Abstract
Background
Uterine fibroids (UF) are commonly associated with heavy menstrual bleeding (HMB) and anemia; however limited data are available on the prevalence of anemia in women with UF, with or without HMB, and the additional incremental burden of HMB and anemia in women with UF and the associated costs of care are unclear.
Objectives
To describe the clinical and economic burden of anemia in women diagnosed with UF, including those with HMB, compared with a control cohort of women without UF or HMB.
Study Design
This was a retrospective observational study using claims data from the Merative MarketScan Commercial Database. The study included women aged 18–55 years newly diagnosed with UF. The first UF claim served as the index date, and women were followed over 12-month preindex and postindex periods. Patients with UF were categorized into cohorts based on the presence and order of HMB claims: UF only, UF then HMB (UF-HMB), and HMB then UF (HMB-UF). UF cohorts were then matched 1:1:1 on age. A control (non-UF/non-HMB) cohort comprising women with no claims for UF or HMB during the study period was identified and matched 5:1 to the 3 UF cohorts based on age. Cohorts were additionally classified based on the presence of anemia. Demographics were assessed at index; clinical characteristics, treatment characteristics for the UF cohorts, healthcare resource utilization, and cost outcomes were assessed during the preindex and postindex periods.
Results
The study included 22,057 women in each UF cohort and 110,285 women in the control cohort. After age-based matching, mean (SD) age was 43.5 (5.9) years for all cohorts. Postindex anemia was most common in women in the UF-HMB (32.0%) and HMB-UF (35.3%) cohorts compared with the UF only (14.3%) and control (4.4%) cohorts. During the postindex period, procedures including hysterectomy and blood transfusions were more common in women with anemia (UF only: 13.4% and 1.8%, respectively; UF-HMB: 37.8% and 7.9%; HMB-UF: 40.8% and 5.7%) compared with women without anemia (UF only: 11.1% and 0%; UF-HMB: 28.1% and 0.1%; HMB-UF: 30.3% and 0%). All-cause and obstetrics/gynecology-related total costs were generally higher in women with anemia compared with women without anemia in all cohorts in both the preindex and postindex periods.
Conclusions
This analysis underscores the significant clinical and economic burden of anemia in women with UF, as well as women with UF and HMB. The findings highlight the necessity for early detection and proactive management of UF and associated anemia to mitigate severe complications and reduce healthcare costs.
Key words: blood transfusion, gonadotropin-releasing hormone agonist, gonadotropin-releasing hormone (GnRH) antagonist, hormonal contraceptive, hypertension, hysterectomy, iron-deficiency anemia, obesity, pain, tranexamic acid
AJOG Global Reports at a Glance.
Why was the study conducted?
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To describe the clinical and economic burden of anemia in women with uterine fibroids and heavy menstrual bleeding.
What are the key findings?
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Women with heavy menstrual bleeding prior to the diagnosis of uterine fibroids have higher rates of anemia, hysterectomy, and healthcare resource utilization and costs vs women without uterine fibroids and women with uterine fibroids without heavy menstrual bleeding.
What does this study add to what is known?
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This analysis highlights the additional clinical and economic burden imposed by anemia in women with uterine fibroids; findings reveal that ∼32%-35% of women with uterine fibroids and heavy menstrual bleeding experience anemia, further compounding their overall health challenges.
Introduction
Uterine fibroids (UF), common, benign uterine tumors, were estimated to affect over 226 million women globally in 2019.1 Heavy menstrual bleeding (HMB) is one of the most commonly reported symptoms of women with UF2,3 and is often associated with iron-deficiency anemia.4,5 A retrospective database analysis revealed that >25% of women with HMB had a diagnosis of anemia,6 with HMB the potential underlying cause for up to 30% of all iron-deficiency anemia cases.7 Absolute iron deficiency most often affects women 18 to 50 years of age,8 coinciding with ages in which UF are most prevalent.1 Anemia has been associated with increased risk of serious clinical events such as myocardial infarction and acute ischemic stroke,9,10 and increased healthcare resource utilization (HCRU), including inpatient hospitalizations and transfusions.6,11 These findings underscore the critical importance of recognizing and addressing anemia as a UF-related symptom.
