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Record W4388295566 · doi:10.2196/53092

Effectiveness and Safety of Different Estradiol Regimens in Transgender Women (TREAT Study): Protocol for a Randomized Controlled Trial

2023· article· en· W4388295566 on OpenAlexvenueno aff
Samuel Cortez, Dominic Moog, Christopher S. Lewis, Kelley Williams, Cynthia Herrick, Melanie E. Fields, Teddi Gray, Zhaohua Guo, Ginger E. Nicol, Thomas Baranski

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institutes of HealthInstitute of Clinical and Translational Sciences
KeywordsMedicineTransgenderSpironolactoneRandomized controlled trialAdverse effectGynecologyTestosterone (patch)Clinical trialHormone therapyFamily medicineInternal medicineBreast cancerPsychologyCancerAldosterone

Abstract

fetched live from OpenAlex

BACKGROUND: Current guidelines for gender-affirming hormone therapy (GAHT) for transgender women are mostly based on clinical experience from experts in the field and treatments used on postmenopausal women. While care is currently provided with the best available evidence, there is a critical gap in knowledge about the safest and most effective estradiol routes of administration for GAHT in transgender women; this statement is supported by the World Professional Association for Transgender Health on their Standards of Care for the Health of Transgender and Gender Diverse People, version 8. Furthermore, the reported rates of cardiometabolic adverse events in transgender women highlight the importance of investigating changes in lipoproteins, glucose, and insulin sensitivity, among other markers while receiving GAHT. OBJECTIVE: This study aims to evaluate the degree of testosterone suppression achieved at 1, 6, and 12 months in treatment-naive transgender women when randomized to GAHT with estradiol and spironolactone as antiandrogens. As a secondary aim, this study will assess the treatment effect on metabolic and coagulation factors from baseline to 6 and 12 months after initiating GAHT. METHODS: This is a prospective pilot, open-label, randomized clinical trial conducted at an adult transgender clinic in a tertiary medical center. The 3 treatment arms include once-daily sublingual 17-β estradiol, twice-daily sublingual 17-β estradiol, and transdermal 17-β estradiol. All participants received spironolactone as an antiandrogen. Transgender women aged 18 to 45 years who are being evaluated for the initiation of GAHT with 17-β estradiol and did not have a history of coagulopathy, cigarette smoking, liver disease, dyslipidemia requiring treatment, or use of gonadotropin-releasing hormone agonist were eligible to enroll. The main outcome is the total testosterone suppression at 1 and 6 months after the initiation of GAHT, and the secondary outcome is to assess treatment effect in a lipid panel; homeostatic model assessment for insulin resistance; coagulation factors II, IX, and XI; Von Willebrand factor; activated protein C resistance; protein C; and protein S at baseline, 6 months, and 12 months after therapy is initiated. RESULTS: This study was funded in March 2022, and enrollment concluded in August 2022. It was concluded in July 2023, and currently, the results are being analyzed for publication. CONCLUSIONS: The Transgender Estradiol Affirming Therapy (TREAT) study offers a rigorous and reproducible approach to answer important questions regarding GAHT in transgender women, specifically, the most effective 17-β estradiol regimen to suppress testosterone levels to 50 ng/dL, as currently recommended. TRIAL REGISTRATION: ClinicalTrials.gov NCT05010707; https://clinicaltrials.gov/study/NCT05010707. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53092.

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)0.036
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.069
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.030
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0030.003
Science and technology studies0.0030.004
Scholarly communication0.0050.004
Open science0.0040.002
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0690.012

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 head0.218
GPT teacher head0.599
Teacher spread0.381 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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