How Effective is Population-Based Cancer Screening? Regression Discontinuity Estimates from the US Guideline Screening Initiation Ages
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We estimate the marginal benefits of population-based cancer screening by comparing cancer test and detection rates on either side of US guideline-recommended initiation ages (age 40 for breast cancer and age 50 for colorectal cancer during the study period). Using a regression discontinuity design and self-reported test data from national health surveys, we find test rates for breast and colorectal cancer increase at the guideline age thresholds by 109% and 78%, respectively. Data from cancer registries in twelve US states indicate that cancer detection rates increase at the same thresholds by 50% and 49%, respectively. We estimate significant effects of screening on earlier breast cancer detection (1.2 cases/1000 screened) at age 40 and colorectal cancer detection (1.1 cases/1000 individuals screened) at age 50. Forty-eight and 73% of the increases in breast and colorectal case detection occur among middle-stage cancers (localized and regional) with most of the remainder among early-stage (in-situ). Our analysis suggests that the cost of detecting an asymptomatic case of breast cancer at age 40 via population-based screening is $107,000-134,000 and that the cost of detecting an asymptomatic case of colorectal cancer at age 50 is $473,000-485,000.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it