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  1. Article ; Online: Statistical Issues and Lessons Learned From COVID-19 Clinical Trials With Lopinavir-Ritonavir and Remdesivir.

    Yin, Guosheng / Zhang, Chenyang / Jin, Huaqing

    JMIR public health and surveillance

    2020  Volume 6, Issue 3, Page(s) e19538

    Abstract: ... issues and lessons learned from the recent three clinical trials on COVID-19 treatments, we suggest more ... treatments were completed: one for lopinavir-ritonavir and two for remdesivir. One trial reported ... identify several key issues in the design and analysis of three COVID-19 trials and reanalyze the data ...

    Abstract Background: Recently, three randomized clinical trials on coronavirus disease (COVID-19) treatments were completed: one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir was superior to placebo in shortening the time to recovery, while the other two showed no benefit of the treatment under investigation.
    Objective: The aim of this paper is to, from a statistical perspective, identify several key issues in the design and analysis of three COVID-19 trials and reanalyze the data from the cumulative incidence curves in the three trials using more appropriate statistical methods.
    Methods: The lopinavir-ritonavir trial enrolled 39 additional patients due to insignificant results after the sample size reached the planned number, which led to inflation of the type I error rate. The remdesivir trial of Wang et al failed to reach the planned sample size due to a lack of eligible patients, and the bootstrap method was used to predict the quantity of clinical interest conditionally and unconditionally if the trial had continued to reach the originally planned sample size. Moreover, we used a terminal (or cure) rate model and a model-free metric known as the restricted mean survival time or the restricted mean time to improvement (RMTI) to analyze the reconstructed data. The remdesivir trial of Beigel et al reported the median recovery time of the remdesivir and placebo groups, and the rate ratio for recovery, while both quantities depend on a particular time point representing local information. We use the restricted mean time to recovery (RMTR) as a global and robust measure for efficacy.
    Results: For the lopinavir-ritonavir trial, with the increase of sample size from 160 to 199, the type I error rate was inflated from 0.05 to 0.071. The difference of RMTIs between the two groups evaluated at day 28 was -1.67 days (95% CI -3.62 to 0.28; P=.09) in favor of lopinavir-ritonavir but not statistically significant. For the remdesivir trial of Wang et al, the difference of RMTIs at day 28 was -0.89 days (95% CI -2.84 to 1.06; P=.37). The planned sample size was 453, yet only 236 patients were enrolled. The conditional prediction shows that the hazard ratio estimates would reach statistical significance if the target sample size had been maintained. For the remdesivir trial of Beigel et al, the difference of RMTRs between the remdesivir and placebo groups at day 30 was -2.7 days (95% CI -4.0 to -1.2; P<.001), confirming the superiority of remdesivir. The difference in the recovery time at the 25th percentile (95% CI -3 to 0; P=.65) was insignificant, while the differences became more statistically significant at larger percentiles.
    Conclusions: Based on the statistical issues and lessons learned from the recent three clinical trials on COVID-19 treatments, we suggest more appropriate approaches for the design and analysis of ongoing and future COVID-19 trials.
    MeSH term(s) Adenosine Monophosphate/analogs & derivatives ; Adenosine Monophosphate/therapeutic use ; Alanine/analogs & derivatives ; Alanine/therapeutic use ; COVID-19/drug therapy ; Coronavirus Infections/drug therapy ; Data Interpretation, Statistical ; Drug Therapy, Combination ; Humans ; Lopinavir/therapeutic use ; Randomized Controlled Trials as Topic/methods ; Research Design ; Ritonavir/therapeutic use ; Treatment Outcome
    Chemical Substances Lopinavir (2494G1JF75) ; remdesivir (3QKI37EEHE) ; Adenosine Monophosphate (415SHH325A) ; Ritonavir (O3J8G9O825) ; Alanine (OF5P57N2ZX)
    Keywords covid19
    Language English
    Publishing date 2020-07-10
    Publishing country Canada
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2369-2960
    ISSN (online) 2369-2960
    DOI 10.2196/19538
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Statistical Issues and Lessons Learned From COVID-19 Clinical Trials With Lopinavir-Ritonavir and Remdesivir

    Yin, Guosheng / Zhang, Chenyang / Jin, Huaqing

    JMIR Public Health and Surveillance, Vol 6, Iss 3, p e

    2020  Volume 19538

    Abstract: ... were completed: one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir ... identify several key issues in the design and analysis of three COVID-19 trials and reanalyze the data ... in favor of lopinavir-ritonavir but not statistically significant. For the remdesivir trial of Wang et al ...

    Abstract BackgroundRecently, three randomized clinical trials on coronavirus disease (COVID-19) treatments were completed: one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir was superior to placebo in shortening the time to recovery, while the other two showed no benefit of the treatment under investigation. ObjectiveThe aim of this paper is to, from a statistical perspective, identify several key issues in the design and analysis of three COVID-19 trials and reanalyze the data from the cumulative incidence curves in the three trials using more appropriate statistical methods. MethodsThe lopinavir-ritonavir trial enrolled 39 additional patients due to insignificant results after the sample size reached the planned number, which led to inflation of the type I error rate. The remdesivir trial of Wang et al failed to reach the planned sample size due to a lack of eligible patients, and the bootstrap method was used to predict the quantity of clinical interest conditionally and unconditionally if the trial had continued to reach the originally planned sample size. Moreover, we used a terminal (or cure) rate model and a model-free metric known as the restricted mean survival time or the restricted mean time to improvement (RMTI) to analyze the reconstructed data. The remdesivir trial of Beigel et al reported the median recovery time of the remdesivir and placebo groups, and the rate ratio for recovery, while both quantities depend on a particular time point representing local information. We use the restricted mean time to recovery (RMTR) as a global and robust measure for efficacy. ResultsFor the lopinavir-ritonavir trial, with the increase of sample size from 160 to 199, the type I error rate was inflated from 0.05 to 0.071. The difference of RMTIs between the two groups evaluated at day 28 was –1.67 days (95% CI –3.62 to 0.28; P=.09) in favor of lopinavir-ritonavir but not statistically significant. For the remdesivir trial of Wang et al, the difference of RMTIs at day 28 was –0.89 days ...
    Keywords Public aspects of medicine ; RA1-1270
    Subject code 310
    Language English
    Publishing date 2020-07-01T00:00:00Z
    Publisher JMIR Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Statistical Issues and Lessons Learned from COVID-19 Clinical Trials with Lopinavir-Ritonavir and Remdesivir

    Yin, Guosheng / Zhang, Chenyang / Jin, Huaqing

    medRxiv

    Abstract: ... Conclusions: Based on the statistical issues and lessons learned from the recent three clinical trials ... were completed, one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir ... in the three trials using more appropriate statistical methods. Methods: The lopinavir-ritonavir trial enrolled ...

    Abstract Background: Since the outbreak of the novel coronavirus disease 2019 (COVID-19) in December 2019, it has rapidly spread in more than 200 countries or territories with over 8 million confirmed cases and 440,000 deaths by June 17, 2020. Recently, three randomized clinical trials on COVID-19 treatments were completed, one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir was superior to placebo in shortening the time to recovery, while the other two showed no benefit of the treatment under investigation. However, several statistical issues in the original design and analysis of the three trials are identified, which might shed doubts on their findings and the conclusions should be evaluated with cautions. Objective: From statistical perspectives, we identify several issues in the design and analysis of three COVID-19 trials and reanalyze the data from the cumulative incidence curves in the three trials using more appropriate statistical methods. Methods: The lopinavir-ritonavir trial enrolled 39 additional patients due to insignificant results after the sample size reached the planned number, which led to inflation of the type I error rate. The remdesivir trial of Wang et al. failed to reach the planned sample size due to a lack of eligible patients, while the bootstrap method was used to predict the quantity of clinical interest conditionally and unconditionally if the trial had continued to reach the originally planned sample size. Moreover, we used a terminal (or cure) rate model and a model-free metric known as the restricted mean survival time or the restricted mean time to improvement (RMTI) in this context to analyze the reconstructed data due to the existence of death as competing risk and a terminal event. The remdesivir trial of Beigel et al. reported the median recovery time of the remdesivir and placebo groups and the rate ratio for recovery, while both quantities depend on a particular time point representing local information. We reanalyzed the data to report other percentiles of the time to recovery and adopted the bootstrap method and permutation test to construct the confidence intervals as well as the P values. The restricted mean time to recovery (RMTR) was also computed as a global and robust measure for efficacy. Results: For the lopinavir-ritonavir trial, with the increase of sample size from 160 to 199, the type I error rate was inflated from 0.05 to 0.071. The difference of terminal rates was -8.74% (95% CI [-21.04, 3.55]; P=.16) and the hazards ratio (HR) adjusted for terminal rates was 1.05 (95% CI [0.78, 1.42]; P=.74), indicating no significant difference. The difference of RMTIs between the two groups evaluated at day 28 was -1.67 days (95% CI [-3.62, 0.28]; P=.09) in favor of lopinavir-ritonavir but not statistically significant. For the remdesivir trial of Wang et al., the difference of terminal rates was -0.89% (95% CI [-2.84, 1.06]; P=.19) and the HR adjusted for terminal rates was 0.92 (95% CI [0.63, 1.35]; P=.67). The difference of RMTIs at day 28 was -0.89 day (95% CI [-2.84, 1.06]; P=.37). The planned sample size was 453, yet only 236 patients were enrolled. The conditional prediction shows that the HR estimates would reach statistical significance if the target sample size had been maintained, and both conditional and unconditional prediction delivered significant HR results if the trial had continued to double the target sample size. For the remdesivir trial of Beigel et al., the difference of RMTRs between the remdesivir and placebo groups up to day 30 was -2.7 days (95% CI [-4.0, -1.2]; P<.001), confirming the superiority of remdesivir. The difference in recovery time at the 25th percentile (95% CI [-3, 0]; P=.65) was insignificant, while the differences manifested to be statistically significant at larger percentiles. Conclusions: Based on the statistical issues and lessons learned from the recent three clinical trials on COVID-19 treatments, we suggest more appropriate approaches for the design and analysis for ongoing and future COVID-19 trials.
    Keywords covid19
    Language English
    Publishing date 2020-06-19
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.06.17.20133702
    Database COVID19

