Family history of breast cancer increases the risk of prostate cancer: results from the EPICAP study
Bibliographic record
Abstract
// Pierre-Jean Lamy 1, 2 , Brigitte Trétarre 3 , Xavier Rebillard 1 , Marie Sanchez 4 , Sylvie Cénée 4 and Florence Ménégaux 4 1 Service Urologie, Clinique Beau Soleil, Montpellier, France 2 Institut d’Analyse Génomique-Imagenome, Labosud, Montpellier, France 3 Registre des Tumeurs de l’Hérault, ICM, Montpellier, France 4 Université Paris-Saclay, Université Paris-Sud, CESP (Center for Research in Epidemiology and Population Health), Inserm, Team Cancer and Environment, Villejuif, France Correspondence to: Pierre-Jean Lamy, email: pierre-jean.lamy@labosud-ocbiologie.fr Keywords: family history of cancer; epidemiology; prostate cancer; breast cancer; Gleason score Abbreviations: BCa: breast cancer; GS: Gleason score; OR: Odd ratio; PCa: prostate cancer Received: March 01, 2018 Accepted: April 17, 2018 Published: May 04, 2018 ABSTRACT Introduction: Familial aggregation is now well established with an increased risk of prostate cancer in patients with a family history of prostate cancer in first degree relatives. The aim of this paper was to investigate the role of family history of cancer in first degree relatives in prostate cancer risk. Results: As expected, a family history of prostate cancer in first-degree relatives was more frequent in cases than in controls (OR 3.10, 95% CI 2.32–4.15). A family history of early BCa (before age 50) in first-degree relatives was more frequent in cases than in controls (OR 1.79, 95% CI 1.09–2.94) with higher risk of aggressive PCa. The association was more pronounced for BCa in daughters (OR 15.26 95% CI 1.95–120). Conclusions: In summary, a family history of BCa in first degree relatives before age 50 may increases the risk of PCa with higher Gleason score. This finding could suggest a specific prostate surveillance and/or genetic counselling for men who present such familial history. Methods: EPIdemiological study of Prostate CAncer (EPICAP) is a population-based case-control study specifically designed to investigate the role of environmental and genetic factors in prostate cancer. Detailed information on family history of cancer in first degree relatives (parents, brothers and sisters, children) was collected as well as the age of occurrence and the localization of each cancer. Overall, 819 cases and 879 controls have been included.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".