PROJECT SUMMARY / ABSTRACT
As treatment regimens for chronic hepatitis C evolve at a rapid pace, the decision to treat immediately or defer
for the promise of future therapy has become increasingly complex. Treatment considerations must balance
multiple patient characteristics, preferences, and treatment efficacy data, much of which fraught with
uncertainty. Decision analytic modeling can augment traditional clinical studies by elucidating the comparative
benefits and harms of treatment timing in different patient populations. The active integration of treatment
priorities and challenges as directly elicited from patients and providers during the modeling process can
ensure the relevancy of such analyses to key stakeholders as well as the effective dissemination of results.
Such data could be highly useful in communicating tailored, patient-oriented estimates of risks and benefits of
HCV therapy between health care providers affected patients, thereby improving informed medical decision
making. Additionally, a clearer understanding of data uncertainty in the current literature could lead to rational
priority setting for future research in hepatitis C care and treatment.
I have developed a strong foundation in biostatistics, epidemiology, and decision-analytic methods through the
completion of a Masters of Public Health, as well as through broad analytic experience within highly rigorous
research environments at the Massachusetts General Hospital, Northwestern University, and now the
University of Chicago. Through this K99/R00 proposal I will further develop my expertise in complex disease
modeling, and examine, within the context of provider and patient interaction, how medical decision-making
can be better informed by stakeholder engagement as well as better understanding of data uncertainty.
Through Aim 1 I propose to develop a community partnership through the creation of a Patient and
Stakeholder Advisory Board (PSAB) in order to inform the design of a decision-analytic model, identify the
factors impacting decision-making surrounding hepatitis C treatment, review and monitor model outputs and
optimize the dissemination of results. This will be achieved through systematic process throughout the course
of the award and will utilize nominal group techniques, focused surveys and open discussion. I will then use
the knowledge gained from this partnership to adapt and further develop a published state transition model of
HCV natural history and treatment (Aim 2) that may serve as a platform to evaluate clinical questions requiring
sequential decision-making between current and future therapies. I will use this model to examine the
comparative effectiveness of immediate versus deferred treatment for different subpopulations of patients
afflicted with hepatitis C (Aim 3). Using advanced sensitivity analysis techniques and value of information
analyses, I will identify areas of future research in hepatitis C natural history and treatment that would have
greatest impact on overall clinical outcomes (Aim 4). The proposed analysis addresses the specific research
priorities of the Department of Health and Human Services Action Plan for the Prevention, Care, & Treatment
of Viral Hepatitis to advance research in care for the diverse populations living with viral hepatitis, and is fully
aligned with the mission of Section 6301(b) of the Patient Protection and Affordable Care Act to strengthen
data-driven, patient-centered outcomes research.
To ensure the success of this proposed K99/R00 project I have assembled a highly experienced and expert
team of mentors and scientific advisors, including my mentor Dr. David Meltzer MD, PhD, and co-mentor Dr.
Donald Jensen, MD, who will provide training in advanced analytic methodologies such as complex model
building, value of information analysis, and qualitative methods, as well as content expertise in hepatitis C
natural history and treatment. The University of Chicago is a world-class research institution, and the
Department of Medicine and Section of Hospital Medicine have committed resources and support based on the
strength of this proposal, as well as my own potential to contribute meaningfully to the field of comparative
effectiveness research in hepatitis C. The K99/R00 award will provide a critical mechanism, through high
intensity advanced training, expert mentorship, and analytic platform building to achieve a rapid transition to
independence and to establish a career in patient-centered decision-analytic outcomes research.
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