ArticleFrontiers in pharmacology2024
Clinical predictors of treatment response to gabapentin in women with unexplained chronic pelvic pain.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Introduction: Chronic pelvic pain affects up to 24% of women worldwide and for up to 55% of these there is no associated pathology. Despite this there are no established treatments in this cohort. This is a secondary analysis of a randomised-controlled trial (GaPP2) to explore if there are measures which enable us to predict treatment outcome. Methods: GaPP2 recruited women with chronic pelvic pain and no identified pathology and compared the response to gabapentin and placebo. This analysis used variables collected at baseline including validated questionnaires. Binary logistic regression was used to create models to explore whether baseline variables predicted treatment response. Treatment response was determined using 30% reduction in average pain intensity, 30% reduction in worst pain intensity and the Patient Global Impression of Change ('marked' or 'very marked' improvement) individually. We also explored whether baseline variables predicted the occurrence of side-effects (dizziness, visual disturbances and drowsiness). Results: Using the Patient Global Impression of Change questionnaire, we found a significant binary logistic regression ( Discussion: Researchers and clinicians are increasingly aware of the importance of personalised medicine and treatment decisions being driven by knowledge of what treatments work for whom. Our data suggests an important role of the Patient Global Impression of Change in clinical trials as it may better reflect balance between symptoms reduction and side-effects and therefore be more useful in clinician-patients joint decision making.
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