Rebecca Nash

State Variation in the Receipt of a Contralateral Prophylactic Mastectomy Among Women Who Received a Diagnosis of Invasive Unilateral Early-Stage Breast Cancer in the United States, 2004-2012

Importance The use of contralateral prophylactic mastectomies (CPMs) among patients with invasive unilateral breast cancer has increased substantially during the past decade in the United States despite the lack of evidence for survival benefit. However, whether this trend varies by state or whether it is correlated with changes in proportions of reconstructive surgery among these patients is unclear. Objective To determine state variation in the temporal trend and in the proportion of CPMs among women with early-stage unilateral breast cancer treated with surgery. Design, Setting, and Participants A retrospective cohort study of 1.2 million women 20 years of age or older diagnosed with invasive unilateral early-stage breast cancer and treated with surgery from January 1, 2004, through December 31, 2012, in 45 states and the District of Columbia as compiled by the North American Association of Central Cancer Registries. Data analysis was performed from August 1, 2015, to August 31, 2016. Exposure Contralateral prophylactic mastectomy. Main Outcomes and Measures Temporal changes in the proportion of CPMs among women with early-stage unilateral breast cancer treated with surgery by age and state, overall and in relation to changes in the proportions of those who underwent reconstructive surgery. Results Among the 1 224 947 women with early-stage breast cancer treated with surgery, the proportion who underwent a CPM nationally increased between 2004 and 2012 from 3.6% (4013 of 113 001) to 10.4% (12 890 of 124 231) for those 45 years or older and from 10.5% (1879 of 17 862) to 33.3% (5237 of 15 745) for those aged 20 to 44 years. The increase was evident in all states, although the magnitude of the increase varied substantially across states. For example, among women 20 to 44 years of age, the proportion who underwent a CPM from 2004-2006 to 2010-2012 increased from 14.9% (317 of 2121) to 24.8% (436 of 1755) (prevalence ratio [PR], 1.66; 95% CI, 1.46-1.89) in New Jersey compared with an increase from 9.8% (162 of 1657) to 32.2% (495 of 1538) (PR, 3.29; 95% CI, 2.80-3.88) in Virginia. In this age group, CPM proportions for the period from 2010 to 2012 were over 42% in the contiguous states of Nebraska, Missouri, Colorado, Iowa, and South Dakota. From 2004 to 2012, the proportion of reconstructive surgical procedures among women aged 20 to 44 years who were diagnosed with early-stage breast cancer and received a CPM increased in many states; however, it did not correlate with the proportion of women who received a CPM. Conclusions and Relevance The increase in the proportion of CPMs among women with early-stage unilateral breast cancer treated with surgery varied substantially across states. Notably, in 5 contiguous Midwest states, nearly half of young women with invasive early-stage breast cancer underwent a CPM from 2010 to 2012. Future studies should examine the reasons for the geographic variation and increasing trend in the use of CPMs.

Cancer in Transgender People: Evidence and Methodological Considerations

Transgender people comprise a diverse group of individuals whose gender identity or expression differs from that originally assigned to them at birth. Some, but not all, transgender people elect to undergo medical gender affirmation, which may include therapy with cross-sex hormones and/or surgical change of the genitalia and other sex characteristics. As cross-sex hormones administered for the purposes of gender affirmation may be delivered at high doses and over a period of decades, the carcinogenicity of hormonal therapy in transgender people is an area of considerable concern. In addition, concerns about cancer risk in transgender patients have been linked to sexually transmitted infections, increased exposure to well-known risk factors such as smoking and alcohol use, and the lack of adequate access to screening. Several publications have identified cancer as an important priority in transgender health research and called for large-scale studies. The goals of this article are to summarize the evidence on factors that may differentially affect cancer risk in transgender people, assess the relevant cancer surveillance and epidemiologic data available to date, and offer an overview of possible methodological considerations for future studies investigating cancer incidence and mortality in this population.

