The statistical approach in trial-based economic evaluations matters: get your statistics together!

Elizabeth N. Mutubuki, Mohamed El Alili*, Judith E. Bosmans, Teddy Oosterhuis, Frank J. Snoek, Raymond W.J.G. Ostelo, Maurits W. van Tulder, Johanna M. van Dongen

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

BACKGROUND: Baseline imbalances, skewed costs, the correlation between costs and effects, and missing data are statistical challenges that are often not adequately accounted for in the analysis of cost-effectiveness data. This study aims to illustrate the impact of accounting for these statistical challenges in trial-based economic evaluations.

METHODS: Data from two trial-based economic evaluations, the REALISE and HypoAware studies, were used. In total, 14 full cost-effectiveness analyses were performed per study, in which the four statistical challenges in trial-based economic evaluations were taken into account step-by-step. Statistical approaches were compared in terms of the resulting cost and effect differences, ICERs, and probabilities of cost-effectiveness.

RESULTS: In the REALISE study and HypoAware study, the ICER ranged from 636,744€/QALY and 90,989€/QALY when ignoring all statistical challenges to - 7502€/QALY and 46,592€/QALY when accounting for all statistical challenges, respectively. The probabilities of the intervention being cost-effective at 0€/ QALY gained were 0.67 and 0.59 when ignoring all statistical challenges, and 0.54 and 0.27 when all of the statistical challenges were taken into account for the REALISE study and HypoAware study, respectively.

CONCLUSIONS: Not accounting for baseline imbalances, skewed costs, correlated costs and effects, and missing data in trial-based economic evaluations may notably impact results. Therefore, when conducting trial-based economic evaluations, it is important to align the statistical approach with the identified statistical challenges in cost-effectiveness data. To facilitate researchers in handling statistical challenges in trial-based economic evaluations, software code is provided.

Original languageEnglish
Article number475
Pages (from-to)1-12
Number of pages12
JournalBMC health services research
Volume21
Issue number1
Early online date19 May 2021
DOIs
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
Both the REALISE and HypoAware studies were funded by the Netherlands Organization for Health Research and Development (REALISE-171102010 and HypoAware - 837001406).

Funding Information:
Raymond W.J.G. Ostelo reports grants from The Netherlands Organization for Scientific Research, grants from The Netherlands Organization for Health Research and Development, grants from SIA-RAAK PRO, grants from European Centre for Chiropractic Research Excellence (ECCRE), grants from EUROSPINE, grants from FRIESLAND Zorgverzekeraar, grants from Scientific College Physiotherapy (WCF) of the Royal Dutch Association for Physiotherapy (KNGF), grants from CZ Health Care Insurance and grants from The European Chiropractic Union (ECU), outside the submitted work; Frank J. Snoek reports grants from ZonMW - Dutch Health Services Research, during the conduct of the HypoAware study; Maurits W. van Tulder reports non-financial support from various professional organizations, others from Swedish and Canadian governmental grant agencies and grants from various research grant agencies, outside the submitted work; Elizabeth N. Mutubuki, Mohamed El Alili, Judith E. Bosmans, Teddy Oosterhuis and Johanna M. van Dongen declare that they have no conflict of interest.

Publisher Copyright:
© 2021, The Author(s).

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

  • Baseline imbalances
  • Clinical trial
  • Cost-benefit analysis
  • Missing data
  • Skewed data
  • Statistical methods

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