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  4. Article ; Online: Statistical Issues and Lessons Learned from COVID-19 Clinical Trials with Lopinavir-Ritonavir and Remdesivir

    Yin, G. / Zhang, C. / Jin, H.

    Abstract: ... Conclusions: Based on the statistical issues and lessons learned from the recent three clinical trials ... were completed, one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir ... in the three trials using more appropriate statistical methods. Methods: The lopinavir-ritonavir trial enrolled ...

    Abstract Background: Since the outbreak of the novel coronavirus disease 2019 (COVID-19) in December 2019, it has rapidly spread in more than 200 countries or territories with over 8 million confirmed cases and 440,000 deaths by June 17, 2020. Recently, three randomized clinical trials on COVID-19 treatments were completed, one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir was superior to placebo in shortening the time to recovery, while the other two showed no benefit of the treatment under investigation. However, several statistical issues in the original design and analysis of the three trials are identified, which might shed doubts on their findings and the conclusions should be evaluated with cautions. Objective: From statistical perspectives, we identify several issues in the design and analysis of three COVID-19 trials and reanalyze the data from the cumulative incidence curves in the three trials using more appropriate statistical methods. Methods: The lopinavir-ritonavir trial enrolled 39 additional patients due to insignificant results after the sample size reached the planned number, which led to inflation of the type I error rate. The remdesivir trial of Wang et al. failed to reach the planned sample size due to a lack of eligible patients, while the bootstrap method was used to predict the quantity of clinical interest conditionally and unconditionally if the trial had continued to reach the originally planned sample size. Moreover, we used a terminal (or cure) rate model and a model-free metric known as the restricted mean survival time or the restricted mean time to improvement (RMTI) in this context to analyze the reconstructed data due to the existence of death as competing risk and a terminal event. The remdesivir trial of Beigel et al. reported the median recovery time of the remdesivir and placebo groups and the rate ratio for recovery, while both quantities depend on a particular time point representing local information. We reanalyzed the data to report other percentiles of the time to recovery and adopted the bootstrap method and permutation test to construct the confidence intervals as well as the P values. The restricted mean time to recovery (RMTR) was also computed as a global and robust measure for efficacy. Results: For the lopinavir-ritonavir trial, with the increase of sample size from 160 to 199, the type I error rate was inflated from 0.05 to 0.071. The difference of terminal rates was -8.74% (95% CI [-21.04, 3.55]; P=.16) and the hazards ratio (HR) adjusted for terminal rates was 1.05 (95% CI [0.78, 1.42]; P=.74), indicating no significant difference. The difference of RMTIs between the two groups evaluated at day 28 was -1.67 days (95% CI [-3.62, 0.28]; P=.09) in favor of lopinavir-ritonavir but not statistically significant. For the remdesivir trial of Wang et al., the difference of terminal rates was -0.89% (95% CI [-2.84, 1.06]; P=.19) and the HR adjusted for terminal rates was 0.92 (95% CI [0.63, 1.35]; P=.67). The difference of RMTIs at day 28 was -0.89 day (95% CI [-2.84, 1.06]; P=.37). The planned sample size was 453, yet only 236 patients were enrolled. The conditional prediction shows that the HR estimates would reach statistical significance if the target sample size had been maintained, and both conditional and unconditional prediction delivered significant HR results if the trial had continued to double the target sample size. For the remdesivir trial of Beigel et al., the difference of RMTRs between the remdesivir and placebo groups up to day 30 was -2.7 days (95% CI [-4.0, -1.2]; P<.001), confirming the superiority of remdesivir. The difference in recovery time at the 25th percentile (95% CI [-3, 0]; P=.65) was insignificant, while the differences manifested to be statistically significant at larger percentiles. Conclusions: Based on the statistical issues and lessons learned from the recent three clinical trials on COVID-19 treatments, we suggest more appropriate approaches for the design and analysis for ongoing and future COVID-19 trials.
    Keywords covid19
    Publisher MedRxiv; WHO
    Document type Article ; Online
    DOI 10.1101/2020.06.17.20133702
    Database COVID19

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