Additional UF symptoms include pain, bulk symptoms such as pelvic pressure and increased urination frequency or volume, and infertility.3,12, 13, 14 Iron-deficiency anemia can exacerbate symptom burden, leading to fatigue, lack of energy, and weakness.15 Women with UF also report psychological distress, feelings of helplessness, negative body image and sexuality, and lack of support.16
Despite high prevalence and significant symptom burden in women with UF, results of a survey of US women suggest that at-risk women may not seek appropriate medical treatment.17 Delay in care may result from lack of knowledge,18 stigma,16 normalization of symptoms, or lack of access to healthcare.17,18 Additionally, there can be a significant gap between the onset of symptoms and a formal diagnosis, even among women who do seek care. In a cross-sectional survey of US women, respondents averaged ∼3.6 years before seeking treatment for UF, with 32% waiting more than 5 years.19 Evidence from a separate survey of US women also suggests that women who experience the most severe symptoms and lowest quality of life are those without a clinical diagnosis.17
Treatment options for UF include expectant management, pharmacotherapy, and interventional and surgical procedures.20 The American College of Obstetricians and Gynecologists recommend an individualized treatment approach that involves shared decision-making, balancing patient symptom burden and treatment goals with risks of treatment options.20 Pharmacologic options include hormonal contraceptives, tranexamic acid, gonadotropin-releasing hormone (GnRH) agonists,20 and newer therapies such as GnRH antagonists in combination with estradiol and norethindrone acetate, which have been approved by the US Food & Drug Administration (FDA) for the treatment of UF-associated HMB.21,22 In particular, recent clinical studies evaluating GnRH antagonists in combination with estradiol and norethindrone acetate demonstrated reduction in HMB23,24 and anemia23 in women with UF. For women with anemia, the American Society of Hematology recommends identifying and treating the underlying cause of iron-deficiency anemia.25 Depending on the identified underlying cause, treatment might involve addressing dietary history, managing medical conditions with medication, or interventions to stop bleeding sources,25,26 which may contribute to increased HCRU and costs.6
The additional incremental burden of HMB and anemia in women with UF and associated costs of care remain unclear. Limited data are available on the prevalence of anemia in women with UF, with or without HMB. The objective of this retrospective observational study was to describe the clinical burden of anemia and HMB in women diagnosed with UF and overall cost of care associated with the additional incremental burden of both anemia and HMB in UF.
Materials and methods
Study design and patient identification
This study used Merative MarketScan Commercial Database claims data from October 1, 2015, to June 30, 2022. The study included women who were 18–55 years old with newly diagnosed UF, defined as ≥1 inpatient claim for UF or ≥2 nondiagnostic outpatient claims for UF occurring ≥30 days apart. The first qualifying UF claim served as the index date. Preindex was defined as the 12 months before the first qualifying UF claim (index), during which baseline characteristics and medical history were assessed. Postindex was defined as the 12 months after the first qualifying UF claim (index). Treatments, HCRU, and costs were assessed in preindex and postindex periods. Individuals with claims for UF during the preindex period were excluded as they represented prevalent UF cases. Eligible women with UF were categorized into cohorts based on the presence and order of HMB claims: UF only, UF then HMB (UF-HMB), and HMB then UF (HMB-UF). To control for age-related confounding, eligible women in each UF cohort were matched 1:1:1 by age, resulting in final UF cohorts of equal size. A control (non-UF/non-HMB) cohort was identified, which included women with no claims for UF or HMB during the study period and was matched 5:1 to the 3 UF cohorts by age. The index date for the control cohort was a random obstetrics/gynecology visit occurring during the same period as the UF cohort date (Figure 1). All women were required to have continuous medical and pharmacy eligibility and no claims for malignancy other than non-melanoma skin cancer during preindex and postindex periods. Women in UF and control cohorts were further classified into 4 categories based on presence of anemia: (1) anemia occurring preindex, (2) anemia occurring postindex, (3) anemia occurring postindex only (ie, newly diagnosed; a subset of those with postindex anemia), and (4) no anemia postindex.
Figure 1.
Study design. The study period was defined as October 1, 2015, to June 30, 2022. Women were selected and categorized into cohorts based on the presence and order of HMB claims or as control during the patient section window (October 1, 2016, to June 30, 2021). The index date was defined as the date of the first UF claim for the UF cohorts and a random OB/GYN visit date for the control cohort. HMB, heavy menstrual bleeding; OB/GYN, obstetrics and gynecology; UF, uterine fibroids.
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
Outcomes and statistical analysis
Demographics and clinical characteristics were assessed at index. Study outcomes were reported preindex and postindex. Outcomes assessed included UF-related comorbid conditions, UF-related symptoms, treatment characteristics, and UF-related procedures. All-cause and gynecology-related HCRU (inpatient visits, emergency room [ER] visits, outpatient office visits, other outpatient services, and outpatient pharmacy claims) and costs were assessed. Cost outcomes were based on the paid amounts of adjudicated claims. Gynecology-related HCRU and costs were identified based on presence of a gynecology-related diagnosis code on the claim line.
All outcomes were defined via International Classification of Diseases, 10th Revision, Clinical Modification codes; Current Procedural Terminology 4th edition codes; Healthcare Common Procedure Coding System codes; or National Drug Codes appearing in the administrative claims record (Supplemental Tables 1-3). This study used deidentified patient records and therefore did not require Institutional Review Board approval. Chi-square or Fisher’s exact test (categorical variables) and t-test (continuous variables) were used to compare differences in outcomes between the 3 UF cohorts and the control cohort.
