Sep 28

SS 10 - Patient Reported Outcomes/QoL/Survivorship 1: Fixing What's Broken and Reaching for the Sky

164 - Characterizing Symptom Trajectories in Prostate Cancer Patients Receiving Radiation Therapy

05:45pm - 05:55pm PT

Room 314

Presenter(s)

Minji Lee, PhD - Mayo Clinic Rochester, Rochester, MN

M. K. Lee¹, A. Amundson², and M. R. Waddle²; ¹Mayo Clinic, Rochester, MN, ²Department of Radiation Oncology, Mayo Clinic, Rochester, MN

Purpose/Objective(s): The NCI’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) characterizes patient-reported Adverse events (AEs). This study aimed to analyze the internal structure, composite average method, and longitudinal trajectory patterns of PRO-CTCAE in patients treated with radiation therapy (RT) for prostate cancer.

Materials/Methods: We included 3,944 out of 12,316 patients who received RT for prostate cancer at a tertiary medical center and its affiliated regional practices, including sites in MN, WI, FL, and AZ from 2015 - 2025 and completed the PRO-CTCAE questionnaire on 14 AE terms. PRO-CTCAE items (scored 0-4) were combined into composite scores (0-3) based on frequency, severity, or interference attributes. Composite score distributions were calculated for baseline, end of treatment, and 4 timepoints after treatment. The factor structure was determined using the eigenvalue test and exploratory factor analysis (EFA), with model fit assessed by the root mean square error of approximation (RMSEA). Confirmatory factor analysis (CFA) was performed, evaluating comparative fit index (CFI), Tucker-Lewis index (TLI), RMSEA, and standardized root mean square residual (SRMR). Latent class growth mixture models (GMM) were applied to identify symptom trajectory patterns based on composite averages.

Results: More than 50% of patients reported diarrhea during or after treatment (baseline 36%), while about 75% experienced urinary urgency (baseline 65%), frequency of urination (baseline 75%), erection difficulty (baseline 71%). The eigenvalue test revealed two major factors and a two factor exploratory factor model had good fit (RMSEA=0.05) with gastrointestinal, urinary, and systemic symptoms (factor 1) with factor loadings ranging from 0.32 to 0.76, and sexual and vasomotor symptoms (factor 2) with factor loadings ranging from 0.27 to 0.91. CFA showed good model fit for factor 1 (CFI=0.98, TLI=0.97, RMSEA=0.076, SRMR=0.074) and factor 2 (CFI=0.99, TLI=0.99, RMSEA=0.088, SRMR=0.043). GMM analysis identified a 3-class trajectory model for factor 1, with a consistently low symptom trajectory (88.8%), an increasing trajectory (4.9%), and a decreasing trajectory after 6-month FU (6.3%). Factor 2 followed a 4-class trajectory model, with consistently low symptoms (39.3%), high symptoms (32.7%), increasing and then decreasing at 12-month FU (17.4%), and symptoms decreasing until 12-month FU before plateauing (10.7%).

Conclusion: This study successfully characterized the symptom trajectories in prostate cancer patients undergoing RT using the PRO-CTCAE composite average method, providing valuable insights into symptom progression over time. Next steps will be developing a predictive model using clinical and treatments factors to identify patients more likely to follow each trajectory.