Predicting treatment outcomes of pain patients attending tertiary multidisciplinary pain treatment centers: A pain trajectory approach

Abstract

Background : Though multidisciplinary pain treatment (MPT) is considered the gold standard for managing chronic pain, it is unclear which patients benefit most from this high-cost treatment approach. Aims : The goals were to identify subgroups of patients sharing similar pain severity trajectories over time and predictors of MPT responsiveness. Methods : Participants were 1894 patients (mean age = 53.18 years [SD = 14.0]; female = 60.3%) enrolled in the Quebec Pain Registry with moderate to severe baseline pain severity. Patients completed validated questionnaires on pain and related constructs before initiating treatment and 6, 12, and 24 months later. Results : Trajectory analyses of pain severity (intensity and interference) showed that a three-class model best fit the data. Two of the trajectories, which included 24.5% of patients, showed significant improvement in pain severity levels over time (improvers). Compared to patients in the nonimproving trajectory (non-improvers), improvers were younger and more likely to suffer from neuropathic pain and had pain of shorter duration, lower worst pain intensity, lower sleep disturbances and depression scores at baseline, a lower tendency to catastrophize, and better physical health–related quality of life (QOL). This predictive model had a specificity of 96.2% and a sensitivity of 23.6%. Conclusions : Only a minority of patients exhibited an improvement in their pain severity with MPT. Several patients’ characteristics were significantly associated with pain trajectory membership. Early identification of nonimprovers, through examination of baseline characteristics and rates of change in pain scores, can provide valuable information about prognosis and open the doors for evaluation of different cost-effective treatment approaches. Abbreviations : CP = chronic pain; MPT = multidisciplinary pain treatment; QPR = Quebec Pain Registry; QOL = quality of life.

Defining pain and interference recovery trajectories after acute non-catastrophic musculoskeletal trauma through Growth Mixture Modeling 

“…LGCA standards. Some research groups have identi ed smaller trajectory classes hidden within larger samples (though these tend to represent 10% or less of the overall proportion), while other large scale analyses have similarly reported three trajectories (16,44). While it is possible that other trajectories comprised of smaller proportions exist in our data but were not identi ed, we propose that these would be rare enough to not substantively affect prognosis or treatment decisions.…”

“…Despite some differences in shape, the 3-trajectory model has now been identi ed with striking consistency across clinical populations worldwide. This includes trajectories of pain and disability in a large population-level study of people with chronic pain in Canada (44), and post-operative pain in Belgium and the United States (45,46). Even in studies that have identi ed more trajectories in hip (Netherlands) (47) and low back pain (UK) (48), the existence of three stable classes represent the highest proportions with other smaller classes representing participants with uctuating symptoms.…”

Winner of The Ronald Melzack – Canadian Journal of Pain 2017 Paper of the Year Award/Récipiendaire du Prix Ronald Melzack Pour L’Annee 2017 Des Articles Parus Dans La Revue Canadienne De La Douleur

“…Sixty percent of the voting members ranked the Pagé et al 1 article as their number one choice, making it the clear winner.…”

“…The novelty of the Pagé et al 1 study lies in the use of latent class trajectory analysis to identify subgroups of individuals who show a similar pattern of the outcome over time within a class and a different pattern between classes. This differs from more traditional statistical approaches that tend to classify participants using overall averages.…”

“…1 Using growth mixture modeling for multivariate latent classes they examined the patients' pain intensity and pain interference trajectories over a two-year period using data collected at baseline and at 6, 12, and 24 months. The threegroup trajectory solution (non-improvers, steady improvers and early improvers) was collapsed to form a group of improvers (25% of the sample) and non-improvers (75% of the sample) followed by binary logistic regression to predict trajectory group membership from among a variety of pretreatment risk factors.…”