Results
Cohort selection and characteristics
The study included 22,057 women in each UF cohort and 110,285 women in the control cohort (Figure 2). Demographics at index were well balanced with respect to age and clinical characteristics (Table 1). Overall mean (SD) age was 43.5 (5.9) years. All cohorts had a Charlson comorbidity index (CCI) score of 0.2–0.3 at baseline. Hypertension (range: 14.5%‒28.0%), obesity (13.7%‒27.0%; Table 2), chronic pulmonary disease (7.3%‒10.2%), and mild or moderate diabetes (4.5%‒10.1%; Table 1) were the most common preindex comorbid conditions.
Figure 2.
Patient attrition. HMB, heavy menstrual bleeding; UF, uterine fibroids.
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
Table 1.
Patient demographics and preindex (before the first UF Claim) clinical characteristicsa for women with UF with and without HMB and women in a control cohort from the Merative MarketScan commercial database.
| Characteristic | UF only |
UF-HMB |
HMB-UF |
Control |
||||
|---|---|---|---|---|---|---|---|---|
| Anemia n=3163 |
No anemia n=18,894 |
Anemia n=7059 |
No anemia n=14,998 |
Anemia n=7791 |
No anemia n=14,266 |
Anemia n=4863 |
No anemia n=105,422 |
|
| Mean (SD) age, y | 43.0 (5.7) | 43.6 (6.0) | 43.5 (5.6) | 43.5 (6.1) | 43.7 (5.6) | 43.4 (6.1) | 42.8 (6.3) | 43.6 (5.9) |
| Age category, y, n (%) | ||||||||
| 18-25 | 10 (0.3) | 59 (0.3) | 14 (0.2) | 55 (0.4) | 22 (0.3) | 47 (0.3) | 17 (0.4) | 328 (0.3) |
| 26-35 | 335 (10.6) | 1847 (9.8) | 633 (9.0) | 1549 (10.3) | 621 (8.0) | 1561 (10.9) | 688 (14.2) | 10,222 (9.7) |
| 36-45 | 1632 (51.6) | 9019 (47.7) | 3534 (50.1) | 7117 (47.5) | 3859 (49.5) | 6792 (47.6) | 2304 (47.4) | 50,951 (48.3) |
| 46-55 | 1186 (37.5) | 7969 (42.2) | 2878 (40.8) | 6277 (41.9) | 3289 (42.2) | 5866 (41.1) | 1854 (38.1) | 43,921 (41.7) |
| Mean (SD) proportion of county-level raceb | ||||||||
| Non-Hispanic Black | 21.3 (15.4) | 17.8 (14.8) | 20.2 (15.2) | 17.5 (14.7) | 20.0 (15.3) | 17.4 (14.6) | 21.0 (15.8) | 18.2 (14.9) |
| Non-Hispanic White | 51.3 (20.0) | 55.2 (21.0) | 53.0 (20.2) | 56.5 (21.0) | 53.9 (20.2) | 57.4 (20.7) | 55.3 (20.4) | 58.6 (20.2) |
| Hispanic | 18.4 (16.6) | 17.8 (16.4) | 18.3 (16.7) | 17.5 (16.1) | 17.7 (16.5) | 16.8 (15.7) | 16.1 (15.6) | 15.3 (14.6) |
| Asian | 6.6 (6.8) | 6.7 (7.2) | 6.1 (6.4) | 6.1 (6.7) | 5.9 (6.2) | 5.8 (6.3) | 5.3 (5.5) | 5.5 (5.9) |
| Native Hawaiian/Other Pacific Islander | 0.2 (0.3) | 0.2 (0.2) | 0.2 (0.2) | 0.2 (0.2) | 0.2 (0.2) | 0.2 (0.3) | 0.2 (0.2) | 0.2 (0.2) |
| American Indian & Alaska Native | 0.8 (0.7) | 0.9 (1.3) | 0.8 (1.3) | 0.9 (1.2) | 0.9 (1.5) | 0.9 (1.1) | 0.8 (1.2) | 0.8 (1.4) |
| Region, n (%) | ||||||||
| South | 1896 (59.9) | 10,099 (53.5) | 4370 (61.9) | 8396 (56.0) | 4653 (59.7) | 7867 (55.2) | 2973 (61.1) | 60,170 (57.1) |
| North Central | 484 (15.3) | 3105 (16.4) | 1033 (14.6) | 2412 (16.1) | 1349 (17.3) | 2642 (18.5) | 787 (16.2) | 20,007 (19.0) |
| Northeast | 346 (10.9) | 2350 (12.4) | 728 (10.3) | 1664 (11.1) | 651 (8.4) | 1313 (9.2) | 688 (14.2) | 12,606 (12.0) |
| West | 437 (13.8) | 3340 (17.7) | 928 (13.2) | 2526 (16.8) | 1138 (14.6) | 2444 (17.1) | 415 (8.5) | 12,639 (12.0) |
