Birth Order and Risk of Non-Hodgkin Lymphoma—True Association or Bias?
Bibliographic record
Abstract
There is inconsistent evidence that increasing birth order may be associated with risk of non-Hodgkin lymphoma (NHL). The authors examined the association between birth order and related variables and NHL risk in a pooled analysis (1983-2005) of 13,535 cases and 16,427 controls from 18 case-control studies within the International Lymphoma Epidemiology Consortium (InterLymph). Overall, the authors found no significant association between increasing birth order and risk of NHL (P-trend = 0.082) and significant heterogeneity. However, a significant association was present for a number of B- and T-cell NHL subtypes. There was considerable variation in the study-specific risks which was partly explained by study design and participant characteristics. In particular, a significant positive association was present in population-based studies, which had lower response rates in cases and controls, but not in hospital-based studies. A significant positive association was present in higher-socioeconomic-status (SES) participants only. Results were very similar for the related variable of sibship size. The known correlation of high birth order with low SES suggests that selection bias related to SES may be responsible for the association between birth order and NHL.
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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 | 0.147 | 0.331 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".