Longitudinal retrospective study of real-world adherence to colorectal cancer screening before and after the COVID-19 pandemic in the USA
Bibliographic record
Abstract
Introduction: At-home stool tests are an increasingly popular practice for colorectal cancer screening, especially when access to healthcare facilities is challenging. However, there is limited information about whether stool tests provide sufficient coverage when patients must undergo repeat testing. This study evaluates repeat preventative stool tests over 2 year periods in a healthcare system with 51 hospitals and over 1000 clinics across seven western US states, before and after the onset of the COVID-19 pandemic. Methods: We conduct a real-world, observational, retrospective and longitudinal study based on electronic medical records. We measure the rate of repeat screening and mean delay in repeat screening among patients who receive an initial stool test. We estimate the changes in the likelihood of colorectal cancer screening using a Cox proportional hazard model. Results: Our sample included 4 03 085 patients. The share of patients with an initial negative stool test who received a repeat screening ranged from 38% to 49% across different years. Among patients who received a repeat screening, there is a delay of 3 months on average. The volume of stool tests increased during the pandemic: the HR of screening after the onset of the pandemic to that before the pandemic was 1.18 (95% CI (1.15, 1.20), p<0.001). Conclusions: Our findings show that less than 50% of patients received a repeat stool test, creating gaps in their screening coverage. The increase in stool tests during the pandemic is partly due to a substitution away from colonoscopies, underscoring the increasing importance of stool tests in CRC screening. Programmes that aim to increase CRC screening uptake should focus on repeated testing after an initial screening.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".