Prognosis research strategy (PROGRESS) 4: Stratified medicine research

Abstract

In patients with a particular disease or health condition, stratified medicine seeks to identify those who will have the most clinical benefit or least harm from a specific treatment. In this article, the fourth in the PROGRESS series, the authors discuss why prognosis research should form a cornerstone of stratified medicine, especially in regard to the identification of factors that predict individual treatment response A woman with newly diagnosed breast cancer is deciding on a course of therapy, guided by her physician. Evidence on the average prognosis1 and effectiveness of therapeutic interventions is available from studies of large groups of patients with breast cancer in observational studies and randomised trials. But the patient and doctor are faced with making a decision in an individual case, where the prognosis and response to treatment may deviate from average. One way to select the optimal treatment is to consider a test that predicts treatment effect, such as the human epidermal growth factor receptor 2 (HER-2) status.2 The use of HER-2 status in breast cancer management is an example of the translation of results from prognosis research toward improved patient outcomes. The prognosis of breast cancer patients is highly variable,1 HER-2 was discovered as a prognostic factor,3 which provided a specific target for an intervention (trastuzumab), which was then evaluated in trials which recruited women with HER-2 positive cancers (see fig 1⇓). After the success of these trials in improving clinical outcome, trastuzumab is now given to the subgroup (stratum) of women who are HER-2 positive, but not to those testing negative;4 this type of approach has been termed stratified medicine. Fig 1 Example of stratified medicines research, with translation from discovery of human epidermal growth factor receptor 2 (HER-2) status as a prognostic factor for metastatic breast …