Cohort profile: pathways to care among people with disorders of sex development (DSD).

PURPOSE: The 'DSD Pathways' study was initiated to assess health status and patterns of care among people enrolled in large integrated healthcare systems and diagnosed with conditions comprising the broad category of disorders (differences) of sex development (DSD). The objectives of this communication are to describe methods of cohort ascertainment for two specific DSD conditions-classic congenital adrenal hyperplasia with 46,XX karyotype (46,XX CAH) and complete androgen insensitivity syndrome (CAIS). PARTICIPANTS: Using electronic health records we developed an algorithm that combined diagnostic codes, clinical notes, laboratory data and pharmacy records to assign each cohort candidate a 'strength-of-evidence' score supporting the diagnosis of interest. A sample of cohort candidates underwent a review of the full medical record to determine the score cutoffs for final cohort validation. FINDINGS TO DATE: Among 5404 classic 46,XX CAH cohort candidates the strength-of-evidence scores ranged between 0 and 10. Based on sample validation, the eligibility cut-off for full review was set at the strength-of-evidence score of ≥7 among children under the age of 8 years and ≥8 among older cohort candidates. The final validation of all cohort candidates who met the cut-off criteria identified 115 persons with classic 46,XX CAH. The strength-of-evidence scores among 648 CAIS cohort candidates ranged from 2 to 10. There were no confirmed CAIS cases among cohort candidates with scores <6. The in-depth medical record review for candidates with scores ≥6 identified 61 confirmed cases of CAIS. FUTURE PLANS: As the first cohort of this type, the DSD Pathways study is well-positioned to fill existing knowledge gaps related to management and outcomes in this heterogeneous population. Analyses will examine diagnostic and referral patterns, adherence to care recommendations and physical and mental health morbidities examined through comparisons of DSD and reference populations and analyses of health status across DSD categories.

Is There a Link Between Hormone Use and Diabetes Incidence in Transgender People? Data From the STRONG Cohort.

BACKGROUND: Risk of type 2 diabetes mellitus (T2DM) in transgender and gender diverse (TGD) persons, especially those receiving gender-affirming hormone therapy (GAHT) is an area of clinical and research importance. METHODS: We used data from an electronic health record-based cohort study of persons 18 years and older enrolled in 3 integrated health care systems. The cohort included 2869 transfeminine members matched to 28 300 cisgender women and 28 258 cisgender men on age, race/ethnicity, calendar year, and site, and 2133 transmasculine members similarly matched to 20 997 cisgender women and 20 964 cisgender men. Cohort ascertainment spanned 9 years from 2006 through 2014 and follow-up extended through 2016. Data on T2DM incidence and prevalence were analyzed using Cox proportional hazards and logistic regression models, respectively. All analyses controlled for body mass index. RESULTS: Both prevalent and incident T2DM was more common in the transfeminine cohort relative to cisgender female referents with odds ratio and hazard ratio (95% CI) estimates of 1.3 (1.1-1.5) and 1.4 (1.1-1.8), respectively. No significant differences in prevalence or incidence of T2DM were observed across the remaining comparison groups, both overall and in TGD persons with evidence of GAHT receipt. CONCLUSION: Although transfeminine people may be at higher risk for T2DM compared with cisgender females, the corresponding difference relative to cisgender males is not discernable. Moreover, there is little evidence that T2DM occurrence in either transfeminine or transmasculine persons is attributable to GAHT use.

Changes in Size and Demographic Composition of Transgender and Gender Non-Binary Population Receiving Care at Integrated Health Systems.

OBJECTIVE: To examine temporal changes in the number and demographic composition of transgender/gender non-binary (TGNB) population using data from integrated health care systems. METHODS: Electronic health records from Kaiser Permanente health plans in Georgia and Northern and Southern California were used to identify TGNB individuals, who sought care from January 2006 to December 2014, and the data were analyzed by year, site, age, and sex assigned at birth. RESULTS: In 2006, the number of TGNB people (and corresponding 95% CI) per 100 000 population were 3.5 (1.9, 6.3) in Georgia, 5.5 (4.8, 6.4) in Southern California, and 17 (16, 19) in Northern California. In 2014, these frequencies increased to 38 (32, 45), 44 (42, 46), and 75 (72, 78) per 100 000 population, respectively. When analyzed by age, the most rapid increase was observed among persons 18 to 25 years old, and this increase accelerated after 2010. The ratio of transmasculine to transfeminine persons also changed from 1:1.7 in 2006 to 1:1 in 2014 overall and from 1:1 in 2006 to 1.8:1 in 2014 among persons <18 years of age. CONCLUSION: This analysis confirms previous observations that the proportion of TGNB people is growing, especially among young adults. The composition of the TGNB population is also changing from predominantly transfeminine to roughly 1:1 overall and to predominantly transmasculine in children and adolescents.

