Dataset Information

Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain.

ABSTRACT: Low back pain (LBP) is a major health problem. Globally it is responsible for the most years lived with disability. The most problematic type of LBP is chronic LBP (pain lasting longer than 3 mo); it has a poor prognosis and is costly, and interventions are only moderately effective. Targeting interventions according to risk profile is a promising approach to prevent the onset of chronic LBP. Developing accurate prognostic models is the first step. No validated prognostic models are available to accurately predict the onset of chronic LBP. The primary aim of this study was to develop and validate a prognostic model to estimate the risk of chronic LBP.We used the PROGRESS framework to specify a priori methods, which we published in a study protocol. Data from 2,758 patients with acute LBP attending primary care in Australia between 5 November 2003 and 15 July 2005 (development sample, n = 1,230) and between 10 November 2009 and 5 February 2013 (external validation sample, n = 1,528) were used to develop and externally validate the model. The primary outcome was chronic LBP (ongoing pain at 3 mo). In all, 30% of the development sample and 19% of the external validation sample developed chronic LBP. In the external validation sample, the primary model (PICKUP) discriminated between those who did and did not develop chronic LBP with acceptable performance (area under the receiver operating characteristic curve 0.66 [95% CI 0.63 to 0.69]). Although model calibration was also acceptable in the external validation sample (intercept = -0.55, slope = 0.89), some miscalibration was observed for high-risk groups. The decision curve analysis estimated that, if decisions to recommend further intervention were based on risk scores, screening could lead to a net reduction of 40 unnecessary interventions for every 100 patients presenting to primary care compared to a "treat all" approach. Limitations of the method include the model being restricted to using prognostic factors measured in existing studies and using stepwise methods to specify the model. Limitations of the model include modest discrimination performance. The model also requires recalibration for local settings.Based on its performance in these cohorts, this five-item prognostic model for patients with acute LBP may be a useful tool for estimating risk of chronic LBP. Further validation is required to determine whether screening with this model leads to a net reduction in unnecessary interventions provided to low-risk patients.

SUBMITTER: Traeger AC

PROVIDER: S-EPMC4871494 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain.

Traeger Adrian C AC Henschke Nicholas N Hübscher Markus M Williams Christopher M CM Kamper Steven J SJ Maher Christopher G CG Moseley G Lorimer GL McAuley James H JH

PLoS medicine 20160517 5

<h4>Background</h4>Low back pain (LBP) is a major health problem. Globally it is responsible for the most years lived with disability. The most problematic type of LBP is chronic LBP (pain lasting longer than 3 mo); it has a poor prognosis and is costly, and interventions are only moderately effective. Targeting interventions according to risk profile is a promising approach to prevent the onset of chronic LBP. Developing accurate prognostic models is the first step. No validated prognostic mode ...[more]

PMID: 27187782

Similar Datasets

Project description:BACKGROUND:Low back pain (LBP) encompasses heterogeneous patients unlikely to respond to a unique treatment. Identifying sub-groups of LBP may help to improve treatment outcomes. This is a hypothesis-setting study designed to create a clinical prediction rule (CPR) that will predict favorable outcomes in soldiers with sub-acute and chronic LBP participating in a multi-station exercise program. METHODS:Military members with LBP participated in a supervised program comprising 7 stations each consisting of exercises of increasing difficulty. Demographic, impairment and disability data were collected at baseline. The modified Oswestry Disability Index (ODI) was administered at baseline and following the 6-week program. An improvement of 50% in the initial ODI score was considered the reference standard to determine a favorable outcome. Univariate associations with favorable outcome were tested using chi-square or paired t-tests. Variables that showed between-group (favorable/unfavorable) differences were entered into a logistic regression after determining the sampling adequacy. Finally, continuous variables were dichotomized and the sensitivity, specificity and positive and negative likelihood ratios were determined for the model and for each variable. RESULTS:A sample of 85 participants was included in analyses. Five variables contributed to prediction of a favorable outcome: no pain in lying down (p = 0.017), no use of antidepressants (p = 0.061), FABQ work score < 22.5 (p = 0.061), fewer than 5 physiotherapy sessions before entering the program (p = 0.144) and less than 6 months' work restriction (p = 0.161). This model yielded a sensitivity of 0.78, specificity of 0.80, LR+ of 3.88, and LR- of 0.28. A 77.5% probability of favorable outcome can be predicted by the presence of more than three of the five variables, while an 80% probability of unfavorable outcome can be expected if only three or fewer variables are present. CONCLUSION:The use of prognostic factors may guide clinicians in identifying soldiers with LBP most likely to have a favorable outcome. Further validation studies are needed to determine if the variables identified in our study are treatment effect modifiers that can predict success following participation in the multi-station exercise program. TRIAL REGISTRATION:ClinicalTrials.gov Identifier: NCT03464877 registered retrospectively on 14 March 2018.

Project description:BackgroundChronic low back pain (cLBP) is a complex with a heterogenous clinical presentation. A better understanding of the factors that contribute to cLBP is needed for accurate diagnosis, optimal treatment, and identification of mechanistic targets for new therapies. The Back Pain Consortium (BACPAC) Research Program provides a unique opportunity in this regard, as it will generate large clinical datasets, including a diverse set of harmonized measurements. The Theoretical Model Working Group was established to guide BACPAC research and to organize new knowledge within a mechanistic framework. This article summarizes the initial work of the Theoretical Model Working Group. It includes a three-stage integration of expert opinion and an umbrella literature review of factors that affect cLBP severity and chronicity.MethodsDuring Stage 1, experts from across BACPAC established a taxonomy for risk and prognostic factors (RPFs) and preliminary graphical depictions. During Stage 2, a separate team conducted a literature review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to establish working definitions, associated data elements, and overall strength of evidence for identified RPFs. These were subsequently integrated with expert opinion during Stage 3.ResultsThe majority (∼80%) of RPFs had little strength-of-evidence confidence, whereas seven factors had substantial confidence for either a positive association with cLBP (pain-related anxiety, serum C-reactive protein, diabetes, and anticipatory/compensatory postural adjustments) or no association with cLBP (serum interleukin 1-beta / interleukin 6, transversus muscle morphology/activity, and quantitative sensory testing).ConclusionThis theoretical perspective will evolve over time as BACPAC investigators link empirical results to theory, challenge current ideas of the biopsychosocial model, and use a systems approach to develop tools and algorithms that disentangle the dynamic interactions among cLBP factors.

Dataset Information

Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain.

Publications

Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets