Association between recent oncologic treatment and mortality among patients with carcinoma who are hospitalized with COVID-19: A multicenter study

Impact of plasma Epstein-Barr virus DNA in posttreatment nasopharyngeal carcinoma patients after SARS-CoV-2 infection

BACKGROUND

Nasopharyngeal carcinoma (NPC) is prevalent in southern China. EBV DNA is the most useful biomarker in NPC. However, the value of EBV DNA in posttreatment NPC patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains unclear.

METHODS

Sixty-four eligible NPC patients were enrolled between December 2022 and February 2023. Patients who met the following criteria were included: had non-metastatic NPC, completed radical treatment, were first firstly infected with SARS-CoV-2 and their EBV DNA changed from undetectable to detectable.

RESULTS

At the end of follow-up, 81.25% (52/64) of patients were confirmed not to relapse with undetectable EBV DNA (no-relapse). In addition, 18.75% (12/64) of patients experienced relapse with consistent detection of EBV DNA (yes-relapse). For all 64 patients, the average time from diagnosis of coronavirus disease 2019 (COVID-19) to detection of detectable EBV DNA was 35.41 days (2 to 139 days). For 52 no-relapse patients, the average time from EBV DNA changing from detectable to undetectable was 63.12 days (6 to 147 days). The levels of EBV DNA were greater in yes-relapse patients than that in no-relapse patients, and the average of EBV DNA levels were 1216 copies/ml and 53.18 copies/ml, respectively. Using 62.3 copies/mL as the threshold, the area under the curve for EBV DNA was 0.88 for distinguishing yes-relapse patients from no-relapse patients. The sensitivity and specificity were 81.97% (95% CI 0.71-0.95) and 86.67% (95% CI 0.70-0.95), respectively.

CONCLUSION

For NPC patients infected with SARS-CoV-2, EBV DNA alone is insufficient for monitoring relapse after radical therapy. Long-term follow-up and underlying mechanistic investigations of EBV DNA changes are urgently needed.

Risk factors for mortality among lung cancer patients with covid-19 infection: A systematic review and meta-analysis

BACKGROUND

Lung cancer patients with coronavirus disease 2019 (COVID-19) infection experience high mortality rates. The study aims to determine the risk factors for mortality in lung cancer patients with COVID-19 infection.

MATERIALS AND METHODS

Followed the PRISMA reporting guidelines, PubMed, Embase, and Web of Science were systematically searched to February 20, 2023, for studies of lung cancer patients with COVID-19 infection. The main outcome of interest was the risk factor for mortality. We also compared the mortality rate of those patients among different continents. A pooled risk ratio (RR) with 95% CI was presented as the result of this meta-analysis.

RESULTS

Meta-analysis of 33 studies involving 5018 patients showed that pooled mortality rate of lung cancer in COVID-19 patients was 0.31 (95% CI: 0.25-0.36). Subgroup analysis based on the continents showed significant difference of the mortality rate was observed between Asia and the rest of world (χ2 = 98.96, P < 0.01). Older age (SMD: 0.24, 95% CI: 0.09-0.40, P < 0.01), advanced lung cancer (RR: 1.14, 95% CI: 1.04-1.26, P < 0.01), coexisting comorbidities such as hypertension (RR: 1.17, 95% CI: 1.01-1.35, P = 0.04) and cardiovascular disease (RR: 1.40, 95% CI: 1.03-1.91, P = 0.03) were associated with higher risk of mortality rate in those patients.

CONCLUSIONS

Findings of this meta-analysis confirms an increased risk of mortality in lung cancer patients with COVID-19 infection, whose risk factors for these patients appear to be exacerbated by older age, advanced-stage lung cancer, and comorbidities such as hypertension and cardiovascular disease.

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.

Modifiable contributing factors to COVID-19: A comprehensive review

The devastating complications of coronavirus disease 2019 (COVID-19) result from an individual's dysfunctional immune response following the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Multiple toxic stressors and behaviors contribute to underlying immune system dysfunction. SARS-CoV-2 exploits the dysfunctional immune system to trigger a chain of events ultimately leading to COVID-19. The current study identifies eighty immune system dysfunction-enabling toxic stressors and behaviors (hereafter called modifiable contributing factors (CFs)) that also link directly to COVID-19. Each CF is assigned to one of the five categories in the CF taxonomy shown in Section 3.3.: Lifestyle (e.g., diet, substance abuse); Iatrogenic (e.g., drugs, surgery); Biotoxins (e.g., micro-organisms, mycotoxins); Occupational/Environmental (e.g., heavy metals, pesticides); Psychosocial/Socioeconomic (e.g., chronic stress, lower education). The current study shows how each modifiable factor contributes to decreased immune system capability, increased inflammation and coagulation, and increased neural damage and neurodegeneration. It is unclear how real progress can be made in combatting COVID-19 and other similar diseases caused by viral variants without addressing and eliminating these modifiable CFs.