Cohort profile: Study of Transition, Outcomes and Gender (STRONG) to assess health status of transgender people

Purpose The Study of Transition, Outcomes and Gender (STRONG) was initiated to assess the health status of transgender people in general and following gender-affirming treatments at Kaiser Permanente health plans in Georgia, Northern California and Southern California. The objectives of this communication are to describe methods of cohort ascertainment and data collection and to characterise the study population. Participants A stepwise methodology involving computerised searches of electronic medical records and free-text validation of eligibility and gender identity was used to identify a cohort of 6456 members with first evidence of transgender status (index date) between 2006 and 2014. The cohort included 3475 (54%) transfeminine (TF), 2892 (45%) transmasculine (TM) and 89 (1%) members whose natal sex and gender identity remained undetermined from the records. The cohort was matched to 127 608 enrollees with no transgender evidence (63 825 women and 63 783 men) on year of birth, race/ethnicity, study site and membership year of the index date. Cohort follow-up extends through the end of 2016. Findings to date About 58% of TF and 52% of TM cohort members received hormonal therapy at Kaiser Permanente. Chest surgery was more common among TM participants (12% vs 0.3%). The proportions of transgender participants who underwent genital reconstruction surgeries were similar (4%–5%) in the two transgender groups. Results indicate that there are sufficient numbers of events in the TF and TM cohorts to further examine mental health status, cardiovascular events, diabetes, HIV and most common cancers. Future plans STRONG is well positioned to fill existing knowledge gaps through comparisons of transgender and reference populations and through analyses of health status before and after gender affirmation treatment. Analyses will include incidence of cardiovascular disease, mental health, HIV and diabetes, as well as changes in laboratory-based endpoints (eg, polycythemia and bone density), overall and in relation to gender affirmation therapy.

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

The prevalence of mental health conditions among transfeminine and transmasculine youth 3 to 17 years old at initial presentation is estimated and compared with matched cisgender counterparts. 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.

