Literature DB >> 33593341

Identification of subgroup effect with an individual participant data meta-analysis of randomised controlled trials of three different types of therapist-delivered care in low back pain.

Siew Wan Hee1, Dipesh Mistry2, Tim Friede3, Sarah E Lamb4, Nigel Stallard1, Martin Underwood5,6, Shilpa Patel5.   

Abstract

BACKGROUND: Proven treatments for low back pain, at best, only provide modest overall benefits. Matching people to treatments that are likely to be most effective for them may improve clinical outcomes and makes better use of health care resources.
METHODS: We conducted an individual participant data meta-analysis of randomised controlled trials of three types of therapist delivered interventions for low back pain (active physical, passive physical and psychological treatments). We applied two statistical methods (recursive partitioning and adaptive risk group refinement) to identify potential subgroups who might gain greater benefits from different treatments from our individual participant data meta-analysis.
RESULTS: We pooled data from 19 randomised controlled trials, totalling 9328 participants. There were 5349 (57%) females with similar ratios of females in control and intervention arms. The average age was 49 years (standard deviation, SD, 14). Participants with greater psychological distress and physical disability gained most benefit in improving on the mental component scale (MCS) of SF-12/36 from passive physical treatment than non-active usual care (treatment effects, 4.3; 95% confidence interval, CI, 3.39 to 5.15). Recursive partitioning method found that participants with worse disability at baseline gained most benefit in improving the disability (Roland Morris Disability Questionnaire) outcome from psychological treatment than non-active usual care (treatment effects, 1.7; 95% CI, 1.1 to 2.31). Adaptive risk group refinement did not find any subgroup that would gain much treatment effect between psychological and non-active usual care. Neither statistical method identified any subgroups who would gain an additional benefit from active physical treatment compared to non-active usual care.
CONCLUSIONS: Our methodological approaches worked well and may have applicability in other clinical areas. Passive physical treatments were most likely to help people who were younger with higher levels of disability and low levels of psychological distress. Psychological treatments were more likely to help those with severe disability. Despite this, the clinical importance of identifying these subgroups is limited. The sizes of sub-groups more likely to benefit and the additional effect sizes observed are small. Our analyses provide no evidence to support the use of sub-grouping for people with low back pain.

Entities:  

Keywords:  IPD; Low back pain; Physical interventions; Psychological interventions; Stratification; Subgroups; Therapist delivered interventions

Mesh:

Year:  2021        PMID: 33593341      PMCID: PMC7885433          DOI: 10.1186/s12891-021-04028-8

Source DB:  PubMed          Journal:  BMC Musculoskelet Disord        ISSN: 1471-2474            Impact factor:   2.362


  38 in total

1.  Subgroup analyses in randomized trials: risks of subgroup-specific analyses; power and sample size for the interaction test.

Authors:  Sara T Brookes; Elise Whitely; Matthias Egger; George Davey Smith; Paul A Mulheran; Tim J Peters
Journal:  J Clin Epidemiol       Date:  2004-03       Impact factor: 6.437

2.  Adaptive risk group refinement.

Authors:  Michael LeBlanc; James Moon; John Crowley
Journal:  Biometrics       Date:  2005-06       Impact factor: 2.571

3.  A randomized trial comparing a group exercise programme for back pain patients with individual physiotherapy in a severely deprived area.

Authors:  Jane L Carr; Jennifer A Klaber Moffett; Elaine Howarth; Stewart J Richmond; David J Torgerson; David A Jackson; Caroline J Metcalfe
Journal:  Disabil Rehabil       Date:  2005-08-19       Impact factor: 3.033

4.  Randomised controlled trial of exercise for low back pain: clinical outcomes, costs, and preferences.

Authors:  J K Moffett; D Torgerson; S Bell-Syer; D Jackson; H Llewlyn-Phillips; A Farrin; J Barber
Journal:  BMJ       Date:  1999-07-31

5.  Group cognitive behavioural treatment for low-back pain in primary care: a randomised controlled trial and cost-effectiveness analysis.

Authors:  Sarah E Lamb; Zara Hansen; Ranjit Lall; Emanuela Castelnuovo; Emma J Withers; Vivien Nichols; Rachel Potter; Martin R Underwood
Journal:  Lancet       Date:  2010-02-25       Impact factor: 79.321

Review 6.  Nonpharmacologic therapies for acute and chronic low back pain: a review of the evidence for an American Pain Society/American College of Physicians clinical practice guideline.

Authors:  Roger Chou; Laurie Hoyt Huffman
Journal:  Ann Intern Med       Date:  2007-10-02       Impact factor: 25.391

7.  Identifying patients with chronic pain who respond to acupuncture: results from an individual patient data meta-analysis.

Authors:  Nadine E Foster; Emily A Vertosick; George Lewith; Klaus Linde; Hugh MacPherson; Karen J Sherman; Claudia M Witt; Andrew J Vickers
Journal:  Acupunct Med       Date:  2020-06-22       Impact factor: 2.267

8.  Methodological criteria for the assessment of moderators in systematic reviews of randomised controlled trials: a consensus study.

Authors:  Tamar Pincus; Clare Miles; Robert Froud; Martin Underwood; Dawn Carnes; Stephanie J C Taylor
Journal:  BMC Med Res Methodol       Date:  2011-01-31       Impact factor: 4.615

9.  Comparison of stratified primary care management for low back pain with current best practice (STarT Back): a randomised controlled trial.

Authors:  Jonathan C Hill; David G T Whitehurst; Martyn Lewis; Stirling Bryan; Kate M Dunn; Nadine E Foster; Kika Konstantinou; Chris J Main; Elizabeth Mason; Simon Somerville; Gail Sowden; Kanchan Vohora; Elaine M Hay
Journal:  Lancet       Date:  2011-09-28       Impact factor: 79.321

10.  Can we convert between outcome measures of disability for chronic low back pain?

Authors:  Tom Morris; Siew Wan Hee; Nigel Stallard; Martin Underwood; Shilpa Patel
Journal:  Spine (Phila Pa 1976)       Date:  2015-05-15       Impact factor: 3.468

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  2 in total

1.  Significant other interactions in people with chronic low back pain: Subgrouping and multidimensional profiles.

Authors:  Martin Rabey; Brendan Buldo; Magnus Duesund Helland; Courtenay Pang; Michelle Kendell; Darren Beales
Journal:  Br J Pain       Date:  2021-12-27

Review 2.  Spinal manipulative therapy in older adults with chronic low back pain: an individual participant data meta-analysis.

Authors:  Alan Jenks; Annemarie de Zoete; Maurits van Tulder; Sidney M Rubinstein
Journal:  Eur Spine J       Date:  2022-05-28       Impact factor: 2.721

  2 in total

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