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

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.

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

“…While many suggested possible interventions for Clusters 2 and 3 are psychological in nature recent research suggests those with higher disability levels may show greater improvements from such interventions . 82…”

“…While many suggested possible interventions for Clusters 2 and 3 are psychological in nature recent research suggests those with higher disability levels may show greater improvements from such interventions. 82 Multiple comparisons in this study increase the possibility of type I error. 83 However, as LCA is an exploratory technique for determining the existence of clusters, 77 when profiling derived clusters it may be more appropriate to maintain p-values such that there may be a greater chance of a type I error but less chance of a type II error.…”

Best Practice Physiotherapy for Patients with Low Back Pain in Primary Care : Clinical Outcomes and Explanatory Factors

“…One systematic review that included larger randomised controlled trials (RCT) found the following potential treatment moderators in LBP interventions on disability and pain (high evidence): age, employment status, back pain status, medication use, treatment expectations and educational level 90 . All factors, except treatment expectations, have been confirmatory tested 91,92 in metaanalyses of individual participant data 93 . However, they failed to reach clinically meaningful levels of effect modification of different therapist delivered interventions compared to non-active usual care 91 , or of manipulative treatment compared to other treatments 92 .…”

“…All factors, except treatment expectations, have been confirmatory tested 91,92 in metaanalyses of individual participant data 93 . However, they failed to reach clinically meaningful levels of effect modification of different therapist delivered interventions compared to non-active usual care 91 , or of manipulative treatment compared to other treatments 92 . Identifying and confirming factors moderating the treatment effects is challenging due to inconsistent availability of participant characteristics, heterogeneity in treatments, and insufficient power to plausibly show an interaction effect [90][91][92] .…”

Do baseline patient reported outcome measures predict changes in self-reported function, following a chronic pain rehabilitation programme?

“…4 Stratification using a screening tool, clinical judgement or according to baseline patient reported outcomes, could reduce the burden of disability and assist with delivery of the right care at the right time. 5,6 Recent guidance issued by NICE 7 found insufficient evidence to indicate whether any psychological, biological or social factors are predictive of successful outcomes in pain management and further research into barriers to successful pain management were recommended. 7 The potential for high risk of bias, in the current evidence base was highlighted due to exclusion of people in studies with particular psychological prognostic features.…”