Prognostic Factors and Models for Predicting Work Absence in Adults with Musculoskeletal Conditions Consulting a Healthcare Practitioner: A Systematic Review.

PURPOSE: It is difficult to predict which employees, in particular those with musculoskeletal pain, will return to work quickly without additional vocational advice and support, which employees will require this support and what levels of support are most appropriate. Consequently, there is no way of ensuring the right individuals are directed towards the right services to support their occupational health needs. The aim of this review will be to identify prognostic factors for duration of work absence in those already absent and examine the utility of prognostic models for work absence. METHODS: Eight databases were search using a combination of subject headings and key words focusing on work absence, musculoskeletal pain and prognosis. Two authors independently assessed the eligibility of studies, extracted data from all eligible studies and assessed risk of bias using the QUIPS or PROBAST tools, an adapted GRADE was used to assess the strength of the evidence. To make sense of the data prognostic variables were grouped according to categories from the Disability Prevention Framework and the SWiM framework was utilised to synthesise findings. RESULTS: A total of 23 studies were included in the review, including 13 prognostic models and a total of 110 individual prognostic factors. Overall, the evidence for all prognostic factors was weak, although there was some evidence that older age and better recovery expectations were protective of future absence and that previous absence was likely to predict future absences. There was weak evidence for any of the prognostic models in determining future sickness absence. CONCLUSION: Analysis was difficult due to the wide range of measures of both prognostic factors and outcome and the differing timescales for follow-up. Future research should ensure that consistent measures are employed and where possible these should be in-line with those suggested by Ravinskaya et al. (2023).

One-stage individual participant data meta-analysis models for continuous and binary outcomes: Comparison of treatment coding options and estimation methods.

A one-stage individual participant data (IPD) meta-analysis synthesizes IPD from multiple studies using a general or generalized linear mixed model. This produces summary results (eg, about treatment effect) in a single step, whilst accounting for clustering of participants within studies (via a stratified study intercept, or random study intercepts) and between-study heterogeneity (via random treatment effects). We use simulation to evaluate the performance of restricted maximum likelihood (REML) and maximum likelihood (ML) estimation of one-stage IPD meta-analysis models for synthesizing randomized trials with continuous or binary outcomes. Three key findings are identified. First, for ML or REML estimation of stratified intercept or random intercepts models, a t-distribution based approach generally improves coverage of confidence intervals for the summary treatment effect, compared with a z-based approach. Second, when using ML estimation of a one-stage model with a stratified intercept, the treatment variable should be coded using "study-specific centering" (ie, 1/0 minus the study-specific proportion of participants in the treatment group), as this reduces the bias in the between-study variance estimate (compared with 1/0 and other coding options). Third, REML estimation reduces downward bias in between-study variance estimates compared with ML estimation, and does not depend on the treatment variable coding; for binary outcomes, this requires REML estimation of the pseudo-likelihood, although this may not be stable in some situations (eg, when data are sparse). Two applied examples are used to illustrate the findings.

Comparative effectiveness of treatment options for plantar heel pain: a systematic review with network meta-analysis.

OBJECTIVE: To evaluate the comparative effectiveness of current treatment options for plantar heel pain (PHP). DESIGN: Systematic review and network meta-analysis (NMA). DATA SOURCES: Medline, EMBASE, CINAHL, AMED, PEDro, Cochrane Database, Web of Science and WHO Clinical Trials Platform were searched from their inception until January 2018. STUDY SELECTION: Randomised controlled trials (RCTs) of adults with PHP investigating common treatments (ie, corticosteroid injection, non-steroidal anti-inflammatory drugs, therapeutic exercise, orthoses and/or extracorporeal shockwave therapy (ESWT)) compared with each other or a no treatment, placebo/sham control. DATA EXTRACTION AND ANALYSIS: Data were extracted and checked for accuracy and completeness by pairs of reviewers. Primary outcomes were pain and function. Comparative treatment effects were analysed by random effects NMA in the short term, medium term and long term. Relative ranking of treatments was assessed by surface under the cumulative ranking probabilities (0-100 scale). RESULTS: Thirty-one RCTs (total n=2450 patients) were included. There was no evidence of inconsistency detected between direct and indirect treatment comparisons in the networks, but sparse data led to frequently wide CIs. Available evidence does not suggest that any of the commonly used treatments for the management of PHP are better than any other, although corticosteroid injections, alone or in combination with exercise, and ESWT were ranked most likely to be effective for the management of short-term, medium-term and long-term pain or function; placebo/sham/control appeared least likely to be effective; and exercise appeared to only be beneficial for long-term pain or function. CONCLUSIONS: Current evidence is equivocal regarding which treatment is the most effective for the management of PHP. Given limited understanding of long-term effects, there is need for large, methodologically robust multicentre RCTs investigating and directly comparing commonly used treatments for the management of PHP. PROSPERO REGISTRATION NUMBER: CRD42016046963.

