer patients aged ≥ 70 years diagnosed from 2005-2015 from the US surveillance, epidemiology, and end results (SEER) database were retrospectively analyzed. The best cut-off point was selected using the x-tile software for the three continuity indices: age, tumor size, and number of regional lymph nodes. All patients were categorized into either the neoadjuvant radiotherapy and surgery group (R_S group), the surgical treatment group (S group), or the surgery and adjuvant radiotherapy group (S_R group). The propensity score allocation was used to match each included study subject in a 1:1 ratio, and the restricted mean survival time method (RMST) was used to predict the mean survival of rectal cancer patients within 5 and 10 years. The prognostic risk factors for rectal cancer patients were determined using univariate and multivariate Cox regression analyses, and nomograms were constructed. A subgroup stratification analysis of patients with different treatment combination regimens was performed using the Kaplan-Meier method, and log-rank tests were used for between-group comparisons. The model's predictive accuracy was assessed by receiver operating characteristic (ROC) curves, correction curves, and a clinical decision curve analysis (DCA).

RESULTS

A total of 7556 cases of sample data from 2005 to 2015 were included, which were categorized into 6639 patients (87.86%) in the S group, 408 patients (5.4%) in the R_S group, and 509 patients (6.74%) in the S_R group, according to the relevant order of radiotherapy and surgery. After propensity score matching (PSM), the primary clinical characteristics of the groups were balanced and comparable. The difference in the mean survival time before and after PSM was not statistically significant in both R_S and S groups (P value > 0.05), and the difference in the mean survival time after PSM was statistically substantial in S_R and S groups (P value < 0.05). In the multifactorial Cox analysis, the M1 stage and Nodes ≥ 9 were independent risk factors. An age between 70-75 was an independent protective factor for patients with rectal cancer in the R_S and S groups. The Marital_status, T4 stage, N2 stage, M1 stage, and Nodes ≥ 9 were independent risk factors for patients with rectal cancer in the S_R and S groups, and an age between 70-81 was an independent protective factor. The ROC curve area, the model C index, and the survival calibration curve suggested good agreement between the actual and predicted values of the model. The DCA for 3-year, 5-year, and 10-year survival periods indicated that the model had some potential for application.

CONCLUSIONS

The results of the study showed no significant difference in the overall survival (OS) between elderly patients who received neoadjuvant radiotherapy and surgery and those who received surgery alone; elderly patients who received surgery and adjuvant radiotherapy had some survival benefits compared with those who received surgery alone, though the benefit of adjuvant radiotherapy was not significant. Therefore, radiotherapy for rectal cancer patients older than 70 years old should be based on individual differences in condition, and a precise treatment plan should be developed.

Previous immune checkpoint inhibitor therapy is associated with decreased COVID-19-related hospitalizations and complications in patients with cancer: Results of a propensity-matched analysis of the OnCovid registry

OBJECTIVES

To date, studies have not provided definitive answers regarding whether previous immune checkpoint inhibitor (ICI) treatment alters outcomes for cancer patients with COVID-19.

METHODS

The OnCovid registry (NCT04393974) was searched from February 27, 2020, to January 31, 2022, for patients who received systemic anti-cancer therapy in the 4 weeks before laboratory-confirmed COVID-19 diagnosis. Propensity-score matching using country, vaccination status, primary tumor type, sex, age, comorbidity burden, tumor stage, and remission status investigated differences in predefined clinical outcomes comparing those who had or had not received ICIs.

RESULTS

Of 3523 patients screened, 137 ICI-only and 1378 non-ICI met inclusion criteria. Before matching, ICI patients were older, male, enrolled at centers in Italy, and had histories of smoking, thoracic cancers, advanced cancer stages, and active malignancies (P ≤0.02). After matching, there were 120 ICI and 322 non-ICI patients. ICI patients had no differences (odds ratio: 95% CI) in presenting COVID-19 symptoms (0.69: 0.37-1.28), receipt of COVID-specific therapy (0.88: 0.54-1.41), 14-day (0.95: 0.56-1.61), or 28-day (0.79: 0.48-1.29) mortalities. However, ICI patients required less COVID-19-related hospitalization (0.37: 0.21-0.67) and oxygen therapy (0.51: 0.31-0.83) and developed fewer complications (0.57: 0.36-0.92).

CONCLUSION

In this propensity-score matched analysis, previous ICI therapy did not worsen and potentially improved COVID-19 outcomes in patients with cancer.

COVID-19 outcomes in persons with hemophilia: results from a US-based national COVID-19 surveillance registry

BACKGROUND

Hypercoagulable state contributing to thrombotic complications worsens COVID-19 severity and outcomes, whereas anticoagulation improves outcomes by alleviating hypercoagulability.

OBJECTIVES

To examine whether hemophilia, an inherent hypocoagulable condition, offers protection against COVID-19 severity and reduces venous thromboembolism (VTE) risk in persons with hemophilia (PwH).

METHODS

A 1:3 propensity score-matched retrospective cohort study used national COVID-19 registry data (January 2020 through January 2022) to compare outcomes between 300 male PwH and 900 matched controls without hemophilia.

RESULTS

Analyses of PwH demonstrated that known risk factors (older age, heart failure, hypertension, cancer/malignancy, dementia, and renal and liver disease) contributed to severe COVID-19 and/or 30-day all-cause mortality. Non-central nervous system bleeding was an additional risk factor for poor outcomes in PwH. Odds of developing VTE with COVID-19 in PwH were associated with pre-COVID VTE diagnosis (odds ratio [OR], 51.9; 95% CI, 12.8-266; p < .001), anticoagulation therapy (OR, 12.7; 95% CI, 3.01-48.6; p < .001), and pulmonary disease (OR, 16.1; 95% CI, 10.4-25.4; p < .001). Thirty-day all-cause mortality (OR, 1.27; 95% CI, 0.75-2.11; p = .3) and VTE events (OR, 1.32; 95% CI, 0.64-2.73; p = .4) were not significantly different between the matched cohorts; however, hospitalizations (OR, 1.58; 95% CI, 1.20-2.10; p = .001) and non-central nervous system bleeding events (OR, 4.78; 95% CI, 2.98-7.48; p < .001) were increased in PwH. In multivariate analyses, hemophilia did not reduce adverse outcomes (OR, 1.32; 95% CI, 0.74-2.31; p = .2) or VTE (OR, 1.14; 95% CI, 0.44-2.67; p = .8) but increased bleeding risk (OR, 4.70; 95% CI, 2.98-7.48; p < .001).

CONCLUSION

After adjusting for patient characteristics/comorbidities, hemophilia increased bleeding risk with COVID-19 but did not protect against severe disease and VTE.

Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review

The explosive growth of biomedical Big Data presents both significant opportunities and challenges in the realm of knowledge discovery and translational applications within precision medicine. Efficient management, analysis, and interpretation of big data can pave the way for groundbreaking advancements in precision medicine. However, the unprecedented strides in the automated collection of large-scale molecular and clinical data have also introduced formidable challenges in terms of data analysis and interpretation, necessitating the development of novel computational approaches. Some potential challenges include the curse of dimensionality, data heterogeneity, missing data, class imbalance, and scalability issues. This overview article focuses on the recent progress and breakthroughs in the application of big data within precision medicine. Key aspects are summarized, including content, data sources, technologies, tools, challenges, and existing gaps. Nine fields-Datawarehouse and data management, electronic medical record, biomedical imaging informatics, Artificial intelligence-aided surgical design and surgery optimization, omics data, health monitoring data, knowledge graph, public health informatics, and security and privacy-are discussed.

COVID-19 in Patients with Melanoma: A Single-Institution Study

We conducted a single-center, non-interventional retrospective study of melanoma patients with COVID-19 (1 March 2020 until 17 March 2023). The cohort was further divided into three groups according to the periods of SARS-CoV-2 variant dominance in Greece. We recorded demographics, comorbidities, vaccination data, cancer diagnosis/stage, types of systemic melanoma treatments, date of COVID-19 diagnosis and survival. We identified 121 patients. The vast majority (87.6%) had advanced disease (stages III or IV). A total of 80.1% of the patients were receiving immune checkpoint inhibitor-based therapies, 92.5% had asymptomatic/mild COVID-19 and 7.4% had moderate/severe/critical disease, while 83.5% contracted COVID-19 during the third period of the pandemic. Sixteen patients (13.2%) were hospitalized for COVID-19 with a median length of stay of 12 days (range: 1-55 days). Advanced age, heart failure, number of comorbidities (≤1 vs. >1), vaccination status and the time period of the infection correlated with more severe COVID-19, whereas only heart failure and time period were independently correlated with severity. The 30-day mortality rate after COVID-19 was 4.2%. With a median follow-up of 340 days post-COVID-19, 17.4% of patients were deceased. In this cohort of melanoma patients with COVID-19, the 30-day mortality rate was low. There was no association between melanoma stage, treatment receipt and type of treatment with COVID-19 severity.

Sample average treatment effect on the treated (SATT) analysis using counterfactual explanation identifies BMT and SARS-CoV-2 vaccination as protective risk factors associated with COVID-19 severity and survival in patients with multiple myeloma

Patients with multiple myeloma (MM), an age-dependent neoplasm of antibody-producing plasma cells, have compromised immune systems and might be at increased risk for severe COVID-19 outcomes. This study characterizes risk factors associated with clinical indicators of COVID-19 severity and all-cause mortality in myeloma patients utilizing NCATS' National COVID Cohort Collaborative (N3C) database. The N3C consortium is a large, centralized data resource representing the largest multi-center cohort of COVID-19 cases and controls nationwide (>16 million total patients, and >6 million confirmed COVID-19+ cases to date). Our cohort included myeloma patients (both inpatients and outpatients) within the N3C consortium who have been diagnosed with COVID-19 based on positive PCR or antigen tests or ICD-10-CM diagnosis code. The outcomes of interest include all-cause mortality (including discharge to hospice) during the index encounter and clinical indicators of severity (i.e., hospitalization/emergency department/ED visit, use of mechanical ventilation, or extracorporeal membrane oxygenation (ECMO)). Finally, causal inference analysis was performed using the Coarsened Exact Matching (CEM) and Propensity Score Matching (PSM) methods. As of 05/16/2022, the N3C consortium included 1,061,748 cancer patients, out of which 26,064 were MM patients (8,588 were COVID-19 positive). The mean age at COVID-19 diagnosis was 65.89 years, 46.8% were females, and 20.2% were of black race. 4.47% of patients died within 30 days of COVID-19 hospitalization. Overall, the survival probability was 90.7% across the course of the study. Multivariate logistic regression analysis showed histories of pulmonary and renal disease, dexamethasone, proteasome inhibitor/PI, immunomodulatory/IMiD therapies, and severe Charlson Comorbidity Index/CCI were significantly associated with higher risks of severe COVID-19 outcomes. Protective associations were observed with blood-or-marrow transplant/BMT and COVID-19 vaccination. Further, multivariate Cox proportional hazard analysis showed that high and moderate CCI levels, International Staging System (ISS) moderate or severe stage, and PI therapy were associated with worse survival, while BMT and COVID-19 vaccination were associated with lower risk of death. Finally, matched sample average treatment effect on the treated (SATT) confirmed the causal effect of BMT and vaccination status as top protective factors associated with COVID-19 risk among US patients suffering from multiple myeloma. To the best of our knowledge, this is the largest nationwide study on myeloma patients with COVID-19.

The evolving landscape of COVID-19 and post-COVID condition in patients with chronic lymphocytic leukemia: A study by ERIC, the European research initiative on CLL

In this retrospective international multicenter study, we describe the clinical characteristics and outcomes of patients with chronic lymphocytic leukemia (CLL) and related disorders (small lymphocytic lymphoma and high-count monoclonal B lymphocytosis) infected by SARS-CoV-2, including the development of post-COVID condition. Data from 1540 patients with CLL infected by SARS-CoV-2 from January 2020 to May 2022 were included in the analysis and assigned to four phases based on cases disposition and SARS-CoV-2 variants emergence. Post-COVID condition was defined according to the WHO criteria. Patients infected during the most recent phases of the pandemic, though carrying a higher comorbidity burden, were less often hospitalized, rarely needed intensive care unit admission, or died compared to patients infected during the initial phases. The 4-month overall survival (OS) improved through the phases, from 68% to 83%, p = .0015. Age, comorbidity, CLL-directed treatment, but not vaccination status, emerged as risk factors for mortality. Among survivors, 6.65% patients had a reinfection, usually milder than the initial one, and 16.5% developed post-COVID condition. The latter was characterized by fatigue, dyspnea, lasting cough, and impaired concentration. Infection severity was the only risk factor for developing post-COVID. The median time to resolution of the post-COVID condition was 4.7 months. OS in patients with CLL improved during the different phases of the pandemic, likely due to the improvement of prophylactic and therapeutic measures against SARS-CoV-2 as well as the emergence of milder variants. However, mortality remained relevant and a significant number of patients developed post-COVID conditions, warranting further investigations.

COVID-19 in cancer patients: The impact of vaccination on outcomes early in the pandemic

BACKGROUND

With the rapid evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the development of effective and safe vaccines was of utmost importance to protect vulnerable individuals, including cancer patients. Studies comparing the clinical outcomes of cancer patients with or without vaccination against coronavirus disease 2019 (COVID-19) have not demonstrated clear benefit. We aimed to determine the protective effects of COVID-19 vaccination by comparing vaccinated and unvaccinated cancer patients after the initial phase of vaccine roll-out and to identify risk factors associated with hospitalization, severe COVID-19, and 30-day COVID-19 attributable mortality.