| Insurance type, n (%) | ||||||||
| EPO/PPO | 1420 (44.9) | 8676 (45.9) | 3300 (46.8) | 7052 (47.0) | 3604 (46.3) | 6729 (47.2) | 2451 (50.4) | 51,294 (48.7) |
| CDHP/HDHP | 750 (23.7) | 5045 (26.7) | 1611 (22.8) | 3703 (24.7) | 1848 (23.7) | 3560 (25.0) | 1065 (21.9) | 27,563 (26.2) |
| HMO | 627 (19.8) | 3438 (18.2) | 1242 (17.6) | 2541 (16.9) | 1434 (18.4) | 2518 (17.7) | 696 (14.3) | 14,858 (14.1) |
| POS | 215 (6.8) | 999 (5.3) | 581 (8.2) | 1109 (7.4) | 555 (7.1) | 887 (6.2) | 418 (8.6) | 7879 (7.5) |
| Comprehensive/indemnity | 90 (2.9) | 478 (2.5) | 168 (2.4) | 317 (2.1) | 186 (2.4) | 330 (2.3) | 120 (2.5) | 2005 (1.9) |
| Other/unknown | 61 (1.9) | 258 (1.4) | 157 (2.2) | 276 (1.8) | 164 (2.1) | 242 (1.7) | 113 (2.3) | 1823 (1.7) |
| Mean (SD) preindex CCI score | 0.3 (0.8) | 0.2 (0.6) | 0.3 (0.8) | 0.2 (0.6) | 0.3 (0.8) | 0.2 (0.6) | 0.5 (1.1) | 0.2 (0.6) |
| Preindex CCI conditions in ≥2% of women in any cohort, n (%) | ||||||||
| Chronic pulmonary disease | 275 (8.7) | 1495 (7.9) | 604 (8.6) | 1300 (8.7) | 798 (10.2) | 1268 (8.9) | 480 (9.9) | 7690 (7.3) |
| Diabetes (mild or moderate) | 210 (6.6) | 968 (5.1) | 489 (6.9) | 768 (5.1) | 571 (7.3) | 742 (5.2) | 489 (10.1) | 4789 (4.5) |
| Mild liver disease | 68 (2.2) | 302 (1.6) | 95 (1.4) | 212 (1.4) | 130 (1.7) | 203 (1.4) | 113 (2.3) | 1252 (1.2) |
| Rheumatic disease | 67 (2.1) | 302 (1.6) | 128 (1.8) | 272 (1.8) | 172 (2.2) | 262 (1.8) | 201 (4.1) | 1931 (1.8) |
| Renal disease | 54 (1.7) | 123 (0.7) | 87 (1.2) | 93 (0.6) | 93 (1.2) | 85 (0.6) | 133 (2.7) | 621 (0.6) |
| Diabetes with chronic complications | 52 (1.6) | 173 (0.9) | 95 (1.4) | 116 (0.8) | 105 (1.4) | 122 (0.9) | 126 (2.6) | 844 (0.8) |
CCI, Charlson comorbidity index; CDHP, consumer-directed health plan; EPO, exclusive provider organization; HDHP, high-deductible health plan; HMB, heavy menstrual bleeding; HMO, health maintenance organization; POS, point of service; PPO, preferred provider organization; UF, uterine fibroid; USD, US dollar.
Anemia and no anemia patient numbers shown are based on the presence of postindex anemia diagnoses
Race is not available in the MarketScan Commercial Database; therefore, county-level race data were obtained from the Robert Wood Johnson Foundation (RWJF) County Health Rankings. This publicly available dataset provides social determinants of health (eg, race, income level, healthcare access) for almost every US county from national sources, including the National Center for Health Statistics, Center for Disease Control’s Behavioral Risk Factor Surveillance System, the American Community Survey, and the USDA Food Environment Atlas. Patients were linked to their county of residence in RWJF dataset using ZIP code and county-state identifiers at the index date. Race was reported as the proportion of the county population identifying with each racial group.
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
Table 2.
Preindex (before the first UF claim) and postindex comorbidities and UF symptomsa for women with UF with and without HMB and women in a control cohort from the Merative MarketScan commercial database.
