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Systematic Review of Decision Analytic Modelling in Economic Evaluations of Low Back Pain and Sciatica

  • James A. HallEmail author
  • Kika Konstantinou
  • Martyn Lewis
  • Raymond Oppong
  • Reuben Ogollah
  • Sue Jowett
Systematic Review

Abstract

Background

Low back pain (LBP) and sciatica place significant burden on individuals and healthcare systems, with societal costs alone likely to be in excess of £15 billion. Two recent systematic reviews for LBP and sciatica identified a shortage of modelling studies in both conditions.

Objectives

The aim of this systematic review was to document existing model-based economic evaluations for the treatment and management of both conditions; critically appraise current modelling techniques, analytical methods, data inputs, and structure, using narrative synthesis; and identify unresolved methodological problems and gaps in the literature.

Methods

A systematic literature review was conducted whereby 6512 records were extracted from 11 databases, with no date limits imposed. Studies were abstracted according to a predesigned protocol, whereby they must be economic evaluations that employed an economic decision model and considered any management approach for LBP and sciatica. Study abstraction was initially performed by one reviewer who removed duplicates and screened titles to remove irrelevant studies. Overall, 133 potential studies for inclusion were then screened independently by other reviewers. Consensus was reached between reviewers regarding final inclusion.

Results

Twenty-one publications of 20 unique models were included in the review, five of which were modelling studies in LBP and 16 in sciatica. Results revealed a poor standard of modelling in both conditions, particularly regarding modelling techniques, analytical methods, and data quality. Specific issues relate to inappropriate representation of both conditions in terms of health states, insufficient time horizons, and use of inappropriate utility values.

Conclusion

High-quality modelling studies, which reflect modelling best practice, as well as contemporary clinical understandings of both conditions, are required to enhance the economic evidence for treatments for both conditions.

Notes

Acknowledgements

Nadia Corp, Research Associate: Systematic Reviews at Keele University, assisted with the development of the search strategy.

Author Contributions

JH, SJ, KK, RaO and ReO contributed to the study conception and design, design of the search strategies and article selection, and interpretation of data. JH conducted the search strategies and retrieved identified articles, performed data extraction, and drafted the manuscript. JH, SJ, KK, RaO, ML contributed to manuscript preparation. All authors approved the final version of the article.

Compliance with Ethical Standards

This research was undertaken as part of a PhD project, with a 3-year research stipend for JAH funded by the Institute for Primary Care and Health Sciences, Keele University. KK was supported through a Higher Education Funding Council for England (HEFCE) Senior Clinical Lecturer award.

Conflict of interest

ML, RaO, ReO, and SJ have no conflicts of interest to declare.

Supplementary material

40258_2019_471_MOESM1_ESM.pdf (12 kb)
Supplementary material 1 (PDF 12 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Arthritis Research UK Primary Care Centre, Research Institute for Primary Care and Health SciencesKeele UniversityStaffordshireUK
  2. 2.Haywood Hospital, Midlands Partnership Foundation TrustStaffordshireUK
  3. 3.Keele Clinical Trials Unit, Keele UniversityStaffordshireUK
  4. 4.Health Economics Unit, Institute of Applied Health ResearchUniversity of BirminghamBirminghamUK
  5. 5.Nottingham Clinical Trials Unit, School of Medicine, University of NottinghamNottinghamUK

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