Sex differences in pain expressed by patients across diverse disease states: individual patient data meta-analysis of 33,957 participants in 10 randomized controlled trials

Jessica X. L. Li, Xia Wang, Amanda Henry, Craig S. Anderson, Naomi Hammond, Katie Harris, Hueiming Liu, Kelly Loffler, John Myburgh, Jeyaraj Pandian, Brendan Smyth, Balasubramanian Venkatesh, Cheryl Carcel, Mark Woodward

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The experience of pain is determined by many factors and has a significant impact on quality of life. This study aimed to determine sex differences in pain prevalence and intensity reported by participants with diverse disease states in several large international clinical trials. Individual participant data meta-analysis was conducted using EuroQol-5 Dimension (EQ-5D) questionnaire pain data from randomised controlled trials published between January 2000 and January 2020 and undertaken by investigators at the George Institute for Global Health. Proportional odds logistic regression models, comparing pain scores between females and males and fitted with adjustments for age and randomized treatment, were pooled in a random-effects meta-analysis. In 10 trials involving 33,957 participants (38% females) with EQ-5D pain score data, the mean age ranged between 50 and 74. Pain was reported more frequently by females than males (47% vs 37%; P < 0.001). Females also reported greater levels of pain than males (adjusted odds ratio 1.41, 95% CI 1.24-1.61; P < 0.001). In stratified analyses, there were differences in pain by disease group (P for heterogeneity <0.001), but not by age group or region of recruitment. Females were more likely to report pain, and at a higher level, compared with males across diverse diseases, all ages, and geographical regions. This study reinforces the importance of reporting sex-disaggregated analysis to identify similarities and differences between females and males that reflect variable biology and may affect disease profiles and have implications for management.

Original languageEnglish
Pages (from-to)1666-1676
Number of pages11
JournalPain
Volume164
Issue number8
Early online date24 Mar 2023
DOIs
Publication statusPublished - 1 Aug 2023

Keywords

  • Meta-analysis
  • Pain
  • Sex differences

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