Convalescent plasma for hospitalized patients with COVID-19: an open-label, randomized controlled trial

Abstract

The efficacy of convalescent plasma for coronavirus disease 2019 (COVID-19) is unclear. Although most randomized controlled trials have shown negative results, uncontrolled studies have suggested that the antibody content could influence patient outcomes. We conducted an open-label, randomized controlled trial of convalescent plasma for adults with COVID-19 receiving oxygen within 12 d of respiratory symptom onset ( NCT04348656 ). Patients were allocated 2:1 to 500 ml of convalescent plasma or standard of care. The composite primary outcome was intubation or death by 30 d. Exploratory analyses of the effect of convalescent plasma antibodies on the primary outcome was assessed by logistic regression. The trial was terminated at 78% of planned enrollment after meeting stopping criteria for futility. In total, 940 patients were randomized, and 921 patients were included in the intention-to-treat analysis. Intubation or death occurred in 199/614 (32.4%) patients in the convalescent plasma arm and 86/307 (28.0%) patients in the standard of care arm-relative risk (RR) = 1.16 (95% confidence interval (CI) 0.94-1.43, P = 0.18). Patients in the convalescent plasma arm had more serious adverse events (33.4% versus 26.4%; RR = 1.27, 95% CI 1.02-1.57, P = 0.034). The antibody content significantly modulated the therapeutic effect of convalescent plasma. In multivariate analysis, each standardized log increase in neutralization or antibody-dependent cellular cytotoxicity independently reduced the potential harmful effect of plasma (odds ratio (OR) = 0.74, 95% CI 0.57-0.95 and OR = 0.66, 95% CI 0.50-0.87, respectively), whereas IgG against the full transmembrane spike protein increased it (OR = 1.53, 95% CI 1.14-2.05). Convalescent plasma did not reduce the risk of intubation or death at 30 d in hospitalized patients with COVID-19. Transfusion of convalescent plasma with unfavorable antibody profiles could be associated with worse clinical outcomes compared to standard care.

Conflict of interest statement

The authors declare no competing interests.

© 2021. The Author(s).

Figures

Fig. 1. Enrollment, randomization and follow-up.

Patient flow in the CONCOR-1 study detailing the intention-to-treat population, per-protocol analysis population and excluded patients. Othera, n = 26: <16 years of age (n = 13), <18 years of age (n = 5), ABO-compatible plasma unavailable (n = 5) and other (n = 3). bIncludes not receiving supplemental oxygen at the time of randomization (but on oxygen at screening) and any symptom onset >12 d before randomization for protocol version 5.0 or earlier.

Fig. 2. Study outcomes.

a, Patient outcomes for the primary and secondary endpoints. b, Cumulative incidence functions of the primary outcome (intubation or death) by day 30 and of in-hospital death by day 90. aRR and 95% CI; hazard ratio ((HR), 95% CI); and mean difference ((MD), with 95% CI based on robust bootstrap standard errors). bSeventeen patients were discharged before day 30 and were lost to follow-up at 30 d, and two withdrew consent before day 30; thus, outcomes collected at day 30 (primary outcome and some other secondary outcomes for day 30) were missing. cExcluding 11 patients on chronic kidney replacement therapy at baseline. dIntention-to-treat survival analyses were based on the complete baseline population (940 randomized patients minus two patients who withdrew consent).

Fig. 3. Subgroup analyses.

Forest plots are presented for the subgroup analyses for the intention-to-treat population. P values for RR and homogeneity are two sided without adjustment for multiple comparisons. BMI, body mass index.

Fig. 4. The effect-modifying role of convalescent plasma antibody content for the primary outcome.

a, Absolute antibody amounts transfused per patient (n = 597) in the CCP arm for each marker, expressed as the product of volume and concentration. Center line: median; box limits: 25th and 75th percentiles; whiskers: 1.5× IQR; points: outliers. b, Effect-modifying role of CCP content for the primary outcome for each marker. The top row presents the trends in CCP effect compared to SOC as a function of the marker value, along with 95% CIs. Marker values are expressed as standard deviations of log values centered around the mean (standardized log). The horizontal dotted line represents CCP with no effect (OR = 1). The P values (two-sided test for trend without adjustment for multiple comparisons) refer to the effect modification observed with each marker (Supplementary Table 10). The histograms present the frequency distribution by marker. c,d, Contour plots of the OR for the primary outcome as a function of marker combinations. Overlaid data points indicate the value of the two markers for each CCP transfusion. Mfi, mean fluorescence intensity; OD, optical density; S, SARS-CoV-2 spike protein; SOC, standard of care.