An automated algorithm using free-text clinical notes to improve identification of transgender people.

Accurate identification of transgender persons is a critical first step in conducting transgender health studies. To develop an automated algorithm for identifying transgender individuals from electronic medical records (EMR) using free-text clinical notes. The development and validation of the algorithm was based on data from an integrated healthcare system that served as a participating site in the multicenter Study of Transition Outcomes and Gender. The training and test datasets each contained a total of 300 individuals identified between 2006 and 2014. Both datasets underwent a full medical record review by experienced research abstractors. The validated algorithm was then implemented to identify transgender individuals in the EMR using all clinical notes of patients that received care between January 1, 2015 and June 30, 2018. Validation of the algorithm against the full chart review demonstrated a high degree of accuracy with 97% sensitivity, 95% specificity, 94% positive predictive value, and 97% negative predictive value. The algorithm classified 7,409 individuals (3.5%) as "Definitely transgender" and 679 individuals (0.3%) as "Probably transgender" out of 212,138 candidates with a total of 378,641 clinical notes. The computerized NLP algorithm can support essential efforts to improve the health of transgender people.

Suicide Attempts Among a Cohort of Transgender and Gender Diverse People.

INTRODUCTION: Transgender and gender diverse people often face discrimination and may experience disproportionate emotional distress that leads to suicide attempts. Therefore, it is essential to estimate the frequency and potential determinants of suicide attempts among transgender and gender diverse individuals. METHODS: Longitudinal data on 6,327 transgender and gender diverse individuals enrolled in 3 integrated healthcare systems were analyzed to assess suicide attempt rates. Incidence was compared between transmasculine and transfeminine people by age and race/ethnicity and according to mental health status at baseline. Cox proportional hazards models examined rates and predictors of suicide attempts during follow-up. Data were collected in 2016, and analyses were conducted in 2019. RESULTS: During follow-up, 4.8% of transmasculine and 3.0% of transfeminine patients had at least 1 suicide attempt. Suicide attempt rates were more than 7 times higher among patients aged <18 years than among those aged >45 years, more than 3 times higher among patients with previous history of suicide ideation or suicide attempts than among those with no such history, and 2-5 times higher among those with 1-2 mental health diagnoses and more than 2 mental health diagnoses at baseline than among those with none. CONCLUSIONS: Among transgender and gender diverse individuals, younger people, people with previous suicidal ideation or attempts, and people with multiple mental health diagnoses are at a higher risk for suicide attempts. Future research should examine the impact of gender-affirming healthcare use on the risk of suicide attempts and identify targets for suicide prevention interventions among transgender and gender diverse people in clinical settings.

Longitudinal Changes in Hematologic Parameters Among Transgender People Receiving Hormone Therapy.

CONTEXT: The effect of gender-affirming hormone therapy (HT) on erythropoiesis is an area of priority in transgender health research. OBJECTIVE: To compare changes in hematologic parameters and rates of erythrocytosis and anemia among transgender people to those of cisgender controls. DESIGN: Longitudinal observational study. PARTICIPANTS AND SETTING: We compared 559 transfeminine (TF) and 424 transmasculine (TM) people enrolled in 3 integrated health care systems to matched cisgender referents. INTERVENTIONS AND OUTCOME: Hormone therapy receipt was ascertained from filled prescriptions. Hemoglobin (Hb) and hematocrit (Hct) levels were examined from the first blood test to HT initiation, and from the start of HT to the most recent blood test. Rates of erythrocytosis and anemia in transgender participants and referents were compared by calculating adjusted hazard ratios and 95% confidence intervals (CI). RESULTS: In the TF group, there was a downward trend for both Hb and Hct. The corresponding changes in the TM cohort were in the opposite direction. TM study participants experienced a 7-fold higher rate (95% CI: 4.1-13.4) of erythrocytosis relative to matched cisgender males, and an 83-fold higher rate (95% CI: 36.1-191.2) compared to cisgender females. The corresponding rates for anemia were elevated in TF subjects but primarily relative to cisgender males (hazard ratio 5.9; 95% CI: 4.6-7.5). CONCLUSIONS: Our results support previous recommendations that hematological parameters of transgender people receiving HT should be interpreted based on their affirmed gender, rather than their sex documented at birth. The clinical significance of erythrocytosis following testosterone therapy, as well as anemia following feminizing HT, requires further investigation.

Cross-sex Hormones and Acute Cardiovascular Events in Transgender Persons: A Cohort Study.

