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
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.
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 | 0.369 | 0.599 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.026 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".