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Life sciences · Journal article
Menopause the Journal of the North American Menopause Society · October 6, 2026
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Objective: To evaluate Latin American physicians’ awareness regarding the recent revised statement of the US Food and Drug Administration (FDA) “black box warning” on menopausal hormone therapy (MHT) and to analyze its self-reported impact on clinical practice. Methods: A multicenter cross-sectional study was conducted in thirteen Latin American countries. Physicians caring for peri- and postmenopausal women completed an anonymous survey assessing awareness of the revised FDA communication, perceived clarity, self-reported impact on clinical practice, and MHT prescribing patterns. Bivariate analyses and multivariable logistic regression were performed. Results: A total of 2,166 physicians participated, mainly obstetrician-gynecologists (75.7%) and endocrinologists (9.0%). Overall, 80.7% were aware of the FDA revised statement. In addition, 90.5% considered that the previous warning had overestimated breast cancer risk, and 78.9% believed that the revised communication provides a more balanced view of risks and benefits. Changes in clinical practice were reported by 59.4% of participants, whereas 18.7% reported increased MHT prescribing. Furthermore, 53.3% modified the way they explain breast cancer risk, and 40.4% reported spending more time on patient education and shared decision-making. Physicians with ≤20 years of professional experience and those from specialties other than obstetrics and gynecology or endocrinology were more likely to report that the FDA revised statement would influence their therapeutic conduct. Conclusions: The revised FDA communication appears to have influenced Latin American physicians’ views and self-reported clinical practice, promoting a more balanced view of MHT and encouraging patient education and shared decision-making. However, the increase in MHT prescribing rates was relatively modest, and overall findings should be interpreted cautiously given the cross-sectional design, self-reported nature of the data, and potential selection bias.