Abstract
Objective
The aim of this study was to investigate the impact of estrogen and progesterone analog supplementation on the development of autoimmune conditions.
Methods
This retrospective observational study used data from the TriNetX network, which comprised over 100 million patients from 89 health care organizations. We compared patients exposed to estrogen and progesterone analogs to those exposed to progesterone‐only therapy, using 1:1 propensity score matching based on age, ethnicity, and additional criteria. The primary outcomes were incidences of various autoimmune conditions.
Results
We included 3,338,925 patients in the group who received estrogen and progesterone and 2,090,758 patients in the group who received progesterone only. Prematching, the group who received combined therapy showed increased risks for Sjögren disease (risk ratio [RR] 1.46), rheumatoid arthritis (RR 1.1), and other autoimmune conditions. Postmatching, significant associations persisted for most conditions, with increased risks for systemic sclerosis, systemic lupus erythematosus, giant cell arteritis, Behcet disease, psoriatic arthritis, reactive arthritis, and ankylosing spondylitis. The group who received combination therapy appeared to have lower risks of developing antiphospholipid syndrome (RR 0.7).
Conclusion
Combined estrogen and progesterone therapy is associated with an increased risk of several autoimmune conditions. The role of estrogen, despite its protective effects against some conditions, underscores the complex interplay of sex hormones in autoimmunity. Further prospective studies are needed to elucidate underlying mechanisms and evaluate causality.
INTRODUCTION
It is a well‐described fact that most autoimmune conditions are several‐fold more common in female patients than in male patients. The mechanism of the sex discrepancy in the incidence of autoimmunity is incompletely recognized but likely involves hormonal and genetic factors. 1 A recent murine study implicates the long noncoding RNA Xist in sex‐biased autoimmunity. 1 , 2 Xist silences one of the two X chromosomes in female patients by binding to several RNPs, which can become autoantigens when cells die, triggering autoimmune responses. This binding and subsequent immune reprogramming lead to increased autoantibody production and autoimmune pathology, as observed in transgenic male mice expressing Xist. 3 Another demonstration of the chromosomal contribution to autoimmune disease is given by the observation that male patients with Klinefelter syndrome, who have a karyotype including two X chromosomes, are at higher risk for developing autoimmune conditions including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), diabetes mellitus type 1, and multiple sclerosis (MS), among others. 4
Several lines of evidence also suggest female hormones, in particular estrogen, increase the susceptibility to autoimmunity. 5 Estrogen and progesterone receptors are expressed in various types of immune cells, including lymphocytes, macrophages, and dendritic cells. 6 Estrogen has immune‐stimulatory effects in T and B cells and thus plays a role in pathogenesis of autoimmune disease. 7 Estrogen enhances humoral responses by enhancing B cell differentiation and Ig production. 8 , 9 , 10 , 11 , 12 , 13
Hormones, particularly estrogen, exhibit dualistic effects during autoimmune conditions. For instance, SLE tends to worsen during pregnancy, 14 whereas pregnant women with MS often experience a reduction in relapse rates. 15 These observations are mirrored by murine experiments that show that ovariectomy or estrogen receptor α knock‐out ameliorates murine lupus, 16 but estrogen is protective in experimental autoimmune encephalomyelitis, a murine MS model, by promoting immune regulatory cells. 17
The onset patterns of autoimmune diseases suggest a potential role for progesterone because these conditions are more prevalent in postpubertal female patients. 18 In vitro studies have shown that progesterone directly affects immune cells, 9 , 19 inhibiting neutrophil chemotaxis 20 and enhancing T helper (Th) 2–related antibody responses. 18 , 21 High doses of progesterone can suppress toll‐like receptor 9–induced interferon (IFN)‐alpha production, which may help mitigate Th1‐driven autoimmunity. 22 Progesterone, through its receptors, also appears to modulate B cell differentiation pathways and could alter immune‐mediated damage in autoimmune diseases by posttranslationally modifying Igs. 11 , 18
Autoimmunity is shaped by hormonal status, including estrogen, but this relationship is not always straightforward. Given the conflicting data on hormonal effects, there is particular interest in exploring whether supplemental estrogen and progesterone might balance each other in immune interactions or, conversely, synergistically elevate the risk of autoimmune conditions. Unopposed progesterone therapy, by stimulating a Th2 response, 18 might be associated with higher risks for autoimmune conditions characterized by anamnestic antibody release. This study determined these hormones might independently or jointly influence immune pathways associated with autoimmunity; it was conducted using an international‐level database to demonstrate whether estrogen supplementation impacts the development of autoimmune diseases.