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

Transgender persons are a diverse group whose gender identity differs from a male or female sex designation, which usually is assigned at birth (1). Although some transgender persons may not self-identify on the basis of binary definitions (2), a person whose gender identity differs from a male sex designation at birth often is referred to as male-to-female, transfeminine, or trans woman, and a person whose gender identity differs from a female sex designation at birth often is referred to as female-to-male, transmasculine, or trans man (3, 4). Some transgender persons undergo medical treatment to align their physical appearance with their gender identity (5, 6). A specific area of concern in transgender health is the risk for acute cardiovascular events (ACVEs), including venous thromboembolism (VTE), ischemic stroke, and myocardial infarction, which might plausibly be related to cross-sex hormone therapy (7). As reviewed elsewhere (811), the direct evidence addressing this issue is sparse and inconsistent because of the predominance of small studies with very few reported events. A direct evaluation of the evidence regarding the incidence of ACVEs requires a longitudinal study that includes large numbers of transfeminine and transmasculine participants, with sufficient follow-up, appropriate control groups, and documented cross-sex hormone use among participants (12). Integrated health care systems with electronic medical records (EMRs) allow efficient identification and follow-up of hard-to-reach population subgroups, such as transgender persons. Our objective was to compare ACVE incidence rates in a cohort of transgender persons enrolled in 3 such health care systems with rates observed in age-, race-, site-, and membership-matched cisgender men and women (reference cohorts). Methods Cohort Ascertainment This study took place at Kaiser Permanente sites in Georgia, northern California, and southern California and was coordinated by Emory University. All activities were reviewed and approved by the institutional review boards of the 4 institutions. The methods of cohort ascertainment were described in detail previously (13, 14). As summarized in the Supplement and Supplement Figure 1, cohort selection involved a 3-step algorithm: an initial EMR search to identify cohort candidates (step 1), validation of transgender status (step 2), and determination of transmasculine or transfeminine status (step 3). Supplement. Technical Appendix Ten male and 10 female cisgender Kaiser Permanente enrollees were matched to each member of the final validated transgender cohort by race/ethnicity (non-Hispanic white, non-Hispanic black, Asian/Pacific Islander, Hispanic, and other), year of birth (within a 5-year interval), study site, and calendar year of membership based on the index date. Index date was defined as the first recorded evidence of transgender status. We used both male and female cisgender reference groups because hormone serum concentrations among transgender persons may range from normal physiologic male to normal physiologic female levels, depending on receipt and dosage of hormone therapy as well as individual characteristics (15). A 10:1 ratio was used to allow stratified analyses (for example, by hormone therapy type) while ensuring a sufficient number of cisgender referents for each cohort member. Each transgender cohort member was linked to matched referents via a unique cluster identification number (ID) to allow subanalyses. Data Collection and Analysis Only persons aged 18 years or older at their index date who were determined to be transmasculine or transfeminine, along with their matched referents, were included. All study participants were characterized with respect to their Kaiser Permanente enrollment history and their cigarette smoking status, body mass index (BMI; kilograms per square meter), blood pressure, and total blood cholesterol level at baseline. Variable categorization is presented in the footnotes to the tables and in the Supplement. Transgender hormone treatment was determined through EMR linkages to prescription data by using national drug codes. Linkages with the International Classification of Diseases, Ninth Revision and 10th Revision (ICD-9 and ICD-10), and Current Procedural Terminology codes were used to ascertain surgeries and other interventions. Feminizing drugs (such as estradiol and spironolactone) in a participant recorded as male at birth and masculinizing drugs (such as testosterone) in a participant documented as female at birth were considered evidence of hormone therapy. In both the transgender and the reference cohorts, ACVEs were ascertained on the basis of ICD-9 or ICD-10 codes. The lists of codes and numbers of cases ascertained by each code are specified in Supplement Table 3. Only ACVEs with a diagnosis date during follow-up were used in the analyses. History of ACVEs was defined as having an event with a diagnosis date before the start of follow-up. Statistical Analysis All transgender cohort members were characterized as transfeminine or transmasculine and grouped further according to their history of cross-sex hormone use. Follow-up in the overall analysis extended from the index date until the first occurrence of the event of interest, disenrollment from the plan for more than 90 days, death, or the end of the study period (30 November 2016). For participants who began hormone therapy at Kaiser Permanente after the index date (hormone initiation cohort), additional analyses were conducted. In these analyses, follow-up started on the date of the first filled prescription for estrogen or testosterone for transfeminine or transmasculine participants, respectively. Matched referents were assigned the same start date for follow-up. Missing covariate values for BMI, blood pressure, and total cholesterol level were assigned by using multiple imputation methods (n= 5 imputations). Incidence rates were calculated as the number of cases per 1000 person-years, and the corresponding 95% CIs were calculated by using the Poisson distribution. Both unadjusted KaplanMeier curves and weighted cumulative incidence curves adjusted for covariates at the population means were constructed to compare the incidence of each ACVE type in the transmasculine and transfeminine participants with those in the corresponding matched reference cohorts. Risk differences at 2, 4, 6, and 8 years were calculated directly from the adjusted cumulative incidence curves. The 95% CI for each risk difference estimate was calculated via a bootstrapping procedure using 1000 random samples with replacement. In the primary analysis, we used multivariable Cox proportional hazards models to compare ACVE rates in the overall transfeminine and transmasculine cohorts and among members of the hormone initiation cohorts with those in the matched cisgender reference groups, after controlling for history of any ACVE, smoking status, BMI, blood pressure, and blood cholesterol level ascertained near the index date. Each model was stratified by cluster ID to account for matching. Proportional hazards assumptions were tested by examining log-minus-log plots for each variable in the model and by performing a goodness-of-fit test using Schoenfeld residuals (16). The results of the Cox models were expressed as adjusted hazard ratios with corresponding 95% CIs. Because the weighted cumulative incidence curves could not account for matching, hazard ratios from models that were not stratified by cluster ID were also calculated and are included in Supplement Tables 4 and 5. When evidence (such as log-minus-log survival plots) suggested that the proportional hazards assumption was violated, stratified Cox models were used to control for covariates, and extended Cox models with time-dependent hazard ratio estimates were used for the main independent variables of interest (16). Although the cohort size precluded detailed analyses by specific hormone therapy regimens, some examination of treatment subcategories was possible. These secondary exploratory analyses focused on transfeminine cohort subgroups defined on the basis of administration route (oral or other) and estrogen type (estradiol or other). In addition, the highest daily hormone dosages were summarized for participants who had an event of interest and in those who received hormone therapy but remained ACVE-free. We examined the effect of different case and exposure definitions, risk factors, and analytic approaches by conducting a series of sensitivity analyses (Supplement). To investigate the effects of unaccounted confounding, we calculated a range of E-values for the main results and the lower limits of their 95% CIs observed in Cox regression models (17). The data analyses were performed with SAS, version 9.4 (SAS Institute). E-values were obtained by using an online calculator for hazard ratios with an outcome prevalence of less than 15%. Role of the Funding Source This study was funded by the Patient-Centered Outcomes Research Institute (PCORI) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. Results A total of 6456 transgender cohort members were identified in the EMR. After persons younger than 18 years at their index date (n= 1347), those with unknown sex designation at birth (n= 75), and those with no follow-up data (n= 74) were excluded, the study group included 4960 transgender participants and matched reference cohorts of 48686 cisgender men and 48775 cisgender women. The transgender cohort comprised 2842 (57%) transfeminine and 2118 (43%) transmasculine persons (Table 1). More than 50% of participants in both groups were non-Hispanic whites; Hispanics represented 18% of transfeminine and 14% of transmasculine participants,

