Background & Aims

Chronic musculoskeletal pain (CMP) is a major health and socio-economic problem and represents the most prevalent set of chronic pain conditions. The diverse potential symptoms highlight the multidimensionality of the condition, which often requires interdisciplinary rehabilitation. Interdisciplinary multimodal pain treatment (IMPT) offers the best clinical care for pain sufferers and is the most cost-effective long-term treatment option. However, IMPT is not successful for all patients. Several predictors for IMPT success for different outcome measures have been reported, but with inconsistent results. A prediction model including these potentially predictors may result in more efficient rehabilitation and increased personalized healthcare. The aim of the current study was to determine and validate a prognostic model for the success of an IMPT program for patients with CMP.

Methods

Patients diagnosed with CMP visiting a rehabilitation center in The Netherlands and completing the full 10-week IMPT-program were included. Patients were assessed at baseline and the end of the IMPT-program. Socio-demographic and disease characteristics were inventoried, and patients filled in patient reported outcome measures that are included in the Dutch Dataset Pain Rehabilitation, supplemented with the Checklist Individual Strength and Symptom CheckList-90. Mixed model logistic regression with treatment success immediately after IMPT, was used to build four prediction models with disability (Global Perceived Effect and Pain Disability Index), health-related quality of life regarding physical and mental functioning (SF-12 Physical and Mental Component Scale) as dependent measures, respectively. Based on current literature and consensus between clinicians, researchers and patients, 53 demographic and candidate predictors were selected as independent variables a within the models.

Results

Two thousand, three hundred and nine patients with CMP were included in the study. Treatment was considered successful for 43%, 31%, 31%, and 57% of the patients for Global Perceived Effect, SF-12 Physical and Mental component, and Pain Disability Index, respectively. Backward selection reduced the number of predictors to 17, 11, 13, and 17 for the models of Global Perceived Effect, SF-12 Physical and Mental component, and Pain Disability Index, respectively. The area under the curve varied from 0.71 to 0.81. The sensitivity at the optimal cut-off for the models varied from 0.62 to 0.69, while the specificity varied from 0.67 to 0.81. Overall, there was only one predictor present in all four models (treatment control from the illness perception questionnaire-short version), while seven other predictors were present in three models. Additionally, the direction (positive/negative) of each predictor varies for the different models.

Conclusions

Treatment success appears to be outcome dependent as well as the predictors. Selecting the appropriate outcome measure in collaboration with the patient is important since this can influence the selection of interventions within the IMPT or topics to be discussed during treatment. An increase of one point in perceptions of treatment control results in an increased probability of success for Global Perceived Effect and Pain Disability Index, but a decreased probability of success for SF-12 Physical and Mental Component Scale. Apparently, patients rate the success regarding disability different compared to health-related quality of life.
External validation of these models is necessary before the development of a decision tool can be started. Once the models are externally validated a decision tool can be developed and a new step in patient care can be made.

References

1.Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain 2006;10(4):287-333.
2.Elbers S, Wittink H, Konings S, Kaiser U, Kleijnen J, Pool J et al. Longitudinal outcome evaluations of Interdisciplinary Multimodal Pain Treatment programmes for patients with chronic primary musculoskeletal pain: A systematic review and meta-analysis. Eur J Pain 2022;26(2):310-35.
3.Volker G, van Vree F, Wolterbeek R, van Gestel M, Smeets R, Koke A et al. Long-Term Outcomes of Multidisciplinary Rehabilitation for Chronic Musculoskeletal Pain. Musculoskeletal Care 2017;15(1):59-68.
4.World Health Organization. Regional Office for E, Health Evidence N, European Observatory on Health S, Policies, Coulter A, Parsons S et al. Where are the patients in decision-making about their own care? Copenhagen: World Health Organization. Regional Office for Europe; 2008.

Presenting Author

Michel GCAM Mertens

Poster Authors

Michel Mertens

PhD

Research Group MOVANT, Department of Rehabilitation Sciences and Physiotherapy,University of Antwerp

Lead Author

Lissa Breugelmans

Research School CAPHRI, Department of Rehabilitation Medicine, Maastricht University.

Lead Author

Laura MWE Beckers

PhD

Maastricht University

Lead Author

Sander van Kuijk

Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical

Lead Author

Miranda van Hooff

PhD

Sint Maartenskliniek, Nijmegen

Lead Author

Bjorn Winkens

Department of Methodology and Statistics, Care and Public Health Research Institute (CAPHRI), Maastr

Lead Author

Robert Smeets

Maastricht University, School for Public Health and Primary Care, Department

Lead Author

Topics

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