Right hand digit ratio (2D:4D) is associated with prostate cancer: Findings of an admixed population study
Bibliographic record
Abstract
Objective: Digit ratios are considered putative markers for prenatal hormone exposure, as well as the action of HOX andAR genes. Such genes have been connected to carcinogenesis and digit ratio could help to identify patients that bear suchpredisposition. The purpose of this study was to investigate the possible correlations between digit ratio, prostate cancer(PCA) - the most common cancer in men – and benign prostate hyperplasia (BPH) in a multiethnic sample of men between50 and 80 years, the main risk group for this disease.Methods: Digital images of the right hands of patients diagnosed with PCA (n=40), BPH (n=40) and age-matchedcontrols (n=40) were obtained. Fingers were measured using Adobe Photoshop 7.0® and the mean ratios between the 2ndand 4th digits were compared. Data were analyzed by Student’s t test and regression models (α=0.05). Risk factors (dietaryfactors, tobacco consumption, age and familial history) were similar among the three study groups.Results: Males in the PCA group presented significantly lower digit ratio (P=0.04) in comparison with males withoutprostatic lesions.Conclusions: Males with the lower digit ratio seem to be more prone to undergo malignization of prostatic lesions. Similarrisk factors for the three groups allows us to infer that digit ratio could add to the research of etiological factors and be aputative marker for the screening of patients’, especially in a admixed population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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 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".