MétaCan
Menu
Back to cohort
Record W2977166543 · doi:10.1093/humrep/dez222

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

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

Bibliographic record

VenueHuman Reproduction · 2019
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
FundersQueen's University BelfastQueen's UniversityCancer Research UK
KeywordsMedicineOdds ratioHormone replacement therapy (female-to-male)PopulationMelanomaInternal medicineMedical prescriptionCohort studyConfoundingRetrospective cohort studyCohortOncologyGynecologyEnvironmental health

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.294
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueHuman ReproductionSame topicMenopause: Health Impacts and TreatmentsFrench-language works237,207