| Comorbidity or symptom, n (%) | UF only |
UF-HMB |
HMB-UF |
Control |
||||
|---|---|---|---|---|---|---|---|---|
| Anemia n=3163 |
No anemia n=18,894 |
Anemia n=7059 |
No anemia n=14,998 |
Anemia n=7791 |
No anemia n=14,266 |
Anemia n=4863 |
No anemia n=105,422 |
|
| Preindex period | ||||||||
| Comorbidities of interest occurring in >1% of any cohort | ||||||||
| Hypertension | 753 (23.8) | 3459 (18.3) | 1676 (23.7) | 2919 (19.5) | 2183 (28.0) | 3010 (21.1) | 1172 (24.1) | 15,286 (14.5) |
| Obesity | 659 (20.8) | 3081 (16.3) | 1454 (20.6) | 2637 (17.6) | 2100 (27.0) | 3089 (21.7) | 1117 (23.0) | 14,406 (13.7) |
| Endometriosis | 45 (1.4) | 309 (1.6) | 51 (0.7) | 191 (1.3) | 160 (2.1) | 354 (2.5) | 48 (1.0) | 568 (0.5) |
| UF symptom | ||||||||
| Bulk symptoms | 1373 (43.4) | 8226 (43.5) | 2646 (37.5) | 6305 (42.0) | 3675 (47.2) | 7293 (51.1) | 1888 (38.8) | 32,605 (30.9) |
| Abdominal distension | 187 (5.9) | 968 (5.1) | 229 (3.2) | 560 (3.7) | 298 (3.8) | 560 (3.9) | 130 (2.7) | 1671 (1.6) |
| Backache | 513 (16.2) | 3048 (16.1) | 1029 (14.6) | 2501 (16.7) | 1188 (15.3) | 2450 (17.2) | 862 (17.7) | 14,930 (14.2) |
| Constipation | 161 (5.1) | 735 (3.9) | 283 (4.0) | 514 (3.4) | 388 (5.0) | 562 (3.9) | 232 (4.8) | 2733 (2.6) |
| Leg pain | 196 (6.2) | 1202 (6.4) | 458 (6.5) | 991 (6.6) | 555 (7.1) | 1027 (7.2) | 372 (7.7) | 6417 (6.1) |
| Pelvic pressure/pain | 735 (23.2) | 4391 (23.2) | 1226 (17.4) | 3135 (20.9) | 2071 (26.6) | 4442 (31.1) | 792 (16.3) | 11,148 (10.6) |
| Urinary frequency/incontinence | 241 (7.6) | 1576 (8.3) | 470 (6.7) | 1243 (8.3) | 691 (8.9) | 1478 (10.4) | 426 (8.8) | 7195 (6.8) |
| Anemia | 1011 (32.0) | 733 (3.9) | 2379 (33.7) | 799 (5.3) | 4254 (54.6) | 1297 (9.1) | 1584 (32.6) | 2186 (2.1) |
| Fatigue | 328 (10.4) | 1572 (8.3) | 716 (10.1) | 1362 (9.1) | 1143 (14.7) | 1694 (11.9) | 660 (13.6) | 8509 (8.1) |
| Postindex period | ||||||||
| Comorbidities of interest occurring in >1% of any cohort | ||||||||
| Hypertension | 988 (31.2) | 4020 (21.3) | 2292 (32.5) | 3618 (24.1) | 2663 (34.2) | 3534 (24.8) | 1368 (28.1) | 16,766 (15.9) |
| Obesity | 899 (28.4) | 3985 (21.1) | 2271 (32.2) | 3590 (23.9) | 2751 (35.3) | 3778 (26.5) | 1487 (30.6) | 17,665 (16.8) |
| Endometriosis | 232 (7.3) | 1468 (7.8) | 1045 (14.8) | 2255 (15.0) | 1312 (16.8) | 2311 (16.2) | 78 (1.6) | 939 (0.9) |
| UF symptom | ||||||||
| Bulk symptoms | 1775 (56.1) | 10,229 (54.1) | 4475 (63.4) | 9671 (64.5) | 4577 (58.8) | 8388 (58.8) | 2287 (47.0) | 35,992 (34.1) |
| Abdominal distension | 234 (7.4) | 1122 (5.9) | 400 (5.7) | 779 (5.2) | 344 (4.4) | 606 (4.3) | 176 (3.6) | 1855 (1.8) |
| Backache | 522 (16.5) | 3176 (16.8) | 1076 (15.2) | 2625 (17.5) | 1260 (16.2) | 2493 (17.5) | 984 (20.2) | 15,478 (14.7) |
| Constipation | 213 (6.7) | 946 (5.0) | 505 (7.2) | 765 (5.1) | 548 (7.0) | 699 (4.9) | 306 (6.3) | 3036 (2.9) |
| Leg pain | 263 (8.3) | 1245 (6.6) | 521 (7.4) | 1093 (7.3) | 601 (7.7) | 1056 (7.4) | 443 (9.1) | 6826 (6.5) |
| Pelvic pressure/pain | 1172 (37.1) | 6776 (35.9) | 3396 (48.1) | 7440 (49.6) | 3297 (42.3) | 5891 (41.3) | 1051 (21.6) | 13,088 (12.4) |
| Urinary frequency/ incontinence | 349 (11.0) | 2126 (11.3) | 892 (12.6) | 1998 (13.3) | 904 (11.6) | 1794 (12.6) | 518 (10.7) | 8732 (8.3) |
| Anemia | 3163 (100) | 0 | 7059 (100) | 0 | 7791 (100) | 0 | 4863 (100) | 0 |
| Fatigue | 440 (13.9) | 1595 (8.4) | 1011 (14.3) | 1483 (9.9) | 1136 (14.6) | 1396 (9.8) | 776 (16.0) | 8980 (8.5) |
HMB, heavy menstrual bleeding; UF, uterine fibroid.
Anemia and no anemia patient numbers shown are based on the presence of postindex anemia diagnoses.
