Comparison of a Target Trial Emulation Framework vs Cox Regression to Estimate the Association of Corticosteroids With COVID-19 Mortality

  1. Katherine L. Hoffman
  2. Edward J. Schenck
  3. Michael J. Satlin
  4. William Whalen
  5. Di Pan
  6. Nicholas Williams
  7. Iván Díaz

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Communication and adoption of modern study design and analytical techniques is of high importance for the improvement of clinical research from observational data.

Objective

To compare a modern method for statistical inference, including a target trial emulation framework and doubly robust estimation, with approaches common in the clinical literature, such as Cox proportional hazards models.

Design, Setting, and Participants

This retrospective cohort study used longitudinal electronic health record data for outcomes at 28-days from time of hospitalization within a multicenter New York, New York, hospital system. Participants included adult patients hospitalized between March 1 and May 15, 2020, with COVID-19 and not receiving corticosteroids for chronic use. Data were analyzed from October 2021 to March 2022.

Exposures

Corticosteroid exposure was defined as more than 0.5 mg/kg methylprednisolone equivalent in a 24-hour period. For target trial emulation, exposures were corticosteroids for 6 days if and when a patient met criteria for severe hypoxia vs no corticosteroids. For approaches common in clinical literature, treatment definitions used for variables in Cox regression models varied by study design (no time frame, 1 day, and 5 days from time of severe hypoxia).

Main Outcomes and Measures

The main outcome was 28-day mortality from time of hospitalization. The association of corticosteroids with mortality for patients with moderate to severe COVID-19 was assessed using the World Health Organization (WHO) meta-analysis of corticosteroid randomized clinical trials as a benchmark.

Results

A total of 3298 patients (median [IQR] age, 65 [53-77] years; 1970 [60%] men) were assessed, including 423 patients who received corticosteroids at any point during hospitalization and 699 patients who died within 28 days of hospitalization. Target trial emulation analysis found corticosteroids were associated with a reduced 28-day mortality rate, from 32.2%; (95% CI, 30.9%-33.5%) to 25.7% (95% CI, 24.5%-26.9%). This estimate is qualitatively identical to the WHO meta-analysis odds ratio of 0.66 (95% CI, 0.53-0.82). Hazard ratios using methods comparable with current corticosteroid research range in size and direction, from 0.50 (95% CI, 0.41-0.62) to 1.08 (95% CI, 0.80-1.47).

Conclusions and Relevance

These findings suggest that clinical research based on observational data can be used to estimate findings similar to those from randomized clinical trials; however, the correctness of these estimates requires designing the study and analyzing the data based on principles that are different from the current standard in clinical research.

Article activity feed

  1. Version published to 10.1001/jamanetworkopen.2022.34425
  2. Version published to 10.1101/2022.05.27.22275037v4 on medRxiv
  3. Version published to 10.1101/2022.05.27.22275037v2 on medRxiv
  4. Version published to 10.1101/2022.05.27.22275037v3 on medRxiv
  5. ScreenIT

    SciScore for 10.1101/2022.05.27.22275037: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are limitations of our study. First, while our study time frame of Spring 2020 is ideal in terms of corticosteroid experimentation, it includes New York City’s initial pandemic surge conditions and rapidly changing clinical practice. We cannot rule out the presence of unmeasured confounding. Second, we did not have the data to look at individual corticosteroid types, making an exact comparison to a specific randomized trial impossible. Despite these limitations, our study has numerous strengths and serves as an example in which the current standard for clinical research methods fail to recover the correct treatment effect where a modern causal inference method succeeds. Using observational data to guide clinical practice is possible, but relies on the incorporation of advanced epidemiological and statistical methodology principles. We hope this study emphasizes the importance of incorporating these innovative techniques into study designs and statistical analyses of observational data.

    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.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  6. Version published to 10.1101/2022.05.27.22275037v1 on medRxiv