COVID-19 and Lung Cancer Survival: An Updated Systematic Review and Meta-Analysis

Introduction: The outbreak of COVID-19 poses an unprecedented challenge to global public health. Patients with cancer are at a higher risk during the SARS-CoV-2 pandemic. Patients with lung cancer and COVID-19 were compared to those without cancer and those with other malignancies for the main outcome of this study. The aim of this study was to evaluate the differences in susceptibility, disease severity, and mortality between lung cancer patients and the general population. Methods: Using PRISMA reporting guidelines, we conducted a systematic review and meta-analysis of the published literature. The Cochrane Library database, PubMed, EMBASE, and PubMed Central were comprehensively searched for published papers until 31 May 2022. A pooled risk ratio (OR) with 95% CI was presented as the result of this meta-analysis. Results: We included 29 studies involved 21,257 patients with lung cancer and SARS-CoV-2 infection. Analysis data showed that mortality in patients with lung cancer was significantly higher than that in patients without cancer (HR = 2.00 [95%CI 1.52, 2.63], p < 0.01) or with other malignancies (HR = 1.91 [95%CI 1.53, 2.39], p < 0.01). In addition, we also observed a higher risk of severe infection in terms of life-threatening or required ICU admission/mechanical ventilation for lung cancer patients (HR = 1.47 [95%CI 1.06, 2.03], p = 0.02) than for patients with no cancer or other malignancies. Regarding lung cancer as a risk factor for acquiring SARS-CoV-2 infection, we could not reach statistical significance (hazard ratio [HR] =2.73 [95%CI 0.84, 8.94], p = 0.1). Conclusion: Lung cancer represents an important comorbidity and modifies COVID-19 prognosis in terms of disease severity and mortality. More patients experience severe or even fatal events. Considering their inherent fragility, patients with lung cancer, and generally all oncological populations, should be treated more carefully during the COVID-19 pandemic.

Challenges posed by COVID-19 in cancer patients: A narrative review

A novel coronavirus, or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the causative agent of coronavirus disease 2019 (COVID-19). In early 2020, the World Health Organization declared COVID-19 the sixth public health emergency of international concern. The COVID-19 pandemic has substantially affected many groups within the general population, but particularly those with extant clinical conditions, such as having or being treated for cancer. Cancer patients are at a higher risk of developing severe COVID-19 since the malignancy and chemotherapy may negatively affect the immune system, and their immunocompromised condition also increases the risk of infection. Substantial international efforts are currently underway to develop specific methods for diagnosing and treating COVID-19. However, cancer patients' risk profiles, management, and outcomes are not well understood. Thus, the main objective of this review is to discuss the relevant evidence to understand the prognosis of COVID-19 infections in cancer patients more clearly, as well as helping to improve the clinical management of these patients.

Coronavirus disease 2019 in immunocompromised patients: a comprehensive review of coronavirus disease 2019 in hematopoietic stem cell recipients

PURPOSE OF REVIEW

Immunocompromised patients are notably vulnerable to severe coronavirus disease 2019. This review summarizes COVID-19 features and outcomes in autologous and allogeneic hematopoietic stem cell transplantation (HSCT) recipients.

RECENT FINDINGS

Recent findings suggest that HSCT recipients exhibit a high burden of comorbidities and COVID-19 clinical features almost similar to the general COVID population. Furthermore, HSCT recipients exhibit a protracted SARS-CoV-2 shedding, prolonging duration of symptoms and promoting the generation of highly mutated viruses. Last, most of studies report a higher COVID-19 mortality in HSCT recipients, mainly driven by age, comorbidities, time from transplantation, and immunosuppression because of both treatments and underlying hematological malignancy.

SUMMARY

Further studies are warranted to determine the proper impact of HSCT-related immune disorders on COVID-19 outcomes, and to evaluate specific treatments and vaccination strategy in this high-risk population. Taken together, those findings emphasize the need for more rigorous surveillance and preemptive measures for all HSCT recipients.

