Abstract A018: Colorectal Cancer Screening Remains Low Despite High Burden And Rising Early-Onset Cases In Puerto Rico, 2016–2021
Bibliographic record
Abstract
Abstract Background: Puerto Rico has one of the highest rates of colorectal cancer (CRC) in the United States and its territories, including a growing burden of early-onset cases. To address this public health concern, the Puerto Rico Department of Health enacted Administrative Order No. 334, which mandates annual fecal immunochemical test (FIT) screening for all individuals aged 40 and older. Methods: We analyzed Puerto Rico Health Insurance Administration (PRHIA) Vital claims data from 2016 to 2021 (N = 129,858) to evaluate utilization of CRC screening modalities. We assessed uptake in the year following implementation of the administrative order and prospectively through 2021. Screening modalities examined included FIT/iFOBT, Guaiac FOBT, Screening Colonoscopy Results: Across all years examined (2016–2021), adults aged 40–49 were significantly less likely to undergo any CRC screening modality compared with those aged 50 and older. Odds ratios remained consistent over time, ranging from 0.46 to 0.48 (2016 OR = 0.47, 95% CI: 0.46–0.49; 2018 OR = 0.46, 95% CI: 0.45–0.48; 2019 OR = 0.48, 95% CI: 0.47–0.50; 2020 OR = 0.46, 95% CI: 0.44–0.47; 2021 OR = 0.47, 95% CI: 0.46–0.49). These findings indicate that, despite the administrative order expanding screening eligibility, uptake among younger adults remains substantially lower compared to those aged 50 and older. Conclusions: Despite the 2016 administrative order expanding elegibility for colorectal cancer screening to adults aged 40 yeras and older in Puerto Rico, uptake among younger adults remains consistently low. Across 2017-2021, individuals aged 40-49 were abouth half as likely to undergo screening compared with those aged 50 and older. These findindings highlight persistent gaps in policy implementation and underscore the need for targeted outreach education and system-level strategies to improve early detection and reduce the growing burden of colorectal cancer in Puerto Rico. Citation Format: Vivian Colon-Lopez, Hector Contreras, Francisco Muñoz, Erika Escabi, Maria Gonzalez-Pons. Colorectal Cancer Screening Remains Low Despite High Burden And Rising Early-Onset Cases In Puerto Rico, 2016–2021 [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 A018.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".