Article Text

Download PDFPDF

An algorithm comprising 7 baseline variables predicted the 2 year work disability status in non-specific back pain
  1. Arthur T Evans, MD, MPH1,
  2. Nortin M Hadler, MD2
  1. 1Cook County Hospital and Rush Medical College
 Chicago, Illinois, USA
  2. 2University of North Carolina at Chapel Hill
 Chapel Hill, North Carolina, USA

    Statistics from

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

 Q In patients with non-specific back pain associated with ⩾1 day’s absence from work, what variable or set of variables best predicts the 2 year work disability status?

    Clinical impact ratings GP/FP/Primary care ★★★★★☆☆


    Embedded ImageDesign:

    a cohort study (Recherche sur les Affections Musculo-Squelettiques [RAMS]- Prognosis Study) with a qualitative phase to identify additional predictors, and a quantitative phase for prediction analysis. More than 100 potential predictors were measured at baseline and at 6 and 12 weeks. Predictive models of 2 year outcome were developed with recursive partitioning on a 40% random sample of the cohort, and validated in the rest.

    Embedded ImageSetting:

    7 primary care settings in Quebec City, Quebec, Canada.

    Embedded ImagePatients:

    860 adult workers (mean age 39 y, 58% men) who consulted for non-specific back pain associated with ⩾1 day’s absence from work.

    Embedded ImageDescription of prediction guide:

    the final model had 7 questions pertaining to patients’ recovery expectations, radiating pain, previous back surgery, self reported pain severity, frequent change of position because of back pain, irritability and bad temper, and difficulty sleeping.

    Embedded ImageOutcomes:

    return to work in good health (RWGH) categorised as success, partial success, failure after attempt, and failure.


    The probability of success was highest (0.84, 95% CI 0.77 to 0.91) for patients without previous back surgery who expected to recover within 3 months and rated their pain as 4–10 (on a scale of none [0] to 10) but who did not change their positions frequently to get comfortable; and lowest (0.25, CI 0.18 to 0.32) in patients with radiating pain (into the arms or legs) who did not expect to recover within 3 months. Patients with the lowest probability of success also had the highest probability of failure (0.46, CI 0.38 to 0.54). The probability of partial success varied from 0.08, CI 0.02 to 0.14 (in patients with the highest probability of success) to 0.45, CI 0.30 to 0.60 (in patients without previous back surgery who anticipated to recover within 3 months, rated the pain as 4–10, changed positions often to get comfortable, were more irritable than usual but who slept as usual). Sensitivity and specificity and positive and negative likelihood ratios for the collapsed outcome (success plus partial success v failure after attempt plus failure) are in the table.

    Measures of validity for a clinical prediction rule developed from 7 baseline variables for predicting the 2 year work disability status in non-specific back pain*


    In patients with non-specific back pain associated with ⩾1 day’s absence from work, the best, although limited, prediction of the 2 year work disability status was obtained with 7 baseline variables.

    Abstract and commentary also appears in ACP Journal Club.


    The bottom line for clinicians: don’t use the prediction rule by Dionne et al for several reasons. Firstly, it should be validated in another setting, and its clinical use should be shown to cause more good than harm. Secondly, the rule’s potential use is suspect considering that 40% of predictions in the validation sample were erroneous. Finally, the predicted outcome—RWGH—is an unstable psychosocial construct that is highly influenced by interpersonal, economic, and political factors. Wasson et al warned against using such outcomes.1

    The psychosocial nature of the outcome is underscored by the fact that the best single predictor was the patient’s own premonition of their future status: “Do you think you will be back to your normal work within 3 months?” Is this an example of dispassionate foresight or self fulfilling prophecy? Because the rule predicted failure to return to work 2–3 times more often than what was actually observed, it is possible that informing patients of an ominous prediction would adversely influence outcomes further. Another striking observation is that outcome status at 12 weeks had a predictive accuracy >90%. That prolonged disability seals one’s fate is a long standing reproach to all involved in workplace health and safety. How the persistence of disability renders back pain unremitting is a conundrum for clinical investigation. The answer may be hiding in studies such as this by Dionne et al.

    Living with back pain reflects the psychosocial assaults on our coping capacity that operate at home and at work.2 Furthermore, this psychosocial context has a temporal component, includes the vortex of disability determination itself, and is bedevilled by the idiosyncrasies of life. No wonder a “predictive rule” for job absenteeism in the setting of back pain is a will-o-the-wisp.


    View Abstract


    • For correspondence: Dr C E Dionne, Hôpital du Saint-Sacrement, Québec, Québec, Canada. clermont.dionne{at}

    • Source of funding: Quebec Institute for Occupational Safety and Health.