Abstract 2390: Longitudinal assessment of circulating tumor DNA in patients with advanced colorectal cancer: A proposed general statistical framework and visualization tool
Authors: Christopher R. Pretz, Jiemin Liao, Leylah Drusbosky, Amar Das
Journal: Cancer Research (2024)

Abstract Background: Understanding how ctDNA levels change over time can act as a surrogate marker for disease progression. Since ctDNA evolution is complicated—exhibiting variability within and between patients—we propose a rigorous and flexible statistical framework that comprehensively represents these types of time-varying biomarkers. We propose employing a hierarchal random effects cubic spline model due to its advantages over traditional longitudinal modeling approaches such as the former’s ability to incorporate patient characteristics and create patient-specific results. Visualization of individual patient trajectories may provide clinical utility in precision oncology settings. Methods: 167 patients with CRC were selected from GuardantINFORM, a real-world database linking genomic and claims data. All patients received chemotherapy and had at least three serial liquid biopsy tests completed via Guardant360. To meet model assumptions, ctDNA levels, measured by maximum variant allele frequency on each test, were transformed into logits. Due to the model’s hierarchal structure, an unconditional cubic spline model was fit first, producing an estimated response pattern for the cohort. Next, as patient-level results are of interest, the unconditional model was built upon by fitting a conditional model that incorporated covariates consisting of demographic, health status, and mortality information, which provided numerous patient-level response patterns. The best fitting conditional model was guided by Akaike’s information criteria. Results: Since model parameter estimates are uninterpretable, and because numerous patient-level projections are generated (each covariate value combination produces a unique projection), an R-Shiny application was developed to visually present and compare results in an intuitive interactive fashion. Additionally, to enhance the understanding of patient response patterns, velocity plots, which provides the instantaneous rate of change in ctDNA levels at different time points, are also provided. Conclusions: We demonstrate that the proposed method can successfully be applied to genomic data to describe and explore complex patient-level temporal ctDNA patterns while accounting for the impact of covariate values have on these patterns. We implemented the proposed methodology as a visualization tool that can be used in a wide variety of settings, ranging from hypothesis testing in clinical trials to patient monitoring. Results from the model can further our basic conceptualization of ctDNA dynamics and enhance our ability to integrate these results into targeted, patient centric, clinical decision-making. Citation Format: Christopher R. Pretz, Jiemin Liao, Leylah Drusbosky, Amar Das. Longitudinal assessment of circulating tumor DNA in patients with advanced colorectal cancer: A proposed general statistical framework and visualization tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2390.