Prognostic factors, characterizing the background level of risk of relapse, and predictive factors, characterizing the degree of responsiveness to a specific treatment, are both used to select adjuvant therapies for patients with early-stage breast cancer. Determining how best to utilize available factors is challenging. We review various prognostic and predictive factors and present examples to illustrate how these factors can be used to improve our understanding about selection of adjuvant treatments, re-evaluation of data from previous clinical trials and design of future studies. Steroid-hormone-receptor status of the primary tumour and patient age/menopausal status (primarily reflecting the robustness of ovarian function) are the key features that predict responsiveness to chemotherapy and endocrine therapies. Qualitative interactions between these factors, and effects of combining chemotherapy and endocrine therapies, may confound treatment comparison. The STEPP (Subpopulation Treatment Effect Pattern Plots) method, by investigating the patterns of treatment effects within randomized clinical trials or datasets from meta-analyses, will help to identify features that predict responsiveness to the treatments under study without the pitfalls of selective retrospective subset analysis. Subset analyses according to steroid-hormone-receptor status and patient age should now be considered as prospectively defined. Future clinical trials should be designed as tailored treatment investigations, with endocrine therapies being evaluated within populations of patients with endocrine-responsive tumours, and chemotherapy questions being addressed within populations of patients with endocrine non-responsive disease.
|Number of pages||11|
|Issue number||SUPPL. 3|
|Publication status||Published - 2001|
ASJC Scopus subject areas
- Obstetrics and Gynaecology