Machine Learning to Calculate Heparin Dose in COVID-19 Patients with Active Cancer

To realize a machine learning (ML) model to estimate the dose of low molecular weight heparin to be administered, preventing thromboembolism events in COVID-19 patients with active cancer. Methods: We used a dataset comprising 131 patients with active cancer and COVID-19. We considered five ML models: logistic regression, decision tree, random forest, support vector machine and Gaussian naive Bayes. We decided to implement the logistic regression model for our study. A model with 19 variables was analyzed. Data were randomly split into training (70%) and testing (30%) sets. Model performance was assessed by confusion matrix metrics on the testing data for each model as positive predictive value, sensitivity and F1-score. Results: We showed that the five selected models outperformed classical statistical methods of predictive validity and logistic regression was the most effective, being able to classify with an accuracy of 81%. The most relevant result was finding a patient-proof where python function was able to obtain the exact dose of low weight molecular heparin to be administered and thereby to prevent the occurrence of VTE. Conclusions: The world of machine learning and artificial intelligence is constantly developing. The identification of a specific LMWH dose for preventing VTE in very high-risk populations, such as the COVID-19 and active cancer population, might improve with the use of new training ML-based algorithms. Larger studies are needed to confirm our exploratory results.

Contributing factors common to COVID‑19 and gastrointestinal cancer

The devastating complications of coronavirus disease 2019 (COVID-19) result from the dysfunctional immune response of an individual following the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Multiple toxic stressors and behaviors contribute to underlying immune system dysfunction. SARS-CoV-2 exploits the dysfunctional immune system to trigger a chain of events, ultimately leading to COVID-19. The authors have previously identified a number of contributing factors (CFs) common to myriad chronic diseases. Based on these observations, it was hypothesized that there may be a significant overlap between CFs associated with COVID-19 and gastrointestinal cancer (GIC). Thus, in the present study, a streamlined dot-product approach was used initially to identify potential CFs that affect COVID-19 and GIC directly (i.e., the simultaneous occurrence of CFs and disease in the same article). The nascent character of the COVID-19 core literature (~1-year-old) did not allow sufficient time for the direct effects of numerous CFs on COVID-19 to emerge from laboratory experiments and epidemiological studies. Therefore, a literature-related discovery approach was used to augment the COVID-19 core literature-based ‘direct impact’ CFs with discovery-based ‘indirect impact’ CFs [CFs were identified in the non-COVID-19 biomedical literature that had the same biomarker impact pattern (e.g., hyperinflammation, hypercoagulation, hypoxia, etc.) as was shown in the COVID-19 literature]. Approximately 2,250 candidate direct impact CFs in common between GIC and COVID-19 were identified, albeit some being variants of the same concept. As commonality proof of concept, 75 potential CFs that appeared promising were selected, and 63 overlapping COVID-19/GIC potential/candidate CFs were validated with biological plausibility. In total, 42 of the 63 were overlapping direct impact COVID-19/GIC CFs, and the remaining 21 were candidate GIC CFs that overlapped with indirect impact COVID-19 CFs. On the whole, the present study demonstrates that COVID-19 and GIC share a number of common risk/CFs, including behaviors and toxic exposures, that impair immune function. A key component of immune system health is the removal of those factors that contribute to immune system dysfunction in the first place. This requires a paradigm shift from traditional Western medicine, which often focuses on treatment, rather than prevention.

Clinical Characteristics of Cancer Patients With COVID-19: A Retrospective Multicentric Study in 19 Hospitals Within Hubei, China

Objective: This study aimed to determine the association between prognosis of COVID-19 patients with and without cancer. Moreover, we compared the prognosis of cancer patients subjected to anti-tumor therapy with those who have not undergone anti-tumor therapy in the past 6 months.

Methods and Results: A total of 7,926 adult patients with COVID-19 were retrospectively enrolled in Hubei Province,China between December 31, 2019 and February 20, 2020. Two hundred and seventy seven cancer patients (cancer group, median age 64 [IQR 56–70] years; 50.90% male) and 7,649 non-cancer patients were identified (non-cancer group, median age 55 [IQR 42–64] years; 48.19% male). The mortality rate was lower in the non-cancer group compared to the cancer group (4.50 vs. 9.03%; P < 0.001). The duration between onset and admission shorter in the cancer group (Days, 9 [IQR 5–18]) compared to the non-cancer group (Days, 10; [IQR 6–19]; P = 0.036). ICU occupancy was higher in the cancer group (n[%], 30[10.83%]) than in the non-cancer group (n[%], 314[4.11%]). In reviewing the anti-tumor therapy, data from 277 selected cancer patients were obtained out of which 74 patients had undergone anti-tumor therapy (mean age 65 [IQR 51–67] years; 45.95% male), 203 had not undergone anti-tumor therapy (non-anti-tumor therapy group, mean age 63 [IQR 53–75] years; 49.75% male) in the past 6 months. The mortality rate for the anti-tumor therapy group and the non-anti-tumor therapy group was similar (9.46 vs. 8.87%; P = 0.879).

