UCSF

Using menopausal hormone therapy (HT) for more than five years puts women at increased risk for breast, ovarian, and endometrial cancer, cardiovascular disease (CVD), gallbladder disease, incontinence, and dementia. For this reason, HT is not recommended beyond this therapeutic window, except in rare circumstances. Nevertheless, data on filled prescriptions indicate that over a third of HT prescriptions are written for women over age 60. These alarming facts raised the research questions: "What factors influence older women to use HT beyond the menopause transition?" and "How do older women weigh the risks and benefits of HT?"

Conventional grounded theory methods were used to interview 30 long-term users of systemic HT, code transcripts, and analyze data. Results showed that long-term users perceived that HT gave them control of numerous symptoms they attributed to menopause, enabled them to maintain attributes associated with youth and femininity, and helped them avoid diseases associated with aging, such as dementia and CVD. Risk was rarely mentioned in interviews; it was generally disregarded; and most participants did not know that age and length of HT use increase the risk of breast cancer. Users were observed to be the primary drivers of long-term HT, although gynecology specialty providers played a major role by giving reassurance about risk and continuing to prescribe HT.

Arguing that the science behind the quantification of HT risk is faulty, some hormone manufacturers promote HT for long-term use. This promotion is largely directed at gynecology specialists through strategies such as ghostwriting, and, as a consequence, many of them remain skeptical of prescribing guidelines that recommend limiting duration of use. Key concepts from the literature on decision making that help explain disregard of risk information were identified.

Study findings are applicable to any clinical encounter that involves weighing benefit and risk. Recommendations to providers: Learn to distinguish science from marketing. Help patients understand that positive feelings about treatment may be based on unrealistic expectations for efficacy and underestimation of risk. Discuss judgment biases and cite base rates when providing risk statistics in clinical encounters. Such interventions could potentially strengthen joint decision making and improve patient outcomes.