METHODS

We performed a retrospective cohort study of cancer patients with COVID-19 diagnosed by polymerase chain reaction on nasal swabs between January 1, 2021 and July 30, 2021. Outcomes of interest included hospitalization, severe COVID-19, and 30-day COVID-19 attributable mortality. Univariate and multivariate analyses were performed to identify factors associated with clinical outcomes, using vaccination status as a variable of interest in all models.

RESULTS

Key risk factors, such as age ≥ 60 years; comorbidities including diabetes mellitus, heart failure, and lung diseases; and specific cancer types (leukemia and lymphoma) were independently associated with hospital admission for COVID-19, severe COVID-19, and 30-day COVID-19 attributable mortality in cancer patients regardless of their vaccination status. Vaccinated patients were protected against severe COVID-19 but with no impact on hospitalization or mortality due to COVID-19.

CONCLUSION

Our study highlights a significant benefit of COVID-19 vaccination for cancer patients-specifically its protection against severe COVID-19.

An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C)

Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both symbolic and statistical methods, as well as highlight the need for federated annotation and evaluation to resolve several pitfalls encountered in the course of these efforts.

Patient and carer experiences of lung cancer referral pathway in a regional health service: a qualitative study

BACKGROUND

Lung cancer referral pathways aim to reduce delays and improve referral patterns of people with suspected lung cancer.

AIM

As part of implementing a lung cancer referral pathway at a regional Australian hospital, this study aimed to explore the experiences and perceptions of people with lung cancer and their carers.

METHODS

In-depth interviews were used to elicit data for thematic analysis in this cross-sectional descriptive qualitative study. Patients with newly diagnosed lung cancer and their carers at a regional academic cancer centre were invited to participate in interviews. Five interviews were conducted face-to-face, and 14 interviews were conducted by telephone (as per interviewee preference). Interviews were audiorecorded, transcribed and qualitatively analysed. Descriptive phrases were used to generate initial inductive codes and themes.

RESULTS

Nineteen participants approached agreed to take part in the study. Factors that positively impacted the care experience were good communication, timeliness and patient advocacy and support. Improper communication, long waiting times for investigations and appointments, uncertainty about the process and inconsistent advice from providers negatively impacted the care experience. Participants preferred face-to-face or video-linked consultations over telephone consultations.

CONCLUSIONS

Understanding the experiences of rural and regional patients and carers with the lung cancer referral pathway is important to improve quality of care. Implementing changes to the referral pathway to improve patient and carer experiences needs to be an ongoing quality improvement exercise.

Coronavirus disease 2019 and lung cancer: where are we?

Oncology patients are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection due to hospital contact and an immunological system that can be compromised by antineoplastic therapy and supportive treatments. Certain similarities have been described in the physiopathology of coronavirus disease 2019 (COVID-19) and lung cancer (LC) that may explain the higher probability of these patients of developing a more serious disease with more frequent hospitalizations and even death, especially with the addition of smoking, cardiovascular and respiratory comorbidities, old age and corticosteroids use. Pre-existing lesions and cancer therapies change the normal architecture of the lungs, so diagnostic scales such as COVID-19 Reporting and Data System (CO-RADS) are of vital importance for a correct diagnosis and patient homogenization, with a high inter-observer correlation. Moreover, anticancer treatments have required an adaptation to reduce the number of visits to the hospital [hypofractionated radiotherapy (RT), larger intervals between chemotherapy cycles, delay in follow-up tests, among others]. In a way, this has also caused a delay in the diagnosis of new cancers. On the other hand, vaccination has had a positive impact on the mortality of these patients, who maintain a similar seroprevalence to the rest of the population, with a similar impact in mortality.

Clinical characteristics, racial inequities, and outcomes in patients with breast cancer and COVID-19: A COVID-19 and cancer consortium (CCC19) cohort study

Background

Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations.

Methods

This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity.

Results

1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32-1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70-6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83-12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63-3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20-2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66-3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89-22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status.

Conclusions

Using one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients.

Funding

This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication.

Clinical trial number

CCC19 registry is registered on ClinicalTrials.gov, NCT04354701.

Outcomes of breakthrough COVID-19 infections in patients with hematologic malignancies

Patients with hematologic malignancies have both an increased risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and higher morbidity/mortality. They have lower seroconversion rates after vaccination, potentially leading to inferior coronavirus disease 2019 (COVID-19) outcomes, despite vaccination. We consequently evaluated the clinical outcomes of COVID-19 infections in 243 vaccinated and 175 unvaccinated patients with hematologic malignancies. Hospitalization rates were lower in the vaccinated group when compared with the unvaccinated group (31.3% vs 52.6%). However, the rates of COVID-19-associated death were similar at 7.0% and 8.6% in vaccinated and unvaccinated patients, respectively. By univariate logistic regression, females, older patients, and individuals with higher modified Charlson Comorbidity Index scores were at a higher risk of death from COVID-19 infections. To account for the nonrandomized nature of COVID-19 vaccination status, a propensity score weighting approach was used. In the final propensity-weighted model, vaccination status was not significantly associated with the risk of death from COVID-19 infections but was associated with the risk of hospitalization. The predicted benefit of vaccination was an absolute decrease in the probability of death and hospitalization from COVID-19 infections by 2.3% and 22.9%, respectively. In conclusion, COVID-19 vaccination status in patients with hematologic malignancies was associated with a decreased risk of hospitalization but not associated with a decreased risk of death from COVID-19 infections in the pre-Omicron era. Protective strategies, in addition to immunization, are warranted in this vulnerable patient population.

The Disease Influenced Vaccine Acceptance Scale-Six (DIVAS-6): Validation of a Measure to Assess Disease-Related COVID-19 Vaccine Attitudes and Concerns

Patients with underlying comorbidities are particularly vulnerable to poor outcomes from SARS-CoV-2 infection. Despite the context-specific nature of vaccine hesitancy, there are currently no scales that incorporate disease or treatment-related hesitancy factors. We developed a six-item scale assessing disease-related COVID-19 vaccine attitudes and concerns (The Disease Influenced COVID-19 Vaccine Acceptance Scale-Six: DIVAS-6). A survey incorporating the DIVAS-6 was completed by 4683 participants with severe and/or chronic illness (3560 cancer; 842 diabetes; 281 multiple sclerosis (MS)). The survey included the Oxford COVID-19 Vaccine Hesitancy Scale, the Oxford COVID-19 Vaccine Confidence and Complacency Scale, demographic, disease-related, and vaccination status questions. The six items loaded onto two factors (disease complacency and vaccine vulnerability) using exploratory factor analysis and exploratory structural equation modeling. The two factors were internally consistent. Measurement invariance analysis showed the two factors displayed psychometric equivalence across the patient groups. Each factor significantly correlated with the two Oxford COVID-19 Vaccine scales, showing convergent validity. The summary score showed acceptable ability to discriminate vaccination status across diseases, with the total sample providing good-to-excellent discriminative ability. The DIVAS-6 has two factors measuring COVID-19 vaccine attitudes and concerns relating to potential complications of SARS-CoV-2 infection due to underlying disease (disease complacency) and vaccine-related impact on disease progression and treatment (vaccine vulnerability). This is the first validated scale to measure disease-related COVID-19 vaccine concerns and has been validated in people with cancer, diabetes, and MS. It is quick to administer and should assist with guiding information delivery about COVID-19 vaccination in medically vulnerable populations.

