Statistical methods
REGRESSION
The data was analysed using SPSS statistic Version 28. Baseline demographics and characteristics of the patients were summarized using median and range, or mean and standard deviation. The association between baseline hormone levels, and between hormone levels and demographic characteristics (age, BMI, weight, waist circumference) was tested with the Pearson correlation coefficient. The association between treatment discontinuation and baseline hormone levels was tested with the unpaired t-test. A Bonferroni correction for multiple testing was used when appropriate.We tested the effect of the magnitude of change of E2 levels during letrozole treatment in two steps. Firstly, we determined the significance of changes in QoL and symptom scores from baseline to 12 months by a paired t-test. Due to the large number of testable variables a Bonferroni correction was applied, and the level of significance was set as < 0.001. Only scales with significant change during letrozole treatment were tested for association with E2 changes during treatment. The analysis was done by linear regression on score change during treatment by hormone level. In addition to significantly changed single items we also tested the impact of E2 on change in global QoL assessed by the EORTC QLQ-C30 questionnaires.