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

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.