Subject Area

Biostatistics

Abstract

Colorectal cancer (CRC) is the third leading cause of cancer-related death in the United States [45]. CRC is believed to advance from adenomatous polyps creating a unique opportunity for both early detection and cancer prevention [4, 23]. Like other diseases, CRC screening reduces mortality by detecting cancer at earlier, more treatable stages; however, it can also reduce incidence through the removal of precancerous lesions [4]. As a result, screening is recommended for average-risk adults ≥ 45 years of age and includes a variety of tests [4, 12]. Despite alternate screening options, colonoscopy capacity is often cited as a barrier to colorectal cancer (CRC) screening [28, 39, 44]. In this dissertation, we address capacity as a statistical problem rather than a resource one.

In the first part, we apply methods developed to incorporate longitudinal biomarkers for ovarian cancer screening to the data accumulated through a large FIT-based CRC screening program. This requires us to consider multiple methods to accommodate the necessary data transformation given the range for quantitative fecal hemoglobin concentration.

The second part of the dissertation looks at a new diagnostic marker obtained by extracting information from the biomarker trajectories using functional data analysis. The approach addresses problems of missing data and verification bias. Performance however is hindered by data sparsity which can be attributed to the screening process.

The third part of the dissertation revisits the method highlighted in part one to derive and evaluate a decision threshold for clinical implementation.

Degree Date

Spring 5-11-2024

Document Type

Dissertation

Degree Name

Ph.D.

Department

Statistics and Data Science

Advisor

Monnie McGee

Second Advisor

Daniel F. Heitjan,

Third Advisor

Stephen Robertson

Fourth Advisor

Steven Chiou

Fifth Advisor

Amit Singal

Number of Pages

70

Format

.pdf

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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