PATIENTS AND METHODS
Study design and data source
The data for this retrospective observational study were obtained from the multicenter research network TriNetX. The acquired information from electronic health records of 89 participating health care organizations is anonymized and covers more than 100 million patients; thus, the analysis was exempt from institutional review board approval. Despite the data being deidentified, integrated analytics facilitate patient‐level analysis for cohort selection, event incidence, prevalence assessment, and comparison of characteristics and outcomes between matched cohorts.
Study population
The study focused on individuals aged 18 years and older, with data collected from January 1, 2000, to November 4, 2024. The goal was to identify patients receiving combined oral contraceptive therapy (OCT) or hormone replacement therapy (HRT) with estrogen and progesterone analogs and those receiving progesterone‐only medications. Diagnoses were identified through International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD‐10) codes, whereas medications were tracked using RxNorm codes. Exposure to combination therapy was depicted as the presence of both estrogen and progesterone analogs in patient's charts. Combined formulations were not used because they are not embedded as combined codes in the TrinetX database. Detailed information on diagnoses and medications can be found in Supplementary Material, Appendix 1. Because estrogen‐only supplementation is used almost exclusively in postmenopausal patients and our analysis did not involve stratification by age groups and focused on lifetime risks, patients with estrogen analog therapy alone were not included in analysis, regardless of their age. In contrast, the control group included patients receiving only progesterone medications. The index event was defined as the first recorded instance of hormone therapy appearing in patients’ charts. Patients with any history of RxNorm codes for estrogen analogs were excluded from the group who received progesterone only (Supplementary Material, Figure 1).
Study outcomes
The primary outcomes of interest were the incidences of Sjögren disease, systemic sclerosis (SSc), seronegative or seropositive RA, dermatomyositis (DM), polymyositis (PM), SLE, antiphospholipid syndrome (APS), granulomatosis with polyangiitis (GWP), giant cell arteritis (GCA) with or without polymyalgia rheumatica, psoriatic arthritis (PsA), Behcet disease, nonradiographic axial spondyloarthritis (Nr‐axSpA), reactive arthritis, and ankylosing spondylitis (AS). Patients with pre‐existing conditions related to these outcomes were excluded from the study.
Statistical analysis
Patient baseline characteristics were represented as mean ± SD for continuous variables and compared using independent‐sample Student's t‐tests. Categorical variables were presented as n (%) and analyzed using the chi‐square test. To ensure comparability between the groups, a 1:1 propensity score matching technique was employed based on age and ethnicity. Additional matching criteria included neoplastic disorders (such as breast and female genital organ malignancies) and the use of immune checkpoint inhibitors, considering the potential for paraneoplastic emergence of conditions and different cancer profiles in these groups. Patients were also matched based on personal histories of venous embolism, thrombosis, and pulmonary embolism to reduce the likelihood of estrogen supplementation being avoided in this group, which could otherwise bias results toward lower risks of certain autoimmune conditions.
Statistical analyses were conducted using the integrated features of TriNetX online platform. The 1:1 matching was achieved using the nearest‐neighbor algorithm. Balance within patient characteristics was evaluated using the standardized mean difference (SMD), with an SMD of <0.1 indicating adequate balance. Risk ratios (RRs), along with 95% confidence intervals (CIs) and P values, were reported for outcomes of interest, and the relevant tests of significance were two‐tailed, with a P value of <0.05 considered significant.
