Prognostic and predictive biomarkers in patients with COVID-19 treated with tocilizumab in a randomised controlled trial
Bibliographic record
Abstract
Summary Background Retrospective observational studies suggest that interleukin-6 (IL-6), C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, lymphocytes, monocytes, neutrophils, D-dimer, and platelets are associated with disease progression, treatment outcomes, or both, in patients with COVID-19 pneumonia. We explored these candidate prognostic and predictive biomarkers with efficacy outcomes after treatment with tocilizumab, an anti–IL-6 receptor antibody using data from the COVACTA trial for patients hospitalised with severe COVID-19 pneumonia. Methods Candidate biomarkers were measured in 295 patients in the tocilizumab arm and 142 patients in the placebo arm. Efficacy outcomes assessed were clinical status on a seven-category ordinal scale (1, discharge; 7, death), mortality, time to hospital discharge, and mechanical ventilation (if not receiving it at randomisation) through day 28. Prognostic and predictive biomarkers were evaluated continuously with proportional odds, binomial or Fine-Gray models, and additional sensitivity analyses. Findings Modelling in the placebo arm showed all candidate biomarkers except LDH and D-dimer were strongly prognostic for day 28 clinical outcomes of mortality, mechanical ventilation, clinical status, and time to hospital discharge. Modelling in the tocilizumab arm showed a predictive value of ferritin for day 28 clinical outcomes of mortality (predictive interaction p=0.03), mechanical ventilation (predictive interaction p=0.01), and clinical status (predictive interaction p=0.02) compared with placebo. Interpretation Multiple biomarkers prognostic for clinical outcomes were confirmed in COVACTA. Ferritin was identified as a predictive biomarker for the effects of tocilizumab in the COVACTA patient population; high ferritin levels were associated with better clinical outcomes for tocilizumab compared with placebo at day 28. RESEARCH IN CONTEXT Evidence before this study The efficacy and safety of the anti–interleukin-6 receptor antibody tocilizumab in the treatment of patients hospitalised with COVID-19 pneumonia was investigated in COVACTA, a double-blind, randomised, placebo-controlled trial. The primary endpoint of improved clinical status on a seven-category ordinal scale (1, discharged/ready for discharge; 7, death) at day 28 was not met in this trial. Among the secondary endpoints, no difference in mortality at day 28 was observed, but time to hospital discharge was shorter in the tocilizumab group. Subgroup analysis suggested there might be a treatment benefit in patients grouped according to their ordinal scale category at baseline. We searched PubMed on September 14, 2020, using the terms “tocilizumab AND (COVID-19 OR coronavirus) AND biomarker” with no language or date restrictions. The search retrieved 18 articles, four of which identified laboratory measures as potential biomarkers in patients who received tocilizumab for the treatment of COVID-19 pneumonia. The biomarkers reported in these studies include interleukin-6, C-reactive protein, ferritin, fibrinogen, liver transaminases, lymphocytes, platelets, and D-dimer. However, these previous studies were single-centre, retrospective, observational studies. Larger, prospective, controlled trials are needed to investigate potential prognostic and predictive biomarkers to assess the outcomes and response to treatments for COVID-19. Added value of this study This exploratory analysis of data from COVACTA demonstrated interleukin-6, C-reactive protein, ferritin, neutrophils (percentage and absolute count), neutrophil-to-lymphocyte ratio, lymphocytes (percentage and absolute count), monocytes (percentage), and platelets as strong prognostic biomarkers in patients hospitalised with severe COVID-19 pneumonia. More important, ferritin showed predictive value for tocilizumab treatment effects on day 28 clinical outcomes of mortality, mechanical ventilation (among the subgroup of patients not receiving mechanical ventilation at randomisation), and clinical status compared with placebo. Implications of all the available evidence In patients with elevated levels of ferritin at baseline, tocilizumab decreased the probability of death, mechanical ventilation, and worsening clinical status at day 28 compared with placebo, suggesting that ferritin might be useful as a predictive biomarker of efficacy outcomes for tocilizumab in patients with severe COVID-19 pneumonia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".