Features that predict responsiveness to chemotherapy and endocrine therapies

Prognostic factors, characterizing the background level of risk of relapse, and predictive factors, characterizing the degree of responsiveness to a s pecific treatment, are both used to select adjuvant therapies for patients with early-stage breast cancer. Determining how best to utilize available f actors 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-h ormone-receptor status of the primary tumour and patient age/menopausal sta tus (primarily reflecting the robustness of ovarian function) are the key f eatures 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. Th e STEPP (Subpopulation Treatment Effect Pattern Plots) method, by investiga ting the patterns of treatment effects within randomized clinical trials or datasets from meta-analyses, will help to identify features that predict r esponsiveness to the treatments under study without the pitfalls of selecti ve retrospective subset analysis. Subset analyses according to steroid-horm one-receptor status and patient age should now be considered as prospective ly defined. Future clinical trials should be designed as tailored treatment investigations, with endocrine therapies being evaluated within population s of patients with endocrine-responsive tumours, and chemotherapy questions being addressed within populations of patients with endocrine non-responsi ve disease. (C) 2001 Harcourt Publishers Ltd.