COVID-19 Vaccination in Patients With Cancer and Patients Receiving HSCT or CAR-T Therapy: Immune Response, Real-World Effectiveness, and Implications for the Future

Patients with cancer demonstrate an increased vulnerability for infection and severe disease by SARS-CoV-2, the causative agent of COVID-19. Risk factors for severe COVID-19 include comorbidities, uncontrolled disease, and current line of treatment. Although COVID-19 vaccines have afforded some level of protection against infection and severe disease among patients with solid tumors and hematologic malignancies, decreased immunogenicity and real-world effectiveness have been observed among this population compared with healthy individuals. Characterizing and understanding the immune response to increasing doses or differing schedules of COVID-19 vaccines among patients with cancer is important to inform clinical and public health practices. In this article, we review SARS-CoV-2 susceptibility and immune responses to COVID-19 vaccination in patients with solid tumors, hematologic malignancies, and those receiving hematopoietic stem cell transplant or chimeric-antigen receptor T-cell therapy.

The impact of COVID-19 on mortality, length of stay, and cost of care among patients with gastrointestinal malignancies: A propensity score-matched analysis

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the coronavirus 19 (COVID-19) pandemic have had a lasting impact on the care of cancer patients. The impact on patients with gastrointestinal (GI) malignancies remains incompletely understood. We aimed to assess the impact of COVID-19 on mortality, length of stay (LOS), and cost of care among patients with GI malignancies, and identify differences in outcomes based on primary tumor site.

METHODS

We analyzed discharge encounters collected from the National Inpatient Sample (NIS) between March 2020 and December 2020 using propensity score matching (PSM) and COVID-19 as the treatment effect.

RESULTS

Of the 87,684 patient discharges with GI malignancies, 1892 were positive for COVID-19 (C+) and eligible for matching in the PSM model. Following PSM analysis, C+ with GI tumors demonstrated increased incidence of mortality compared to their COVID-19-negative (C-) counterparts (21.3% vs. 11.9%, p < 0.001). C+ patients with colorectal cancer (CRC) had significantly higher mortality compared to those who were C- (40% vs. 24%; p = 0.035). In addition, C+ patients with GI tumors had a longer mean LOS (9.4 days vs. 6.9 days; p < 0.001) and increased cost of care ($26,048.29 vs. $21,625.2; p = 0.001) compared to C- patients. C+ patients also had higher odds of mortality secondary to myocardial infarction relative to C- patients (OR = 3.54, p = 0.001).

CONCLUSIONS

C+ patients with GI tumors face approximately double the odds of mortality, increased LOS, and increased cost of care compared to their C- counterparts. Outcome disparities were most pronounced among patients with CRC.

Updated COVID-19 clearance time among patients with cancer in the Delta and Omicron waves

BACKGROUND

COVID-19 infection delays therapy and in-person evaluation for oncology patients, but clinic clearance criteria are not clearly defined.

METHODS

We conducted a retrospective review of oncology patients with COVID-19 at a tertiary care center during the Delta and Omicron waves and compared clearance strategies.

RESULTS

Median clearance by two consecutive negative tests was 32.0 days (Interquartile Range [IQR] 22.0-42.5, n = 153) and was prolonged in hematologic malignancy versus solid tumors (35.0 days for hematologic malignancy, 27.5 days for solid tumors, p = 0.01) and in patients receiving B-cell depletion versus other therapies. Median clearance by single negative test was reduced to 23.0 days (IQR 16.0-33.0), with recurrent positive rate 25.4% in hematologic malignancy versus 10.6% in solid tumors (p = 0.02). Clearance by a predefined waiting period required 41 days until an 80% negative rate.

CONCLUSIONS

COVID-19 clearance remains prolonged in oncology patients. Single-negative test clearance can balance delays in care with risk of infection in patients with solid tumors.

Antiviral Treatment in Older Chinese Patient with SARS-CoV-2 and Influenza A Virus Co-Infection: A Case Series

Coronavirus disease 2019 (COVID-19) emergence in late 2019, and wide spread quickly in the world. In China, the COVID-19 epidemic situation entered a low level now. With the arrival of flu season, the number of patients with respiratory symptoms is increasing. We reported three cases of patients who co-infected with SARS-CoV-2 and influenza A virus (IAV), and they were all treated with nirmatrelvir-ritonavir (NMV/r) and baloxavir marboxil. Due to the overlapping clinical features between the two diseases, it is important to identified them and gave the antiviral therapy timely.

Influence of SARS-CoV-2 mRNA Vaccine Booster among Cancer Patients on Active Treatment Previously Immunized with Inactivated versus mRNA Vaccines: A Prospective Cohort Study

Cancer patients on chemotherapy have a lower immune response to SARS-CoV-2 vaccines. Therefore, through a prospective cohort study of patients with solid tumors receiving chemotherapy, we aimed to determine the immunogenicity of an mRNA vaccine booster (BNT162b2) among patients previously immunized with an inactivated (CoronaVac) or homologous (BNT162b2) SARS-CoV-2 vaccine. The primary outcome was the proportion of patients with anti-SARS-CoV-2 neutralizing antibody (NAb) seropositivity at 8-12 weeks post-booster. The secondary end points included IgG antibody (TAb) seropositivity and specific T-cell responses. A total of 109 patients were included. Eighty-four (77%) had heterologous vaccine schedules (two doses of CoronaVac followed by the BNT162b2 booster) and twenty-five had (23%) homologous vaccine schedules (three doses of BNT162b2). IgG antibody positivity for the homologous and heterologous regimen were 100% and 96% (p = 0.338), whereas NAb positivity reached 100% and 92% (p = 0.13), respectively. Absolute NAb positivity and Tab levels were associated with the homologous schedule (with a beta coefficient of 0.26 with p = 0.027 and a geometric mean ratio 1.41 with p = 0.044, respectively). Both the homologous and heterologous vaccine regimens elicited a strong humoral and cellular response after the BNT162b2 booster. The homologous regimen was associated with higher NAb positivity and Tab levels after adjusting for relevant covariates.

