Prognostic Factors for Physical Functioning After Multidisciplinary Rehabilitation in Patients With Chronic Musculoskeletal Pain: A Systematic Review and Meta-Analysis
Elena Tseli, Katja Boersma, Britt-Marie Stålnacke, Paul Enthoven, Björn Gerdle, Björn O Äng, Wilhelmus J A Grooten, Elena Tseli, Katja Boersma, Britt-Marie Stålnacke, Paul Enthoven, Björn Gerdle, Björn O Äng, Wilhelmus J A Grooten
Abstract
Objectives: This systematic review aimed to identify and evaluate prognostic factors for long-term (≥6 mo) physical functioning in patients with chronic musculoskeletal pain following multidisciplinary rehabilitation (MDR).
Materials and methods: Electronic searches conducted in MEDLINE, PsycINFO, EMBASE, CINAHL, Web of Science, and Cochrane CENTRAL revealed 25 original research reports, published 1983-2016, (n=9436). Potential prognostic factors relating to initial pain and physical and psychological functioning were synthesized qualitatively and quantitatively in random effects meta-analyses. The level of evidence (LoE) was evaluated with Grading of Recommendations Assessment, Development and Evaluation (GRADE).
Results: Pain-related factors (intensity and chronicity) were not associated with function/disability at long-term follow-up, odds ratio (OR)=0.84; 95% confidence interval (CI), 0.65-1.07 and OR=0.97; 95% CI, 0.93-1.00, respectively (moderate LoE). A better function at follow-up was predicted by Physical factors; higher levels of initial self-reported functioning, OR=1.07; 95% CI, 1.02-1.13 (low LoE), and Psychological factors; low initial levels of emotional distress, OR=0.77; 95% CI, 0.65-0.92, low levels of cognitive and behavioral risk factors, OR=0.85; 95% CI, 0.77-0.93 and high levels of protective cognitive and behavioral factors, OR=1.49; 95% CI, 1.17-1.90 (moderate LoE).
Discussion: While pain intensity and long-term chronicity did not predict physical functioning in chronic pain patients after MDR, poor pretreatment physical and psychological functioning influenced the prognosis negatively. Thus, treatment should further target and optimize these modifiable factors and an increased focus on positive, psychological protective factors may perhaps provide an opening for yet untapped clinical gains.
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References
- Taylor AM, Phillips K, Taylor JO, et al. Is chronic pain a disease in its own right? Discussions from a Pre-OMERACT 2014 Workshop on Chronic Pain. J Rheumatol. 2015;42:1947–1953.
- Breivik H, Collett B, Ventafridda V, et al. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain. 2006;10:287–333.
- Leadley RM, Armstrong N, Lee YC, et al. Chronic diseases in the European Union: the prevalence and health cost implications of chronic pain. J Pain Palliat Care Pharmacother. 2012;26:310–325.
- Turk DC, Dworkin RH, Revicki D, et al. Identifying important outcome domains for chronic pain clinical trials: an IMMPACT survey of people with pain. Pain. 2008;137:276–285.
- International Association for the Study of Pain. Task force on multimodal pain treatment defines terms for chronic pain care. 2017. Available at: . Accessed December 14, 2017.
- Gatchel RJ, McGeary DD, McGeary CA, et al. Interdisciplinary chronic pain management: past, present, and future. Am Psychol. 2014;69:119–130.
- Hoffman BM, Papas RK, Chatkoff DK, et al. Meta-analysis of psychological interventions for chronic low back pain. Health Psychol. 2007;26:1–9.
- Kamper SJ, Apeldoorn AT, Chiarotto A, et al. Multidisciplinary biopsychosocial rehabilitation for chronic low back pain: Cochrane systematic review and meta-analysis. BMJ. 2015;350:h444.
- SBU. Methods for Treatment of Chronic Pain a Systematic Review of the literature (In Swedish: Metoder för behandling av långvarig smärta: en systematisk litteraturöversikt). Stockholm: SBU—Swedish Council on Health Technology Assessment; 2006.