Fig. 5. Meta-analysis of mortality at 30 d in CONCOR-1 and other trials according to convalescent plasma selection strategy.

a, Meta-analysis of trials that used high-titer plasma. b, Meta-analysis of trials that used a mix of low-, medium- and high-titer plasma. df, degrees of freedom.

Extended Data Fig. 1. Cumulative incidence functions of intubation or in-hospital death by day 30.

Panel A presents the intention-to-treat population and panel B presents the per protocol population.

Extended Data Fig. 2. Cumulative incidence functions of in-hospital death by day 90.

Panel A presents the intention-to-treat population and panel B presents the per protocol population.

Extended Data Fig. 3. Kaplan-Meier estimate of distribution of length of stay in hospital by day 90.

Panel A presents the intention-to-treat population and panel B presents the per protocol population.

Extended Data Fig. 4. Subgroup analysis for the per-protocol population.

P-values for relative risk and homogeneity are two-sided without adjustment for multiple comparisons. BMI: Body mass index.

Extended Data Fig. 5. Post-hoc subgroup analyses for the intention-to-treat population.

Subgroups based on corticosteroid use and location at time of randomizations were added post-hoc at time of review. P-values for relative risk and homogeneity are two-sided without adjustment for multiple comparisons.

Extended Data Fig. 6. Post-hoc subgroup analyses for the per-protocol population.

Subgroups based on corticosteroid use and location at time of randomizations were added post-hoc at time of review. P-values for relative risk and homogeneity are two-sided without adjustment for multiple comparisons.

Extended Data Fig. 7. Pairwise scatter plots of plasma antibody markers and empirical distribution functions.

Markers (log transformed and standardized) include antibody (IgM,IgA,IgG) against the receptor binding domain (anti-RBD) by ELISA, plaque reduction neutralization test, IgG antibody against the full transmembrane Spike protein (anti-S IgG) by flow cytometry and the antibody-dependent cellular cytotoxicity (ADCC) assay.corr: Pearson correlation coefficients of pair of antibody markers.

Extended Data Fig. 8. Contour plots of the joint effect-modifying role of antibody markers for convalescent plasma versus standard of care on the composite endpoint of intubation or death.

The contours convey pairwise combinations of antibody markers yielding similar odds ratios for the CCP effect with the black line corresponding to an odds ratio of 1 (that is no effect of CCP). Data points for individual patients are overlaid with colours denoting the blood supply centre. Contours were obtained from fitting generalized additive logistic regression models for the primary outcome adjusting for blood supply center, treatment and the log transformed and standardized biomarkers - smoothing splines were used to relax linearity assumptions. The contour lines with positive slope suggest combinations of high (or low) values for both markers yield similar effects of CCP; the contour lines with negative slopes suggest high values of both markers yield strong CCP effects. For the combination of anti-S IgG with ADCC or anti-S IgG with anti-RBD, the general additive logistic regression models led to a complex equation that was not statistically significant nor clinical interpretable. These combinations were therefore excluded from this figure.

Extended Data Fig. 9. Comparison of in-house ELISA to commercial assays.

Values from the Héma-Québec in-house ELISA measuring antibody (IgM, IgA, IgG) binding the receptor binding domain of SARS-CoV-2 Spike protein (used in the current study) are compared to results from Euroimmun (Panel A) and Ortho Vitros (Panel B) commercial assays measuring IgG binding to subunit 1 of the SARS-CoV-2 Spike protein, which contains the receptor binding domain and which were used to qualify convalescent plasma in previous clinical trials. Each sample was tested with the commercial assays twice.