Outcomes for lymphoid malignancies in the Nurses' Health Study (NHS) as compared to the Surveillance, Epidemiology and End Results (SEER) Program
Bibliographic record
Abstract
Vital statistics for the lymphoid malignancies obtained from the Surveillance, Epidemiology and End Results (SEER) Program have seldom been directly compared to data from alternative national databases. While SEER is recognized as the standard, some lymphoid malignancies-especially the chronic ones--may be underreported. We compared the incidence, all-cause and cause-specific mortality for Hodgkin's lymphoma (HL), non-Hodgkin's lymphoma (NHL), multiple myeloma (MM) and chronic lymphocytic leukaemia (CLL) in SEER to that in the Nurses' Health Study (NHS), a national cohort study of 121,700 female registered nurses, matching for age and race. In over 2.5 million person-years, the incidence of HL was the same as in SEER (SIR=1.01 [0.75, 1.26]), while the incidence of NHL, CLL and MM were slightly higher. All-cause mortality was lower for the lymphoid malignancies except for MM, which was the same; there were no differences in cause-specific mortality, except for MM (HR=1.26 [1.07, 1.48]). Our analysis suggests that, at least among white women, SEER is a reliable data source with respect to lymphoid malignancies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".