Cancer in General Responders Participating in World Trade Center Health Programs, 2003–2013
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
BACKGROUND: Following the September 11, 2001, attacks on the World Trade Center (WTC), thousands of workers were exposed to an array of toxins known to cause adverse health effects, including cancer. This study evaluates cancer incidence in the WTC Health Program General Responder Cohort occurring within 12 years post exposure. METHODS: The study population consisted of 28 729 members of the General Responder Cohort enrolled from cohort inception, July 2002 to December 31, 2013. Standardized incidence ratios (SIRs) were calculated with cancer case inclusion and follow-up starting post September 11, 2001 (unrestricted) and, alternatively, to account for selection bias, with case inclusion and follow-up starting 6 months after enrollment in the WTC Health Program (restricted). Case ascertainment was based on linkage with six state cancer registries. Under the restricted criterion, hazard ratios were estimated using multivariable Cox proportional hazards models for all cancer sites combined and for prostate cancer. RESULTS: Restricted analyses identified 1072 cancers in 999 responders, with elevations in cancer incidence for all cancer sites combined (SIR = 1.09, 95% confidence interval [CI] = 1.02 to 1.16), prostate cancer (SIR = 1.25, 95% CI = 1.11 to 1.40), thyroid cancer (SIR = 2.19, 95% CI = 1.71 to 2.75), and leukemia (SIR = 1.41, 95% CI = 1.01 to 1.92). Cancer incidence was not associated with any WTC exposure index (composite or individual) for all cancer sites combined or for prostate cancer. CONCLUSION: Our analyses show statistically significant elevations in cancer incidence for all cancer sites combined and for prostate and thyroid cancers and leukemia. Multivariable analyses show no association with magnitude or type of exposure.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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