Improvement in health‑related quality of life in patients with heavy menstrual bleeding after treatment and its association with hereditary bleeding disorders.

A total of 100 premenopausal women with HMB without organic gynecological pathology were prospectively recruited. The average age of the sample was 27 years and the mean age of menarche was 12 years. The PBAC and ISTH-BAT scores, along with hemoglobin levels, basic coagulation test results, and iron metabolism values, are summarized in Table 1 . We found that 31 women had HMB secondary to a hemostatic disorder. The most common entity in our series was platelet dysfunction ( n  = 11). Among the 69 women with non-structural non-heavy menstrual bleeding, classification was performed according to the PALM-COEIN system. Cases were categorized as not yet classified, defined as bleeding that does not fit into any of the established categories. Table 1 Clinical characteristics (mean and SD, or frequency) Characteristic Value Age (years) 27.95 (11.38) Age at menarche (years) 12.16 (1.40) Menstrual bleeding duration (days) 7.63 (4.09) PBAC score 351 (259) ISTH BAT score 4.05 (1.77) Hemoglobin levels (g/dL)  13.37 (1.37) Hematocrit (%) 39.41 (3.45) Platelet count (x10 9 /L) 259 (62) Ferritin levels (ng/mL) 25.32 (30.56) Cause of HMB Non-bleeding disorder 69 (69%) Hemostatic disorder 31 (31%)  Definitive platelet dysfunction 11  Hypermobility spectrum disorders 6  Factor VII deficiency 3  von Willebrand disease 2  Hypofibrinogenemia 2  Factor XIII deficiency 1  Noonan Syndrome 1  Bleeding disorder of unknown cause 5 Treatment (%)  Combined oral contraceptives  43  Levonorgestrel IUD  14  Tranexamic acid 7  Contraceptive vaginal ring  5  Oral iron  14  Intravenous iron   2  Other 3  None 12 Values are means and standard deviations, or frequencies (and percentages). PBAC Pictorial Blood Assessment Chart, ISTH International Society on Thrombosis and Haemostasis, HMB Heavy menstrual bleeding, IUD Intrauterine device Clinical characteristics (mean and SD, or frequency) Values are means and standard deviations, or frequencies (and percentages). PBAC Pictorial Blood Assessment Chart, ISTH International Society on Thrombosis and Haemostasis, HMB Heavy menstrual bleeding, IUD Intrauterine device Table  2 presents the SF-12 ® v2 health dimensions and summary scores for 100 participants. The mean Physical Component Summary (PCS) score was 60.0 ± 20.5, while the Mental Component Summary (MCS) score was 47.9 ± 14.2, indicating lower perceived mental health compared to physical functioning. Within individual dimensions, participants reported moderate scores for general health (61.5 ± 17.9 ) , energy/vitality (54.0 ± 23.4), and calm/peacefulness (62.6 ± 22.3). More pronounced limitations were observed in social functioning (27.2 ± 28.2) and feelings of being downhearted/blue (37.8 ± 23.9 ) , suggesting substantial psychosocial impact. Physical activity-related items such as moderate activities (47.5 ± 14.9) and climbing several flights of stairs (46.5 ± 16.3) also showed reduced performance. Table 2 SF-12®v2 Health Dimensions and Summary Scores (n=100) Questionnaire Mean SD SF-12 ® v2  General health 61.5 17.9  Moderate activities 47.5 14.9  Climb several flights of stairs 46.5 16.3  Accomplished less (physical) 62.0 48.8  Limited in kind of work 70.0 46.1  Pain - interference 50.0 50.3  Accomplished less (emotional) 56.0 49.9  Did work less carefully 72.3 26.8  Calm and peaceful 62.6 22.3  Energy or vitality 54.0 23.4  Downhearted and blue 37.8 23.9  Social limitations 27.2 28.2  PCS 60.0 20.5  MCS 47.9 14.2 SD Standard deviation, SF‑12®v2 Short Form‑12 Health Survey, version 2, PCS Physical Component Summary, MCS Mental Component Summary. SF-12®v2 Health Dimensions and Summary Scores (n=100) SD Standard deviation, SF‑12®v2 Short Form‑12 Health