RESULTS
We included 3,338,925 patients in the group who received the estrogen and progesterone combination and 2,090,758 in the group who received progesterone only. Patients in both groups were predominantly White (65.8% vs 56.3%, SMD 0.1), patients in the exposure group were younger (30.9 ± 13.3 years vs 35.2 ± 15.7 years, SMD 0.29), group who received progesterone only had higher number of patients diagnosed with neoplasms (12.8% vs 9%, SMD 0.12), breast cancer (0.9% vs 0.2%, SMD 0.12), and neoplasms of female genital organs (0.7% vs 0.2%, SMD 0.07). Among these groups, an extremely low percentage of patients received immune checkpoint inhibitors. Prematching, the group who received progesterone only had higher prevalences of unclassified venous embolism and thrombosis (1.3% vs 0.3%, SMD 0.1), personal history of venous thrombosis and embolism (0.9% vs 0.2%, SMD 0.1), and pulmonary embolism (0.7% vs 0.14%, SMD 0.9; Table 1).
Table 1.
Baseline patient characteristics of study groups, before and after propensity score matching
| Before propensity score matching | After propensity score matching | |||||
|---|---|---|---|---|---|---|
| Characteristics | Group who received estrogen and progesterone (n = 3,338,925), % | Group who received progesterone only (n = 2,090,758), % | Standardized mean difference | Group who received estrogen and progesterone (n = 1,948,343), % | Group who received progesterone only (n = 1,948,343), % | Standardized mean difference |
| Age, mean ± SD, y | 30.9 ± 13.3 | 35.2 ± 15.7 | 0.29 | 33.6 ± 13.6 | 33.7 ± 14 | 0.009 |
| Female | 100 | 100 | – | 100 | 100 | – |
| Hispanic | 31.8 | 36.8 | 0.1 | 27.5 | 26.6 | 0.02 |
| White | 65.8 | 56.3 | 0.2 | 57 | 57.5 | 0.009 |
| Black | 11.8 | 18 | 0.18 | 17.1 | 17 | 0.002 |
| Asian | 3.7 | 4.9 | 0.05 | 3.9 | 4.4 | 0.02 |
| Unknown | 18.7 | 20.8 | 0.06 | 22 | 21.1 | 0.01 |
| Held diagnosis | ||||||
| Neoplasms | 9 | 12.8 | 0.12 | 10.8 | 11 | 0.006 |
| Breast cancer | 0.2 | 0.9 | 0.09 | 0.35 | 0.3 | 0.006 |
| Malignant neoplasms of female genital organs | 0.2 | 0.7 | 0.07 | 0.3 | 0.3 | 0.003 |
| Other venous embolism and thrombosis | 0.3 | 1.3 | 0.1 | 0.51 | 0.54 | 0.004 |
| History of venous thrombosis and embolism | 0.2 | 0.9 | 0.1 | 0.32 | 0.37 | 0.008 |
| Pulmonary embolism | 0.14 | 0.7 | 0.9 | 0.23 | 0.26 | 0.005 |
| Received medication | ||||||
| Pembrolizumab | 0.01 | 0.06 | 0.02 | 0.0 | 0.0 | – |
| Nivolumab | 0.005 | 0.03 | 0.02 | 0.0 | 0.0 | – |
| Ipilimumab | 0.003 | 0.009 | 0.008 | 0.0 | 0.0 | – |
Prematching, the group who received combined estrogen and progesterone hormone therapy showed a significantly increased risk for Sjögren disease (RR 1.46, 95% CI 1.4–1.5, P < 0.01), RA (RR 1.1, 95% CI 1.09–1.15, P < 0.01), Behcet disease (RR 1.5, 95% CI 1.28–1.7, P < 0.01), PsA (RR 1.3, 95% CI 1.17–1.29, P < 0.01), reactive arthritis (RR 1.65, 95% CI 1.4–1.9, P < 0.01), and AS (RR 1.3, 95% CI 1.26–1.42, P < 0.01). The group who received the combination therapy appeared to have lower risks for SLE (RR 0.95, 95% CI 0.90–0.99, P = 0.002), GCA (RR 0.8, 95% CI 0.7–0.9, P < 0.01), and APS (RR 0.63, 95% CI 0.60–0.67, P < 0.01). Risk differences for SSc, DM, PM, GWP, and Nr‐axSpA were not significant.
