Remdesivir or Nirmatrelvir/Ritonavir Therapy for Omicron SARS-CoV-2 Infection in Hematological Patients and Cell Therapy Recipients

Efficacy and safety of antiviral therapies for the treatment of persistent COVID-19 in immunocompromised patients since the Omicron surge: a systematic review

BACKGROUND

Persistent COVID-19 (pCOVID-19) in immunocompromised patients is characterized by unspecific symptoms and pulmonary infiltrates due to ongoing severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication. Treatment options remain unclear, leading to different approaches, including combination therapy and extended durations. The purpose of this study was to assess the efficacy and safety of antiviral therapies for pCOVID-19 in immunocompromised patients since the Omicron surge.

METHODS

We searched MEDLINE and Scopus from 1 January 2022 to 6 August 2024 for cohort studies and case series on nirmatrelvir/ritonavir, remdesivir, ensitrelvir and molnupiravir. Evidence certainty was rated using Grading of Recommendations Assessment, Development, and Evaluation for outcomes including viral clearance, recurrence/relapse, mortality, adverse events (AEs) and symptom resolution.

RESULTS

Thirteen studies involving 127 cases were included. Evidence certainty was very low. In combination therapy with at least two direct antiviral agents, viral clearance was 79%, with a 16% recurrence rate. All-cause mortality was 9%, and mortality was 6% while SARS-CoV-2 positive. In 47 cases, AEs were reported in 11%. Symptom resolution ranged from 3 to 6 days in two studies. In combination therapy with one direct antiviral agent and passive immunization, viral clearance was 89%, with an 11% recurrence rate and no deaths. In four documented cases, no AEs were observed. In monotherapy, viral clearance was 100%, with a 15% recurrence rate. One death, unrelated to SARS-CoV-2, occurred. In 12 documented cases, no AEs were observed.

CONCLUSIONS

Based on very low certainty evidence, combining one direct antiviral with passive immunization resulted in high rates of viral clearance and few recurrences. AEs occurred in cases treated with at least two direct antivirals. Controlled studies are needed.

COVID-19 Outcomes Among Hematopoietic Cell Transplant and Chimeric Antigen Receptor T-Cell Recipients in the Era of SARS-CoV-2 Omicron Variants and COVID-19 Therapeutics

Recipients of cellular therapies, including hematopoietic cell transplant (HCT) and chimeric antigen receptor T-cell (CART) therapy, are at risk for poor outcomes from coronavirus disease 2019 (COVID-19). There are limited data describing outcomes among patients in the pre- and early post-cellular therapy period during the Omicron era when multiple antiviral therapeutics were widely available. The objective of this study is to describe COVID-19 treatment and outcomes in patients diagnosed with COVID-19 during the pre- or early post-cellular therapy period. This is a single-center retrospective cohort study of adult HCT and CART recipients diagnosed with COVID-19 in the pre- and early post-cellular therapy period who tested positive for COVID-19 at our cancer center between January 1, 2022 and March 1, 2023. Primary outcomes were 30-day COVID-19-related hospitalization and death. A secondary outcome was development of persistent COVID-19, defined by a positive SARS-CoV-2 polymerase chain reaction (PCR) 31 to 90 days after COVID-19 diagnosis. Among 65 patients included, 52 (80%) received at least one COVID-19 therapeutic. The most common treatment after initial COVID-19 diagnosis was nirmatrelvir/ritonavir (29%), followed by monoclonal antibody therapy (26%) and remdesivir (11%). Of the 64 patients with at least 30 days of follow-up, 8 (12%) had at least one COVID-19-related hospitalization and one patient died, though cause of death was not due to COVID-19. Of the 8 patients hospitalized for COVID-19, one had severe disease and 7 had mild or moderate infection. Persistent COVID-19 was observed in 13/65 (20%) patients, with 4 patients requiring additional antiviral therapy. Three pre-cellular therapy patients had delays in receiving cellular therapy due to persistent COVID-19. During the Omicron era, rates of 30-day COVID-19-related hospitalization and death were relatively low in this cohort of pre- and early post-HCT and CART recipients, the majority of whom received treatment with at least one antiviral agent. Persistent COVID-19 occurred in 1 in 5 patients in the peri-cellular therapy period and led to cellular therapy treatment delays in several patients, highlighting the need for new COVID-19 treatment strategies.

