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IntroductionHead-to-head studies comparing COVID-19 mRNA vaccine effectiveness in immunocompromised individuals, who are vulnerable to severe disease are lacking, as large sample sizes are required to make meaningful inferences. MethodsThis observational comparative effectiveness study was conducted in closed administrative claims data from the US HealthVerity database (December 11, 2020-January 10, 2022, before omicron). A 2-dose mRNA-1273 versus BNT162b2 regimen was assessed for preventing medically-attended breakthrough COVID-19 diagnosis and hospitalizations among immunocompromised adults. Inverse probability of treatment weighting was applied to balance baseline characteristics between vaccine groups. Incidence rates from patient-level data and hazard ratios (HRs) using weighted Cox proportional hazards models were calculated. ResultsOverall, 57,898 and 66,981 individuals received a 2-dose regimen of mRNA-1273 or BNT161b2, respectively. Among the weighted population, mean age was 51 years, 53% were female, and baseline immunodeficiencies included prior blood transplant (8%-9%), prior organ transplant (7%), active cancer (12%-13%), primary immunodeficiency (25%-26%), HIV (20%-21%), and immunosuppressive therapy use (60%-61%). Rates per 1,000 person-years (PYs; 95% confidence intervals [CI]s) of breakthrough medically-attended COVID-19 were 25.82 (23.83-27.97) with mRNA-1273 and 30.98 (28.93, 33.18) with BNT162b2 (HR, 0.83; 95% CI, 0.75-0.93). When requiring evidence of an antigen or polymerase chain reaction test before COVID-19 diagnosis, the HR for medically-attended COVID-19 was 0.78 (0.67-0.92). Breakthrough COVID-19 hospitalization rates per 1,000 PYs (95% CI) were 3.66 (2.96-4.51) for mRNA-1273 and 4.68 (3.91-5.59) for BNT162b2 (HR, 0.78; 0.59-1.03). Utilizing open and closed claims for outcome capture only, or both cohort entry/outcome capture, produced HRs (95% CIs) for COVID-19 hospitalization of 0.72 (0.57-0.92) and 0.66 (0.58-0.76), respectively. ConclusionsAmong immunocompromised adults, a 2-dose mRNA-1273 regimen was more effective in preventing medically-attended COVID-19 in any setting (inpatient and outpatient) than 2-dose BNT162b2. Results were similar for COVID-19 hospitalization, although statistical power was limited when using closed claims only. Study RegistrationNCT05366322
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STRUCTURED ABSTRACTO_ST_ABSImportanceC_ST_ABSAlgorithms for classification of inpatient COVID-19 severity are necessary for confounding control in studies using real-world data (RWD). ObjectiveTo explore use of electronic health record (EHR) data to inform an administrative data algorithm for classification of supplemental oxygen or noninvasive ventilation (O2/NIV) and invasive mechanical ventilation (IMV) to assess disease severity in hospitalized COVID-19 patients. DesignIn this retrospective cohort study, we developed an initial procedure-based algorithm to identify O2/NIV, IMV, and NEITHER O2/NIV nor IMV in two inpatient RWD sources. We then expanded the algorithm to explore the impact of adding diagnoses indicative of clinical need for O2/NIV (hypoxia, hypoxemia) or IMV (acute respiratory distress syndrome) and O2-related patient vitals available in the EHR. Observed changes in severity categorization were used to augment the administrative algorithm. SettingOptum de-identified COVID-19 EHR data and HealthVerity claims and chargemaster data (March - August 2020). ParticipantsAmong patients hospitalized with COVID-19 in each RWD source, our motivating example selected dexamethasone (DEX+) initiators and a random selection of patients who were non-initiators of a corticosteroid of interest (CSI-) matched on date of DEX initiation, age, sex, baseline comorbidity score, days since admission, and COVID-19 severity level (NEITHER, O2/NIV, IMV) on treatment index. Main Outcome and MeasuresInpatient COVID-19 severity was defined using the algorithms developed to classify respiratory support requirements among hospitalized COVID-19 patients (NEITHER, O2/NIV, IMV). Measures were reported as the treatment-specific distributions of patients in each severity level, and as observed changes in severity categorization between the initial procedure-based and expanded algorithms. ResultsIn the administrative data cohort with 5,524 DEX+ and CSI- patient pairs matched using the initial procedure-based algorithm, 30% were categorized as O2/NIV, 5% as IMV, and 65% as NEITHER. Among patients assigned NEITHER via the initial algorithm, use of an expanded algorithm informed by the EHR-based algorithm shifted 54% DEX+ and 28% CSI- to O2/NIV, and 2% DEX+ and 1% CSI- to IMV. Among patients initially assigned O2/NIV, 7% DEX+ and 3% CSI- shifted to IMV. Conclusions and RelevanceApplication of learnings from an EHR-based exploration to our administrative algorithm minimized treatment-differential misclassification of COVID-19 severity.
