Does the source of death information affect cancer screening efficacy results? A study of the use of mortality review versus death certificates in four randomized trials
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Often in randomized controlled trials of cancer screening, cause of death is determined by a mortality review committee. However, little is known regarding how findings from mortality review compare to those from death certificates alone. PURPOSE: To examine the results of four different U. S. trials of cancer screening when death certificate data only were used, as compared to results using all available mortality review information. METHODS: Trials included were the Health Insurance Plan of New York breast screening trial (HIP), the Minnesota trial of fecal occult blood testing, and the Johns Hopkins and Mayo Lung Projects, which each examined chest x-ray and sputum cytology. The sensitivity, specificity, positive and negative predictive values, and Cohen's kappa for death certificates were calculated for all arms of all trials. Separate intention-to-screen analyses were conducted for each trial using cause of death information from either death certificates alone or full mortality review data. RESULTS: Generally there was excellent agreement between the death certificates and the mortality review committee as to the underlying cause of death (kappa >0.85 in all cases); death certificate agreement was similar between arms in all trials. Modest changes in the screening effectiveness estimates were observed when mortality review information was utilized, ranging from a 9% decrease to a 2% increase in the calculated mortality rate ratios. However, in one instance (HIP) a statistically significant benefit of screening was observed when mortality review committee data were used (rate ratio (RR) 0.77, 95% confidence interval (CI) 0.62- 0.95) but not when death certificate data were used (RR 0.82, 95% CI 0.65-1.03). LIMITATIONS: Although considered to be the gold standard, even carefully conducted mortality review may result in errors in cause of death assignment. CONCLUSIONS: For each trial, results were similar regardless of the source of cause of death information.
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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 | 0.093 | 0.432 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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