Abstract B024: Feasibility of survey-based data collection in a diverse colorectal cancer cohort: Early-onset vs. average-onset
Bibliographic record
Abstract
Abstract BACKGROUND: The incidence of early-onset colorectal cancer (EOCRC) is rising, yet a robust model of underlying factors across diverse populations is unknown. Most studies have examined a single factor or were performed in non-diverse populations leaving a gap in understanding of how these factors interact. The collection of comprehensive, patient-reported data across different populations in CRC will enable a deeper understanding of these associations to inform early intervention strategies. METHODS: A pilot survey study was conducted at UT Southwestern Simmons Comprehensive Cancer Center (SCCC) and its affiliated safety-net hospital, Parkland Health and Hospital System (PHHS). The objective was to evaluate the feasibility of a multidomain survey in colorectal cancer patients. Eligible patients (≥18 years, stage I–IV adenocarcinoma, diagnosed within 12 months) completed baseline surveys in English or Spanish on demographics, lifestyle, symptom burden, nutrition (Dietary History Questionnaire), quality of life (EORTC QLQ-30, CR29), and financial toxicity (COST-FACIT). Surveys were administered in REDCap at baseline and three months follow-up. The primary endpoint was survey completion; feasibility was assessed by recruitment, participation, and completion rates. Descriptive comparisons were made between EOCRC (<50 years) and average-age onset colorectal cancer (AOCRC; ≥50 years). RESULTS: From March 2024 to April 2025, 66 patients were approached, and 60 (91%) consented; all completed the baseline survey (100%), confirming feasibility across academic and safety-net settings. However, for the three-month follow-up survey participation decreased by 50%. The cohort was evenly distributed by sex (48% female, 52% male) and site (50% Parkland, 50% UTSW). Participants were diverse (42% Hispanic, 18% Black, 42% Non-Hispanic White) with variable socioeconomic status: 38% reported income <$35,000, 23% >$100,000, 28% were unable to work, and 23% were employed. Hospital utilization differed: 96% of Non-Hispanic Whites were treated at SCCC, while most Hispanic and Black patients were seen at PHHS. Parkland Financial Assistance was reported by 77%, highest among Hispanic patients. Nineteen patients (32%) had EOCRC (median age 42, range 30–48) and 41 (68%) had AOCRC (median age 64, range 51–82). EOCRC patients were more often Hispanic (58% vs. 32%), treated at Parkland (58% vs. 46%), and received assistance more frequently (47% vs. 34%). CONCLUSION: This pilot study confirms that comprehensive, survey-based data collection is feasible in a racially, ethnically, and financially diverse CRC cohort. These preliminary findings highlight the clinical and sociodemographic differences of EOCRC and AOCRC across distinct groups. Future work will expand longitudinal follow-up, incorporate electronic health record data, and leverage tumor registry phenotypes to enable low-touch, systematic patient recruitment for a more robust sample at current institution, and nationally. Citation Format: Citlalli Lopez, L. Joseph Su, Luis Gonzalez, Yu-Lun Liu, Rasmi Nair, Lindsay Cowell, Emina Huang, Syed M. Kazmi. Feasibility of survey-based data collection in a diverse colorectal cancer cohort: Early-onset vs. average-onset [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr B024.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".