Postmatching, significant associations persisted for Sjögren disease, RA, Behcet disease, PsA, reactive arthritis, and AS. Additionally, increased risks for SSc (RR 1.2, 95% CI 1.08–1.3, P < 0.01) and GCA (RR 1.28, 95% CI 1.12–1.5, P < 0.01) in the group who received combination therapy became significant. The lower risk of SLE prematching turned into a significantly increased risk in the group who received combination therapy (RR 1.07, 95% CI 1.03–1.1, P < 0.01), whereas the risk for APS remained lower (RR 0.7, 95% CI 0.68–0.74, P < 0.01). No significant risk differences were noted for Nr‐axSpA, DM, PM, and GWP (Tables 2 and 3).
Table 2.
Risks of connective tissue diseases in patients who received estrogen and progesterone analogs versus those who received progesterone only*
| Outcome | Before propensity score matching | After propensity score matching | ||||
|---|---|---|---|---|---|---|
| Overall risk, % (n) | Risk ratio (CI) | P value | Overall risk, % (n) | Risk ratio (CI) | P value | |
| Sjögren disease | ||||||
| Estrogen and progesterone | 0.41 (13,364 of 3,228,437) | 1.46 (1.4–1.5) | <0.01 | 0.46 (8,972 of 1,942,164) | 1.65 (1.6–1.7) | <0.01 |
| Progesterone alone | 0.29 (5,794 of 2,042,112) | 1.46 (1.4–1.5) | <0.01 | 0.3 (5,427 of 1,942,989) | 1.65 (1.6–1.7) | <0.01 |
| Systemic sclerosis | ||||||
| Estrogen and progesterone | 0.05 (1,667 of 3,235,028) | 1 (0.95–1.1) | 0.58 | 0.06 (1,112 of 1,947,155) | 1.2 (1.08–1.3) | <0.01 |
| Progesterone alone | 0.05 (1,032 of 2,046,701) | 1 (0.95–1.1) | 0.58 | 0.05 (944 of 1,946,891) | 1.2 (1.08–1.3) | <0.01 |
| Rheumatoid arthritis | ||||||
| Estrogen and progesterone | 0.5 (16,048 of 3,222,559) | 1.1 (1.09–1.15) | <0.01 | 0.6 (10,772 of 1,937,962) | 1.3 (1.2–1.4) | <0.01 |
| Progesterone alone | 0.4 (9,031 of 2,034,013) | 1.1 (1.09–1.15) | <0.01 | 0.4 (8,198 of 1,936,755) | 1.3 (1.2–1.4) | <0.01 |
| Dermatomyositis | ||||||
| Estrogen and progesterone | 0.018 (569 of 3,236,330) | 1 (0.9–1.18) | 0.68 | 0.02 (366 of 1,948,105) | 1.13 (0.9–1.3) | 0.1 |
| Progesterone alone | 0.017 (350 of 2,048,119) | 1 (0.9–1.18) | 0.68 | 0.017 (32 of 1,948,060) | 1.13 (0.9–1.3) | 0.1 |
| Polymyositis | ||||||
| Estrogen and progesterone | 0.01 (372 of 3,236,295) | 0.9 (0.8–1) | 0.2 | 0.014 (270 of 1,948,047) | 1.19 (0.9–1.4) | 0.05 |
| Progesterone alone | 0.01 (261 of 2,048,013) | 0.9 (0.8–1) | 0.2 | 0.012 (227 of 1,947,993) | 1.19 (0.9–1.4) | 0.05 |
| Systemic lupus erythematosus | ||||||
| Estrogen and progesterone | 0.3 (9,619 of 3,227,353) | 0.95 (0.9–0.99) | 0.002 | 0.33 (6,410 of 1,941,456) | 1.07 (1.03–1.1) | <0.01 |
| Progesterone alone | 0.3 (6,378 of 2,035,251) | 0.95 (0.9–0.99) | 0.002 | 0.31 (5,995 of 1,936,857) | 1.07 (1.03–1.1) | <0.01 |
| Antiphospholipid syndrome | ||||||
| Estrogen and progesterone | 0.13 (4,185 of 3,234,189) | 0.63 (0.6–0.67) | <0.01 | 0.14 (2,705 of 1,946,439) | 0.7 (0.68–0.74) | <0.01 |
| Progesterone alone | 0.2 (4,175 of 2,042,430) | 0.63 (0.6–0.67) | <0.01 | 0.2 (3,812 of 1,943,587) | 0.7 (0.68–0.74) | <0.01 |
