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Enregistrement W2977166543 · doi:10.1093/humrep/dez222

Hormone replacement therapy and the risk of melanoma in post-menopausal women

2019· article· en· W2977166543 sur OpenAlexfundno aff
Blánaid Hicks, Kasper Bruun Kristensen, Sidsel Arnspang Pedersen, Lisbet Rosenkrantz Hölmich, Anton Pottegård

Notice bibliographique

RevueHuman Reproduction · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueMenopause: Health Impacts and Treatments
Établissements canadiensnon disponible
Organismes subventionnairesQueen's University BelfastQueen's UniversityCancer Research UK
Mots-clésMedicineOdds ratioHormone replacement therapy (female-to-male)PopulationMelanomaInternal medicineMedical prescriptionCohort studyConfoundingRetrospective cohort studyCohortOncologyGynecologyEnvironmental health

Résumé

récupéré en direct d'OpenAlex

STUDY QUESTION: Is hormone replacement therapy (HRT) associated with an increased risk of melanoma skin cancer or prognostic outcomes amongst post-menopausal women? SUMMARY ANSWER: Whilst we found evidence of an association with melanoma risk, the lack of dose-response and associations observed with recent use, localised disease and intravaginal oestrogens suggests this is a non-causal association. WHAT IS KNOWN ALREADY: Evidence on HRT and melanoma risk remains inconclusive, with studies providing conflicting results. Furthermore, evidence on melanoma survival is sparse, with only one previous study reporting protective associations with HRT use, likely attributable to immortal time bias. STUDY DESIGN, SIZE, DURATION: We conducted a nation-wide population-based case-control study and a retrospective cohort study utilising the Danish healthcare registries. Case-control analyses included 8279 women aged 45-85 with a first-ever diagnosis of malignant melanoma between 2000 and 2015, matched by age and calendar time to 165 580 population controls. A cohort of 6575 patients with a diagnosis of primary malignant melanoma between 2000 and 2013 and followed through 2015 was examined to determine if HRT use had an impact on melanoma survival outcomes. PARTICIPANTS/MATERIALS, SETTING, METHODS: Based on prescriptions dispensed since 1995, ever-use of HRT was defined as having filled at least one prescription for HRT prior to the index date. In total, 2629 cases (31.8%) and 47 026 controls (28.4%) used HRT. Conditional logistic regression was used to calculate odds ratios (ORs) for melanoma risk according to HRT use, compared with non-use, adjusting for potential confounders. For cohort analyses, Cox proportional hazards models was used to estimate adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) for second melanoma incidence and all-cause mortality associated with HRT. MAIN RESULTS AND THE ROLE OF CHANCE: High use of HRT was associated with an OR of 1.21 (95% CI 1.13-1.29) for melanoma risk, with no evidence of a dose-response pattern. Results were most pronounced amongst recent high users (OR, 1.28; 95% CI 1.17-1.41), for localised disease (OR, 1.25; 95% CI 1.15-1.36) and for intravaginal oestrogen therapy (OR, 1.38; 95% CI 1.13-1.68). Compared with non-use, there was no evidence of an association for secondary melanoma for post-diagnostic new-use (fully adjusted HR, 1.56; 95% CI 0.64-3.80) or continuous HRT use (fully adjusted HR, 1.26; 95% CI 0.89-1.78). Similar associations were observed for all-cause mortality. LIMITATIONS, REASONS FOR CAUTION: Despite the large sample size and the use of robust population-based registries with almost complete coverage, we lacked information on some important confounders including sun exposure. WIDER IMPLICATIONS OF THE FINDINGS: Whilst we cannot rule out an association between HRT use and melanoma risk, the associations observed are also compatible with increased healthcare utilisation and thus increased melanoma detection amongst HRT users. No association between HRT use and melanoma survival outcomes was observed. This should provide some reassurance to patients and clinicians, particularly concerning the use of HRT in patients with a history of melanoma. STUDY FUNDING/COMPETING INTEREST(S): B.M.H. is funded by a Cancer Research UK Population Research Postdoctoral Fellowship. The funding source had no influence on the design or conduct of this study. A.P. reports participation in research projects funded by Alcon, Almirall, Astellas, Astra-Zeneca, Boehringer-Ingelheim, Servier, Novo Nordisk and LEO Pharma, all with funds paid to the institution where he was employed (no personal fees) and with no relation to the work reported in this article. The other authors have no competing interests to declare. TRIAL REGISTRATION NUMBER: N/A.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,676
Score d'incertitude au seuil0,240

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,025
Tête enseignante GPT0,294
Écart entre enseignants0,270 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations19
Publié2019
Routes d'admission1
Résumé présentoui

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