Predictors of persistent neuropathic pain : a systematic review

Background: Characterization of the prognostic variables for persistent neuropathic pain (PNP) remains incomplete despite multiple articles addressing this topic. To provide more insight into the recovery and prognosis of neuropathic pain, high-quality data are required that provide information about the predictors that contribute to the development of PNP. Objective: To determine the methodological quality of studies about predictors for PNP and to summarize findings of predictors found in high-quality studies. Study Design: A systematic review. Setting: VU University Medical Center, Amsterdam, The Netherlands. Methods: Studies were identified by searching the electronic databases PubMed, Embase, and Cochrane Library. Methodological quality of each article was independently assessed by 2 reviewers. Results: Forty-six relevant studies were identified, classified into 4 different neuropathic pain (NP)syndromes: postherpetic neuralgia (n = 35), radicular pain and sciatica (n = 3), postsurgical pain (n = 6), and other types of NP (n = 2). Seven studies were of high quality. The 3 high-quality studies found for PHN reported male gender, older age, smoking, trauma at the site of lesion, missed antiviral prescriptions, higher acute pain severity, higher rash severity, more neuropathic characteristics, shorter rash duration, and a lower health status as predictors for PNP. For persistence of radicular pain one high-quality study reported negative outcome expectancies, pain-related fear of movement, and passive pain coping as predictors for PNP. Psychological distress, acute pain, breast cancer surgery, higher body mass index, area of secondary hyperalgesia, neuropathic characteristics, hypoesthesia, and hyperesthesia were found to be predictive for postsurgical pain in 3 high-quality studies. Limitations: Some publications may have been missed during literature search. The low-quality of the studies could be the result of an incomplete description of their methods. Conclusions: High-quality studies mainly assessed factors related to disease functions and structures. Due to shortcomings in methodological quality and limited areas of predictor selection, there is a need for high-quality studies focusing on predictor measurement, statistical analysis and the use of a standardized set of predictors.