Identifying potential moderators for response to treatment in low back pain: A systematic review

Gurung, Tara; Ellard, David R; Mistry, Dipesh; Patel, Shilpa; Underwood, Martin

doi:10.1016/j.physio.2015.01.006

Cited by 59 publications

(71 citation statements)

References 34 publications

(62 reference statements)

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“…62 We hypothesized that prognostic stratified care would be less effective compared to best current care for older (≥65 years) compared to younger patients. 28, 32, 46, 63, 66, 76 …”

Section: Methodsmentioning

confidence: 99%

“…We hypothesized that prognostic stratified care would be less effective compared to best current care for patients reporting lower expectations for recovery. 4, 8, 22, 28, 33, 54 …”

Section: Methodsmentioning

confidence: 99%

“…44, 59 Pincus et al 59 recommend four key criteria for treatment effect modification analysis using clinical trial data: 1) potential modifiers should be measured prior to randomization; 2) selection of potential modifiers should be based on theory or evidence; 3) measurement of baseline factors should be reliable and valid; and 4) an explicit test of the interaction between potential modifiers and treatment is required. Gurung et al 28 recently used these criteria in their systematic review of potential LBP treatment effect modifiers from four clinical trials, testing acupuncture, 12, 78 exercise and manual therapy, 71 and psychological treatment. 46 Variables associated with treatment outcome that had strong evidence included patients’ age, employment status and type, back pain severity, narcotic medication use, treatment expectations and education level.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Treatment Effect Modifiers in the STarT Back Trial: A Secondary Analysis

Beneciuk

Hill

Campbell

et al. 2017

The Journal of Pain

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Identification of patient characteristics influencing treatment outcomes is a top low back pain (LBP) research priority. Results from the STarT Back Trial support the effectiveness of prognostic stratified care for LBP compared to current best care, however patient characteristics associated with treatment response have not yet been explored. The purpose of this secondary analysis was to identify treatment-effect modifiers within the STarT Back Trial at 4 months follow-up (n=688). Treatment response was dichotomized using back-specific physical disability measured by the Roland-Morris Disability Questionnaire (≥7). Candidate modifiers were identified using previous literature and evaluated using logistic regression with statistical interaction terms to provide preliminary evidence of treatment-effect modification. Socioeconomic status (SES) was identified as an effect modifier for disability outcomes (OR = 1.71, P=.028). High SES patients receiving prognostic stratified care were 2.5 times less likely to have a poor outcome compared to low SES patients receiving best current care (OR = 0.40, P=.006). Education level (OR = 1.33, P=.109) and number of pain medications (OR = 0.64, P=.140) met our criteria for effect modification with weaker evidence (0.20>P≥0.05). These findings provide preliminary evidence for SES, education, and number of pain medications as treatment-effect modifiers of prognostic stratified care delivered in the STarT Back Trial. Perspective This analysis provides preliminary exploratory findings about the characteristics of patients who might least likely benefit from targeted treatment using prognostic stratified care for low back pain.

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“…62 We hypothesized that prognostic stratified care would be less effective compared to best current care for older (≥65 years) compared to younger patients. 28, 32, 46, 63, 66, 76 …”

Section: Methodsmentioning

confidence: 99%

“…We hypothesized that prognostic stratified care would be less effective compared to best current care for patients reporting lower expectations for recovery. 4, 8, 22, 28, 33, 54 …”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identifying Treatment Effect Modifiers in the STarT Back Trial: A Secondary Analysis

Beneciuk

Hill

Campbell

et al. 2017

The Journal of Pain

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“…Treatment moderators identified in Stage 1 and those that have been identified in the systematic review (see Table 9.1; Gurung et al, 2013) will make up the list of covariates to be considered for the clinical/health economic prediction rules analysis.…”

Section: Modellingmentioning

confidence: 99%

Identifying back pain subgroups: developing and applying approaches using individual patient data collected within clinical trials

Patel

Hee

Mistry

et al. 2016

Programme Grants Appl Res

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Total word count including appendix: 93,499 ii ABSTRACT BackgroundThere is good evidence that therapist delivered interventions have modest beneficial effects for people with low back pain (LBP). Identification of subgroups of people with LBP who may benefit from these different treatment approaches is an important research priority. Aim and objectivesOverall aim was to improve the clinical and cost-effectiveness of LBP treatment by providing patients, their clinical advisors, and health service purchasers with better information about which participants are most likely to benefit from which treatment To achieve these objectives required substantial methodological work including the development and evaluation of some novel statistical approaches. This programme of work was not designed to analyse main effect of interventions and no such interpretations should be made.iii MethodsFirstly, we reviewed the literature on treatment moderators and subgroups. We initially invited investigators of trials of therapist-delivered interventions for LBP with >179 participants to share their data with us; some further smaller trials offered to us were also included. Using these trials we developed a repository of individual participant data of therapist delivered interventions for LBP. Using this dataset we sought to identify which participant characteristics, if any, predict response to different treatments (moderators) for clinical and cost effectiveness outcomes.We did an ANCOVA to identify potential moderators to apply in our main analyses.Subsequently we developed and applied three methods of subgroup identification; recursive partitioning (interaction trees and subgroup identification based on a differential effect search), adaptive risk group refinement, and an individual participant data indirect network meta-analysis to identify sub-groups defined by multiple parameters. ResultsWe included data from 19 randomised controlled trials with 9,328 participants (mean age 49 years, 57% females). Our prespecified analyses using recursive partitioning and adaptive risk group refinement performed well and allowed us to identify some subgroups. The differences in the effect size in the different subgroups were typically small, and unlikely to be clinically meaningful. Increasing baseline severity on the outcome of interest was the strongest driver of sub-group identification that we identified. Additionally we explored the application of Bayesian indirect network metaanalysis. This method produced varying probabilities that a particular treatment choice would be most likely to be effective for a specific patient profile. ConclusionThese data lack clinical or cost-effectiveness justification for the use of baseline characteristics in the development of subgroups for back pain. The methodological developments from this work have the potential to be applied in other clinical areas.iv The pooled repository database will serve as a valuable resource to the LBP research community. FundingFunding from the NIHR Programme Grants for Ap...

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“…These are all important factors to include when making a decision about intervention, not only due to the risk of a poor outcome, but also to ensure that the symptoms from which the patient is suffering are targeted. Another factor is treatment expectation; in patients with non-specific LBP, those with greater positive expectation gain more benefit from non-surgical treatments (such as acupuncture, group cognitive behavioural approach, group exercise, and manual therapy followed by exercise) (41).…”

Section: Psychological Factorsmentioning

confidence: 99%

Pre-surgery physiotherapy and pain thresholds in patients with degenerative lumbar spine disorders

Lindbäck¹

2018

Linköping University Medical Dissertations

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Identifying potential moderators for response to treatment in low back pain: A systematic review

Abstract: There are insufficient robust data on moderators to be useful in clinical practice. This review has identified some important potential moderators of treatment effect worthy of testing in future confirmatory analyses.

Cited by 59 publications

References 34 publications

Identifying Treatment Effect Modifiers in the STarT Back Trial: A Secondary Analysis

Identifying Treatment Effect Modifiers in the STarT Back Trial: A Secondary Analysis

Identifying back pain subgroups: developing and applying approaches using individual patient data collected within clinical trials

Pre-surgery physiotherapy and pain thresholds in patients with degenerative lumbar spine disorders

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