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
UF-related comorbidity and symptom rates were higher in the UF cohorts than the control cohort (Table 2). A significantly greater percentage of women in the UF cohorts had hypertension (P<.001) or obesity (P<.001) preindex and postindex compared with the control cohort. Preindex (ie, before UF diagnosis), bulk symptoms were present in 40.6% to 49.7% of women in UF cohorts compared with 31.3% in the control cohort. Pelvic pain/pressure was the predominant bulk symptom across all UF cohorts, and rates increased from the preindex to postindex period in all cohorts.
Anemia diagnosis
The prevalence of anemia was higher in the UF with HMB cohorts compared with UF only and control cohorts. Preindex anemia rates were 14.4% in the UF-HMB cohort and 25.2% in the HMB-UF cohort compared with 7.9% in the UF only cohort and 3.4% in the control cohort. Postindex, anemia prevalence increased across all groups, reaching 32.0% in the UF-HMB cohort, 35.3% in the HMB-UF cohort, 14.4% in the UF only cohort, and 4.4% in the control cohort (Figure 3). Of women with postindex only anemia diagnoses, 68.0%, 66.3%, and 45.4% were newly diagnosed with anemia after UF diagnosis (ie, did not have anemia preindex) in the UF only, UF-HMB, and HMB-UF cohorts, respectively.
Figure 3.
Anemia diagnosis preindex vs postindex in the UF and control cohorts. Hatched regions and associated percentages represent the percentage of patients in each cohort with a postindex only anemia diagnosis (ie, newly diagnosed after UF diagnosis). HMB, heavy menstrual bleeding; UF, uterine fibroids.
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
Treatment patterns
Pharmacologic therapy
Postindex, oral contraception prescriptions increased across all UF cohorts (Supplemental Figure 1); women in the UF-HMB cohort with anemia demonstrated the most pronounced rise, from 9.3% preindex to 18.2% postindex. The prescription of GnRH agonist or antagonist increased from preindex to postindex across all 3 UF cohorts for women with and without anemia (Supplemental Figures 2), albeit at low absolute rates; the greatest increases were observed in women with anemia in the UF-HMB cohort from 0.2% preindex to 4.0% postindex. Utilization of tranexamic acid, an antifibrinolytic agent, rose among women with anemia (Supplemental Figure 3). For example, tranexamic acid use in the UF-HMB cohort with anemia increased from 1.5% preindex to 8.7% postindex. Although the use of pharmacologic therapies increased, a considerable proportion of women (13%–39%) in UF cohorts received no pharmacologic therapy of interest (Supplemental Figure 4). Prescription pain medication use also increased across all cohorts from preindex to postindex (Supplemental Figure 5).
Postindex UF-related procedures
Overall, >50% of women in UF cohorts had ≥1 surgical/gynecologic procedure, postindex. Among therapeutic procedures, hysterectomy was most common (range: 11%–34%) (Table 3). Ultrasound was used frequently postindex across all cohorts with UF (range: 54.9%–74.3%). A greater percentage of women in the UF-HMB and HMB-UF cohorts had a UF-related procedure postindex compared with the UF only cohort (44.3% and 47.0% vs 16.2%, respectively). Among women with anemia, rates of hysterectomy were higher, particularly in UF-HMB (37.8%) and HMB-UF (40.8%) cohorts compared with the UF only cohort (13.4%).
Table 3.
Postindex (after the first UF claim) medical procedures in women with UF with and without anemiaa from the Merative MarketScan commercial database.
| UF-related procedure, n (%) | UF only |
UF-HMB |
HMB-UF |
|||
|---|---|---|---|---|---|---|
| Anemia n=3163 |
No anemia n=18,894 |
Anemia n=7059 |
No anemia n=14,998 |
Anemia n=7791 |
No anemia n=14,266 |
|
| Ultrasound | 1609 (50.9) | 11,271 (59.7) | 5279 (74.8) | 11,108 (74.1) | 4298 (55.2) | 7817 (54.8) |
| Endometrial ablation | 11 (0.4) | 61 (0.3) | 390 (5.5) | 695 (4.6) | 702 (9.0) | 1066 (7.5) |
| Hysterectomy | 425 (13.4) | 2091 (11.1) | 2666 (37.8) | 4216 (28.1) | 3178 (40.8) | 4316 (30.3) |
| Myomectomy | 203 (6.4) | 760 (4.0) | 804 (11.4) | 1373 (9.2) | 1075 (13.8) | 1473 (10.3) |
| Uterine artery ablation | 40 (1.3) | 139 (0.7) | 289 (4.1) | 354 (2.4) | 307 (3.9) | 225 (1.6) |
| Radiofrequency ablation | 3 (0.1) | 4 (0.0) | 15 (0.2) | 19 (0.1) | 16 (0.2) | 8 (0.1) |
| Blood transfusion | 56 (1.8) | 6 (0.0) | 558 (7.9) | 16 (0.1) | 445 (5.7) | 5 (0.0) |
HMB, heavy menstrual bleeding; UF, uterine fibroid.
Anemia and no anemia patient numbers shown are based on the presence of postindex anemia diagnoses.
