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Menopausal hormone therapy and the incidence of carpal tunnel syndrome in postmenopausal women: Findings from the Women’s Health Initiative

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  • Tala Al-Rousan
  • Jeffrey A Sparks
  • Mary Pettinger
  • Rowan Chlebowski
  • JoAnn E Manson
  • Andrew M Kauntiz
  • Robert Wallace

Abstract

Importance: Carpal tunnel syndrome (CTS) is a common and debilitating condition that commonly affects postmenopausal women. Objective: To determine the effect of menopausal hormone therapy (HT) in healthy postmenopausal women on CTS risk. Design: We conducted a secondary analysis of the Women’s Health Initiative’s (WHI) HT trials linked to Medicare claims data. Separate intention-to-treat analyses were performed for the two trials; the conjugated equine estrogens alone (CEE alone) and the trial of CEE plus medroxyprogesterone acetate (MPA) trial. (ClinicalTrials.gov, NCT number): NCT00000611. Setting: Two randomized, double-blind, placebo-controlled trials conducted at 40 US clinical centers. Participants: The sample size included in the analysis was 16,053 community-dwelling women aged ≥65 years at study entry or those who later aged into Medicare eligibility, and who were enrolled in Medicare (including Part A and/or Part B coverage). Intervention: Women with hysterectomy were randomized to 0.625 mg/d of conjugated equine estrogens (CEE) or placebo (n = 8376). Women without hysterectomy were randomized to estrogen plus progestin (E+P), given as CEE plus 2.5 mg/d of medroxyprogesterone acetate (n = 14203). Main outcome(s): The primary outcome was incident CTS and the secondary outcome was therapeutic CTS procedure occurring during the intervention phases of the trials. Results: A total of 16,053 women were randomized in both trials. During mean follow up of 4.5 ± 2.8 years in the CEE trial (n = 6,833), there were 203 incident CTS cases in the intervention and 262 incident CTS cases in the placebo group (HR, 0.78; 95% CI, 0.65–0.94; P = 0.009). The CEE+MPA trial (n = 9,220) followed participants for a mean of 3.7 ± 2.3 years. There were 173 incident CTS cases in the intervention compared to 203 cases in the placebo group (HR, 0.80, 95% CI, 0.65–0.97; P = 0.027). Conclusions: These findings suggest a protective effect of menopausal HT on the incidence of CTS among postmenopausal women. A potential therapeutic role for other forms of estrogen therapy in the management of CTS warrants future research.

Suggested Citation

  • Tala Al-Rousan & Jeffrey A Sparks & Mary Pettinger & Rowan Chlebowski & JoAnn E Manson & Andrew M Kauntiz & Robert Wallace, 2018. "Menopausal hormone therapy and the incidence of carpal tunnel syndrome in postmenopausal women: Findings from the Women’s Health Initiative," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-15, December.
    • Handle: RePEc:plo:pone00:0207509
    DOI: 10.1371/journal.pone.0207509
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    1. James M. Robins & Dianne M. Finkelstein, 2000. "Correcting for Noncompliance and Dependent Censoring in an AIDS Clinical Trial with Inverse Probability of Censoring Weighted (IPCW) Log-Rank Tests," Biometrics, The International Biometric Society, vol. 56(3), pages 779-788, September.
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