Individual participant data meta-analysis of continuous outcomes: A comparison of approaches for specifying and estimating one-stage models.

One-stage individual participant data meta-analysis models should account for within-trial clustering, but it is currently debated how to do this. For continuous outcomes modeled using a linear regression framework, two competing approaches are a stratified intercept or a random intercept. The stratified approach involves estimating a separate intercept term for each trial, whereas the random intercept approach assumes that trial intercepts are drawn from a normal distribution. Here, through an extensive simulation study for continuous outcomes, we evaluate the impact of using the stratified and random intercept approaches on statistical properties of the summary treatment effect estimate. Further aims are to compare (i) competing estimation options for the one-stage models, including maximum likelihood and restricted maximum likelihood, and (ii) competing options for deriving confidence intervals (CI) for the summary treatment effect, including the standard normal-based 95% CI, and more conservative approaches of Kenward-Roger and Satterthwaite, which inflate CIs to account for uncertainty in variance estimates. The findings reveal that, for an individual participant data meta-analysis of randomized trials with a 1:1 treatment:control allocation ratio and heterogeneity in the treatment effect, (i) bias and coverage of the summary treatment effect estimate are very similar when using stratified or random intercept models with restricted maximum likelihood, and thus either approach could be taken in practice, (ii) CIs are generally best derived using either a Kenward-Roger or Satterthwaite correction, although occasionally overly conservative, and (iii) if maximum likelihood is required, a random intercept performs better than a stratified intercept model. An illustrative example is provided.

Moderators of the effect of therapeutic exercise for knee and hip osteoarthritis: a systematic review and individual participant data meta-analysis.

BACKGROUND: Many international clinical guidelines recommend therapeutic exercise as a core treatment for knee and hip osteoarthritis. We aimed to identify individual patient-level moderators of the effect of therapeutic exercise for reducing pain and improving physical function in people with knee osteoarthritis, hip osteoarthritis, or both. METHODS: We did a systematic review and individual participant data (IPD) meta-analysis of randomised controlled trials comparing therapeutic exercise with non-exercise controls in people with knee osteoathritis, hip osteoarthritis, or both. We searched ten databases from March 1, 2012, to Feb 25, 2019, for randomised controlled trials comparing the effects of exercise with non-exercise or other exercise controls on pain and physical function outcomes among people with knee osteoarthritis, hip osteoarthritis, or both. IPD were requested from leads of all eligible randomised controlled trials. 12 potential moderators of interest were explored to ascertain whether they were associated with short-term (12 weeks), medium-term (6 months), and long-term (12 months) effects of exercise on self-reported pain and physical function, in comparison with non-exercise controls. Overall intervention effects were also summarised. This study is prospectively registered on PROSPERO (CRD42017054049). FINDINGS: Of 91 eligible randomised controlled trials that compared exercise with non-exercise controls, IPD from 31 randomised controlled trials (n=4241 participants) were included in the meta-analysis. Randomised controlled trials included participants with knee osteoarthritis (18 [58%] of 31 trials), hip osteoarthritis (six [19%]), or both (seven [23%]) and tested heterogeneous exercise interventions versus heterogeneous non-exercise controls, with variable risk of bias. Summary meta-analysis results showed that, on average, compared with non-exercise controls, therapeutic exercise reduced pain on a standardised 0-100 scale (with 100 corresponding to worst pain), with a difference of -6·36 points (95% CI -8·45 to -4·27, borrowing of strength [BoS] 10·3%, between-study variance [τ2] 21·6) in the short term, -3·77 points (-5·97 to -1·57, BoS 30·0%, τ2 14·4) in the medium term, and -3·43 points (-5·18 to -1·69, BoS 31·7%, τ2 4·5) in the long term. Therapeutic exercise also improved physical function on a standardised 0-100 scale (with 100 corresponding to worst physical function), with a difference of -4·46 points in the short term (95% CI -5·95 to -2·98, BoS 10·5%, τ2 10·1), -2·71 points in the medium term (-4·63 to -0·78, BoS 33·6%, τ2 11·9), and -3·39 points in the long term (-4·97 to -1·81, BoS 34·1%, τ2 6·4). Baseline pain and physical function moderated the effect of exercise on pain and physical function outcomes. Those with higher self-reported pain and physical function scores at baseline (ie, poorer physical function) generally benefited more than those with lower self-reported pain and physical function scores at baseline, with the evidence most certain in the short term (12 weeks). INTERPRETATION: There was evidence of a small, positive overall effect of therapeutic exercise on pain and physical function compared with non-exercise controls. However, this effect is of questionable clinical importance, particularly in the medium and long term. As individuals with higher pain severity and poorer physical function at baseline benefited more than those with lower pain severity and better physical function at baseline, targeting individuals with higher levels of osteoarthritis-related pain and disability for therapeutic exercise might be of merit. FUNDING: Chartered Society of Physiotherapy Charitable Trust and the National Institute for Health and Care Research.

