MétaCan
Menu
Back to cohort

Abstract P6-13-06: Estrogen-based hormone replacement [HRT] therapy is substantially more effective than tamoxifen in reducing breast cancer mortality and breast cancer case fatality ratio: Emergence of a new paradigm

2019· article· en· W2935812534 on OpenAlexaff
Joseph Ragaz, Shayan Shakeraneh, Hong Qian, Wilson Ks, Hong Yuen Wong, JJ Spinelli

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsSt. Paul's HospitalCentre for Advancing Health OutcomesUniversity of VictoriaUniversity of British ColumbiaProvidence Health CareBC Cancer Agency
Fundersnot available
KeywordsMedicineBreast cancerHazard ratioTamoxifenHormone replacement therapy (female-to-male)OncologyGynecologyInternal medicinePlaceboCancerCase fatality rateObstetricsConfidence intervalEpidemiology

Abstract

fetched live from OpenAlex

Abstract OBJECTIVE: To compare, in the setting of breast cancer (BrCa) prevention, the impact of estrogen-based hormone replacement therapy (E-HRT) vs. tamoxifen (TAM) on breast cancer mortality (BrCa-M) and breast cancer case fatality ratio (BrCa-CFR), by analyzing data from the Women's Health Initiative Trial 2 (WHI HRT Trial 2, E-HRT vs. placebo [P])1 and the International Breast Cancer Intervention Study 1 (IBIS-1), TAM vs. P.2 METHODS: Hazard ratios (HR) and confidence intervals (CI) for BrCa incidence and mortality were extracted from the original WHI HRT Trial 2 and IBIS-1 trials.1,2 BrCa-CFRs were estimated by dividing the mortality HR by the incidence HR. Subsequently, to compare E-HRT vs. TAM outcomes, the ratios of HRs (HR1/HR2) between the two trials were estimated separately for BrCa-M and BrCa-CFR. The 95% CI was derived through logarithmic transformation of the 95% CI originally reported. RESULTS: Mortality and Case Fatality Outcomes: Impact of E-HRT versus TAM, expressed as ratio of HRs E-HRT vs. Placebo, HR1TAM vs. Placebo, HR2HR1/HR2pMortality0.55 (0.33-0.92)1.19 (0.68-2.10)0.46 (0.22-0.99)0.046Case Fatality0.70 (0.40-1.20)1.68 (0.93-3.01)0.42 (0.18-0.94)0.040 CONCLUSIONS: While acknowledging between-trial comparisons including eligibility differences, E-HRT yields significant reductions in BrCa mortality and case fatality as compared with TAM (54% and 58% respectively). These unexpected breast cancer mortality reductions represent major public health gains, additional to the already known superiority of E-HRT over TAM in terms of skeletal fracture rates and Alzheimer's dementia mortality reduction, and, in women entering menopause, also of cardiac and all-cause mortality reductions. REFERENCES: 1. Manson JE, Aragaki AK, Rossouw JE, et al. Menopausal Hormone Therapy and Long-term All-Cause and Cause-Specific Mortality: The Women's Health Initiative Randomized Trials. JAMA 2017;318:927-38. 2. Cuzick J, Sestak I, Cawthorn S, et al. Tamoxifen for prevention of breast cancer: extended long-term follow-up of the IBIS-I breast cancer prevention trial. The Lancet Oncology 2015;16:67-75. Citation Format: Ragaz J, Shakeraneh S, Qian H, Wilson KS, Wong H, Spinelli JJ. Estrogen-based hormone replacement [HRT] therapy is substantially more effective than tamoxifen in reducing breast cancer mortality and breast cancer case fatality ratio: Emergence of a new paradigm [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-13-06.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.083
GPT teacher head0.432
Teacher spread0.349 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicCancer Risks and FactorsFrench-language works237,207