- SBU. Rehabilitation of Chronic Pain [In Swedish: Rehabilitering vid långvarig smärta En systematisk litteraturöversikt] SBU-rapport. Stockholm: SBU—Swedish Council on Health Technology Assessment; 2010.
- Scascighini L, Toma V, Dober-Spielmann S, et al. Multidisciplinary treatment for chronic pain: a systematic review of interventions and outcomes. Rheumatology (Oxford). 2008;47:670–678.
- van Geen JW, Edelaar MJ, Janssen M, et al. The long-term effect of multidisciplinary back training: a systematic review. Spine. 2007;32:249–255.
- van Middelkoop M, Rubinstein SM, Kuijpers T, et al. A systematic review on the effectiveness of physical and rehabilitation interventions for chronic non-specific low back pain. Eur Spine J. 2011;20:19–39.
- Craig P, Dieppe P, Macintyre S, et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337:a1655.
- Kaiser U, Treede R-D, Sabatowski R. Multimodal pain therapy in chronic noncancer pain—gold standard or need for further clarification? Pain. 2017;158:1853–1859.
- Riley RD, Hayden JA, Steyerberg EW, et al. and for the PG. Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research. PLoS Med. 2013;10:e1001380.
- Clark GM. Prognostic factors versus predictive factors: examples from a clinical trial of erlotinib. Mol Oncol. 2008;1:406–412.
- Croft P, Altman DG, Deeks JJ, et al. The science of clinical practice: disease diagnosis or patient prognosis? Evidence about “what is likely to happen” should shape clinical practice. BMC Med. 2015;13:20.
- de Rooij A, Roorda LD, Otten RH, et al. Predictors of multidisciplinary treatment outcome in fibromyalgia: a systematic review. Disabil Rehabil. 2013;35:437–449.
- van der Hulst M, Vollenbroek-Hutten MM, Ijzerman MJ. A systematic review of sociodemographic, physical, and psychological predictors of multidisciplinary rehabilitation—or, back school treatment outcome in patients with chronic low back pain. Spine (Phila Pa 1976). 2005;30:813–825.
- Wessels T, van Tulder M, Sigl T, et al. What predicts outcome in non-operative treatments of chronic low back pain? A systematic review. Eur Spine J. 2006;15:1633–1644.
- Artus M, Campbell P, Mallen CD, et al. Generic prognostic factors for musculoskeletal pain in primary care: a systematic review. BMJ Open. 2017;7:e012901.
- Laisne F, Lecomte C, Corbiere M. Biopsychosocial predictors of prognosis in musculoskeletal disorders: a systematic review of the literature (corrected and republished)*. Disabil Rehabil. 2012;34:1912–1941.
- Valentin GH, Pilegaard MS, Vaegter HB, et al. Prognostic factors for disability and sick leave in patients with subacute non-malignant pain: a systematic review of cohort studies. BMJ Open. 2016;6:e007616.
- Tseli E, Grooten WJA, Stålnacke B-M, et al. Predictors of multidisciplinary rehabilitation outcomes in patients with chronic musculoskeletal pain: protocol for a systematic review and meta-analysis. Syst Rev. 2017;6:199.
- Taylor AM, Phillips K, Patel KV, et al. Assessment of physical function and participation in chronic pain clinical trials: IMMPACT/OMERACT recommendations. Pain. 2016;157:1836–1850.
- Main CJ, Keefe FJ, Jensen MP, et al. Fordyce’s Behavioral Methods for Chronic Pain and Illness: Republished With Invited Commentaries. Philadelphia, PA: Wolters Kluwer; 2014.
- Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62:1006–1012.
- Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA. 2000;283:2008–2012.
- Turk DC, Dworkin RH, Allen RR, et al. Core outcome domains for chronic pain clinical trials: IMMPACT recommendations. Pain. 2003;106:337–345.
- Vertitas Health Innovation Ltd. Covidence systematic review software. Vertitas Health Innovation Ltd: Melbourne, Australia. Available at: .
- Shamseer L, Moher D, Clarke M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015;349:g7647.
- Hayden JA, van Der Windt DA, Cartwright JL, et al. Assessing bias in studies of prognostic factors. Ann Intern Med. 2013;158:280–287.
