ArticleFrontiers in pain research (Lausanne, Switzerland)2026
Exploring predictors of analgesic response in adult women regularly using NSAIDs: insights from a machine learning approach.
Article in Frontiers in pain research (Lausanne, Switzerland), 2026. 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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Abstract
Introduction: Non-steroidal anti-inflammatory drugs (NSAIDs) are considered a first-line treatment for dysmenorrhea (menstrual pain). However, as much as 20% of women fail to achieve sufficient pain relief from NSAIDs, although factors associated with NSAID non-response are not well-known. The purpose of this study was to investigate factors associated with analgesic response to NSAIDs for dysmenorrhea. Methods: Data were from a large survey study of adult women who reported regularly using NSAIDs for dysmenorrhea. Demographic information, menstrual characteristics, comorbid conditions, and psychosocial factors were collected. NSAID non-response was defined as self-reported minimal or no menstrual pain relief from NSAIDs. We repeatedly applied a group least absolute shrinkage and selection operator (LASSO) logistic regression 100 times, and averaged results to account for model uncertainty and to identify variables related to NSAID non-response. Results: Of 512 women (mean age = 34.0 years, SD = 9.4) who met inclusion criteria, 182 (35.5%) were classified as NSAID non-responders. NSAID non-responders reported significantly higher average menstrual pain severity than responders (mean = 7.4 vs. 6.2 on a 0-10 scale, Discussion: In this large cross-sectional cohort, women reporting inadequate menstrual pain relief from NSAIDs had more severe menstrual pain and related symptoms, along with indicators of pain amplification (sleep disturbance). Most psychosocial factors (e.g., negative mood) did not correlate with NSAID non-response. These findings underscore the heterogeneity of dysmenorrhea and suggest that clinical factors alone may be insufficient to predict NSAID effectiveness. Further prospective studies are needed to confirm these associations and to explore whether interventions (such as optimizing NSAID timing or addressing sleep disturbances) could improve menstrual pain outcomes for those with NSAID non-response.
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