Abstract
Quality of life (QoL) is a complex, ordinal endpoint with multiple conditioning factors. A predictive model of QoL after adjuvant chemotherapy can support decision making or the communication of information about the range of treatment options available. Patients with localized breast cancer (n = 219) were prospectively recruited at 17 centers. Participants completed the EORTC QLQ-C30 questionnaire. The primary aim was to predict health status upon completion of adjuvant chemotherapy adjusted for multiple covariates. We developed a Bayesian model with six covariates (chemotherapy regimen, TNM stage, axillary lymph node dissection, perceived risk of recurrence, age, type of surgery, and baseline EORTC scores). This model allows both prediction and causal inference. The patients with mastectomy reported a discrete decline on all QoL scores. The effect of surgery depended on the interaction with age. Women with ages on either end of the range displayed worse scores, especially with mastectomy. The perceived risk of recurrence had a striking effect on health status. In conclusion, we have developed a predictive model of health status in patients with early breast cancer based on the individual's profile.