#### Background Pain, although unpleasant, is essential for survival. Whenever the body is damaged, nerve cells detecting the injury send an electrical message via the spinal cord to the brain and, as a result, action is taken to prevent further damage. Usually pain is short-lived, but sometimes it continues for weeks, months, or years. Long-lasting (chronic) pain can be caused by an ongoing, often inflammatory condition (for example, arthritis) or by damage to the nervous system itself—experts call this “neuropathic” pain. Damage to the brain or spinal cord causes central neuropathic pain; damage to the nerves that convey information from distant parts of the body to the spinal cord causes peripheral neuropathic pain. One example of peripheral neuropathic pain is “radicular” low back pain (also called sciatica). This is pain that radiates from the back into the legs. By contrast, axial back pain (the most common type of low back pain) is confined to the lower back and is non-neuropathic. #### Why Was This Study Done? Chronic pain is very common—nearly 10% of American adults have frequent back pain, for example—and there are many treatments for it, including rest, regulated exercise (physical therapy), pain-killing drugs (analgesics), and surgery. However, the best treatment for any individual depends on the exact nature of their pain, so it is important to assess their pain carefully before starting treatment. This is usually done by scoring overall pain intensity, but this assessment does not reflect the characteristics of the pain (for example, whether it occurs spontaneously or in response to external stimuli) or the complex biological processes involved in pain generation. An assessment designed to take such factors into account might improve treatment outcomes and could be useful in the development of new therapies. In this study, the researchers develop and test a new, standardized tool for the assessment of chronic pain that, by examining many symptoms and signs, aims to distinguish between pain subtypes. #### What Did the Researchers Do and Find? One hundred thirty patients with several types of peripheral neuropathic pain and 57 patients with non-neuropathic (axial) low back pain completed a structured interview of 16 questions and a standardized bedside examination of 23 tests. Patients were asked, for example, to choose words that described their pain from a list provided by the researchers and to grade the intensity of particular aspects of their pain from zero (no pain) to ten (the maximum imaginable pain). Bedside tests included measurements of responses to light touch, pinprick, and vibration—chronic pain often alters responses to harmless stimuli. Using “hierarchical cluster analysis,” the researchers identified six subgroups of patients with neuropathic pain and two subgroups of patients with non-neuropathic pain based on the patterns of symptoms and signs revealed by the interviews and physical tests. They then used “classification tree analysis” to identify the six questions and ten physical tests that discriminated best between pain subtypes and combined these items into a tool for a Standardized Evaluation of Pain (StEP). Finally, the researchers asked whether StEP, which took 10–15 minutes, could identify patients with radicular back pain and discriminate them from those with axial back pain in an independent group of 137 patients with chronic low back pain. StEP, they report, accurately diagnosed these two conditions and was well accepted by the patients. #### What Do These Findings Mean? These findings indicate that a standardized assessment of pain-related signs and symptoms can provide a simple, quick diagnostic procedure that distinguishes between radicular (neuropathic) and axial (non-neuropathic) low back pain. This distinction is crucial because these types of back pain are best treated in different ways. In addition, the findings suggest that it might be possible to identify additional pain subtypes using StEP. Because these subtypes may represent conditions in which different pain mechanisms are acting, classifying patients in this way might eventually enable physicians to tailor treatments for chronic pain to the specific needs of individual patients rather than, as at present, largely guessing which of the available treatments is likely to work best.