The cost of chronic back pain and the limited resources that we have to deal with it, has led to many studies that attempt to ‘screen’ patients with low back pain in order to target treatment at the patients who need it most. I have had a clinical interest in this idea for some years and have spent the last 12 months with my head buried in the literature. One thing that is not all that clear is what in fact all these ‘screening’ studies are actually ‘screening’ for: Prognosis. Prediction. Subgrouping. Psychosocial profile. Risk. The fact is that not all screening studies are the same. I think they can be divided into two categories: predictive screening and screening for risk factors. Sound similar? Well they are. And they aren’t.
Predictive screening hopes to tell us which patients are likely to recover well from an episode of pain, and which patients won’t. It seems very sensible that determining this at an early stage – and targeting more complex management to this ‘at risk’ group – is likely to be a more affordable and effective approach to managing (even preventing?) chronic pain. Having trawled the literature, I now know that this is a lot easier said than done.
Studies which screen for risk factors on the other hand, are more interested in identifying psychological or physical characteristics that are linked to poor outcome. The patient-specific profiles that emerge can then be used to guide individualised treatments or clump people with similar profiles together and treat them as a group. This approach also seems to have merit, but is not without its problems – including screening for characteristics that are thought to be linked to poor outcomes, without evidence that they actually are (or worse – evidence that they are not!). Studies show that it is probably a safer bet to stick with psychological characteristics (e.g. catastrophic thinking/“If I bend my back will break”) than physical ones (e.g. how far I can bend over) as better recovery predictors.
This blog post was triggered by a paper that deals specifically with the latter – screening for risk factors. Beneciuk et al. (2015) look further into the use of the widely popular StarT Back Screening Tool (SBT) to see how it holds up in a secondary care setting. In brief, the SBT is a 9-item questionnaire that screens low back pain patients for factors found to be linked with a poor prognosis, and then classifies them as low, medium or high ‘risk’. The tool was devised for use in a UK primary care setting – that is, first-contact health care (such as seeing a GP). Since predictive screening questionnaires should generally only be applied to similar groups of patients in similar settings (Moons et al. 2009), this study is a worthwhile step towards understanding its usefulness in alternative settings.
The Physical Therapy clinics from which 146 patients were recruited for this study are regarded as ‘secondary care’ because all patients were referred from physicians. Participants completed clinical measures of pain and disability, the SBT, and 6 psychological measures that relate specifically to individual aspects of the SBT. The authors aimed to assess whether the SBT scores and these 6 measures were related, and compare the SBT risk categorisations with statistically-calculated categorisations based on the other measures.
They found that risk-dependent relationships existed between the psychological measures and SBT classification, with depression scores having the strongest influence on risk category. To explain further; there was a relationship between risk categorisation and depression scores, such that patients who were classified as ‘low risk’ were less depressed, and those who were classified as ‘high risk’ were most depressed. This relationship was also found to be present – but not as strongly – for fear-avoidance, catastrophising, kinesiophobia and anxiety.
Analysis of scores across all of the psychological measures lead to two distinct patient subgroups being formed: those with either ‘low’ or ‘elevated’ ‘pain-associated psychological distress, maladaptive coping and disability’. If you didn’t spot it, that was an important finding: the 3-tiered subgrouping offered by the SBT in a primary care setting (Hill et al. 2008) does not fit so well in secondary care.
So, while it seems that in a secondary care setting the SBT can efficiently and adequately screen for psychological distress, there are several reasons to be cautious. First, the SBT does not provide a detailed psychological assessment and further assessment of depression in particular, may be warranted for high risk patients. Second, the tool is imperfect – with some patients classified into the wrong ‘risk’ group. Third, someone has to use these data to do a predictive study before we know whether this 2-tiered system has any predictive value. It’s a long road isn’t it?
An approach to managing back pain that relies on accurate early screening still looks like a great idea and it is promising that the SBT continues to be investigated with rigour. For this tool to work well in practice however, research must confirm the SBT’s ability to accurately prognose* as well as prove its subgrouping application to offer advantages for care provision. Moreover, the precision with which it categorises people, the benefit patients get from being so categorised and treated, and the economic trade-offs, need to be sufficient to make it all worthwhile. At this stage, the most parsimonious^ conclusion I can draw from a year in this space is that clinicians working in secondary care should keep a close eye on this developing field, but not jump in by applying it to direct clinical decisions just yet.
(*this is a real word, ^so is this)
About Emma Karran
Emma is a Physiotherapy clinician and educator with a long-held interest in pain science and the biopsychosocial management of LBP. Having worked in varied private practice, hospital and university settings and obtained a Grad. Dip. in Psychology, she is now super-pleased to be indulging in a PhD with BiM at UniSA.
Emma’s research interests relate to understanding the usefulness of screening instruments for predicting LBP outcomes and developing a novel psycho-education intervention for patients ‘at risk’. She is particularly intrigued by ‘reassurance’ and the potential to reconsider spinal imaging interpretation in order to positively impact recovery.
Emma’s favourite things include her kids, cycling, the Tassie wilderness, good books and family camping trips. She is determined to make sure all of these fit in to her PhD experience.
Beneciuk, J., Bishop, M., Fritz, J., Robinson, M., Asal, N., Nisenzon, A., & George, S. (2012). The STarT Back Screening Tool and Individual Psychological Measures: Evaluation of Prognostic Capabilities for Low Back Pain Clinical Outcomes in Outpatient Physical Therapy Settings Physical Therapy, 93 (3), 321-333 DOI: 10.2522/ptj.20120207
Beneciuk, J., Robinson, M., & George, S. (2015). Subgrouping for Patients With Low Back Pain: A Multidimensional Approach Incorporating Cluster Analysis and the STarT Back Screening Tool The Journal of Pain, 16 (1), 19-30 DOI: 10.1016/j.jpain.2014.10.004
Hill, J., Dunn, K., Lewis, M., Mullis, R., Main, C., Foster, N., & Hay, E. (2008). A primary care back pain screening tool: Identifying patient subgroups for initial treatment Arthritis & Rheumatism, 59 (5), 632-641 DOI: 10.1002/art.23563
Moons, K., Altman, D., Vergouwe, Y., & Royston, P. (2009). Prognosis and prognostic research: application and impact of prognostic models in clinical practice BMJ, 338 (jun04 2) DOI: 10.1136/bmj.b606
Morsø, L., Kent, P., Manniche, C., & Albert, H. (2013). The predictive ability of the STarT Back Screening Tool in a Danish secondary care setting European Spine Journal, 23 (1), 120-128 DOI: 10.1007/s00586-013-2861-y