Real-world Effectiveness of Casirivimab and Imdevimab in Patients With COVID-19 in the Ambulatory Setting: An Analysis of Two Large US National Claims Databases
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Abstract
Background
In a phase III clinical trial, casirivimab and imdevimab (CAS+IMD) reduced the composite endpoint of COVID-19-related hospitalizations or all-cause mortality in outpatients at risk of severe disease. This study assessed real-world effectiveness of CAS+IMD.
Methods
Data from Optum ® Clinformatics ® Data Mart (CDM) and IQVIA Pharmetrics Plus (PMTX+) were used to identify patients diagnosed with COVID-19 in ambulatory settings between December 2020 and March 2021 (PMTX+) and June 2021 (CDM), and either treated with CAS+IMD or untreated but treatment-eligible under Emergency Use Authorization. CAS+IMD-treated patients were matched to untreated patients and followed up to 30 days for the outcome of all-cause mortality or COVID-19-related hospitalizations (CDM) and COVID-19-related hospitalizations (PMTX+). Kaplan-Meier estimators were used to calculate outcome risks; Cox proportional-hazard models estimated adjusted hazard ratios (aHR) with 95% confidence intervals (CI).
Results
For CDM, 1116 CAS+IMD-treated patients were matched to 5294 untreated patients; for PMTX+, 3280 CAS+IMD-treated patients were matched to 16,284 untreated patients. The 30-day outcome risk was 2.1% and 5.3% in treated and untreated cohorts, respectively (CDM), and the 30-day risk of COVID-19-related hospitalization was 1.9% and 4.8%, respectively (PMTX+); translating to a 61% lower adjusted outcome risk (CDM aHR 0.39 (95% CI 0.26–0.60; PMTX+ aHR 0.39 (95% CI 0.30–0.51). The benefit of treatment was maintained across multiple subgroups of high-risk patients; earlier intervention was associated with improved outcomes.
Conclusions
This real-world study further supports randomized clinical trial findings that treatment with CAS+IMD reduces the risk of hospitalization and mortality in patients infected with susceptible variants.
Article activity feed
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SciScore for 10.1101/2022.02.28.22270796: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Since both databases contain de-identified data and are fully compliant with the Health Insurance Portability and Accountability Act, institutional review board/ethics committee approval was not required. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis A variable matching ratio was used to balance between minimizing bias and maximizing the matched sample size to strengthen the statistical power and improve generalizability [20]. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Res…SciScore for 10.1101/2022.02.28.22270796: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Since both databases contain de-identified data and are fully compliant with the Health Insurance Portability and Accountability Act, institutional review board/ethics committee approval was not required. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis A variable matching ratio was used to balance between minimizing bias and maximizing the matched sample size to strengthen the statistical power and improve generalizability [20]. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Potential limitations of this analysis include that claims data do not capture COVID-19 disease severity (eg, viral load) or symptom data, including time of symptom onset, which are important predictors of hospitalization and mortality and may be used by clinicians to inform treatment decisions. Since the study was non-randomized, this limitation may result in residual confounding due to channeling bias; some patients may not have been treated because they may have had milder disease than those who were treated, potentially leading to underestimation of CAS+IMD effectiveness. Potentially important confounders such as BMI and COVID-19 vaccination are not well captured in claims data; assuming patients with higher BMI and those who are unvaccinated would be more likely to have worse disease and be treated, residual confounding would likely bias results against CAS+IMD. Misclassification may similarly result from use of days from diagnosis to treatment as a proxy for the duration from symptom onset to treatment as, for many patients, COVID-19 symptoms are likely to have started prior to diagnosis. Furthermore, the data were sourced at a time when vaccinations were not routinely available, particularly in the PMTX+ database, thus limiting the generalizability of our findings. Additionally, the current findings may not be generalizable to future variants, such as Omicron, where laboratory studies have found markedly reduced neutralization activity [24, 25]. Finally, the claims dat...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- No funding statement was detected.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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