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.

COVID-19 in cancer patients: update from the joint analysis of the ESMO-CoCARE, BSMO, and PSMO international databases

BACKGROUND

COVID-19 has significantly affected patients with cancer and revealed unanticipated challenges in securing optimal cancer care across different disciplines. The European Society for Medical Oncology COVID-19 and CAncer REgistry (ESMO-CoCARE) is an international, real-world database, collecting data on the natural history, management, and outcomes of patients with cancer and SARS-CoV-2 infection.

METHODS

This is the 2nd CoCARE analysis, jointly with Belgian (Belgian Society of Medical Oncology, BSMO) and Portuguese (Portuguese Society of Medical Oncology, PSMO) registries, with data from January 2020 to December 2021. The aim is to identify significant prognostic factors for COVID-19 hospitalization and mortality (primary outcomes), as well as intensive care unit admission and overall survival (OS) (secondary outcomes). Subgroup analyses by pandemic phase and vaccination status were carried out.

RESULTS

The cohort includes 3294 patients (CoCARE: 2049; BSMO: 928, all hospitalized by eligibility criteria; PSMO: 317), diagnosed in four distinct pandemic phases (January to May 2020: 36%; June to September 2020: 9%; October 2020 to February 2021: 41%; March to December 2021: 12%). COVID-19 hospitalization rate was 54% (CoCARE/PSMO), ICU admission 14%, and COVID-19 mortality 22% (all data). At a 6-month median follow-up, 1013 deaths were recorded with 73% 3-month OS rate. No significant change was observed in COVID-19 mortality among hospitalized patients across the four pandemic phases (30%-33%). Hospitalizations and ICU admission decreased significantly (from 78% to 34% and 16% to 10%, respectively). Among 1522 patients with known vaccination status at COVID-19 diagnosis, 70% were non-vaccinated, 24% had incomplete vaccination, and 7% complete vaccination. Complete vaccination had a protective effect on hospitalization (odds ratio = 0.24; 95% confidence interval [0.14-0.38]), ICU admission (odds ratio = 0.29 [0.09-0.94]), and OS (hazard ratio = 0.39 [0.20-0.76]). In multivariable analyses, COVID-19 hospitalization was associated with patient/cancer characteristics, the first pandemic phase, the presence of COVID-19-related symptoms or inflammatory biomarkers, whereas COVID-19 mortality was significantly higher in symptomatic patients, males, older age, ethnicity other than Asian/Caucasian, Eastern Cooperative Oncology Group performance status ≥2, body mass index <25, hematological malignancy, progressive disease versus no evident disease, and advanced cancer stage.

CONCLUSIONS

The updated CoCARE analysis, jointly with BSMO and PSMO, highlights factors that significantly affect COVID-19 outcomes, providing actionable clues for further reducing mortality.

COVID-19 Outcomes in Patients with Cancer Receiving Immune Checkpoint Inhibitors: A Systematic Review

Introduction

Immune checkpoint inhibitors (ICIs) can cause inflammatory and immune-related adverse events (irAEs) that might worsen the course of COVID-19. We conducted a systematic review (PROSPERO ID: CRD42022307545) to evaluate the clinical course and complications of COVID-19 in patients with cancer receiving ICI.

Methods

We searched Medline and Embase through January 5, 2022. We included studies evaluating patients with cancer who received ICI and developed COVID-19. Outcomes included mortality, severe COVID-19, intensive care unit (ICU) and hospital admissions, irAEs, and serious adverse events. We pooled data with random effects meta-analysis.

Results

Twenty-five studies met study eligibility (n = 36,532 patients: 15,497 had COVID-19 and 3220 received ICI). Most studies (71.4%) had a high risk of comparability bias. There were no significant differences in mortality (relative risk [RR] 1.29; 95% CI 0.62-2.69), ICU admission (RR 1.20; 95% CI 0.71-2.00), and hospital admission (RR 0.91; 95% CI 0.79-1.06) when comparing patients treated with ICI with patients without cancer treatment. When pooling adjusted odds ratios (ORs), no statistically significant differences were observed in mortality (OR 0.95; 95% CI 0.57-1.60), severe COVID-19 (OR 1.05; 95% CI 0.45-2.46), or hospital admission (OR 2.02; 95% CI 0.96-4.27), when comparing patients treated with ICIs versus patients with cancer without ICI therapy. No significant differences were observed when comparing clinical outcomes in patients receiving ICIs versus patients receiving any of the other anticancer therapies.

Conclusion

Although current evidence is limited, COVID-19 clinical outcomes of patients with cancer receiving ICI therapy appear to be similar to those not receiving oncologic treatment or other cancer therapies.

Supportive Care for Patients With Myelodysplastic Syndromes

ABSTRACT

Myelodysplastic syndromes are a heterogeneous group of bone marrow disorders characterized by ineffective hematopoiesis, progressive cytopenias, and an innate capability of progressing to acute myeloid leukemia. The most common causes of morbidity and mortality are complications related to myelodysplastic syndromes rather than progression to acute myeloid leukemia. Although supportive care measures are applicable to all patients with myelodysplastic syndromes, they are especially essential in patients with lower-risk disease who have a better prognosis compared with their higher-risk counterparts and require longer-term monitoring of disease and treatment-related complications. In this review, we will address the most frequent complications and supportive care interventions used in patients with myelodysplastic syndromes, including transfusion support, management of iron overload, antimicrobial prophylaxis, important considerations in the era of COVID-19 (coronavirus infectious disease 2019), role of routine immunizations, and palliative care in the myelodysplastic syndrome population.

Clinical efficacy of the first two doses of anti-SARS-CoV-2 mRNA vaccines in solid cancer patients

INTRODUCTION

Cancer patients are frail individuals, thus the prevention of SARS-CoV-2 infection is essential. To date, vaccination is the most effective tool to prevent COVID-19. In a previous study, we evaluated the immunogenicity of two doses of mRNA-based vaccines (BNT162b2 or mRNA-1273) in solid cancer patients. We found that seroconversion rate in cancer patients without a previous exposure to SARS-CoV-2 was lower than in healthy controls (66.7% vs. 95%, p = 0.0020). The present study aimed to evaluate the clinical efficacy of the vaccination in the same population.

METHODS

This is a single-institution, prospective observational study. Data were collected through a predefined questionnaire through phone call in the period between the second and third vaccine dose. The primary objective was to describe the clinical efficacy of the vaccination, defined as the percentage of vaccinated subjects who did not develop symptomatic COVID-19 within 6 months after the second dose. The secondary objective was to describe the clinical features of patients who developed COVID-19.

RESULTS

From January to June 2021, 195 cancer patients were enrolled. Considering that 7 (3.59%) patients tested positive for SARS-CoV-2 and 5 developed symptomatic disease, the clinical efficacy of the vaccination was 97.4%. COVID-19 disease in most patients was mild and managed at home; only one hospitalization was recorded and no patient required hospitalization in the intensive care unit.

DISCUSSION

Our study suggests that increasing vaccination coverage, including booster doses, could improve the prevention of infection, hospitalization, serious illness, and death in the frail population of cancer patients.

Risk factors and outcomes of COVID-19 in adult patients with hematological malignancies: A single-center study showing lower than expected rates of hospitalization and mortality

BACKGROUND

Studies addressing coronavirus disease 2019 (COVID-19) in patients with hematological malignancies have reported mortality rates of up to 40%; however, included predominantly hospitalized patients.

METHODS

During the first year of the pandemic, we followed adult patients with hematological malignancies treated at a tertiary center in Jerusalem, Israel, who contracted COVID-19, with the aim of studying risk factors for adverse COVID-19-related outcomes. We used remote communication to track patients managed at home-isolation, and patient questioning to assess the source of COVID-19 infection, community versus nosocomial.

RESULTS

Our series included 183 patients, median age was 62.5 years, 72% had at least one comorbidity and 39% were receiving active antineoplastic treatment. Hospitalization, critical COVID-19, and mortality rates were 32%, 12.6%, and 9.8%, respectively, remarkably lower than previously reported. Age, multiple comorbidities, and active antineoplastic treatment were significantly associated with hospitalization due to COVID-19. Treatment with monoclonal antibodies was strongly associated with both hospitalization and critical COVID-19. In older (≥60) patients not receiving active antineoplastic treatment, mortality, and severe COVID-19 rates were comparable to those of the general Israeli population. We did not detect patients that contracted COVID-19 within the Hematology Division.

CONCLUSION

These findings are relevant for the future management of patients with hematological malignancies in COVID-19-affected regions.

COVID-19 in Adult Patients with Hematological Malignancies-Lessons Learned after Three Years of Pandemic

The COVID-19 pandemic is undoubtedly the most difficult health challenge of the 21st century with more than 600 million laboratory-confirmed SARS-CoV-2 infections and over 6.5 million deaths worldwide. The coronavirus pandemic contributed to rapid development of mRNA vaccines, which, along with new antiviral drugs, have been the subject of extensive research for many decades. Nevertheless, elderly, multi-morbid and immunocompromised patients continue to face a more severe clinical course and a higher risk of death from COVID-19, even now that the risk of COVID-19 in the general population is significantly reduced due to the introduction of global vaccination strategies. In this paper, we present the mechanisms of increased susceptibility to infectious complications and the evolution of the clinical course of COVID-19 in patients with hematological malignancies, taking into account the mutation of the virus and the introduction of vaccines and new antiviral drugs. We also present current recommendations for prophylactic and therapeutic management in patients with hematological malignancies.

Humoral response to mRNA-based COVID-19 vaccine and booster effect of a third dose in patients with mature T cell and NK-cell neoplasms

Patients with lymphoid malignancies have impaired humoral immunity caused by the disease itself and its treatment, placing them at risk for severe coronavirus disease-19 (COVID-19) and reduced response to vaccination. However, data for COVID-19 vaccine responses in patients with mature T cell and NK-cell neoplasms are very limited. In this study of 19 patients with mature T/NK-cell neoplasms, anti-severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike antibodies were measured at 3 months, 6 months, and 9 months after the second mRNA-based vaccination. At the time of the second and third vaccinations, 31.6% and 15.4% of the patients were receiving active treatment. All patients received the primary vaccine dose and the third vaccination rate was 68.4%. In patients with mature T/NK-cell neoplasms, both seroconversion rate (p < 0.01) and antibody titers (p < 0.01) after the second vaccination were significantly lower than those in healthy controls (HC). In individuals who received the booster dose, patients had significantly lower antibody titers than those in HC (p < 0.01); however, the seroconversion rate in patients was 100%, which was the same as that in HC. The booster vaccine resulted in a significant increase of antibodies in elderly patients who had shown a response that was inferior to that in younger patients after two doses of vaccination. Since higher antibody titers and higher seroconversion rate reduced the incidence of infection and mortality, vaccination more than three times may have the advantage for patients with mature T/NK-cell neoplasms, especially in elderly patients. Clinical trial registration number: UMIN 000,045,267 (August 26th, 2021), 000,048,764 (August 26th, 2022).

Cancer, more than a “COVID-19 co-morbidity”

Patients with cancer represent a particularly vulnerable population at risk of adverse outcomes related to COVID-19. Collectively, the initial studies, including patients with and without cancer, confirmed that patients with cancer had a higher risk of complications and death related to COVID-19. Subsequent studies on patients with COVID-19 and cancer investigated patient and disease-related factors associated with COVID-19 severity and morality. Multiple interconnected factors include demographics, comorbidities, cancer-associated variables, treatment side effects, and other parameters. However, there is a lack of clarity on the contributions of any one factor. In this commentary, we deconvolute the data of specific risk factors associated with worse outcomes due to COVID-19 in cancer patients and focus on understanding the recommended guidelines to mitigate COVID-19 risk in this vulnerable population. In the first section, we highlight the key parameters, including age and race, cancer status, type of malignancy, cancer therapy, smoking status and comorbidities that impact outcomes for cancer patients with COVID-19. Next, we discuss efforts made at the patient, health system, and population levels to mitigate the effects of the ongoing outbreak for patients with cancer, including (1) screening, barrier and isolation strategies (2), Masking/PPE (3), vaccination, and (4) systemic therapies (e.g., evusheld) to prevent disease onset in patients. In the last section, we discuss optimal treatment strategies for COVID-19, including additional therapies for patients with COVID-19 and cancer. Overall, this commentary focuses on articles with high yield and impact on understanding the evolving evidence of risk factors and management guidelines in detail. We also emphasize the ongoing collaboration between clinicians, researchers, health system administrators and policymakers and how its role will be important in optimizing care delivery strategies for patients with cancer. Creative patient-centered solutions will be critical in the coming years, post the pandemic.

Clinical Characteristics, Racial Inequities, and Outcomes in Patients with Breast Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Cohort Study

Background

Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations.

Methods

This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity.

Results

1,383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32 - 1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70 - 6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83 - 12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63 - 3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20 - 2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66 - 3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89 - 22.6]). Hispanic ethnicity, timing and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status.

Conclusions

Using one of the largest registries on cancer and COVID-19, we identified patient and BC related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to Non-Hispanic White patients.

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types.

Risk of Underlying Diseases and Effectiveness of Drugs on COVID-19 Inpatients Assessed Using Medical Claims in Japan: Retrospective Observational Study

Background

Results of earlier studies have demonstrated underlying diseases such as cancer, diabetes mellitus, immunodeficiency, hypertension and heart failure to be risk factors for severe outcomes and mortality. Furthermore, clinical trials have shown that drugs such as antiviral drugs, antibody cocktails, steroids and anti-inflammatory drugs can be expected to prevent severe COVID-19 outcomes and death.