Extended remdesivir administration in haematological patients with malignancies and COVID-19 during the Omicron era: safety and outcomes

OBJECTIVES

To describe the management of haematological patients experiencing prolonged SARS-CoV-2 viral shedding, as the optimal management strategy for this condition remains undetermined.

METHODS

We conducted a retrospective evaluation of our prospectively followed cohort of haematological patients treated with remdesivir for more than 10 days. Starting January 2023, upon COVID-19 diagnosis, the treatment strategy was based on symptoms and PCR cycle threshold (Ct) as follows: (i) when Ct was 25 or less or if the patient had symptoms, a course of remdesivir for at least 10 days, nirmatrelvir/ritonavir for 5 days (whenever possible) and convalescent plasma was administered; and (ii) when the patient was asymptomatic and had a PCR Ct of more than 25, when possible, a course of 5 days of nirmatrelvir/ritonavir was administered. The patient was considered to have achieved viral clearance and, thus, remdesivir was stopped, in either of these cases: (i) PCR negativity, or (ii) subgenomic RNA negativity.

RESULTS

From January to November 2023, 18 patients benefited from a safe extended remdesivir administration, resulting in detection of SARS-CoV-2 viral clearance in a median time of 3.5 weeks (IQR 2.6-3.9) (min-max 1.6-8.0). No clinical or biological side effects were detected. No patient died or needed further treatment for their COVID-19 episode.

CONCLUSIONS

The extended course of remdesivir, combined with other active therapies for COVID-19 infection, was well tolerated. Cure and virus negativity were obtained in all these high-risk patients.

Are any specific respiratory viruses more severe than others in recipients of allogeneic stem cell transplantation? A focus on lower respiratory tract disease

In the general population, influenza virus, respiratory syncytial virus, and SARS-CoV-2 are considered the most severe community-acquired respiratory viruses (CARVs). However, allogeneic stem cell transplant (allo-SCT) recipients may also face severe courses from other CARVs. This retrospective study compared outcomes of various CARV lower respiratory tract diseases (LRTD) in 235 adult allo-SCT recipients, excluding co-infection episodes. We included 235 adults allo-SCT recipients experiencing 353 CARV LRTD consecutive episodes (130 rhinovirus, 63 respiratory syncytial virus, 43 influenza, 43 human parainfluenza virus, 23 human metapneumovirus, 19 Omicron SARS-CoV-2, 17 common coronavirus, 10 adenovirus and 5 human bocavirus) between December 2013 and June 2023. Day 100 overall survival ranged from 78% to 90% without significant differences among CARV types. Multivariable analysis of day 100 all-cause mortality identified corticosteroid use of >1 to <30 mg/d [Hazard ratio (HR) 2.45, p = 0.02) and ≥30 mg/d (HR 2.20, p = 0.015) along with absolute lymphocyte count <0.2 × 109/L (HR 5.82, p < 0.001) and number of CARV episodes as a continuous variable per one episode increase (HR 0.48, p = 0.001) as independent risk factors for all-cause mortality. Degree of immunosuppression, rather than intrinsic CARV virulence, has the most significant impact on mortality in allo-SCT recipients with CARV-LRTD.

The effect of early versus late remdesivir treatment in hospitalized mild to moderate COVID-19 patients in the Omicron era: A retrospective study

Although real-world studies have found that remdesivir is effective in preventing poor prognosis, more information is needed on the optimal timing of remdesivir administration in high-risk coronavirus disease 2019 (COVID-19) patients in the Omicron era. From February 2022 to January 2023, a single-center retrospective study was performed in Korea. We compared the clinical characteristics and treatment outcomes between early (remdesivir treatment within 0-3 days from symptom onset) and late (≥ 4 days from symptom onset) treatment groups of patients who received remdesivir monotherapy. Of 284 patients, 225 were classified into the early treatment group and 59 were classified into the late treatment group. The early treatment group had a lower rate of 28-day progression to severe disease than the late treatment group (1.4% vs 7.4%, P = .03). Delaying remdesivir treatment ≥ 4 days from symptom onset (adjusted odds ratio [aOR], 6.17; 95% CI, 1.18-32.44; P = .03) and Charlson comorbidity index ≥ 3 (aOR, 9.62; 95% CI, 1.65-56.10; P = .01) were independent risk factors for 28-day progression to severe disease. Our results suggest that early administration of remdesivir could be associated with better prognosis in COVID-19 patients with the Omicron variant, and within 3 days from symptom onset seems to be the appropriate timing.

