How to Quantify and Interpret Treatment Effects in Comparative Clinical Studies of COVID-19
Authors: Derek Hazard, Klaus Kaier, Maja von Cube, Jerome Lambert, Martin Wolkewitz
Journal: Annals of Internal Medicine (2021)

LettersMay 2021How to Quantify and Interpret Treatment Effects in Comparative Clinical Studies of COVID-19FREEDerek Hazard, MSc, Klaus Kaier, PhD, Maja von Cube, PhD, Jerome Lambert, MD, PhD, Martin Wolkewitz, PhDDerek Hazard, MScUniversity of Freiburg, Freiburg, GermanySearch for more papers by this author, Klaus Kaier, PhDUniversity of Freiburg, Freiburg, GermanySearch for more papers by this author, Maja von Cube, PhDUniversity of Freiburg, Freiburg, GermanySearch for more papers by this author, Jerome Lambert, MD, PhDUniversity of Freiburg, Freiburg, GermanySearch for more papers by this author, Martin Wolkewitz, PhDUniversity of Freiburg, Freiburg, GermanySearch for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L20-1439 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR: We applaud McCaw and colleagues (1) for using the “well-established yet underused” method of accounting for competing risks in their time-to-recovery analyses of patients with COVID-19. Although their approach is valid, we recommend that they consider expanding their analysis to the established (and also underused) method of multistate modeling for time-to-event analyses (2). This method avoids several common survival biases (including those mentioned in their article) and gives deep insights into the time-dynamic progress of oxygen support and clinical outcomes in patients with COVID-19 (3).Multistate models represent processes where a patient can occupy one of several states (such as levels of oxygen support) at a given time. This method has been shown on 2 real data sets of patients with COVID-19 that were extracted from published works in the New England Journal of Medicine (4, 5). This approach has several advantages. Unlike a competing risks model, where a patient moves permanently into one of several final states, multistate models allow repeated transitions (such as noninvasive ventilation ↔ invasive ventilation) and thus model patients who may clinically improve and then subsequently decline (or vice versa).Similar to the mean time in recovery displayed in Figure 3, panels B and C, of McCaw and colleagues' article, average duration in specific oxygen support states can be calculated, thus informing decision makers on the health care needs of specific groups of patients. Furthermore, the cumulative incidence curves of various states can be consolidated into a single stacked probability plot. Doing so not only correctly acknowledges active cases by taking into account censoring but also shows how the duration of oxygen support is determined by the competing end points of death and discharge. These plots can show the predicted clinical course of an entire cohort of patients with COVID-19, as well as enable the comparison of patients with differing baseline characteristics. Of note, the graphs can directly show how both clinical end points and end points influencing hospital capacities differ between treatment groups in randomized clinical trials (6).A picture is a thousand words, and it is unfortunate that we cannot include an example plot in this comment. However, researchers can conduct the analyses themselves with code in the statistical software R (R Foundation), example data sets, and plots that are publicly available in our article (3). We agree with the authors that “no single summary measure can capture all the information provided by the cumulative recovery curves.” However, we believe that the easy-to-interpret yet comprehensive information provided by a stacked probability plot is a step in the right direction.References1. McCaw ZR, Tian L, Vassy JL, et al. How to quantify and interpret treatment effects in comparative clinical studies of COVID-19. Ann Intern Med. 2020;173:632-7. [PMID: 32634024]. doi:10.7326/M20-4044 LinkGoogle Scholar2. Andersen PK, Keiding N. Multi-state models for event history analysis. Stat Methods Med Res. 2002;11:91-115. [PMID: 12040698] CrossrefMedlineGoogle Scholar3. Hazard D, Kaier K, von Cube, et al. Joint analysis of duration of ventilation, length of intensive care, and mortality of COVID-19 patients: a multistate approach. BMC Med Res Methodol. 2020;20:206. [PMID: 32781984] doi:10.1186/s12874-020-01082-z CrossrefMedlineGoogle Scholar4. Bhatraju PK, Ghassemieh BJ, Nichols M, et al. COVID-19 in critically ill patients in the Seattle region—case series. N Engl J Med. 2020;382:2012-22. [PMID: 32227758] doi:10.1056/NEJMoa2004500 CrossrefMedlineGoogle Scholar5. Grein J, Ohmagari N, Shin D, et al. Compassionate use of remdesivir for patients with severe covid-19. N Engl J Med. 2020;382:2327-36. [PMID: 32275812] doi:10.1056/NEJMoa2007016 CrossrefMedlineGoogle Scholar6. von Cube M, Grodd M, Wolkewitz M, et al.. Harmonizing heterogeneous endpoints in coronavirus disease 2019 trials without loss of information. Crit Care Med. 2021;49:e11-9. [PMID: 33148952] doi:10.1097/CCM.0000000000004741 CrossrefMedlineGoogle Scholar Comments 0 Comments Sign In to Submit A Comment Author, Article, and Disclosure InformationAuthors: Derek Hazard, MSc; Klaus Kaier, PhD; Maja von Cube, PhD; Jerome Lambert, MD, PhD; Martin Wolkewitz, PhDAffiliations: University of Freiburg, Freiburg, GermanyDisclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=L20-1439. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoHow to Quantify and Interpret Treatment Effects in Comparative Clinical Studies of COVID-19 Zachary R. McCaw , Lu Tian , Jason L. Vassy , Christine Seel Ritchie , Chien-Chang Lee , Dae Hyun Kim , and Lee-Jen Wei How to Quantify and Interpret Treatment Effects in Comparative Clinical Studies of COVID-19 Michael A. Proschan , Dean Follmann , Lori Dodd How to Quantify and Interpret Treatment Effects in Comparative Clinical Studies of COVID-19 Lu Tian , Jason L. Vassy , Christine Seel Ritchie , Chien-Chang Lee , Dae Hyun Kim Metrics May 2021Volume 174, Issue 5 Page: 731 ePublished: 18 May 2021 Issue Published: May 2021 Copyright & PermissionsCopyright © 2021 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...