A novel tool for the assessment of pain: validation in low back pain.
BACKGROUND
Adequate pain assessment is critical for evaluating the efficacy of analgesic treatment in clinical practice and during the development of new therapies. Yet the currently used scores of global pain intensity fail to reflect the diversity of pain manifestations and the complexity of underlying biological mechanisms. We have developed a tool for a standardized assessment of pain-related symptoms and signs that differentiates pain phenotypes independent of etiology.


RESULTS
Using a structured interview (16 questions) and a standardized bedside examination (23 tests), we prospectively assessed symptoms and signs in 130 patients with peripheral neuropathic pain caused by diabetic polyneuropathy, postherpetic neuralgia, or radicular low back pain (LBP), and in 57 patients with non-neuropathic (axial) LBP. A hierarchical cluster analysis revealed distinct association patterns of symptoms and signs (pain subtypes) that characterized six subgroups of patients with neuropathic pain and two subgroups of patients with non-neuropathic pain. Using a classification tree analysis, we identified the most discriminatory assessment items for the identification of pain subtypes. We combined these six interview questions and ten physical tests in a pain assessment tool that we named Standardized Evaluation of Pain (StEP). We validated StEP for the distinction between radicular and axial LBP in an independent group of 137 patients. StEP identified patients with radicular pain with high sensitivity (92%; 95% confidence interval [CI] 83%-97%) and specificity (97%; 95% CI 89%-100%). The diagnostic accuracy of StEP exceeded that of a dedicated screening tool for neuropathic pain and spinal magnetic resonance imaging. In addition, we were able to reproduce subtypes of radicular and axial LBP, underscoring the utility of StEP for discerning distinct constellations of symptoms and signs.


CONCLUSIONS
We present a novel method of identifying pain subtypes that we believe reflect underlying pain mechanisms. We demonstrate that this new approach to pain assessment helps separate radicular from axial back pain. Beyond diagnostic utility, a standardized differentiation of pain subtypes that is independent of disease etiology may offer a unique opportunity to improve targeted analgesic treatment.
Scholz
Joachim
J
Department of Anesthesia and Critical Care, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Mannion
Richard J
RJ
Hord
Daniela E
DE
Griffin
Robert S
RS
Rawal
Bhupendra
B
Zheng
Hui
H
Scoffings
Daniel
D
Phillips
Amanda
A
Guo
Jianli
J
Laing
Rodney J C
RJ
Abdi
Salahadin
S
Decosterd
Isabelle
I
Woolf
Clifford J
CJ
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease; D003663:Decision Trees; D003929:Diabetic Neuropathies / Q000175:diagnosis / Q000503:physiopathology; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D017116:Low Back Pain / Q000175:diagnosis* / Q000503:physiopathology; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009408:Nerve Compression Syndromes / Q000175:diagnosis / Q000503:physiopathology; D051474:Neuralgia, Postherpetic / Q000175:diagnosis / Q000503:physiopathology; D009460:Neurologic Examination; D010147:Pain Measurement / Q000379:methods*; D010812:Physical Stimulation; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D013126:Spinal Nerve Roots; D011795:Surveys and Questionnaires; D055815:Young Adult