- Cooper HM. Research Synthesis and Meta-Analysis: A Step-by-Step Approach. Los Angeles, CA, London: SAGE; 2010.
- Cooper HM, Hedges LV, Valentine JC. The Handbook of Research Synthesis and Meta-Analysis. New York, NY: Russell Sage Foundation; 2009.
- Wilson DB. Practical meta-analysis effect size calculator (Online calculator). The Campbell Collaboration; 2015.
- Lenhard W, Lenhard A. Calculation of effect sizes. Dettelbach, Germany: Psychometrica; 2016.
- Lipsey MW, Wilson D. Practical Meta-Analysis (Applied Social Research Methods). Thousand Oaks, California: SAGE Publications; 2000.
- The Cochrane Collaboration. Review Manager (RevMan) (Computer Program). Version 5.3. Copenhagen: The Nordic Cochrane Centre; 2014.
- Egger M. Systematic Reviews in Health Care : Meta-Analysis in Context. Chichester, GB: BMJ Books; 2008.
- Angst F, Gantenbein AR, Lehmann S, et al. Multidimensional associative factors for improvement in pain, function, and working capacity after rehabilitation of whiplash associated disorder: a prognostic, prospective outcome study. BMC Musculoskelet Disord. 2014;15:130.
- Bremander AB, Holmstrom G, Bergman S. Depression and age as predictors of patient-reported outcome in a multidisciplinary rehabilitation programme for chronic musculoskeletal pain. Musculoskeletal Care. 2011;9:41–48.
- Glattacker M, Heyduck K, Meffert C. Illness beliefs and treatment beliefs as predictors of short-term and medium-term outcome in chronic back pain. J Rehabil Med. 2013;45:268–276.
- Riley RD, Elia EG, Malin G, et al. Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement. Stat Med. 2015;34:2481–2496.
- Atkins DBD, Briss PA, Eccles M, et al. GRADE Working Group. Grading quality of evidence and strength of recommendations. BMJ. 2004;328:1490.
- Huguet A, Hayden JA, Stinson J, et al. Judging the quality of evidence in reviews of prognostic factor research: adapting the GRADE framework. Syst Rev. 2013;2:71.
- Iorio A, Spencer FA, Falavigna M, et al. Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients. BMJ. 2015;350:h870.
- Bendix AF, Bendix T, Haestrup C. Can it be predicted which patients with chronic low back pain should be offered tertiary rehabilitation in a functional restoration program? A search for demographic, socioeconomic, and physical predictors. Spine (Phila Pa 1976). 1998;23:1775–1783.
- Bergstrom G, Jensen IB, Bodin L, et al. The impact of psychologically different patient groups on outcome after a vocational rehabilitation program for long-term spinal pain patients. Pain. 2001;93:229–237.
- Bergström M, Ejelöv M, Mattsson M, et al. One-year follow-up of body awareness and perceived health after participating in a multimodal pain rehabilitation programme—a pilot study. Europ J Physiother. 2014;16:246–254.
- Ciechanowski P, Sullivan M, Jensen M, et al. The relationship of attachment style to depression, catastrophizing and health care utilization in patients with chronic pain. Pain. 2003;104:627–637.
- de Rooij A, van der Leeden M, Roorda LD, et al. Predictors of outcome of multidisciplinary treatment in chronic widespread pain: an observational study. BMC Musculoskelet Disord. 2013;14:133.
- Dobkin PL, Liu A, Abrahamowicz M, et al. Predictors of disability and pain six months after the end of treatment for fibromyalgia. Clin J Pain. 2010;26:23–29.
- Farin E, Gramm L, Schmidt E. The patient-physician relationship in patients with chronic low back pain as a predictor of outcomes after rehabilitation. J Behav Med. 2013;36:246–258.
- Gerdle B, Molander P, Stenberg G, et al. Weak outcome predictors of multimodal rehabilitation at one-year follow-up in patients with chronic pain-a practice based evidence study from two SQRP centres. BMC Musculoskelet Disord. 2016;17:490.