Agreement between medical records and self-reports: Implications for transgender health research

A key priority of transgender health research is the evaluation of long-term effects of gender affirmation treatment. Thus, accurate assessment of treatment receipt is critical. The data for this analysis came from an electronic medical records (EMR) based cohort of transgender individuals. A subset of cohort members were also asked to complete a self-administered survey. Information from the EMR was compared with survey responses to assess the extent of agreement regarding transmasculine (TM)/transfeminine (TF) status, hormone therapy receipt, and type of surgery performed. Logistic regression models were used to assess whether participant characteristics were associated with disagreement between data sources. Agreement between EMR and survey-derived information was high regarding TM/TF status (99%) and hormone therapy receipt (97%). Lower agreement was observed for chest reconstruction surgery (72%) and genital reconstruction surgery (84%). Using survey responses as the “gold standard”, both chest and genital reconstruction surgeries had high specificity (95 and 93%, respectively), but the corresponding sensitivities were low (49 and 68%, respectively). A lower proportion of TM had concordant results for chest reconstruction surgery (64% versus 79% for TF) while genital reconstruction surgery concordance was lower among TF (79% versus 89% for TM). For both surgery types, agreement was highest among the youngest participants. Our findings offer assurance that EMR-based data appropriately classify cohort participants with respect to their TM/TF status or hormone therapy receipt. However, current EMR data may not capture the complete history of gender affirmation surgeries. This information is useful in future studies of outcomes related to gender affirming therapy.

Frequency and distribution of primary site among gender minority cancer patients: An analysis of U.S. national surveillance data

BACKGROUND Transgender people and persons with disorders of sex development (DSD) are two separate categories of gender minorities, each characterized by unique cancer risk factors. Although cancer registry data typically include only two categories of sex, registrars have the option of indicating that a patient is transgender or has a DSD. METHODS Data for primary cancer cases in 46 states and the District of Columbia were obtained from the North American Association of Central Cancer Registries (NAACCR) database for the period 1995-2013. The distributions of primary sites and categories of cancers with shared risk factors were examined separately for transgender and DSD patients and compared to the corresponding distributions in male and female cancer patients. Proportional incidence ratios were calculated by dividing the number of observed cases by the number of expected cases. Expected cases were calculated based on the age- and year of diagnosis-specific proportions of cases in each cancer category observed among male and female patients. RESULTS Transgender patients have significantly elevated proportional incidence ratios (95% confidence intervals) for viral infection induced cancers compared to either males (2.3; 2.0-2.7) or females (3.3; 2.8-3.7). Adult DSD cancer patients have a similar distribution of primary sites compared to male or female patients but DSD children with cancer have ten times more cases of testicular malignancies than expected (95% confidence interval: 4.7-20). CONCLUSION The proportions of certain primary sites and categories of malignancies among transgender and DSD cancer patients are different from the proportions observed for male or female patients.