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
HCRU and costs
HCRU and costs were higher in UF cohorts compared with the control cohort. Preindex to postindex increases in inpatient admissions were greater for UF only (2.9% to 19.5%, respectively), UF-HMB (2.7% to 17.0%), and HMB-UF (3.2% to 18.6%) cohorts vs the control cohort (3.2% to 8.7%) (Figure 4). Increases were more pronounced for women with anemia across all cohorts (Supplemental Figure 6). Women with anemia had higher rates of postindex ER visits than those without anemia.
Figure 4.
Rates of HCRU claims among women with vs without UF. ER, emergency room; HMB, heavy menstrual bleeding; UF, uterine fibroids.
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
Postindex, total all-cause costs were significantly higher in UF cohorts (range: $16,491–$21,993; P<.001) vs the control cohort ($9355) (Figure 5A). Obstetrics/gynecology-related total costs were significantly higher postindex in UF vs control cohorts (range: $3896–$10,651 vs $505; P<.001). UF-HMB and HMB-UF cohorts had the highest overall costs, with all-cause costs at $21,119 and $21,993, respectively, and obstetrics/gynecology-related costs at $10,049 and $10,651, respectively. All-cause and obstetrics/gynecology-related total costs doubled from preindex to postindex for all UF cohorts. Outpatient costs accounted for >50% of total costs for all UF cohorts both preindex and postindex. All-cause and obstetrics/gynecology-related total costs were generally higher in women with anemia in all cohorts compared with women without anemia in all cohorts both preindex and postindex (Supplemental Figures 7 and 8).
Figure 5.
(A) All-cause and (B) obstetrics/gynecology-specific per-patient healthcare costs. Values in bold indicate total (inpatient + outpatient + pharmacy) costs for each cohort. *P<.01 for UF vs control cohorts (total costs). **P<.001 for UF vs control cohorts (total costs).
McKain. Burden of anemia in women with uterine fibroid-associated heavy menstrual bleeding. AJOG Glob Rep 2026.
Comment
Principal findings
This analysis demonstrates that anemia is particularly common in women who have UF who are symptomatic with HMB. Following the diagnosis of UF accompanied by anemia, women exhibited a higher propensity for undergoing treatments, notably invasive procedures, with hysterectomy being a predominant choice. Women with a UF diagnosis, with or without HMB or anemia, had significantly higher all-cause and obstetrics/gynecology-related costs than women without a UF diagnosis, with the combined presence of HMB and anemia amplifying the clinical and economic burden compared with UF alone.
Results in the context of what is known
Women with UF experience distressing symptoms, including pain, HMB, and bulk symptoms,2,3,16,27 that can negatively impact quality of life2,17 and may require treatment. Women with UF and HMB also experience high rates of anemia,6 which can further contribute to symptom burden.15 Our analysis adds to existing evidence of high symptom burden associated with UF and the additional burden that comes with HMB and anemia.
Few studies have evaluated the prevalence of anemia in women with UF and HMB.6,27,28 In agreement with a prior retrospective analysis that demonstrated greater symptom burden, including anemia, in women with UF and HMB compared with women with UF only,27 our study also found higher rates of anemia in women with UF and HMB vs UF alone. This contrasts with another retrospective analysis in which anemia prevalence was as high as 75% in women with various types of UF but did not correlate with HMB.28 Notably, our analysis revealed that anemia was frequently identified before the diagnosis of UF or HMB, suggesting that routine detection of anemia through laboratory tests may prompt further clinical evaluation. Alternatively, UF and HMB may be undetected until symptoms are severe, suggesting that screening for HMB could be beneficial for earlier anemia and UF diagnosis.
Treatment and management of anemia includes iron supplementation (oral or intravenous) and, in more extreme cases, blood transfusions.25,26 Unsurprisingly, and in line with a prior study,6 our analysis shows higher rates of blood transfusions in women with anemia compared with those without anemia. Although a study by Morrison et al6 did not observe higher rates of hysterectomy in women with HMB and anemia, this analysis and the analysis by McKain et al27 demonstrated higher rates of hysterectomy in women with UF with HMB compared with UF alone.27 Higher rates of blood transfusions and hysterectomy may partially explain the increased rates of ER visits and inpatient admissions in the UF cohorts of women with anemia compared with those without, as suggested by our analysis.
A comparative cost analysis estimated that the economic burden of UF in the US increased from $34.4 billion in 2010 to $42.2 billion in 2022, driven in part by increased costs of surgical management.29 In the current study, UF with HMB was associated with both increased all-cause and obstetrics/gynecology-related healthcare costs. Higher rates of anemia, hysterectomies, and blood transfusions in the cohorts of women with HMB suggest that these outcomes may account for the increased cost of care for these cohorts. Indeed, women with anemia in all cohorts had higher all-cause and obstetrics/gynecology-related healthcare costs compared with women without anemia. These results are consistent with results from Morrison et al,6 which showed that the cost of hospitalization was over 13% higher for women with anemia compared with those without anemia, primarily due to additional services required during hospitalization.