The cohorts were matched with age, race and ethnicity, various diagnoses, and medications. Discrepancies between the total number of patients before and after analysis mean that patients were excluded due to the presence of outcomes before the index period. CI, confidence interval.
Table 3.
Risks of vasculitides and arthropathies in patients who were on estrogen and progesterone analogs versus who received progesterone only*
| Outcome | Before propensity score matching | After propensity score matching | ||||
|---|---|---|---|---|---|---|
| Overall risk, % (n) | Risk ratio (CI) | P value | Overall risk, % (n) | Risk ratio (CI) | P value | |
| Granulomatosis with polyangiitis | ||||||
| Estrogen and progesterone | 0.012 (396 of 3,236,285) | 1 (0.9–1.2) | 0.67 | 0.013 (251 of 1,948,086) | 1.15 (0.9–1.4) | 0.1 |
| Progesterone alone | 0.012 (242 of 2,048,081) | 1 (0.9–1.2) | 0.67 | 0.01 (218 of 1,948,012) | 1.15 (0.9–1.4) | 0.1 |
| Giant cell arteritis | ||||||
| Estrogen and progesterone | 0.02 (697 of 3,236,261) | 0.8 (0.7–0.9) | <0.01 | 0.03 (515 of 1,947,992) | 1.28 (1.12–1.5) | <0.01 |
| Progesterone alone | 0.03 (524 of 2,047,784) | 0.8 (0.7–0.9) | <0.01 | 0.02 (403 of 1,947,895) | 1.28 (1.12–1.5) | <0.01 |
| Behcet disease | ||||||
| Estrogen and progesterone | 0.02 (631 of 3,236,096) | 1.5 (1.28–1.7) | <0.01 | 0.017 (337 of 1,947,983) | 1.3 (1.1–1.5) | <0.01 |
| Progesterone alone | 0.01 (271 of 2,048,079) | 1.5 (1.28–1.7) | <0.01 | 0.013 (260 of 1,947,976) | 1.3 (1.1–1.5) | <0.01 |
| Psoriatic arthritis | ||||||
| Estrogen and progesterone | 0.15 (4,783 of 3,233,682) | 1.3 (1.17–1.29) | <0.01 | 0.16 (3,040 of 1,946,340) | 1.28 (1.2–1.35) | <0.01 |
| Progesterone alone | 0.12 (2,462 of 2,045,964) | 1.3 (1.17–1.29) | <0.01 | 0.12 (2,377 of 1,946,060) | 1.28 (1.2–1.35) | <0.01 |
| Nonradiographic axial spondylarthritis | ||||||
| Estrogen and progesterone | 0.008 (252 of 3,236,635) | 1.2 (0.9–1.5) | 0.08 | 0.007 (146 of 1,948,310) | 1.1 (0.9–1.4) | 0.37 |
| Progesterone alone | 0.006 (132 of 2,048,441) | 1.2 (0.9–1.5) | 0.08 | 0.007 (131 of 1,948,312) | 1.1 (0.9–1.4) | 0.37 |
| Reactive arthritis | ||||||
| Estrogen and progesterone | 0.02 (605 of 3,236,288) | 1.65 (1.4–1.9) | <0.01 | 0.02 (359 of 1,948,079) | 1.6 (1.4–1.9) | <0.01 |
| Progesterone alone | 0.01 (232 of 2,048,188) | 1.65 (1.4–1.9) | <0.01 | 0.01 (223 of 1,948,092) | 1.6 (1.4–1.9) | <0.01 |
| Ankylosing spondylitis | ||||||
| Estrogen and progesterone | 0.09 (3,155 of 3,234,653) | 1.3 (1.26–1.42) | <0.01 | 0.1 (1,939 of 1,946,954) | 1.4 (1.3–1.5) | <0.01 |
| Progesterone alone | 0.07 (1,487 of 2,046,960) | 1.3 (1.26–1.42) | <0.01 | 0.07 (1,418 of 1,946,966) | 1.4 (1.3–1.5) | <0.01 |
The cohorts were matched with age, race and ethnicity, various diagnoses, and medications. Discrepancies between the total number of patients before and after analysis mean that patients were excluded due to the presence of outcomes before the index period. CI, confidence interval.
