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A modelling framework for estimation of comparative effectiveness in pharmaceuticals using uncontrolled clinical trials

Hatswell, Anthony James; (2020) A modelling framework for estimation of comparative effectiveness in pharmaceuticals using uncontrolled clinical trials. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

Pharmaceuticals are most commonly studied in randomised controlled trials (RCTs) against a control arm (either active, or placebo). On occasions however treatments are licensed exclusively on the basis of uncontrolled study data - this thesis investigates how comparative effectiveness can be estimated under such circumstances. The role of RCTs in the approval and estimation of comparative effectiveness in pharmaceuticals is discussed, as well as potential methods for analysis where RCT data are not available. A review of all drug approvals from 1999-2014 by the European Medicines Agency and the US Food and Drug Administration is then presented. Performing literature searches in the majority of cases (80%), historical controls have been the primary source of estimates of comparative effectiveness, frequently without attempts to adjust for differences between studies. Given the high usage of historical controls, I focussed on the role of adjustment. This included a simulation study to understand where the method of Matching Adjusted Indirect Comparison (MAIC) is likely to be of use, looking specifically at the effect of model misspecification. Three novel methods (with practical examples) for the creation of historical controls are then presented; using extrapolation from the previous line of therapy, using non-responders to therapy as a surrogate, and comparing to a patient’s own prior data. The conclusion of the work is that there are clearly situations where RCTs cannot, or will not be used – regardless of the statistical issues this raises. In such cases by proactively identifying appropriate historical data, and using appropriate analysis methods – the downsides can be ameliorated, at least in part. A flowchart presenting the available methods (split by data access) is presented. Further research is required on the appropriateness of different sources of historical control data (e.g. registries versus RCT arms), and how to synthesize multiple estimates of effectiveness (e.g. multiple MAICs).

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: A modelling framework for estimation of comparative effectiveness in pharmaceuticals using uncontrolled clinical trials
Event: UCL (University College London)
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2020. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10101174
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