Symptom clusters among MsFLASH clinical trial participants

Area of Science:

• Reproductive Medicine
• Clinical Psychology
• Symptom Science

Background:

• Menopausal symptoms significantly impact quality of life.
• Standardized measures are crucial for objective symptom assessment.
• Identifying symptom clusters can reveal distinct patient profiles.

Purpose of the Study:

• To identify symptom clusters in menopausal women using baseline data from a clinical trial.
• To analyze co-occurring symptoms including hot flashes, sleep, mood, and pain.

Main Methods:

• Latent class analysis was applied to data from 797 women in the Menopausal Strategies: Finding Lasting Answers to Symptoms and Health trial.
• Standardized scales measured hot flash interference, sleep quality, depressed mood, anxiety, and pain.
• Bayesian Information Criterion and Akaike Information Criterion were used to determine the number of classes.

Main Results:

• Five distinct symptom clusters were identified.
• Class 1 (10.5%) and Class 2 (14.1%) exhibited severe hot flash interference, with Class 2 also showing severe mood and pain symptoms.
• Class 3 (39.6%) had moderate sleep and hot flash symptoms, while Class 5 (28.7%) reported low severity across all symptoms.

Conclusions:

• Menopausal women exhibit identifiable symptom clusters based on symptom interference and severity.
• The identified clusters represent distinct symptom profiles, not just varying severity levels.
• These symptom clusters may serve as valuable phenotypes for treatment research and biomarker studies.