Clinical implications
Our analysis revealed a pattern in the timing of anemia recognition, with most diagnoses in the UF-HMB cohort and nearly half in the HMB-UF cohort occurring only after the diagnosis of UF. This suggests that anemia may often go unnoticed by clinicians until symptoms become severe. Potential contributing factors include clinicians not routinely screening menstruating women for anemia, failing to inquire about the heaviness of menstrual cycles, or societal normalization of symptoms causing women to underreport or dismiss them. These findings highlight the need for increased vigilance in evaluating both anemia and menstrual symptoms to enable earlier diagnosis and intervention.
Research implications
Our study provides a descriptive analysis of the effects of anemia on HCRU and costs for UF cohorts; however, additional analyses are warranted to further inform these results. Further research is needed to understand how various treatments for UF-associated HMB affect clinical and economic burden. In the phase 3 UF-1 and UF-2 trials, twice-daily elagolix combination therapy (elagolix 300 mg, estradiol 1 mg, norethindrone acetate 0.5 mg) reduced HMB in women with UF-associated HMB and improved anemia.24 In the international, phase 3 LIBERTY clinical trials and extension studies, once-daily relugolix combination therapy (relugolix 40 mg, estradiol 1 mg, norethindrone acetate 0.5 mg) in women with UF and HMB also decreased HMB and improved anemia and health-related quality of life compared with placebo.23,30, 31, 32 In our analysis, prescriptions for GnRH agonists and antagonists were relatively low compared with other treatment options, potentially owing to the relatively recent FDA approvals. Future studies should investigate whether these therapies reduce reliance on surgical interventions, lower HCRU, and improve cost-effectiveness in real-world settings. Moreover, understanding patient and clinician factors influencing the adoption of these therapies—including adherence, tolerability, and equity in access—could further inform strategies to optimize care for women with UF and HMB.
Strengths and limitations
Strengths include the large sample size and cohort matching, which minimized demographic differences between cohorts at baseline. Limitations include those inherent to retrospective claims analysis as they are descriptive in nature, which limits conclusions regarding causality. Owing to slight imbalances between UF and control cohorts in non-Black races, region of residence, and health plan type that remained after matching, our analysis was unable to evaluate differences related to race, region, and health plan type. The study was limited to women with commercial health coverage; therefore, results may not be generalizable to those with other insurance types or without healthcare coverage. Owing to the nature of retrospective studies and claims data, access to specific information may be limited. Methods of diagnosis were not assessed, and how diagnoses were derived from images was unavailable in the claims database. Additionally, the absence of detailed clinical characteristics, such as lesion size, numbers, or FIGO classification may limit the interpretation of findings, as certain UF characteristics may not be clinically associated with HMB. Claims data may be subject to coding errors leading to potential misclassification owing to billing processes and administrative claims being the primary source of collection as opposed to medical records. Recognition of HMB and/or anemia may also be influenced by diagnosis bias after imaging findings or during preoperative evaluation. Although a 12-month period without a UF claim was imposed before index to increase the certainty that the index date represented the first UF diagnosis, without full medical histories, we cannot exclude the possibility that women had prior UF claims >1 year before index.
Conclusions
These findings emphasize the importance of recognizing signs and symptoms that may lead to the diagnosis of UF. Early recognition and detection of UF may allow for earlier treatment that can alleviate related conditions such as HMB and anemia before they become severe. This study highlights potential gaps in both patient and provider awareness, emphasizing the value of inquiries about menstrual health and the necessity of appropriate screening for anemia. Ongoing efforts in patient and provider education and discussions around shared decision-making are essential to improving outcomes and addressing the clinical and economic burdens of UF-related conditions.
Data availability statement
The data that support the findings of this study are available from Merative via a license, which includes terms and conditions around its appropriate use and licensing fees.
CRediT authorship contribution statement
Laura McKain: Writing – review & editing, Writing – original draft, Conceptualization. Brenna L. Brady: Writing – review & editing, Formal analysis, Data curation, Conceptualization. Anh Thu Tran: Writing – review & editing, Formal analysis, Data curation, Conceptualization. Cassandra Lickert: Writing – review & editing, Project administration, Conceptualization.
Acknowledgments
Medical writing support was provided by Heather Caballes, PhD, CMPP, from Citrus Health Group, Inc., company (Chicago, IL), and was funded by Sumitomo Pharma America, Inc. (Marlborough, MA).
Footnotes
This study used deidentified patient records and therefore did not require Institutional Review Board approval or patient consent.
Disclosures: Laura McKain is an employee of McKain Consulting, LLC, and has received consulting fees from CooperSurgical, Evestra, Inc., Evofem Biosciences, Inc., Gen-Probe, Medicines360, and Sumitomo Pharma America, Inc. Brenna L. Brady and Anh Thu Tran are employees of Merative. Cassandra Lickert is an employee of Sumitomo Pharma America, Inc.
This study was funded by Sumitomo Pharma America, Inc. (Marlborough, MA).
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.xagr.2026.100652.
Appendix. Supplementary materials
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from Merative via a license, which includes terms and conditions around its appropriate use and licensing fees.