Development of a Novel Methodology for Endpoints Assessing Response to Lymphoma Treatment in Real-World Studies
External Institution: Cardinal Health
External Collaborators: Scott Swain, PhD, MPH; Andrew Klink, PhD, MPH; Kristin Zimmerman Savill, PhD; Hsing-Ting Yu, MPH
FDA Collaborators: Nicholas Richardson, DO, MPH; Donna Rivera, PharmD, MSC; Jonathon Vallejo, PhD; Catherine Lerro, PhD, MPH; Kun Wang, PhD; Fatima Rizvi, PharmD
Project Start Date: October 2021
Regulatory Science Challenge
Real-world evidence (RWE) can be submitted to the United States (US) Food and Drug Administration (FDA) to support regulatory approval of oncology drugs by providing supplemental information in addition to data from clinical trials. Use cases for RWE include drug utilization and off-label prescribing, natural history, external comparators, and long-term safety and efficacy. Furthermore, sources of real-world data (RWD) can be incorporated into the drug development process in the form of pragmatic or decentralized clinical trials. However, all sources of data are vulnerable to bias, and RWD can be particularly susceptible since it is mostly recorded for other purposes such as for billing or to record a medical history. One major source of bias in RWE studies is misclassification, where a variable is not accurately categorized. Misclassification is a particularly troubling issue when multiple sources or types of data are used, such as when comparing clinical trial data to RWD, because variables may be captured with unequal accuracy in the individual data sources. Consequently, one of the FDA’s Areas of Interest is to develop, define, and test real-world oncology endpoints from RWD that could be used to generate RWE to complement traditional clinical trial data.
Project Description and Goals
Medical chart review studies in oncology typically rely on physician notes to measure treatment response. We have developed a novel methodology, called real-world Lugano (rwLugano), derived from the Lugano 2014 classification criteria, to assess response to diffuse large B-cell lymphoma (DLBCL) treatment in real-world studies. We calculate rwLugano by extracting clinical data from patient medical records and using that data to compute treatment response using the Lugano 2014 classification. The primary objective of our study is to determine if rwLugano is a more accurate method for lymphoma treatment outcome classification in real-world studies compared to physician-charted response. To do this, we are conducting a retrospective chart review study to identify diffuse large B-cell lymphoma (DLBCL) patients who received first-line systemic therapy within Cardinal Health’s Practice Research Network (PRN), a network of community oncology practices geographically distributed across the US.
We are collecting data including treatment response recorded in the medical chart (i.e., physician-reported response) and clinical data to calculate rwLugano. We are also collecting at least 2 de-identified radiology scans, 1 at baseline and 1 follow-up, for each study patient. Each set of de-identified scans will be provided to 2 radiologists for blinded independent central review (BICR), to replicate clinical trial methodology, and treatment response will be evaluated using Lugano 2014 criteria. We will then assess whether physician-reported response or rwLugano-derived response is more like BICR-reported response. The proposed rwLugano methodology is intended to provide a more objective measure of lymphoma treatment response and to offer a more accurate comparison when using RWD to complement traditional clinical trial data in regulatory submissions for oncology products.