Longitudinal Cohort Study of Gender Affirmation and HIV-Related Health in Transgender and Gender Diverse Adults: The LEGACY Project Protocol
Bibliographic record
Abstract
BACKGROUND: Transgender and gender diverse (TGD) adults in the United States experience health disparities, especially in HIV infection. Medical gender affirmation (eg, hormone therapy and gender-affirming surgeries) is known to be medically necessary and to improve some health conditions. To our knowledge, however, no studies have assessed the effects of gender-affirming medical care on HIV-related outcomes. OBJECTIVE: This study aims to evaluate the effects of medical gender affirmation on HIV-related outcomes among TGD primary care patients. Secondary objectives include characterizing mental health, quality of life, and unmet medical gender affirmation needs. METHODS: LEGACY is a longitudinal, multisite, clinic-based cohort of adult TGD primary care patients from two federally qualified community health centers in the United States: Fenway Health in Boston, and Callen-Lorde Community Health Center in New York. Eligible adult TGD patients contribute electronic health record data to the LEGACY research data warehouse (RDW). Patients are also offered the option to participate in patient-reported surveys for 1 year of follow-up (baseline, 6-month, and 12-month assessments) with optional HIV and sexually transmitted infection (STI) testing. Biobehavioral data from the RDW, surveys, and biospecimen collection are linked. HIV-related clinical outcomes include pre-exposure prophylaxis uptake (patients without HIV), viral suppression (patients with HIV), and anogenital STI diagnoses (all patients). Medical gender affirmation includes hormones, surgeries, and nonhormonal and nonsurgical interventions (eg, voice therapy). RESULTS: The contract began in April 2018. The cohort design was informed by focus groups with TGD patients (n=28) conducted between August-October 2018 and in collaboration with a community advisory board, scientific advisory board, and site-specific research support coalitions. Prospective cohort enrollment began in February 2019, with enrollment expected to continue through August 2020. As of April 2020, 7821 patients are enrolled in the LEGACY RDW and 1756 have completed a baseline survey. Participants have a median age of 29 years (IQR 11; range 18-82). More than one-third (39.7%) are racial or ethnic minorities (1070/7821, 13.68% Black; 475/7821, 6.07% multiracial; 439/7821, 5.61% Asian or Pacific Islander; 1120/7821, 14.32% other or missing) and 14.73% (1152/7821) are Hispanic or Latinx. By gender identity, participants identify as 33.79% (2643/7821) male, 37.07% (2900/7821) female, 21.74% (1700/7821) nonbinary, and 7.39% (578/7821) are unsure or have missing data. Approximately half (52.0%) of the cohort was assigned female sex at birth, and 5.4% (421/7821) are living with HIV infection. CONCLUSIONS: LEGACY is an unprecedented opportunity to evaluate the impact of medical gender affirmation on HIV-related health. The study uses a comprehensive research methodology linking TGD patient biobehavioral longitudinal data from multiple sources. Patient-centeredness and scientific rigor are assured through the ongoing engagement of TGD communities, clinicians, scientists, and site clinical staff undergirded by epidemiological methodology. Findings will inform evidence-based clinical care for TGD patients, including optimal interventions to improve HIV-related outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24198.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".