ArticlePreventing chronic disease2024
Costs and Projected Effect of a Federally Qualified Health Center-Based Mailed Colorectal Cancer Screening Program in Texas.
Article in Preventing chronic disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Leveraging Text Messaging and Behavior Theory to Improve Colorectal Cancer Screening in Federally Qualified Health Centers: Cohort Study.Journal of medical Internet research · 2026Article
- Breast, Cervical, and Colorectal Cancer Screening Rates in Women Aged 45 to 64 Years.JAMA network open · 2026Article
- Cost-Effectiveness Analysis of Implementing a Multisectoral Program for Colorectal Cancer Screening in an African American Community.AJPM focus · 2025Article
- IMPLEMENTING HOME-BASED CANCER PREVENTION AND SCREENING: AN OPPORTUNITY FOR EQUITY.Transactions of the American Clinical and Climatological Association · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Mailed stool testing for colorectal cancer (CRC) may improve screening uptake and reduce the incidence and mortality of CRC, especially among patients at federally qualified health centers (FQHCs). To expand screening programs it is important to identify cost-effective approaches. Methods: We developed a decision-analytic model to estimate the cost, effects on screening and patient outcomes (CRCs detected, CRCs prevented, CRC deaths prevented), and cost-effectiveness of implementing a state-wide mailed stool testing program over 5 years among unscreened, age-eligible (aged 50-75 y) patients at FQHCs in Texas. We compared various outreach strategies and organizational structures (centralized, regional, or a hybrid). We used data from our existing regional mailed stool testing program and recent systematic reviews to set parameters for the model. Costs included start-up and ongoing activities and were estimated in 2022 US dollars from the perspective of a hypothetical third-party payer. Cost-effectiveness was assessed by using both incremental and average cost-effectiveness ratios. Results: Using either a statewide centralized or hybrid organizational configuration to mail stool tests to newly eligible FQHC patients and patients who have responded at least once since program inception is likely to result in the best use of resources over 5 years, enabling more than 110,000 additional screens, detecting an incremental 181 to 194 CRCs, preventing 91 to 98 CRCs, and averting 46 to 50 CRC deaths, at a cost of $10 million to $11 million compared with no program. Conclusions: A statewide mailed stool testing program for FQHC patients can be implemented at reasonable cost with considerable effects on CRC screening outcomes, especially when its structure maximizes program efficiency while maintaining effectiveness.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.