Methods

This study, using inpatient records from the Medical Information Analysis Databank covering national hospital organizations in Japan, was conducted to evaluate the effects of underlying diseases and/or administered drugs on mortality. Subjects were all inpatients receiving oxygen administration and inpatients using respiratory ventilators, categorized by three age classes: all ages, patients 65 years old or older, and patients younger than 65 years old. We used logistic regression to analyze outcomes for underlying diseases, administered drugs, age, sex, the proportion of the mutated strains, and vaccine coverage.

Results

Patients with hypertension, except for younger inpatients, have a lower risk of mortality (estimated coefficient 0.67 among all inpatients (p < 0.01): 0.77 among inpatients with oxygen therapy (p = 0.02) and 0.57 among inpatients with respiratory ventilation w (p = 0.01)). Except for younger inpatients, antibody cocktail (casirivimab/imdevimab or sotrovimab) administration was associated with a higher probability of survival (estimated coefficient 0.27 among all inpatients (p < 0.01)). It raised the survival probability consistently, although other drugs might have reduced the probability of survival.

Conclusion

These findings suggest that antiviral drugs (remdesivir, estimated coefficient 1.44 (p < 0.01)), steroids (dexamethasone, estimated coefficient 1.85 (p < 0.01)), and anti-inflammatory drugs (baricitinib, estimated coefficient 1.62 (p < 0.01), and tocilizumab, estimated coefficient 2.73 (p < 0.01)) might not contribute to survival. These results have not been reported from earlier studies. More sophisticated estimation procedures, such as treatment effect models, are necessary to obtain conclusive results.

Clinical Characteristics and Cause of Death Among Hospitalized Decedents With Cancer and COVID-19

There is scant information on the clinical progression, end-of-life decisions, and cause of death of patients with cancer diagnosed with COVID-19. Therefore, we conducted a case series of patients admitted to a comprehensive cancer center who did not survive their hospitalization. To determine the cause of death, 3 board-certified intensivists reviewed the electronic medical records. Concordance regarding cause of death was calculated. Discrepancies were resolved through a joint case-by-case review and discussion among the 3 reviewers. During the study period, 551 patients with cancer and COVID-19 were admitted to a dedicated specialty unit; among them, 61 (11.6%) were nonsurvivors. Among nonsurvivors, 31 (51%) patients had hematologic cancers, and 29 (48%) had undergone cancer-directed chemotherapy within 3 months before admission. The median time to death was 15 days (95% confidence interval [CI], 11.8 to 18.2). There were no differences in time to death by cancer category or cancer treatment intent. The majority of decedents (84%) had full code status at admission; however, 53 (87%) had do-not-resuscitate orders at the time of death. Most deaths were deemed to be COVID-19 related (88.5%). The concordance between the reviewers for the cause of death was 78.7%. In contrast to the belief that COVID-19 decedents die because of their comorbidities, in our study only 1 of every 10 patients died of cancer-related causes. Full-scale interventions were offered to all patients irrespective of oncologic treatment intent. However, most decedents in this population preferred care with nonresuscitative measures rather than full support at the end of life.

Response to COVID-19 vaccination post CAR T therapy in patients with non-Hodgkin lymphoma and multiple myeloma

COVID-19 adversely affects individuals with cancer. Several studies have found that seroconversion rates among patients with hematologic malignancies are suboptimal when compared to patients without cancer. Patients with non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) are immunocompromised due to impaired humoral and cellular immunity in addition to prescribed immunosuppressive therapy. Chimeric antigen receptor T-cell (CAR T) therapy is now widely used for NHL and MM, but little is known about seroconversion rates after COVID-19 vaccination among these populations. We evaluated SARS-CoV-2 spike-binding IgG antibody levels following COVID-19 vaccination among NHL and MM CAR T therapy recipients. Out of 104 CAR T infusions, 19 patients developed known COVID-19 infection post-CAR T. We tested 17 patients that received CAR T for antibody spike titers post COVID-19 vaccination, only 29 % (n = 5) were able to mount a clinically relevant antibody response (>250 IU/mL).

Impact of COVID-19 Pandemic on Frontline Pembrolizumab-Based Treatment for Advanced Lung Cancer

BACKGROUND

Pembrolizumab monotherapy or pembrolizumab plus chemotherapy has become an important frontline treatment for advanced non-small cell lung cancer (NSCLC). To date, it remains unclear how the coronavirus disease 2019 (COVID-19) pandemic impacted the treatment outcome.

METHODS

A quasi-experimental study was conducted based on a real-world database, comparing pandemic with pre-pandemic patient cohorts. The pandemic cohort consisted of patients who initiated treatment from March to July 2020, with follow-up through March 2021. The pre-pandemic cohort consisted of those initiating treatment between March and July 2019.The outcome was overall real-world survival. Multivariable Cox-proportional hazard models were constructed.

RESULTS

Analyses included data from 2090 patients: 998 in the pandemic cohort and 1092 in the pre-pandemic cohort. Baseline characteristics were comparable, with 33% of patients having PD-L1 expression level ≥50% and 29% of patients receiving pembrolizumab monotherapy. Among those treated with pembrolizumab monotherapy (N = 613), there was a differential impact of the pandemic on survival by PD-L1 expression levels (p-interaction = 0.02). For those with PD-L1 level < 50%, survival was better in the pandemic cohort than the pre-pandemic cohort: hazard ratio (HR) 0.64 (95% CI: 0.43-0.97, p = 0.03). However, for those with PD-L1 level ≥ 50%, survival was not better in the pandemic cohort: HR 1.17 (95% CI: 0.85-1.61, p = 0.34). We found no statistically significant impact of the pandemic on survival among patients treated with pembrolizumab plus chemotherapy.

CONCLUSIONS

The COVID-19 pandemic was associated with an increase in survival among patients with lower PD-L1 expression who were treated with pembrolizumab monotherapy. This finding suggests an increased efficacy of immunotherapy due to viral exposure in this population.

