Yenisel Cruz-Almeida1, Roger B Fillingim. 1. Pain Research and Intervention Center of Excellence, Department of Community Dentistry & Behavioral Science, University of Florida, Gainesville, Florida, USA.
Abstract
OBJECTIVE: This review summarizes the scientific literature relating to the use of quantitative sensory testing (QST) for mechanism-based pain management. DESIGN: A literature search was undertaken using PubMed and search terms including quantitative sensory testing, pain, chronic pain, response to treatment, outcome measure. SETTINGS AND PATIENTS: Studies including QST in healthy individuals and those with painful disorders were reviewed. MEASURES: Publications reported on QST methodological issues including associations among measures and reliability. We also included publications on the use of QST measures in case-control studies, their associations with biopsychosocial mechanisms, QST measures predicting clinical pain, as well as predicting and reflecting treatment responses. RESULTS: Although evidence suggests that QST may be useful in a mechanism-based classification of pain, there are gaps in our current understanding that need to be addressed including making QST more applicable in clinical settings. There is a need for developing shorter QST protocols that are clinically predictive of various pain subtypes and treatment responses without requiring expensive equipment. Future studies are needed, examining the clinical predictive value of QST including sensitivity and specificity for pain classification or outcome prediction. These findings could enable third-party payers' reimbursement, which would facilitate clinical implementation of QST. CONCLUSIONS: With some developments, QST could become a cost-effective and clinically useful component of pain assessment and diagnosis, which can further our progress toward the goal of mechanism-based personalized pain management. Wiley Periodicals, Inc.
OBJECTIVE: This review summarizes the scientific literature relating to the use of quantitative sensory testing (QST) for mechanism-based pain management. DESIGN: A literature search was undertaken using PubMed and search terms including quantitative sensory testing, pain, chronic pain, response to treatment, outcome measure. SETTINGS AND PATIENTS: Studies including QST in healthy individuals and those with painful disorders were reviewed. MEASURES: Publications reported on QST methodological issues including associations among measures and reliability. We also included publications on the use of QST measures in case-control studies, their associations with biopsychosocial mechanisms, QST measures predicting clinical pain, as well as predicting and reflecting treatment responses. RESULTS: Although evidence suggests that QST may be useful in a mechanism-based classification of pain, there are gaps in our current understanding that need to be addressed including making QST more applicable in clinical settings. There is a need for developing shorter QST protocols that are clinically predictive of various pain subtypes and treatment responses without requiring expensive equipment. Future studies are needed, examining the clinical predictive value of QST including sensitivity and specificity for pain classification or outcome prediction. These findings could enable third-party payers' reimbursement, which would facilitate clinical implementation of QST. CONCLUSIONS: With some developments, QST could become a cost-effective and clinically useful component of pain assessment and diagnosis, which can further our progress toward the goal of mechanism-based personalized pain management. Wiley Periodicals, Inc.
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