Lead Investigator: Kenta Yoshida, Genentech, Inc.
Title of Proposal Research: Tumor Growth Inhibition-Overall Survival (TGI-OS) model development and validation for hormone receptor positive (HR+)human epidermal growth factor receptor 2 negative (HER2-) breast cancer
Vivli Data Request: 8563
Funding Source: The researchers are employees of Genentech/Roche.
Potential Conflicts of Interest: Kenta Yoshida is an employee of Genentech, Inc., a member of the Roche Group, and is a Roche stockholder. Conflict of interest will be managed through disclosure of interests when the research is presented and published.
René Bruno is an employee of Roche, and is a Roche stockholder. Conflict of interest will be managed through disclosure of interests when the research is presented and published.
Summary of the Proposed Research:
Breast cancer is one of the most common cancers with more than 200 thousand new diagnoses each year in the US alone. Breast cancer has certain subtypes that influence the treatment options. One such type is called hormone receptor positive (HR+) that represents over 70% of the disease. In a woman’s body, estrogen is the hormone that regulates the menstrual cycle while progesterone is the hormone that supports pregnancy. Cell receptors are proteins either inside a cell or on its surface which receive a signal. Tumor in HR+ breast cancer express receptors against estrogen or progesterone. Another important subtype human epidermal growth factor receptor 2 negative (HER2-); HER2 helps control cell growth in normal cells. While there are multiple treatments available including recently approved drugs, significant unmet needs remain for this combination of subtypes (HR+/HER2-). The purpose of this study is to develop a tool that can enhance the development of new treatments.
One of the key challenges of the development of new cancer treatment is the size of the clinical trials (number of patients). This is because the duration of a patient’s life after treatment, or overall survival (OS), is often used as the main indicator of an effective treatment in clinical trials for cancer, and OS requires a large number of patients to demonstrate efficacy. Therefore, there is a need to develop alternative tools that can predict efficacy with smaller amounts of data.
The approach being investigated in this study is to analyze how the size of the tumor changes over time (time profile) after the treatment. Because tumor time profile has rich information on each patient’s response to treatment, it is believed that modeling tumor time profile can give us prediction of OS with smaller data. It is also believed that relationships between tumor time profile and OS are common across studies, i.e. once we learn such relationships from previous clinical trials, we can predict OS based only on the tumor time profile for a new study, thereby reducing the need for large clinical trials.
This study aims to develop a mathematical model that links tumor time profile with OS using clinical trial data for a recently approved drug (palbociclib). If successful, this can be a useful tool for future drug development in the HR+ breast cancer indication.
MULTICENTER, RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, PHASE 3 TRIAL OF FULVESTRANT (FASLODEX (REGISTERED)). WITH OR WITHOUT PD-0332991 (PALBOCICLIB) +/- GOSERELIN IN WOMEN WITH HORMONE RECEPTOR-POSITIVE, HER2-NEGATIVE METASTATIC BREAST CANCER WHOSE DISEASE PROGRESSED AFTER PRIOR ENDOCRINE THERAPY
Data Contributor: Pfizer
Study ID: NCT01942135
Sponsor ID: A5481023
A RANDOMIZED, MULTICENTER, DOUBLE-BLIND PHASE 3 STUDY OF PD-0332991 (ORAL CDK 4/6 INHIBITOR) PLUS LETROZOLE VERSUS PLACEBO PLUS LETROZOLE FOR THE TREATMENT OF POSTMENOPAUSAL WOMEN WITH ER (+), HER2 (-) BREAST CANCER WHO HAVE NOT RECEIVED ANY PRIOR SYSTEMIC ANTI CANCER TREATMENT FOR ADVANCED DISEASE
Data Contributor: Pfizer
Study ID: NCT01740427
Sponsor ID: A5481008