A pivotal article by Hortobagyi et al in the 1983 Volume 1 issue of Journal of Clinical Oncology addressed the impact of predictive and prognostic models in the setting of metastatic breast cancer. At that time, clinical variables were used in a forward stepwise logistic regression procedure to determine the patient characteristics important in predicting response to doxorubicin-containing chemotherapeutic regimens. Three models for assessing prognosis were generated by this study, which pioneered the use of mathematical algorithmic probability equations and biologic stratification as predictors for individual, rather than random, outcomes. Within the past two decades, the management of metastatic breast cancer has evolved, with the introduction of new chemotherapeutic agents (taxanes, vinorelbine, gemcitabine, and capecitabine), newer hormonal agents, including third-generation aromatase inhibitors, and biologic therapies, such as trastuzumab, bevacizumab, and lapatinib. However, metastatic breast cancer remains incurable, though therapeutic innovation has resulted in modest improvements in survival rates. The original article proposed a model of prognostication with a purely demographic and anatomic base. Since then, thinking has evolved to a biologic and genetic platform. The introduction of novel technology has enabled scientists to further classify breast tumors using methods that can measure differences in thousands of biologic pathways simultaneously. The purpose of this editorial is to highlight the article’s original perspective in light of the rapidly changing field of predictors of response and individualized therapy for the treatment of patients with breast cancer. The original models proposed are still useful in the estimation of risk in patients with breast cancer. Even today, anatomic staging continues to play a major role in guiding treatment decisions. The extent of the disease, disease-free intervals, prior adjuvant therapy, and performance status remain of prognostic value. Although the level of risk may be useful in deciding between certain types of regimens (chemotherapy v hormonal therapy) as an initial treatment option, it does not offer guidance as to actual drug selection for individual patients. It has become clear that the unpredictable clinical behavior of metastatic breast cancer reflects the biologic heterogeneity of the disease. This heterogeneity introduces subgroups that benefit from therapeutic innovations and likely account for the modest improvements in survival. Current technology provides a powerful method to help identify and validate new drug targets, as well as potential diagnostic and prognostic markers for use as predictors of response to new molecular therapeutics. In light of this, the focus has moved increasingly away from dose escalation and intensification of chemotherapy in otherwise unselected patients to the premise of targeting specific biologic pathways in selected patients using pharmacologic or immunologic methods. Although the prototype target in breast cancer has been known for approximately 40 years, we only came to accept, after the 1995 Oxford overview, that essentially all the benefit derived from tamoxifen is limited to patients with estrogen receptor (ER) –positive breast cancer, regardless of stage and age. However, not every patient with ER-positive breast cancer benefits from tamoxifen. For this reason, several endocrine approaches have been developed that interrupt estrogen stimulation, either by directly modulating the ER-signaling pathway or by lowering serum or tumor concentrations of estrogen. Beyond the classic pathway, new evidence suggests that cross-talk exists between the ER and growth factor receptor pathways, contributing to de novo and acquired resistance to endocrine therapy. Inappropriate activation of growth factor signaling can readily promote endocrine therapy failure in breast cancer cells, by either overriding the growth-inhibitory properties of antiestrogenic drugs or by the establishment of a new self-propagating autocrine loop that efficiently drives resistant cell growth. Modern therapies also target deregulated critical biochemical pathways present in cancer cells that result in changes in normal cellular processes such as apoptosis, proliferation, angiogenesis, DNA repair, cell cycle progression, invasion, and metastases. Like ER, some of these molecular defects have prognostic or predictive value, whereas others are implicated in resistance to chemotherapy or hormone therapy. Drugs that target these pathways have been demonstrated to improve response and/or survival in patients with metastatic breast cancer. The adverse prognosis of the human epidermal growth factor receptor 2 (HER2) –positive breast cancer has been recognized since the seminal publication by Slamon et al 20 years ago. Ten years ago, randomized trials of anti-HER2 therapy added to first-line chemotherapy in patients with HER2-overexpressing metastatic disease showed increased clinical benefit and survival. For certain agents, such as lapatinib and trastuzumab, a preclinical knowledge of the drugs’ target led to appropriate patient selection, JOURNAL OF CLINICAL ONCOLOGY C E L E B R A T I N G 2 5 Y E A R S O F J C O VOLUME 26 NUMBER 22 AUGUST 1 2008