Conclusion: The mortality rate was higher in COVID-19 patients with cancer compared to those without cancer. Moreover, anti-tumor therapy in the past 6 months did not worsen the prognosis of cancer patients with COVID-19.

Common contributing factors to COVID-19 and inflammatory bowel disease

The devastating complications of coronavirus disease 2019 (COVID-19) result from an individual's dysfunctional immune response following the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Multiple toxic stressors and behaviors contribute to underlying immune system dysfunction. SARS-CoV-2 exploits the dysfunctional immune system to trigger a chain of events ultimately leading to COVID-19. We have previously identified many contributing factors (CFs) (representing toxic exposure, lifestyle factors and psychosocial stressors) common to myriad chronic diseases. We hypothesized significant overlap between CFs associated with COVID-19 and inflammatory bowel disease (IBD), because of the strong role immune dysfunction plays in each disease. A streamlined dot-product approach was used to identify potential CFs to COVID-19 and IBD. Of the fifty CFs to COVID-19 that were validated for demonstration purposes, approximately half had direct impact on COVID-19 (the CF and COVID-19 were mentioned in the same record; i.e., CF---→COVID-19), and the other half had indirect impact. The nascent character of the COVID-19 core literature (∼ one year old) did not allow sufficient time for the direct impacts of many CFs on COVID-19 to be identified. Therefore, an immune system dysfunction (ID) literature directly related to the COVID-19 core literature was used to augment the COVID-19 core literature and provide the remaining CFs that impacted COVID-19 indirectly (i.e., CF---→immune system dysfunction---→COVID-19). Approximately 13000 potential CFs for myriad diseases (obtained from government and university toxic substance lists) served as the starting point for the dot-product identification process. These phrases were intersected (dot-product) with phrases extracted from a PubMed-derived IBD core literature, a nascent COVID-19 core literature, and the COVID-19-related immune system dysfunction (ID) core literature to identify common ID/COVID-19 and IBD CFs. Approximately 3000 potential CFs common to both ID and IBD, almost 2300 potential CFs common to ID and COVID-19, and over 1900 potential CFs common to IBD and COVID-19 were identified. As proof of concept, we validated fifty of these ∼3000 overlapping ID/IBD candidate CFs with biologic plausibility. We further validated 24 of the fifty as common CFs in the IBD and nascent COVID-19 core literatures. This significant finding demonstrated that the CFs indirectly related to COVID-19 -- identified with use of the immune system dysfunction literature -- are strong candidates to emerge eventually as CFs directly related to COVID-19. As discussed in the main text, many more CFs common to all these core literatures could be identified and validated. ID and IBD share many common risk/contributing factors, including behaviors and toxic exposures that impair immune function. A key component to immune system health is removal of those factors that contribute to immune system dysfunction in the first place. This requires a paradigm shift from traditional Western medicine, which often focuses on treatment, rather than prevention.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Clinical Significance of Plasma D-Dimer in COVID-19 Mortality

It is not clear whether D-dimer can be an independent predictor of coronavirus disease 2019 (COVID-19) mortality, and the cut-off of D-dimer for clinical use remains to be determined. Therefore, a comprehensive analysis is still necessary to illuminate the clinical significance of plasma D-dimer in COVID-19 mortality. We searched PubMed, Embase, Cochrane Library, and Scopus databases until November 2020. STATA software was used for all the statistical analyses. The identifier of systematic review registration was PROSPERO CRD42020220927. A total of 66 studies involving 40,614 COVID-19 patients were included in our meta-analysis. Pooled data showed that patients in high D-dimer group had poor prognosis than those in low D-dimer group [OR = 4.52, 95% CI = (3.61, 5.67), P < 0.001; HR = 2.81, 95% CI = (1.85, 4.27), P < 0.001]. Sensitivity analysis, pooled data based on different effect models and the Duval and Tweedie trim-and-fill method did not change the conclusions. Subgroup analyses stratified by different countries, cutoffs, sample size, study design, and analysis of OR/HR still keep consistent conclusions. D-dimer was identified as an independent predictor for COVID-19 mortality. A series of values including 0.5 μg/ml, 1 μg/ml, and 2 μg/ml could be determined as cutoff of D-dimer for clinic use. Measurement and monitoring of D-dimer might assist clinicians to take immediate medical actions and predict the prognosis of COVID-19.