Our Population Sciences Research spans a wide gamut of focus areas, ranging from Disparities and Cost-Effectiveness Research to Normal Tissue Modeling and Medical Ethics.
Our group are recognized experts in the field of competing risks and their impact on clinical trials. Currently clinical trials largely fail to account for the fact patients have a range of competing risks. The more a population of patients are likely to die from non-cancer causes, for example, the less likely they would benefit from an experimental therapy. Enrolling such patients on a randomized trial would likely result in no benefit from even a potentially highly effective therapy. Improved methods for stratifying patients according to competing event risk are needed to help individualize treatment. We have developed and validated such models. If adopted, they would greatly improve clinical trials.
The following Labs are involved in Competing Risks Research:
Nomogram to Predict the Benefit of Intensive Treatment for Locoregionally Advanced Head and Neck Cancer. This study presents a novel nomogram to help select head and neck patients for more intensive treatment based on their for cancer recurrence relative to their non-cancer mortality.
Given the growing health care costs and efforts to contain such costs, an important area of research is on cost-effectiveness, particularly the cost effectiveness of novel and often more expensive therapies. Only with understanding the benefits of such approaches can a rationale selection of treatment be made.
The following Faculty Labs involved in Cost-Effectiveness Research:
Cost-effectiveness of Intraoperative MRI for Treatment of High-Grade Gliomas. This study presents a clinical decision analysis model for assessing intraoperative MRI in high-grade glioma patients
Disparities research is a focus of multiple CPRM researchers. One area of research is in differences in patient care and treatment outcomes based on race and socioeconomic status. Our group recently received funding from the Department of Defense to study the role of active surveillance in African-American men with prostate cancer. Another interesting area of disparities research is focused on health care providers not patients. Our group has highlighted differences in industry payments to physicians based on gender and how men and women are treated differently in the residency match process.
The following Faculty Labs are involved in Disparities Research:
Differences in marital status and mortality by race/ethnicity and nativity among California cancer patients. The study examined the risk of overall mortality associated with marital status across racial/ethnic groups and sex in data from the California Cancer Registry.
Multiple CPRM faculty have considerable expertise in analyzing patient outcomes in large volume datasets with upwards of hundreds of thousands of patients. Such analyses can help answer important clinical questions, many of which may never to feasible to be addressed in a prospective clinical trial.
The following Faculty Labs involved in Health Outcomes Research:
Association of Treatment with 5α-Reductase Inhibitors with Time to Diagnosis and Mortality in Prostate Cancer. This study analyzes the impact of pre-diagnostic 5α-Reductase Inhibitors (5-ARI) use on the outcomes of prostate cancer patients
Advanced radiotherapy approaches provide the ability to deliver treatment with increased levels of normal tissue sparing. However, some or all of a particular normal tissue may still be included in the treatment. It is crucial to understand how normal tissues respond to different levels of radiation in order to optimize their sparing during the treatment planning process. Several RMAS faculty are experts in normal tissue complication modeling and have studied a wide range of normal tissues.
The following faculty are involved in Normal Tissue Modeling Research:
Normal Tissue Complication Probability (NTCP) modeling of late rectal bleeding following external beam radiotherapy for prostate cancer: A Test of the QUANTEC-recommended NTCP modelThis study tested the normal tissue complication probability (NTCP) model recommended in the recent QUANTEC review (quantitative analysis of normal tissue effects in the clinic).
Big Data can also provide insight into physician behavior surrounding compensation. Our group has performed several novel analyses of national provider databases focused on physician compensation and conflicts of interests.
Are We for Sale? Awareness of Industry-Related Financial Conflicts of Interest in Radiation Oncology. This study presents the first overview of industry-related conflicts of interest in our specialty