The doses and schedules for molecularly targeted therapies are often not well-characterized prior to initiating trials with registrational intent for marketing approval. This can lead to the selection of dosages that have increased toxicity without additional efficacy.
Therapies may be poorly tolerated at approved dosages, leading patients or providers to prematurely modify the dosage or discontinue an otherwise efficacious treatment. FDA launched 'Project Optimus' to emphasize the need for dosage optimization prior to drug approval. An understanding of how the toxicities and dosage modifications for approved targeted therapies affect outcomes for patients in the real world setting will enhance Project Optimus efforts, in collaboration with the Oncology Real World Evidence program, to advance potential patient-centric uses of real-world data. To bridge this knowledge gap, we will investigate the prevalence of dosage modifications in patients and the resulting safety and effectiveness profiles of targeted therapies commonly prescribed for patients with Chronic Lymphocytic Leukemia (CLL) and Chronic Myeloid Leukemia (CML).
We will primarily use real-world data (RWD) sourced from the Clinical Data Warehouse at the University of North Carolina at Chapel Hill to address three key questions. Firstly, we will assess the frequency of dosage modifications in patients in the real-world setting using pharmacy refill records and electronic medical record information. Secondly, we will aim to determine whether modifications in treatment doses, made in response to tolerability, have any negative impact on clinical outcomes including survival. Lastly, we will explore whether the toxicity associated with treatment directly affects clinical outcomes including survival among patients in the real-world setting.
We will primarily utilize the clinical data warehouse at UNC Health Care System for this project, and we are also considering other sources of real-world data, such as medical claims data and randomized clinical trials, where appropriate to support the analyses. Recognizing the potential challenges and biases that can be associated with RWD studies, we will harness the capabilities of statistical modeling and advanced data mining and causal inference approaches to explore methodological approaches to provide valid answers to these questions.
Publications
- Natalie Hollon, Viet Dang, Grace Eramo, Ravi Parekh, Ama Boamah, Janiyah Sutton, Angela Su, Rima Vyas, Sophia Stein, Euguene Lee, Kevin Yanjun Chen, Yanguang Cao, and Benyam Muluneh. Prevalence of dosage modifications and impact on response milestone among patients with CML treated with imatinib using RWD. Meeting Abstract: 2025 ASCO Annual Meeting. J Clin Oncol 43, e23335(2025), number 15 suppl. 2025 May:28. doi: 10.1200/JCO.2025.43.16_suppl.e23335