Survey, version 2, PCS Physical Component Summary, MCS Mental Component Summary. Table  3 presents the distribution of responses across the EQ-5D-3 L health dimensions, together with mean scores for the EQ-5D index, EQ VAS, MBQ, and SAMANTA questionnaires in our cohort of 100 participants. The majority of individuals reported no problems in mobility (84%) and self-care (98%), with only isolated cases of severe impairment. In contrast, usual activities showed a higher proportion of moderate limitations (23%), while pain/discomfort and anxiety/depression were more prevalent, with 41% and 37% of participants, respectively, reporting moderate problems, and 11% and 6% reporting severe problems. The mean EQ-5D index score was 0.82 ± 0.12, and the mean EQ VAS score was 72.5 ± 15.0, indicating an overall moderate-to-good perceived health status. However, menstrual bleeding burden was notable, with a mean MBQ score of 28.8 ± 10.5 and a SAMANTA score of 7.55 ± 2.20, reflecting significant impact of heavy menstrual bleeding on quality of life. Table 3 EQ 5D 3L Health Dimensions, MBQ and SAMANTA score (n=100) EQ‑5D‑3L Dimension Level 1 (No problems) Level 2 (Moderate) Level 3 (Severate) Mobility 84 16 0 Self‑Care 98 1 1 Usual Activities 76 23 1 Pain/Discomfort 48 41 11 Anxiety/Depression 57 37 6 Mean EQ‑5D Index score: 0.82 ± 0.12 Mean EQ‑VAS score: 72.5 ± 15.0 MBQ score: 28.8 ± 10.5 SAMANTA score: 7.55 ± 2.20 EQ‑5D‑3L EuroQol 5‑Dimension 3‑Level questionnaire, VAS Visual Analogue Scale, MBQ Menstrual Bleeding Questionnaire, SAMANTA questionnaire SAngrado Menstrual AbundaNTe en ginecología EQ 5D 3L Health Dimensions, MBQ and SAMANTA score (n=100) Mean EQ‑5D Index score: 0.82 ± 0.12 Mean EQ‑VAS score: 72.5 ± 15.0 MBQ score: 28.8 ± 10.5 SAMANTA score: 7.55 ± 2.20 EQ‑5D‑3L EuroQol 5‑Dimension 3‑Level questionnaire, VAS Visual Analogue Scale, MBQ Menstrual Bleeding Questionnaire, SAMANTA questionnaire SAngrado Menstrual AbundaNTe en ginecología Of the 100 patients included in the study, 88 (88%) required some type of treatment to control their HMB and/or treatment for anemia/iron deficiency. The most frequently used treatment was the combined hormonal contraceptive (43%), followed by the Levonorgestrel IUD (14%). Tranexamic acid was prescribed to control bleeding in seven patients who did not want hormonal treatment. Oral iron was necessary in 14% of women and the administration of intravenous iron was necessary in two patients due to their lack of tolerance to oral iron. Two patients had to be admitted due to bleeding; one required transfusion of two units of red blood cells, and the other was administered intravenous iron. Of the 88 patients enrolled who expressed willingness to initiate therapy, 68 maintained their initial regimen with good adherence and required no modifications. Eight patients discontinued treatment within the first three months of follow-up: one patient stopped oral iron therapy due to gastrointestinal intolerance, and seven patients discontinued combined hormonal contraceptives because of persistent breakthrough bleeding. In addition, 12 patients required treatment adjustments during the same period. Specifically, two patients switched to a different oral contraceptive formulation due to poor tolerance, five patients replaced oral iron therapy with a hormonal approach (one with an intrauterine device and four with combined hormonal contraceptives), and five patients transitioned from combined hormonal contraceptives to an intrauterine device based on personal preference and improved symptom control. All patients who underwent treatment modifications continued their scheduled follow-up visits at six months, maintaining the new regimens without significant adverse events. Of the 100 women enrolled in the study, 60 completed the questionnaires at baseline and at 6 months