Omicron SARS-CoV-2 infection management and outcomes in patients with hematologic disease and recipients of cell therapy

Introduction

Scarce real-life data exists for COVID-19 management in hematologic disease (HD) patients in the Omicron era.

Purpose

To assess the current clinical management and outcome of SARS-CoV-2 infection diagnosed, identify the risk factors for severe outcomes according to the HD characteristics and cell therapy procedures in a real-world setting.

Methods

A retrospective observational registry led by the Spanish Transplant Group (GETH-TC) with 692 consecutive patients with HD from December 2021 to May 2023 was analyzed.

Results

Nearly one-third of patients (31%) remained untreated and presented low COVID-19-related mortality (0.9%). Nirmatrelvir/ritonavir was used mainly in mild COVID-19 cases in the outpatient setting (32%) with a low mortality (1%), while treatment with remdesivir was preferentially administered in moderate-to-severe SARS-CoV-2 infection cases during hospitalization (35%) with a mortality rate of 8.6%. The hospital admission rate was 23%, while 18% developed pneumonia. COVID-19-related mortality in admitted patients was 14%. Older age, autologous hematopoietic stem cell transplantation (SCT), chimeric antigen receptor T-cell therapy, corticosteroids and incomplete vaccination were factors independently associated with COVID-19 severity and significantly related with higher rates of hospital admission and pneumonia. Incomplete vaccination status, treatment with prior anti-CD20 monoclonal antibodies, and comorbid cardiomyopathy were identified as independent risk factors for COVID-19 mortality.

Conclusions

The results support that, albeit to a lower extent, COVID-19 in the Omicron era remains a significant problem in HD patients. Complete vaccination (3 doses) should be prioritized in these immunocompromised patients. The identified risk factors may help to improve COVID-19 management to decrease the rate of severe disease, ICU admissions and mortality.

A machine learning approach to identify groups of patients with hematological malignant disorders

BACKGROUND AND OBJECTIVE

Vaccination against SARS-CoV-2 in immunocompromised patients with hematologic malignancies (HM) is crucial to reduce the severity of COVID-19. Despite vaccination efforts, over a third of HM patients remain unresponsive, increasing their risk of severe breakthrough infections. This study aims to leverage machine learning's adaptability to COVID-19 dynamics, efficiently selecting patient-specific features to enhance predictions and improve healthcare strategies. Highlighting the complex COVID-hematology connection, the focus is on interpretable machine learning to provide valuable insights to clinicians and biologists.

METHODS

The study evaluated a dataset with 1166 patients with hematological diseases. The output was the achievement or non-achievement of a serological response after full COVID-19 vaccination. Various machine learning methods were applied, with the best model selected based on metrics such as the Area Under the Curve (AUC), Sensitivity, Specificity, and Matthew Correlation Coefficient (MCC). Individual SHAP values were obtained for the best model, and Principal Component Analysis (PCA) was applied to these values. The patient profiles were then analyzed within identified clusters.

RESULTS

Support vector machine (SVM) emerged as the best-performing model. PCA applied to SVM-derived SHAP values resulted in four perfectly separated clusters. These clusters are characterized by the proportion of patients that generate antibodies (PPGA). Cluster 1, with the second-highest PPGA (69.91%), included patients with aggressive diseases and factors contributing to increased immunodeficiency. Cluster 2 had the lowest PPGA (33.3%), but the small sample size limited conclusive findings. Cluster 3, representing the majority of the population, exhibited a high rate of antibody generation (84.39%) and a better prognosis compared to cluster 1. Cluster 4, with a PPGA of 66.33%, included patients with B-cell non-Hodgkin's lymphoma on corticosteroid therapy.

CONCLUSIONS

The methodology successfully identified four separate patient clusters using Machine Learning and Explainable AI (XAI). We then analyzed each cluster based on the percentage of HM patients who generated antibodies after COVID-19 vaccination. The study suggests the methodology's potential applicability to other diseases, highlighting the importance of interpretable ML in healthcare research and decision-making.