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

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          Abstract

          Background

          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.

          Methods and Findings

          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.

          Conclusions

          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.

          Abstract

          Adrian Traeger and colleagues report the development and validation of a prognostiv model (PICKUP) for estimating risk of developing chronic low back pain.

          Author Summary

          Why Was This Study Done?
          • A minority of patients who experience an episode of low back pain develop persistent (chronic) pain.

          • Offering tests and treatments to all these patients exposes high numbers of low-risk patients to unnecessary intervention, which is very costly and potentially harmful.

          • A tool to help healthcare practitioners accurately predict whether a patient with a recent episode of low back pain will develop persistent pain stands to greatly reduce the burden of low back pain on the health system and on patients.

          What Did the Researchers Do and Find?
          • We developed a five-item screening questionnaire using study data from 1,230 patients with a recent episode of low back pain.

          • We tested how well this screening questionnaire could predict the onset of persistent pain in a separate sample of 1,528 patients.

          • We found that the screening questionnaire could predict the onset of persistent pain with acceptable levels accuracy (area under the receiver operating characteristic curve = 0.66 [95% CI 0.63 to 0.69]; intercept = 0.55, slope = 0.89).

          What Do These Findings Mean?
          • This brief, easy-to-use screening questionnaire could help healthcare practitioners and researchers make an early estimate of a patient’s risk of persistent low back pain.

          • The screening questionnaire predicted outcome more accurately in patients with low risk scores than in those with high risk scores.

          • Screening patients with a recent episode of low back pain could reduce the number of unnecessary interventions provided to low-risk patients.

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          Most cited references42

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          Internal validation of predictive models: efficiency of some procedures for logistic regression analysis.

          The performance of a predictive model is overestimated when simply determined on the sample of subjects that was used to construct the model. Several internal validation methods are available that aim to provide a more accurate estimate of model performance in new subjects. We evaluated several variants of split-sample, cross-validation and bootstrapping methods with a logistic regression model that included eight predictors for 30-day mortality after an acute myocardial infarction. Random samples with a size between n = 572 and n = 9165 were drawn from a large data set (GUSTO-I; n = 40,830; 2851 deaths) to reflect modeling in data sets with between 5 and 80 events per variable. Independent performance was determined on the remaining subjects. Performance measures included discriminative ability, calibration and overall accuracy. We found that split-sample analyses gave overly pessimistic estimates of performance, with large variability. Cross-validation on 10% of the sample had low bias and low variability, but was not suitable for all performance measures. Internal validity could best be estimated with bootstrapping, which provided stable estimates with low bias. We conclude that split-sample validation is inefficient, and recommend bootstrapping for estimation of internal validity of a predictive logistic regression model.
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            The rising prevalence of chronic low back pain.

            National or state-level estimates on trends in the prevalence of chronic low back pain (LBP) are lacking. The objective of this study was to determine whether the prevalence of chronic LBP and the demographic, health-related, and health care-seeking characteristics of individuals with the condition have changed over the last 14 years. A cross-sectional, telephone survey of a representative sample of North Carolina households was conducted in 1992 and repeated in 2006. A total of 4437 households were contacted in 1992 and 5357 households in 2006 to identify noninstitutionalized adults 21 years or older with chronic (>3 months), impairing LBP or neck pain that limits daily activities. These individuals were interviewed in more detail about their health and health care seeking. The prevalence of chronic, impairing LBP rose significantly over the 14-year interval, from 3.9% (95% confidence interval [CI], 3.4%-4.4%) in 1992 to 10.2% (95% CI, 9.3%-11.0%) in 2006. Increases were seen for all adult age strata, in men and women, and in white and black races. Symptom severity and general health were similar for both years. The proportion of individuals who sought care from a health care provider in the past year increased from 73.1% (95% CI, 65.2%-79.8%) to 84.0% (95% CI, 80.8%-86.8%), while the mean number of visits to all health care providers were similar (19.5 [1992] vs 19.4 [2006]). The prevalence of chronic, impairing LBP has risen significantly in North Carolina, with continuing high levels of disability and health care use. A substantial portion of the rise in LBP care costs over the past 2 decades may be related to this rising prevalence.
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              A systematic review of psychological factors as predictors of chronicity/disability in prospective cohorts of low back pain.

