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Enregistrement W1996678991 · doi:10.1002/ijc.22611

Reply to the letter to the editor Lissowska J, Brinton LA, Zatonski W, Blair A, Bardin‐Mikolajczak A, Peplonska B, Sherman ME, Szeszenia‐Dabrowska N, Chanock S, García‐Closas M. Tobacco smoking, NAT2 acetylation genotype and breast cancer risk. Lissowska et al. (Int J Cancer 2006; 119:1961–69). More evidence for passive and active smoking and breast cancer risk among younger women

2007· letter· en· W1996678991 sur OpenAlexaffabout
Kenneth C. Johnson

Notice bibliographique

RevueInternational Journal of Cancer · 2007
Typeletter
Langueen
DomaineMedicine
ThématiqueCancer Risks and Factors
Établissements canadiensPublic Health Agency of Canada
Organismes subventionnairesnon disponible
Mots-clésMedicinePassive smokingBreast cancerConfidence intervalDemographyCohort studyCohortGynecologyCancerTobacco smokeInternal medicineEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Dear Sir, Lissowska et al. are to be congratulated on collecting lifetime residential and workplace exposure to secondhand smoke for their analysis of passive and active smoking and breast cancer in Poland.1 The report adds to the mounting evidence that active smoking is associated with increased breast cancer risk in younger/premenopausal women,2 (Table 6 in that review) as well as a more general trend toward studies observing increased breast cancer risk associated with smoking including 3 large American cohort studies,3, 4, 5 a large Canadian cohort study,6 two European cohorts7, 8 and studies that have controlled for passive smoking.9 Although the authors conclude that the “data indicate that passive smoking is not associated with breast cancer risk”, they present passive smoking breast cancer risk estimates of 1.28 (95% confidence interval (CI) 0.52–3.11) and 1.27 (95% CI 0.76–2.11) for women aged less than 45 and 45–55, respectively. The estimates are not statistically significant, however they are consistent with results for younger women from three recently published meta-analyses, which found elevated passive smoking summary risk estimates: 2 based on 14 studies of younger, primarily premenopausal women (1.68 (95% CI 1.33–2.12)),9, 10 (Figure 1) and most recently the estimate in the US Surgeon General's 2006 report based on 11 studies of premenopausal women (1.64 (95%CI 1.25–2.14)) (Table 7–10)10 Furthermore, Lissowska et al.'s passive smoking results among older women were also consistent with these meta-analyses—both finding little indication of increased risk for all exposed postmenopausal women.9, 10, 10 Finally, the negative conclusion of the authors is based on very low power in the critical younger age groups. Summary of 14 studies of breast cancer risk associated with passive smoking in younger/premenopausal women 9,10 and Lissowska et al. 1 for age <45 and age 45–55. The passive smoking dose-response analysis presented in the report is inadequate because it only examined risks among all-aged women combined. For women over age 55 the passive risk point estimate was only 1.04, 60% of the passively exposed women were in this age group and these older women likely dominated the highest cumulative exposure category given they have had the longest time period to accumulate exposure. The authors have provided dose-response analyses by age group for active smoking—the same is warranted for passive smoking given the difference in risk estimates by age group. Even though the power would be low, it would be informative for the authors to present tables of breast cancer risk for tertiles of hours/day-years of passive exposure for never active smokers for each of the following categorizations: (i) women under 45; (ii) women 45–55 years; (iii) women under 45 and 45–55 combined given the passive risk estimates were similar for under <45 and 45–55, and to help stabilize risk estimates; (iv) premenopausal women, (the report states that the age groupings were chosen to approximate pre, peri and post menopausal status—why not use menopausal status itself as well, given that it was collected); and (v) for women under 50, as the risk from the passive and active analysis suggests the risks are concentrated in younger women as do meta-analyses. Analyses which collapse the least exposed tertile of passively-exposed women with the never exposed would also help to stabilize risks, but at the expense of some misclassification. Presentation of these analyses would provide a more complete picture of this important work. Yours sincerely, Kenneth C Johnson Ph.D.*, * Evidence and Risk Assessment Division, Centre for Chronic Disease Prevention and Control Public Health Agency of Canada, Ottawa, ON, Canada.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,227
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,004
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,323
Écart entre enseignants0,310 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2007
Routes d'admission2
Résumé présentoui

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