Do comorbidities predict pain and function in knee osteoarthritis following an exercise intervention, and do they moderate the effect of exercise? Analyses of data from three randomized controlled trials.

BACKGROUND: Although exercise is a core treatment for people with knee osteoarthritis (OA), it is currently unknown whether those with additional comorbidities respond differently to exercise than those without. We explored whether comorbidities predict pain and function following an exercise intervention in people with knee OA, and whether they moderate response to: exercise versus no exercise; and enhanced exercise versus usual exercise-based care. METHODS: We undertook analyses of existing data from three randomized controlled trials (RCTs): TOPIK (n = 217), APEX (n = 352) and Benefits of Effective Exercise for knee Pain (BEEP) (n = 514). All three RCTs included: adults with knee pain attributable to OA; physiotherapy-led exercise; data on six comorbidities (overweight/obesity, pain elsewhere, anxiety/depression, cardiac problems, diabetes mellitus and respiratory conditions); the outcomes of interest (six-month Western Ontario and McMaster Universities Arthritis Index knee pain and function). Adjusted mixed models were fitted where data was available; otherwise linear regression models were used. RESULTS: Obesity compared with underweight/normal body mass index was significantly associated with knee pain following exercise, as was the presence compared with absence of anxiety/depression. The presence of cardiac problems was significantly associated with the effect of enhanced versus usual exercise-based care for knee function, indicating that enhanced exercise may be less effective for improving knee function in people with cardiac problems. Associations for all other potential prognostic factors and moderators were weak and not statistically significant. CONCLUSIONS: Obesity and anxiety/depression predicted pain and function outcomes in people offered an exercise intervention, but only the presence of cardiac problems might moderate the effect of exercise for knee OA. Further confirmatory investigations are required.

Subgrouping and TargetEd Exercise pRogrammes for knee and hip OsteoArthritis (STEER OA): a systematic review update and individual participant data meta-analysis protocol.

INTRODUCTION: Knee and hip osteoarthritis (OA) is a leading cause of disability worldwide. Therapeutic exercise is a recommended core treatment for people with knee and hip OA, however, the observed effect sizes for reducing pain and improving physical function are small to moderate. This may be due to insufficient targeting of exercise to subgroups of people who are most likely to respond and/or suboptimal content of exercise programmes. This study aims to identify: (1) subgroups of people with knee and hip OA that do/do not respond to therapeutic exercise and to different types of exercise and (2) mediators of the effect of therapeutic exercise for reducing pain and improving physical function. This will enable optimal targeting and refining the content of future exercise interventions. METHODS AND ANALYSIS: Systematic review and individual participant data meta-analyses. A previous comprehensive systematic review will be updated to identify randomised controlled trials that compare the effects of therapeutic exercise for people with knee and hip OA on pain and physical function to a non-exercise control. Lead authors of eligible trials will be invited to share individual participant data. Trial-level and participant-level characteristics (for baseline variables and outcomes) of included studies will be summarised. Meta-analyses will use a two-stage approach, where effect estimates are obtained for each trial and then synthesised using a random effects model (to account for heterogeneity). All analyses will be on an intention-to-treat principle and all summary meta-analysis estimates will be reported as standardised mean differences with 95% CI. ETHICS AND DISSEMINATION: Research ethical or governance approval is exempt as no new data are being collected and no identifiable participant information will be shared. Findings will be disseminated via national and international conferences, publication in peer-reviewed journals and summaries posted on websites accessed by the public and clinicians. PROSPERO REGISTRATION NUMBER: CRD42017054049.