DISCUSSION
This retrospective real‐world database study showed that patients receiving OCT/HRT have a significantly increased risk of developing autoimmune conditions, including Sjögren disease (RR 1.65), SSc (RR 1.2), RA (RR 1.3), PsA (RR 1.28), Behcet disease (RR 1.3), reactive arthritis (RR 1.6), SLE (RR 1.07), GCA (RR 1.28), and AS (RR 1.4), when compared to women receiving progesterone‐only contraceptives. Interestingly, the analysis suggested that receiving the estrogen and progesterone combination might exert lower risk of APS (RR 0.65) when compared to receiving progesterone‐only therapy. Due to the methods used during analysis, the increased risk observed in the combined therapy group may be primarily attributed to the estrogen component. It should also be highlighted that the study population covers the whole spectrum of middle‐aged female patients who were exposed to estrogens early in their life for birth control and later during menopause with combination HRT. This suggests that many women will encounter these therapies during their lifetime, consequently increasing the risk of developing autoimmune disorders.
The study hypothesis is motivated by observed gender differences in the risk and presentation of various autoimmune conditions, likely due to immunomodulation by sex steroids, nonhormonal factors encoded by sex chromosomes, and sex‐specific autoimmune phenomena. 2 , 23 , 24 The study examines the role of estrogen, given its involvement in autoimmune complications, by comparing the effects of combined estrogen and progesterone supplementation with progesterone alone, because indications for isolated estrogen replacement are limited. 25 Sex hormones, particularly estrogens, have been extensively studied in SLE and RA. They influence critical immune pathways such as type 1 IFN response, CD4+ Th cell differentiation, and autoreactive B cell survival; loss of tolerance to nuclear antigens; and emergence of pathogenic IgG autoantibodies, potentially increasing the risk of autoimmune diseases in genetically predisposed individuals. The balance between progesterone and estrogen may control disease manifestation, with progesterone potentially lowering the risk by blocking estrogen's effects on these pathways. 7 , 8 , 23
Despite growing evidence of serologic abnormalities (Antinuclear antibody, Rheumatoid factor, C‐reactive protein) in healthy young women receiving OCT, 26 they are less likely to develop RA during pregnancy. This disease is most prevalent in middle‐aged women, when estrogen and progesterone levels are declining. 26 , 27 , 28 Thus, the findings demonstrated by this study, showing an increased risk of RA in patients receiving combined OCT/HRT, especially in women in their thirties, were initially surprising. However, this can be explained by hormonal fluctuations, genetic predisposition, 7 and environmental triggers such as infections, smoking, or chronic stress.
