Project Summary

The randomized controlled trial (RCT) is the gold standard in efficacy research. However, RCT participants may not well represent the patient population, a concern frequently voiced in particular for elderly cancer patients. In the absence of robust data from RCTs with fair representation of older adults, comparative effectiveness research (CER) studies, using large, observational healthcare data, are critical for the identification of effective, real-world treatment strategies for the elderly. More generally, CER studies leveraging established, observational healthcare databases can have meaningful and complementary roles in evaluating patient-centered outcomes, in circumstances where RCTs are impractical or unethical.

In CER studies where the primary interest lies in a non-terminal-event-type patient outcome (e.g., cancer recurrence), current methods for CER using large, complex, observational data are suboptimal and lacking to address statistical complexities related to semi-competing risks, clustered measurements, confounding, and incomplete observations. We will address these issues by developing novel design and analytical methods for CER studies where the primary, patient-centered outcome is subject to semi-competing risks. We then aim to implement the developed methods and disseminate the research findings. Specifically, we will:

(1) Develop  robust, time-varying treatment effect, hierarchical regression models for multilevel semi-competing risks data; Evaluate the proposed method using extensive simulations, and compare it with the existing method and a fully competing risks method.

(2) Develop a novel, propensity score weighting method to account for confounding and a novel, multiple imputation method to account for incomplete observations, for multilevel semi-competing risks data; Evaluate the proposed methods using simulations and conduct sensitivity analyses to study the impact of unobserved confounders and model robustness.

(3) Implement the developed method in a CER analysis of SEER-Medicare data to assess the effectiveness of chemoradiotherapy vs. induction chemotherapy for elderly patients with oropharyngeal cancer; disseminate the research findings toward patients, caregivers, clinicians, and healthcare researchers through user-friendly software, peer-reviewed publications, presentations, webinars, and digital media.

The developed methods will be broadly applicable to other health conditions, in cancer and beyond. The resulting, improved CER design and analyses will generate crucial evidence relevant to the decisions of patients, clinicians, and regulators, ensuring that all patients receive high quality, evidence-based care, ultimately improving patient outcomes.

We will meaningfully engage patients and stakeholders throughout the study, from planning to conducting to dissemination, to ensure patient-centeredness. We have established a Healthcare Stakeholder Advisory Panel composed of 6 expert clinicians/behavioral scientists with extensive experience in patient care and healthcare research and one patient advocate. We will hold quarterly advisory panel meetings over the study period to solicit patients’/stakeholders’ input and perspectives on knowledge gaps, design and analytical issues, implementation and dissemination strategies.

Project Information

Hong Zhu, PhD
The University of Texas Southwestern Medical Center

Key Dates

March 2022
August 2026


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Last updated: January 20, 2023