              A systematic review of prospective cohort studies in low back pain. To evaluate the evidence implicating psychological factors in the development of chronicity in low back pain. The biopsychosocial model is gaining acceptance in low back pain, and has provided a basis for screening measurements, guidelines and interventions; however, to date, the unique contribution of psychological factors in the transition from an acute presentation to chronicity has not been rigorously assessed. A systematic literature search was followed by the application of three sets of criteria to each study: methodologic quality, quality of measurement of psychological factors, and quality of statistical analysis. Two reviewers blindly coded each study, followed by independent assessment by a statistician. Studies were divided into three environments: primary care settings, pain clinics, and workplace. Twenty-five publications (18 cohorts) included psychological factors at baseline. Six of these met acceptability criteria for methodology, psychological measurement, and statistical analysis. Increased risk of chronicity (persisting symptoms and/or disability) from psychological distress/depressive mood and, to a lesser extent, somatization emerged as the main findings. Acceptable evidence generally was not found for other psychological factors, although weak support emerged for the role of catastrophizing as a coping strategy. Psychological factors (notably distress, depressive mood, and somatization) are implicated in the transition to chronic low back pain. The development and testing of clinical interventions specifically targeting these factors is indicated. In view of the importance attributed to other psychological factors (particularly coping strategies and fear avoidance) there is a need to clarify their role in back-related disability through rigorous prospective studies.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                17 May 2016
                May 2016
                : 13
                : 5
                : e1002019
                Affiliations
                [1 ]Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia
                [2 ]Neuroscience Research Australia, Sydney, New South Wales, Australia
                [3 ]Institute of Public Health, University of Heidelberg, Heidelberg, Germany
                [4 ]Hunter Medical Research Institute and School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
                [5 ]The George Institute for Global Health, University of Sydney, Sydney, New South Wales, Australia
                [6 ]Sansom Institute for Health Research, University of South Australia, Adelaide, Australia
                Imperial College London, UNITED KINGDOM
                Author notes

                We have read the journal's policy and the authors of this manuscript have the following competing interests: GLM consults to Pfizer Australia, receives lecture fees from Pfizer Australia, NOIgroup Australasia, Kaiser Permanente California, and receives royalties from the following books: Explain Pain, Explain Pain Handbook - Protectometer, Painful Yarns - Metaphors and stories to help understand the biology of pain, and The Graded Motor Imagery Handbook. CW has received grants from government, industry and philanthropic agencies to fund his research. The money is paid to CW's institution. SK receives a research fellowship from the National Health and Medical Research Council of Australia that pays his salary and consultancy fees from AO Spine for methodological advice on unrelated projects.

                Conceived and designed the experiments: AT JM NH MH CW SK GLM CM. Performed the experiments: AT NH CM CW JM. Analyzed the data: AT. Contributed reagents/materials/analysis tools: AT. Wrote the first draft of the manuscript: AT. Contributed to the writing of the manuscript: AT JM NH MH CW SK GLM CM. Enrolled patients: NH CM CW JM. Agree with the manuscript’s results and conclusions: AT JM NH MH CW SK GLM CM. All authors have read, and confirm that they meet, ICMJE criteria for authorship.

                Article
                PMEDICINE-D-15-02557
                10.1371/journal.pmed.1002019
                4871494
                27187782
                14256167-0534-47a9-977f-f01500501474
                © 2016 Traeger et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 August 2015
                : 1 April 2016
                Page count
                Figures: 4, Tables: 5, Pages: 21
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1075670
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1002081
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1047827
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1061279
                AT is supported by a National Health and Medical Research Council PhD Scholarship APP1075670. GLM is supported by a National Health and Medical Research Council research fellowship NHMRC ID 1061279. JM and MH are supported by a National Health and Medical Research Council project grant ID 1047827. CM is supported by a National Health and Medical Research Council research fellowship NHMRC ID 1002081. http://www.nhmrc.gov.au/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Pain
                Lower Back Pain
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