Yearly Archives: 2016

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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SOURCE:   PLoS Med. 2016 (May 17); 13 (5): e1002019

Adrian C. Traeger, Nicholas Henschke, Markus Hübscher,
Christopher M. Williams, Steven J. Kamper,
Christopher G. Maher, G. Lorimer Moseley,
James H. McAuley

Prince of Wales Clinical School,
University of New South Wales,
Sydney, New South Wales, Australia

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.

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Identification Of Subgroups Of Inflammatory And Degenerative MRI Findings In The Spine And Sacroiliac Joints: A Latent Class Analysis Of 1037 Patients With Persistent Low Back Pain

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SOURCE:   Arthritis Res Ther. 2016 (Oct 13); 18 (1): 237

Bodil Arnbak, Rikke Krüger Jensen, Claus Manniche,
Oliver Hendricks, Peter Kent, Anne Grethe Jurik
and Tue Secher Jensen

Research Department,
Spine Centre of Southern Denmark,
Hospital Lillebaelt,
Oestre Hougvej 55, Middelfart, 5500, Denmark.
bodil.arnbak@rsyd.dk

BACKGROUND: &nbsp The aim of this study was to investigate subgroups of magnetic resonance imaging (MRI) findings for the spine and sacroiliac joints (SIJs) using latent class analysis (LCA), and to investigate whether these subgroups differ in their demographic and clinical characteristics.

METHODS: &nbsp The sample included 1037 patients aged 18—40 years with persistent low back pain (LBP). LCA was applied to MRI findings of the spine and SIJs. The resulting subgroups were tested for differences in self-reported demographic and clinical characteristics.

RESULTS: &nbsp A five-class model was identified: Subgroup 1, ‘No or few findings’ (n = 116); Subgroup 2, ‘Mild spinal degeneration’ (n = 540); Subgroup 3, ‘Moderate to severe spinal degeneration’ (n = 229); Subgroup 4, ‘Moderate to severe spinal degeneration with mild SIJ findings’ (n = 68); and Subgroup 5, ‘Mild spinal degeneration with moderate to severe SIJ findings’ (n = 84). The two SIJ subgroups (Subgroups 4 and 5) had a higher median activity limitation score (Roland Morris Disability Questionnaire calculated as a proportional score: 65 (IQR 48—78)/65 (48—78)) compared with Subgroups 1—3 (48 (35—74)/57 (39—74)/57 (39—74)), a higher prevalence of women (68% (95% CI 56—79)/68% (58—78)) compared with Subgroups 2 and 3 (51% (47—55)/40% (33—46)), a higher prevalence of being overweight (67% (95% CI 55—79)/53% (41—65)) compared with Subgroup 1 (36% (26—46)) and a higher prevalence of previous LBP episodes (yes/no: 81% (95% CI 71—91)/79% (70—89)) compared with Subgroup 1 (58% (48—67)). Subgroup 5 was younger than Subgroup 4 (median age 29 years (IQR 25—33) versus 34 years (30—37)) and had a higher prevalence of HLA—B27 (40% (95% CI 29—50)) compared with the other subgroups (Subgroups 1—4: 12% (6—18)/7% (5—10)/6% (3—9)/12% (4—20)). Across the subgroups with predominantly spinal findings (Subgroups 1—3), median age, prevalence of men, being overweight and previous LBP episodes were statistically significantly lower in Subgroup 1, higher in Subgroup 2 and highest in Subgroup 3.

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