Clinical Trial Data Sharing for COVID-19-Related Research

Louis Dron, Alison Dillman, Michael J Zoratti, Jonas Haggstrom, Edward J Mills, Jay J H Park, Louis Dron, Alison Dillman, Michael J Zoratti, Jonas Haggstrom, Edward J Mills, Jay J H Park

Abstract

This paper aims to provide a perspective on data sharing practices in the context of the COVID-19 pandemic. The scientific community has made several important inroads in the fight against COVID-19, and there are over 2500 clinical trials registered globally. Within the context of the rapidly changing pandemic, we are seeing a large number of trials conducted without results being made available. It is likely that a plethora of trials have stopped early, not for statistical reasons but due to lack of feasibility. Trials stopped early for feasibility are, by definition, statistically underpowered and thereby prone to inconclusive findings. Statistical power is not necessarily linear with the total sample size, and even small reductions in patient numbers or events can have a substantial impact on the research outcomes. Given the profusion of clinical trials investigating identical or similar treatments across different geographical and clinical contexts, one must also consider that the likelihood of a substantial number of false-positive and false-negative trials, emerging with the increasing overall number of trials, adds to public perceptions of uncertainty. This issue is complicated further by the evolving nature of the pandemic, wherein baseline assumptions on control group risk factors used to develop sample size calculations are far more challenging than those in the case of well-documented diseases. The standard answer to these challenges during nonpandemic settings is to assess each trial for statistical power and risk-of-bias and then pool the reported aggregated results using meta-analytic approaches. This solution simply will not suffice for COVID-19. Even with random-effects meta-analysis models, it will be difficult to adjust for the heterogeneity of different trials with aggregated reported data alone, especially given the absence of common data standards and outcome measures. To date, several groups have proposed structures and partnerships for data sharing. As COVID-19 has forced reconsideration of policies, processes, and interests, this is the time to advance scientific cooperation and shift the clinical research enterprise toward a data-sharing culture to maximize our response in the service of public health.

Keywords: COVID-19; assessment; bias; challenge; clinical trials; cooperation; data; data-sharing; dataset; error; feasibility; interoperability; intervention; privacy; recruitment; registry; research; security.

Conflict of interest statement

Conflicts of Interest: None declared.

©Louis Dron, Alison Dillman, Michael J Zoratti, Jonas Haggstrom, Edward J Mills, Jay J H Park. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.03.2021.

Figures

Figure 1
Figure 1
Summary of registered clinical trial status for COVID-19–related research.

