The association between the incidence of postmenopausal breast cancer and occupational exposure to selected organic solvents in Montreal
Notice bibliographique
Résumé
Introduction: Breast cancer is the most diagnosed cancer among women and accepted risk factors explain 25% to 47% of cases. Organic solvents are used widely in the workplace. According to a hypothesis postulated in the 1990s, exposure to organic solvents may increase the risk of developing breast cancer, yet there is insufficient data to confirm this hypothesis. The objective of my thesis was to determine whether past occupational exposures to selected organic solvents were associated with the incidence of invasive breast cancer in postmenopausal women in Montréal.Materials and Methods: To meet this objective, I first undertook a structured review of the peer-reviewed case-control and cohort studies that were used to investigate breast cancer and exposure to selected organic solvents that produce reactive metabolites when metabolized in the body. I used SCOPUS, MEDLINE (Ovid) and Web of Science databases to identify epidemiological studies that estimated associations between the risk of developing or dying from malignant breast cancer and past exposure to selected organic solvents with reactive metabolites. Second, I analyzed occupational data from a population-based case-control study (2008 to 2011) that elicited from participants using in-depth interviews information on risk factors for breast cancer as well as details of each job they had during their lifetime. A team of industrial hygienists and chemists translated each detailed job description into specific chemical and physical exposures. I selected six individual solvents and four groups of solvents. Unconditional logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for metrics of past exposures to the selected solvents. Metrics of exposure included any previous exposure, average frequency in hours per week, duration in years, and average cumulative concentration with concentration on a scale of 1 (“low”), 2 (“medium”), 3 (“high”) weighted by hours per work week exposed.Results: I identified 32 papers to include in the review and presented the findings by type of solvent. In the case-control study, 695 cases and 608 controls were enrolled and after adjusting for potential confounding I found increased ORs for average cumulative concentration of exposure to mononuclear aromatic hydrocarbons (OR: 1.52, 95%CI: 1.04, 2.28), chlorinated alkanes (OR: 2.42, 95%CI: 1.23, 5.68), toluene (OR: 1.59, 95%CI: 1.02, 2.59), and a group of organic solvents with reactive metabolites (OR: 1.53, 95%CI: 1.08, 2.24). Positive associations were found across all metrics of exposure and were higher among women who had estrogen positive/progesterone negative tumours. Conclusion: In my review of the literature, I did not find sufficient evidence to determine whether any of the selected organic solvents are implicated in the etiology of postmenopausal breast cancer My results from the population-based case-control study suggest that occupational exposure to certain organic solvents may increase the risk of incident postmenopausal breast cancer.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».