Background: Venous thromboembolism (VTE), ischemic stroke, and myocardial infarction in transgender persons may be related to hormone use. Objective: To examine the incidence of these events in a cohort of transgender persons. Design: Electronic medical record-based cohort study of transgender members of integrated health care systems who had an index date (first evidence of transgender status) from 2006 through 2014. Ten male and 10 female cisgender enrollees were matched to each transgender participant by year of birth, race/ethnicity, study site, and index date enrollment. Setting: Kaiser Permanente in Georgia and northern and southern California. Patients: 2842 transfeminine and 2118 transmasculine members with a mean follow-up of 4.0 and 3.6 years, respectively, matched to 48 686 cisgender men and 48 775 cisgender women. Measurements: VTE, ischemic stroke, and myocardial infarction events ascertained from diagnostic codes through the end of 2016 in transgender and reference cohorts. Results: Transfeminine participants had a higher incidence of VTE, with 2- and 8-year risk differences of 4.1 (95% CI, 1.6 to 6.7) and 16.7 (CI, 6.4 to 27.5) per 1000 persons relative to cisgender men and 3.4 (CI, 1.1 to 5.6) and 13.7 (CI, 4.1 to 22.7) relative to cisgender women. The overall analyses for ischemic stroke and myocardial infarction demonstrated similar incidence across groups. More pronounced differences for VTE and ischemic stroke were observed among transfeminine participants who initiated hormone therapy during follow-up. The evidence was insufficient to allow conclusions regarding risk among transmasculine participants. Limitation: Inability to determine which transgender members received hormones elsewhere. Conclusion: The patterns of increases in VTE and ischemic stroke rates among transfeminine persons are not consistent with those observed in cisgender women. These results may indicate the need for long-term vigilance in identifying vascular side effects of cross-sex estrogen. Primary Funding Source: Patient-Centered Outcomes Research Institute and Eunice Kennedy Shriver National Institute of Child Health and Human Development.

Mental Health of Transgender and Gender Nonconforming Youth Compared With Their Peers.

BACKGROUND: Understanding the magnitude of mental health problems, particularly life-threatening ones, experienced by transgender and/or gender nonconforming (TGNC) youth can lead to improved management of these conditions. METHODS: Electronic medical records were used to identify a cohort of 588 transfeminine and 745 transmasculine children (3-9 years old) and adolescents (10-17 years old) enrolled in integrated health care systems in California and Georgia. Ten male and 10 female referent cisgender enrollees were matched to each TGNC individual on year of birth, race and/or ethnicity, study site, and membership year of the index date (first evidence of gender nonconforming status). Prevalence ratios were calculated by dividing the proportion of TGNC individuals with a specific mental health diagnosis or diagnostic category by the corresponding proportion in each reference group by transfeminine and/or transmasculine status, age group, and time period before the index date. RESULTS: Common diagnoses for children and adolescents were attention deficit disorders (transfeminine 15%; transmasculine 16%) and depressive disorders (transfeminine 49%; transmasculine 62%), respectively. For all diagnostic categories, prevalence was severalfold higher among TGNC youth than in matched reference groups. Prevalence ratios (95% confidence intervals [CIs]) for history of self-inflicted injury in adolescents 6 months before the index date ranged from 18 (95% CI 4.4-82) to 144 (95% CI 36-1248). The corresponding range for suicidal ideation was 25 (95% CI 14-45) to 54 (95% CI 18-218). CONCLUSIONS: TGNC youth may present with mental health conditions requiring immediate evaluation and implementation of clinical, social, and educational gender identity support measures.

A novel method for estimating transgender status using electronic medical records.

PURPOSE: We describe a novel algorithm for identifying transgender people and determining their male-to-female (MTF) or female-to-male (FTM) identity in electronic medical records of an integrated health system. METHODS: A computer program scanned Kaiser Permanente Georgia electronic medical records from January 2006 through December 2014 for relevant diagnostic codes, and presence of specific keywords (e.g., "transgender" or "transsexual") in clinical notes. Eligibility was verified by review of de-identified text strings containing targeted keywords, and if needed, by an additional in-depth review of records. Once transgender status was confirmed, FTM or MTF identity was assessed using a second program and another round of text string reviews. RESULTS: Of 813,737 members, 271 were identified as possibly transgender: 137 through keywords only, 25 through diagnostic codes only, and 109 through both codes and keywords. Of these individuals, 185 (68%, 95% confidence interval [CI]: 62%-74%) were confirmed as definitely transgender. The proportions (95% CIs) of definite transgender status among persons identified via keywords, diagnostic codes, and both were 45% (37%-54%), 56% (35%-75%), and 100% (96%-100%). Of the 185 definitely transgender people, 99 (54%, 95% CI: 46%-61%) were MTF, 84 (45%, 95% CI: 38%-53%) were FTM. For two persons, gender identity remained unknown. Prevalence of transgender people (per 100,000 members) was 4.4 (95% CI: 2.6-7.4) in 2006 and 38.7 (95% CI: 32.4-46.2) in 2014. CONCLUSIONS: The proposed method of identifying candidates for transgender health studies is low cost and relatively efficient. It can be applied in other similar health care systems.