References

    1. Sohrabi C, Alsafi Z, O'Neill N, Khan M, Kerwan A, Al-Jabir A, Iosifidis C, Agha R. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19) Int J Surg. 2020 Apr;76:71–76. doi: 10.1016/j.ijsu.2020.02.034.
    1. Fauci A, Lane H, Redfield R. Covid-19 - navigating the uncharted. N Engl J Med. 2020 Mar 26;382(13):1268–1269. doi: 10.1056/NEJMe2002387.
    1. Velavan TP, Meyer CG. The COVID-19 epidemic. Trop Med Int Health. 2020 Mar;25(3):278–280. doi: 10.1111/tmi.13383. doi: 10.1111/tmi.13383.
    1. Thorlund K, Dron L, Park J, Hsu G, Forrest JI, Mills EJ. A real-time dashboard of clinical trials for COVID-19. The Lancet Digital Health. 2020 Jun;2(6):e286–e287. doi: 10.1016/s2589-7500(20)30086-8.
    1. Siemieniuk RA, Bartoszko JJ, Ge L, Zeraatkar D, Izcovich A, Kum E, Pardo-Hernandez H, Rochwerg B, Lamontagne F, Han MA, Liu Q, Agarwal A, Agoritsas T, Chu DK, Couban R, Darzi A, Devji T, Fang B, Fang C, Flottorp SA, Foroutan F, Ghadimi M, Heels-Ansdell D, Honarmand K, Hou L, Hou X, Ibrahim Q, Khamis A, Lam B, Loeb M, Marcucci M, McLeod SL, Motaghi S, Murthy S, Mustafa RA, Neary JD, Qasim A, Rada G, Riaz IB, Sadeghirad B, Sekercioglu N, Sheng L, Sreekanta A, Switzer C, Tendal B, Thabane L, Tomlinson G, Turner T, Vandvik PO, Vernooij RW, Viteri-García Andrés, Wang Y, Yao L, Ye Z, Guyatt GH, Brignardello-Petersen R. Drug treatments for covid-19: living systematic review and network meta-analysis. BMJ. 2020 Jul 30;370:m2980. doi: 10.1136/bmj.m2980.
    1. Liu N, Huang R, Baldacchino T, Sud A, Sud K, Khadra M, Kim J. Telehealth for noncritical patients with Chronic diseases during the COVID-19 pandemic. J Med Internet Res. 2020 Aug 07;22(8):e19493. doi: 10.2196/19493.
    1. Mascha E, Schober P, Schefold J, Stueber F, Luedi MM. Staffing with disease-based epidemiologic indices may reduce shortage of intensive care unit staff during the COVID-19 pandemic. Anesth Analg. 2020 Jul;131(1):24–30. doi: 10.1213/ANE.0000000000004849.
    1. Mitchell EJ, Ahmed K, Breeman S, Cotton S, Constable L, Ferry G, Goodman K, Hickey H, Meakin G, Mironov K, Quann N, Wakefield N, McDonald A. It is unprecedented: trial management during the COVID-19 pandemic and beyond. Trials. 2020 Sep 11;21(1):784. doi: 10.1186/s13063-020-04711-6.
    1. Cunniffe NG, Gunter SJ, Brown M, Burge SW, Coyle C, De Soyza A, Dymond T, Esmail H, Francis DP, Galloway J, Galloway JB, Gkrania-Klotsas E, Greenaway J, Katritsis G, Kanagaratnam P, Knolle MD, Leonard K, McIntyre ZC, Prudon B, Rampling T, Torok ME, Warne B, Yates M, Matheson NJ, Su L, Villar S, Stewart GD, Toshner M. How achievable are COVID-19 clinical trial recruitment targets? A UK observational cohort study and trials registry analysis. BMJ Open. 2020 Oct 05;10(10):e044566. doi: 10.1136/bmjopen-2020-044566.
    1. Petkova E, Antman EM, Troxel AB. Pooling data from individual clinical trials in the COVID-19 era. JAMA. 2020 Aug 11;324(6):543–545. doi: 10.1001/jama.2020.13042.
    1. Cosgriff CV, Ebner DK, Celi LA. Data sharing in the era of COVID-19. The Lancet Digital Health. 2020 May;2(5):e224. doi: 10.1016/s2589-7500(20)30082-0.
    1. Riley RD, Lambert PC, Abo-Zaid G. Meta-analysis of individual participant data: rationale, conduct, and reporting. BMJ. 2010 Feb 05;340:c221. doi: 10.1136/bmj.c221.
    1. Gorna R, MacDermott N, Rayner C, O’Hara M, Evans S, Agyen L, Nutland W, Rogers N, Hastie C. Long COVID guidelines need to reflect lived experience. The Lancet. 2021 Feb;397(10273):455–457. doi: 10.1016/s0140-6736(20)32705-7.
    1. Tierney JF, Fisher DJ, Burdett S, Stewart LA, Parmar MKB. Comparison of aggregate and individual participant data approaches to meta-analysis of randomised trials: An observational study. PLoS Med. 2020 Jan;17(1):e1003019. doi: 10.1371/journal.pmed.1003019.
    1. Taichman DB, Sahni P, Pinborg A, Peiperl L, Laine C, James A, Hong S, Haileamlak A, Gollogly L, Godlee F, Frizelle FA, Florenzano F, Drazen JM, Bauchner H, Baethge C, Backus J. Data sharing statements for clinical trials: a requirement of the International Committee of Medical Journal Editors. JAMA. 2017 Jun 27;317(24):2491–2492. doi: 10.1001/jama.2017.6514.
    1. Carr D. Sharing research data and findings relevant to the novel coronavirus (COVID-19) outbreak. Wellcome - Press Release. 2020. Jan 31, [2021-03-10]. .
    1. International COVID-19 Data Alliance (ICODA) [2020-12-22].
    1. International COVID-19 Data Alliance (ICODA) Health Data Research UK. [2020-12-22].
    1. Bierer BE, Li R, Barnes M, Sim I. A global, neutral platform for sharing trial data. N Engl J Med. 2016 Jun 23;374(25):2411–2413. doi: 10.1056/nejmp1605348.
    1. COVID-19 - TransCelerate. TansCelerate Biopharma Inc. [2021-03-10].
    1. Transparency during global health emergencies. The Lancet Digital Health. 2020 Sep;2(9):e441. doi: 10.1016/s2589-7500(20)30198-9.
    1. Pandemic fatigue - reinvigorating the public to prevent COVID-19. WHO Regional Office for Europe. 2020. Oct 05, [2021-03-10]. .

Source: PubMed

Sponsorzy i współpracownicy

Warunki medyczne

Interwencje lekowe

3
Subskrybuj