Serum selenium level and cancer risk: a nested case-control study
Bibliographic record
Abstract
Abstract Background Epidemiologic studies have demonstrated a relationship between selenium status and cancer risk among those with low selenium levels. It is of interest to prospectively evaluate the relationship between selenium and cancer among women who reside in a region with ubiquitously low selenium levels. Methods We performed a nested case-control study of baseline serum selenium levels and cancer risk using data and biological samples from 19,573 females that were participants in a biobanking initiative between 2010 and 2014 in Szczecin Poland. Cases included women with any incident cancer ( n = 97) and controls ( n = 184) were women with no cancer at baseline or follow-up. Serum selenium was quantified using mass spectroscopy. Results The odds ratio associated being below the cutoff of 70.0 μg/L compared to a level above 70.0 μg/L was 2.29 (95% CI 1.26–4.19; P = 0.007). The risks for women in the two middle categories were similar and suggests that the normal range be between 70 μg/L and 90 μg/L. There was evidence for an increased risk of cancer among women in the highest category of selenium levels (i.e., > 90 μg/L), but this association did not achieve statistical significance (OR = 1.63; 95%CI 0.63–4.19; P = 0.31). Conclusions Results from this study suggest that suggest that the optimum serum level of selenium in women living in Poland should be between 70 μg/L and 90 μg/L.
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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 | 0.005 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".