Previous studies have noted an increased prevalence of antiphospholipid antibodies in healthy women receiving oral contraceptive (OCP) therapy, mainly anti‐2‐glycoprotein I IgG class. 29 , 30 This is linked to the well‐known prothrombotic condition, APS, and the association between high estrogen doses and venous thromboembolism. 31 Contrarily, this study found a lower APS risk in patients receiving combined OCP therapy/HRT. This may be attributed to estrogen's complex immunomodulatory and anti‐inflammatory effects, which could indirectly reduce antiphospholipid antibody production in susceptible individuals because estrogen is known to promote B cell differentiation. 8 , 9 , 10 , 11 In contrast, progesterone may suppress B cell differentiation, potentially increasing the risk of autoantibody production. 11 , 18 Patients with a history of thromboembolic events and potentially undiagnosed APS might avoid estrogen supplementation, possibly creating a misleading impression of a higher APS risk with unopposed progesterone. However, even after matching for thrombotic history, the results remained statistically significant.
This study's strengths lie in its use of real‐world data, large patient samples, and multicenter design, enhancing external validity, statistical power, and applicability across diverse settings. Future prospective studies could lead to changes in management because health care providers may have to start considering mentioning the risks of developing autoimmune diseases from therapies that involve estrogen/progesterone. Limitations include potential inaccuracies in the TrinetX platform's electronic health records and the inherent misclassification bias and confounding in health care database studies.
Additionally, limitations inherent to the TrinetX platform prevented a comparative analysis across multiple cohorts. The platform's integrated algorithms currently support only two‐cohort matching. Additionally, it is important to clarify that our control group consists of individuals receiving progesterone‐only analogs rather than those entirely unexposed to any contraceptive method. Future improvements to the database may enable cohort creation without the need for ICD‐10 or RxNorm codes for inclusion and exclusion criteria, offering a more flexible and comprehensive analytical framework.
The results of this study may contribute to future studies involving the effect of estrogen/progesterone supplementation in other populations such as transgender female patients and their autoimmune incidence and prevalence. In conclusion, this study highlights the complex role of combined OCT/HRT in the risk of autoimmune conditions. Our findings underscore the intricate interplay of sex hormones, genetic predisposition, and environmental factors in autoimmune disease manifestation. Although we used established outcome definitions and propensity score matching to reduce bias, this study can only establish associations, not causation. Future research, such as prospective cohort studies, is needed to elucidate mechanisms and evaluate causality.
AUTHOR CONTRIBUTIONS
All authors contributed to at least one of the following manuscript preparation roles: conceptualization AND/OR methodology, software, investigation, formal analysis, data curation, visualization, and validation AND drafting or reviewing/editing the final draft. As corresponding author, Dr Tskhakaia confirms that all authors have provided the final approval of the version to be published, and takes responsibility for the affirmations regarding article submission (eg, not under consideration by another journal), the integrity of the data presented, and the statements regarding compliance with institutional review board/Declaration of Helsinki requirements.
Supporting information
Disclosure form
Figure 1: Study Consort Design
Appendix 1: Inclusion/Exclusion Criteria, Matching Criteria and Outcomes with Corresponding ICD‐10 and RxNorm Codes
1Irakli Tskhakaia, MD, Yurilu Gonzalez Moret, MD, Anna‐Kay Palmer, MD, Diego Lema, MD, PhD, Nanuka Tsibadze, MD, Arthur Lau, MD: Jefferson Einstein Hospital, Philadelphia, Pennsylvania; 2M. Carolina Musri, MD: Johns Hopkins Bayview Medical Center and Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland.
Additional supplementary information cited in this article can be found online in the Supporting Information section (http://onlinelibrary.wiley.com/doi/10.1002/acr2.11774).
Author disclosures are available at https://onlinelibrary.wiley.com/doi/10.1002/acr2.11774.
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Figure 1: Study Consort Design
Appendix 1: Inclusion/Exclusion Criteria, Matching Criteria and Outcomes with Corresponding ICD‐10 and RxNorm Codes