Anticancer Therapy and Mortality of Adult Patients with Hematologic Malignancy and COVID-19: A Systematic Review and Meta-Analysis

Coronavirus disease 2019 (COVID-19) might affect cancer treatment outcomes. This systematic review and meta-analysis identified the prognostic predictors of adult patients with hematologic malignancies and COVID-19, and evaluated the effect of anticancer therapy on mortality. We performed a literature search of electronic databases and identified additional studies from the bibliographies of the articles that were retrieved. Two investigators independently extracted data according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. We evaluated study quality using the Newcastle-Ottawa Scale and performed a meta-analyses in order to evaluate the effect of anticancer therapy on mortality among adult patients with hematologic malignancies and COVID-19. Heterogeneity was assessed with the I² statistic. The meta-analysis included 12 studies. The overall mortality rate was 36.3%. The pooled risk difference (RD) in mortality between patients receiving and not receiving anticancer therapy was 0.14 (95% confidence interval [CI]: 0.02-0.26; I² = 76%). The pooled RD in mortality associated with chemotherapy was 0.22 (95% CI: 0.05-0.39; I² = 48%), and with immunosuppression was 0.20 (95% CI: 0.05-0.34; I² = 67%). In the subgroup analyses, anticancer-therapy-associated mortality was higher in females (RD = 0.57; 95% CI: 0.29-0.85; I² = 0%) than in males (RD = 0.28; 95% CI: 0.04-0.52; I² = 0%). Among patients with hematologic malignancies and COVID-19, those receiving anticancer therapy had a higher mortality risk, regardless of sex. The mortality risk was higher in females than in males. These results indicate that caution should be exercised when administering anticancer therapy to patients with hematologic malignancies and COVID-19.

Relations of Current and Past Cancer with Severe Outcomes among 104,590 Hospitalized COVID-19 Patients: The COVID EHR Cohort at the University of Wisconsin

BACKGROUND

There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics.

METHODS

Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined.

RESULTS

6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90).

CONCLUSIONS

Current cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types.

IMPACT

This study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3.

SARS-CoV-2 infection in patients with melanoma: results of the Spanish Melanoma Group registry

BACKGROUND

The Spanish Melanoma Group (GEM) developed a national registry of patients with melanoma infected by SARS-CoV-2 ("GRAVID").

METHODS

The main objective was to describe the COVID-19 fatality rate in patients with melanoma throughout the pandemic, as well as to explore the effect of melanoma treatment and tumor stage on the risk of COVID-19 complications. These are the final data of the register, including cases from February 2020 to September 2021.

RESULTS

One hundred-fifty cases were registered. Median age was 68 years (range 6-95), 61 (40%) patients were females, and 63 (42%) patients had stage IV. Thirty-nine (26%) were on treatment with immunotherapy, and 17 (11%) with BRAF-MEK inhibitors. COVID-19 was resolved in 119 cases, including 85 (57%) patients cured, 15 (10%) that died due to melanoma, and 20 (13%) that died due to COVID-19. Only age over 60 years, cardiovascular disorders, and diabetes mellitus increased the risk of death due to COVID-19, but not advanced melanoma stage nor melanoma systemic therapies. Three waves have been covered by the register: February-May 2020, August-November 2020, and December 2020-April 2021. The first wave had the highest number of registered cases and COVID-19 mortality.

CONCLUSION

Tumor stage or melanoma treatments are non-significant prognostic factors for COVID-19 mortality. During the pandemic in Spain there was a downward trend in the number of patients registered across the waves, as well as in the severity of the infection.

CLINICALTRIALS

GOV IDENTIFIER

NCT04344002.

Physical Therapy for a Multiple Myeloma Patient with COVID-19: A Case Report

Background

This case report describes the successful management of rehabilitation therapy for a hematological malignancy patient who was receiving chemotherapy and had coronavirus disease 2019 (COVID-19).

Case

A 76-year-old man receiving chemotherapy for relapsed refractory multiple myeloma (MM) presented to our hospital with fever and dyspnea and was hospitalized with a diagnosis of COVID-19. Physical therapy (20 min/day, 5 days/week) was started on day 6 of hospitalization while the patient was receiving oxygen therapy. Conditioning exercises and movement exercises were performed in an isolation room, and blood counts, fracture susceptibility, and respiratory status were monitored. The patient was severely immunocompromised and required 34 days of isolation due to persistent severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) infection. Physical function was assessed by manual muscle testing of the lower extremities and by the extent of lower extremity fatigue and dyspnea on exertion, as assessed using the Borg scale. Motor capacity was assessed using the de Morton Mobility Index (DEMMI) score and the Barthel Index (BI). Muscle weakness and severe dyspnea developed 4 days after physical therapy was started. However, physical therapy led to improvements in DEMMI score and BI. The patient was discharged home on day 43 with home medical care.

Discussion

Careful management of MM and COVID-19 facilitated safe treatment with physical therapy. The patient's physical function improved with a carefully planned physical therapy program. Moreover, the patient required prolonged isolation due to persistent viral shedding; however, as a result of the treatment, which was coordinated between physicians and nurses, the patient could be discharged home.

COVID-19 Emotional and Mental Impact on Cancer Patients Receiving Radiotherapy: An Interpretation of Potential Explaining Descriptors

Background: Significant changes in the accessibility and viability of health services have been observed during the COVID-19 period, particularly in vulnerable groups such as cancer patients. In this study, we described the impact of radical practice and perceived changes on cancer patients’ mental well-being and investigated potential outcome descriptors. Methods: Generalized anxiety disorder assessment (GAD-7), patient health (PHQ-9), and World Health Organization-five well-being index (WHO-5) questionnaires were used to assess anxiety, depression, and mental well-being. Information on participants, disease baseline information, and COVID-19-related questions were collected, and related explanatory variables were included for statistical analysis. Results: The mean score values for anxiety, depression, and mental well-being were 4.7 ± 5.53, 4.9 ± 6.42, and 72.2 ± 18.53, respectively. GAD-7 and PHQ-9 scores were statistically associated (p < 0.001), while high values of GAD-7 and PHQ-9 questionnaires were related to low values of WHO-5 (p < 0.001).Using the GAD-7 scale, 16.2% of participants were classified as having mild anxiety (GAD-7 score: 5−9).Mild to more severe anxiety was significantly associated with a history of mental health conditions (p = 0.01, OR = 3.74, 95% CI [1.372−10.21]), and stage category (stage III/IV vs. I/II, p = 0.01, OR = 3.83, 95% CI [1.38−10.64]. From the participants, 36.2% were considered to have depression (PHQ-9 score ≥ 5). Depression was related with older patients (p = 0.05, OR = 1.63, 95% CI [1.16−2.3]), those with previous mental health conditions (p = 0.03, OR = 14.24, 95% CI [2.47−81.84]), those concerned about the COVID-19 impact on their cancer treatment (p = 0.027, OR = 0.19, 95% CI [0.045−0.82]) or those who felt that COVID-19 pandemic has affected mental health (p = 0.013, OR = 3.56, 95% CI [1.30−9.72]). Additionally, most participants (86.7%) had a good well-being score (WHO-5 score ≥ 50). Mental well-being seemed more reduced among stage I−III patients than stage IV patients (p = 0.014, OR = 0.12, 95% CI [0.023−0.65]). Conclusion: There is a necessity for comprehensive cancer care improvement. These patients’ main concern related to cancer therapy, yet the group of patients who were mentally affected by the pandemic should be identified and supported.