To the Editor—We read with interest the article by Kumar and colleagues [1], who reported good experience with the neutralizing monoclonal antibody (mAb) bamlanivimab. We developed a coronavirus disease 2019 (COVID-19) clinic during pandemic surge conditions and prioritized mAb infusion to high-risk patients, particularly with casirivimab/imdevimab, and would like to share our experience given the limited data published on the efficacy of casirivimab/imdevimab. We performed a retrospective review of medical records of patients referred to our clinic from 1 November 2020 to 28 February 2021 and included only those aged older than 18 years and considered high risk. Patients were defined as high risk (and assigned a risk score) if they met more than 1 criteria: age older than 65 years (3 points); body mass index >35 kg/m2 (3 points); age older than 55 years with hypertension, coronary artery disease, or chronic lung disease (2 points); and diabetes mellitus, chronic kidney disease, or immunosuppression (2 points each). One additional point was assigned for Black, Native American, and/or Hispanic/Latino ethnicity. Casirivimab/imdevimab or bamlanivimab was offered to all high-risk outpatients within 5 days of COVID-19 diagnosis via positive polymerase chain reaction. We extracted baseline demographics, medical comorbidities, receipt of mAb, and 30-day outcomes including hospitalization and death related to COVID-19. We performed unadjusted analyses using Fisher’s exact test and t test, and multivariate analysis using logistic regression controlling for risk score and local pandemic intensity. Sensitivity analyses did not find other significant predictors. Tests were 2-sided with an α level of .05 and performed using Stata version 12.1 (StataCorp) and R (R Foundation for Statistical Computing). The study was approved by the Human Research Protections Program at the University of California, San Diego. Among 617 patients, 175 received mAbs and 442 did not (control). The mAb group was older, had more men, more comorbidities, and a higher risk score. Casirivimab/imdevimab was given in 83.4% and bamlanivimab 16.6% of patients. The majority (94%) received mAbs within 5 days of symptom onset. There was a significant reduction in hospitalizations in the mAb group compared with the control (1.7% vs 24%; P < .005) (Table 1), which was noted in the subset of patients only seen in our Telemedicine Clinic as well. Notably, there were no COVID-19–related deaths in the mAb group compared with 12 (2.7%) in controls (P = .024). The mean length of stay for COVID-19–related hospitalization was shorter in those who received mAbs, although this was not statistically significant. The number needed to treat (NNT) to prevent 1 hospitalization was 4.5. Hospitalization and mortality within 30 days were independently associated with receipt of mAbs and the risk score via multivariate analysis. Outcomes of High-Risk Patients With COVID-19 Based on Whether They Received Monoclonal Antibody (mAb Group) or Not (Control) The Clinic cohort consists of the subset of the total cohort that was evaluated in the COVID-19 Clinic. Abbreviations: CI, confidence interval; COVID-19, coronavirus disease 2019; mAb, monoclonal antibody; OR, odds ratio; SD, standard deviation. aMultivariate analysis included adjustment for risk score and local pandemic intensity (measured by rolling daily 7-day average of the number of daily cases in San Diego County, based on the New York Times github project). In this analysis, the risk score was statistically significant: OR = 1.121 per unit, 95% CI (1.016, 1.237), P = .023, as was the San Diego case rate: OR = 1.47 per 1000 daily cases, 95% CI (1.13, 1.93), P = .004. bMultivariate analysis included adjustment for risk score. The risk score was statistically significant: OR = 1.310 per unit, 95% CI (1.028, 1.661), P = .030. The San Diego case rate was not statistically significant at P < .15, and not included in the model. cMultivariate analysis included adjustment for risk score. The risk score was statistically significant: OR = 1.254, 95% CI (1.094, 1.444), P = .0012. The San Diego case rate/1000 population was not statistically significant at P < .15, and not included in the model. Outcomes of High-Risk Patients With COVID-19 Based on Whether They Received Monoclonal Antibody (mAb Group) or Not (Control) The Clinic cohort consists of the subset of the total cohort that was evaluated in the COVID-19 Clinic. Abbreviations: CI, confidence interval; COVID-19, coronavirus disease 2019; mAb, monoclonal antibody; OR, odds ratio; SD, standard deviation. aMultivariate analysis included adjustment for risk score and local pandemic intensity (measured by rolling daily 7-day average of the number of daily cases in San Diego County, based on the New York Times github project). In this analysis, the risk score was statistically significant: OR = 1.121 per unit, 95% CI (1.016, 1.237), P = .023, as was the San Diego case rate: OR = 1.47 per 1000 daily cases, 95% CI (1.13, 1.93), P = .004. bMultivariate analysis included adjustment for risk score. The risk score was statistically significant: OR = 1.310 per unit, 95% CI (1.028, 1.661), P = .030. The San Diego case rate was not statistically significant at P < .15, and not included in the model. cMultivariate analysis included adjustment for risk score. The risk score was statistically significant: OR = 1.254, 95% CI (1.094, 1.444), P = .0012. The San Diego case rate/1000 population was not statistically significant at P < .15, and not included in the model. Similar to the experience of Kumar and colleagues with bamlanivimab, we found that mAb receipt, primarily with casirivimab/imdevimab, was associated with a significant reduction in hospitalization. Unlike Kumar and colleagues, however, we found a lower mortality rate in the mAb group compared with controls and our NNT of 4.5 to prevent 1 hospitalization was lower than what they report. The significant reduction in COVID-19–related hospitalizations and death with early mAb administration should prompt more widespread use and development of dedicated outpatient COVID-19 centers to treat patients with COVID-19 infection, and this strategy may serve as a model in future infectious disease outbreaks. Author contributions. J. D. J., S. A., F. V., and M. R. had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. All authors contributed to data collection; the concept and design; acquisition, analysis, or interpretation of data; critical revision of the manuscript for important intellectual content. Drafting of the manuscript: J. D. J., S. A., and M. R. Statistical analysis: S. A. and F. V. Administrative, technical, or material support and supervision: M. R. Acknowledgements. The authors acknowledge the tremendous efforts of the COVID-19 Clinic Team: Dr Ajay Bharti, Dr Nancy Law, Kathleen Bordeaux, Claudia Guerrero, Diana Paddock, Joseph Bautista, Claudia Medrano, Sarah Arend, Mackenzie Williams, Marvin Ochoa Vega, and Charisse Montilla. They also thank Daryn Ikeda for help with the chart review. Additionally, the authors acknowledge the contributions of Dr David Smith and Dr Constance Benson as leaders of the COVID-19 Therapeutics Committee at the University of California, San Diego, and for input into development of the risk score. Potential conflicts of interest. J. D. J. received grant funding from Astellas, F2G Ltd, and Pfizer. S. A. received grant funding by the Cystic Fibrosis Foundation, received personal fees as a consultant for Merck and Gilead, and served as an unpaid advisor for BioMx. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
No takes yet. Share an insight, caveat, or question.
Jenks et al. (2021) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: