This application addresses broad Challenge Area (05) entitled """"""""Comparative Effectiveness Research (CER)"""""""". Within that area, we are addressing the specific high priority challenge topic 05-CA-104* Comparative Effectiveness Research on Cancer Treatment. Our application also responds to the specific challenge topic 04-CA-110 Treatment of Prostate Cancer. Androgen Deprivation Therapy (ADT) has become increasingly used as primary monotherapy for older men with newly diagnosed localized disease not receiving other curative treatments (surgery or radiotherapy), despite the fact that there is no proven mortality benefit from clinical trials. Given the increasing number of elderly men, the high incidence and survival rates from prostate cancer, and the use of ADT in one-third of 2 million men newly diagnosed or surviving with prostate cancer, there is a growing need for information on effectiveness and costs to inform policy and treatment decisions. Clinical trials are not ongoing or likely to be conducted to address these issues. To address the limitations of prior observational database studies, we propose a new comparative effectiveness study to provide information on the risks and potential benefits of immediate ADT in men diagnosed with localized prostate cancer. Our three aims include estimating the comparative effectiveness of immediate ADT versus observation in terms of all cause and prostate-cancer specific mortality and progression-free survival, estimating the longitudinal direct medical care costs to capture the impact of ADT, and calculating the cost- effectiveness (cost per life years saved) and cost-utility (quality-adjusted life years) using published patient utilities for multiple prostate cancer health states. We will assess all outcomes according to prognostic risk groups defined by age, stage, serum biomarker values (PSA), and other pathological markers of tumor aggressiveness. We will account for variations in baseline comorbidity and sociodemographic factors, and use state-of-the-art comparative effectiveness techniques to address selection bias. The retrospective observational study will be conducted using a large, diverse population of nearly 10,000 men with localized disease diagnosed from 1995-2007 with a mean follow up of 6 years. There are comprehensive computerized clinical utilization data for this population from 2 large integrated health care plans, including longitudinal information on tumor characteristics, risk factors and outcomes. Key variables will be derived from inpatient, outpatient, pharmacy and radiology data and lab test values. In contrast to prior observational studies, ours will have the combination of size, follow up, and detailed clinical information over the entire disease trajectory needed to significantly improve the precision of estimates of mortality and progression-free survival following ADT in sub-groups of men at varying levels of baseline risk. These strengths, and our multi-disciplinary team experienced in prostate cancer research using large databases, ensure that our results will be useful to improve practice, policy, and health outcomes. This is a multisite study to investigate the Challenge Area of Comparative Effectiveness Research on Cancer Treatment and specifically the Treatment of Prostate Cancer. We propose a new comparative effectiveness study to provide information on the risks and potential benefits of immediate ADT in men diagnosed with localized prostate cancer using data from two integrated health delivery systems with access to comprehensive health, utilization, cost, and socioeconomic data.
This is a multisite study to investigate the Challenge Area of Comparative Effectiveness Research on Cancer Treatment and specifically the Treatment of Prostate Cancer. We propose a new comparative effectiveness study to provide information on the risks and potential benefits of immediate ADT in men diagnosed with localized prostate cancer using data from two integrated health delivery systems with access to comprehensive health, utilization, cost, and socioeconomic data.