- Harkapaa K, Jarvikoski A, Estlander A. Health optimism and control beliefs as predictors for treatment outcome of a multimodal back treatment program. Psychol Health. 1996;12:123–134.
- Lillefjell M, Krokstad S, Espnes GA. Prediction of function in daily life following multidisciplinary rehabilitation for individuals with chronic musculoskeletal pain; a prospective study. BMC Musculoskelet Disord. 2007;8:65.
- Lüning-Bergsten C, Lundberg M, Lindberg P, et al. Change in kinesiophobia and its relation to activity limitation after multidisciplinary rehabilitation in patients with chronic back pain. Disabil Rehabil. 2012;34:852–858.
- McGeary DD, Mayer TG, Gatchel RJ. High pain ratings predict treatment failure in chronic occupational musculoskeletal disorders. J Bone Joint Surg A. 2006;88:317–325.
- Moradi B, Benedetti J, Zahlten-Hinguranage A, et al. The value of physical performance tests for predicting therapy outcome in patients with subacute low back pain: a prospective cohort study. Eur Spine J. 2009;18:1041–1049.
- Moss-Morris R, Humphrey K, Johnson MH, et al. Patients’ perceptions of their pain condition across a multidisciplinary pain management program: do they change and if so does it matter? Clin J Pain. 2007;23:558–564.
- Persson E, Lexell J, Rivano-Fischer M, et al. Occupational performance and factors associated with outcomes in patients participating in a musculoskeletal pain rehabilitation programme. J Rehabil Med. 2014;46:546–552.
- Ruscheweyh R, Dany K, Marziniak M, et al. Basal pain sensitivity does not predict the outcome of multidisciplinary chronic pain treatment. Pain Med (Malden, Mass). 2015;16:1635–1642.
- Trief PM, Yuan HA. The use of the MMPI in a chronic back pain rehabilitation program. J Clin Psychol. 1983;39:46–53.
- van Hooff ML, Spruit M, O’Dowd JK, et al. Predictive factors for successful clinical outcome 1 year after an intensive combined physical and psychological programme for chronic low back pain. Eur Spine J. 2014;23:102–112.
- Vendrig AA, Derksen JJ, de Mey HR. Utility of selected MMPI-2 scales in the outcome prediction for patients with chronic back pain. Psychol Assess. 1999;11:381–385.
- Vendrig AA, Derksen JJ, de Mey HR. MMPI-2 Personality Psychopathology Five (PSY-5) and prediction of treatment outcome for patients with chronic back pain. J Pers Assess. 2000;74:423–438.
- Verkerk K, Luijsterburg PA, Heymans MW, et al. Prognosis and course of disability in patients with chronic nonspecific low back pain: a 5- and 12-month follow-up cohort study. Phys Ther. 2013;93:1603–1614.
- Lemstra M, Olszynski WP. The effectiveness of multidisciplinary rehabilitation in the treatment of fibromyalgia—-a randomized controlled trial. Clin J Pain. 2005;21:166–174.
- Gatchel RJ, Peng YB, Peters ML, et al. The biopsychosocial approach to chronic pain: scientific advances and future directions. Psychol Bull. 2007;133:581–624.
- McCracken LM, Turk DC. Behavioral and cognitive-behavioral treatment for chronic pain: outcome, predictors of outcome, and treatment process. Spine. 2002;27:2564–2573.
- Morley S, Eccleston C, Williams A. Systematic review and meta-analysis of randomized controlled trials of cognitive behaviour therapy and behaviour therapy for chronic pain in adults, excluding headache. Pain. 1999;80:1–13.
- McCracken LM, Morley S. The psychological flexibility model: a basis for integration and progress in psychological approaches to chronic pain management. J Pain. 2014;15:221–234.
- Morley S, Williams A. New developments in the psychological management of chronic pain. Can J Psychiatry. 2015;60:168–175.
- Hanssen MM, Peters ML, Boselie JJ, et al. Can positive affect attenuate (persistent) pain? State of the art and clinical implications. Curr Rheumatol Rep. 2017;19:80.
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