after treatment (i.e., a response rate of 60%). We observed a statistically significant mean reduction in the PBAC score after 6 months of follow-up (from 351 [SD, 259] to 176 [SD, 178], p  < 0.001). Also, at 6 months, 47 patients required repeated blood count testing and 43 had their iron profiles reevaluated due to deficiencies identified before treatment. Significant improvements were noted in the hematocrit ( p  = 0.028) and iron levels ( p  = 0.001), while hemoglobin and ferritin levels showed non-significant improvements (Table  4 ). Table 4 PBAC score and hematological parameters before (T0) and after (T6) treatment Parameter N Time Mean (SD) P PBAC score 100 T0 351 (259) <0.001 100 T6 176 (178) Hemoglobin (g/dL) 47 T0 13.34 (1.43) 0.814 47 T6 13.63 (3.20) Hematocrit (%) 47 T0 38.88 (3.47) 0.028 47 T6 39.75 (3.20) Platelets (x10 9 /L) 47 T0 263.8 (73.1) 0.392 47 T6 260.1 (77.0) Iron (mg/dL) 43 T0 65.79 (37.35) 0.001 43 T6 90.95 (46.48) Ferritin (ng/mL) 43 T0 21.35 (18.20) 0.061 43 T6 26.00 (17.90) Pretreatment (T0) and 6 months after treatment (T6); PBAC Pictorial Blood Assessment Chart PBAC score and hematological parameters before (T0) and after (T6) treatment Pretreatment (T0) and 6 months after treatment (T6); PBAC Pictorial Blood Assessment Chart Table  5 illustrates the comparison between SF-12 ® v2 scores at the time of initial consultation (T0), and at the 6-month (T6) follow-up appointments. T6 SF-12 ® v2 PCS and T6 SF-12 ® v2 MCS were significantly improved compared with pretreatment scores ( p  < 0.0001 and p  = 0.030, respectively). Of the 12 domains of the SF-12 ® v2, significant improvements were observed in five following treatment, indicated by higher scores in the domains of moderate activities, climb several flights of stairs, accomplished less (physical), limited in kind of work and pain-interference, reflecting better perceived health status. Table 5 Changes over time in SF 12®v2 domains SF-12 ® v2 and PCS/MCS Time Value P General health T0 58.3 (16.4) 0.709 T6 57.5 (21.7) Moderate activities T0 46.7 (15.6) <0.001 T6 86.7 (28.9) Climb several flights of stairs T0 45 (15.1) <0.001 T6 85.0 (29.5) Accomplished less (physical) T0 61.7 (49.0) 0.007 T6 80.0 (40.3) Limited in kind of work T0 68.3 (46.9) 0.045 T6 81.7 (39.0) Pain-interference T0 50.0 (50.4) 0.011 T6 66.7 (47.5) Accomplished less (emotional) T0 56.7 (50.0) 0.070 T6 68.3 (46.9) Did work less carefully T0 70.8 (27.7) 0.321 T6 74.2 (28.7) Calm and peaceful T0 63.0 (23.5) 0.604 T6 64.7 (24.8) Energy or vitality T0 53.0 (23.5) 0.261 T6 56.3 (23.7) Downhearted and blue T0 38.7 (24.7) 0.321 T6 35.7 (26.3) Social limitations T0 28.0 (29.3) 0.403 T6 24.7 (27.4) PCS T0 58.47 (21.0) <0.001 T6 77.50 (23.36) MCS T0 48.22 (14.61) 0.030 T6 52.72 (16.10) Pretreatment (T0) and 6 months after treatment (T6). SF‑12®v2: Short Form‑12 Health Survey, version 2; PCS Physical Component Summary, MCS Mental Component Summary Changes over time in SF 12®v2 domains Pretreatment (T0) and 6 months after treatment (T6). SF‑12®v2: Short Form‑12 Health Survey, version 2; PCS Physical Component Summary, MCS Mental Component Summary Table  6 shows the comparison of all EQ-D5-3 L domains between pretreatment (T0) and 6 months after treatment (T6). After 6 months of treatment, significant improvements were observed in the measure of anxiety and depression caused by HMB. Statistically non-significant differences were found in the other dimensions evaluated, including those concerned with mobility, personal care, usual activities, and pain or discomfort. Table 6 Changes over time in EQ 5D 3L dimensions Mobility T0 1.18 (0.39) 0.252 T6 1.12 (0.32) Personal care T0 1.05 (0.28) 1.000 T6 1.05 (0.28) Usual activities T0 1.28 (0.49) 0.471 T6 1.23 (0.46) Pain discomfort T0 1.72 (0.72) 0.307 T6 1.62 (0.67) Anxiety / depression T0 1.53 (0.65) 0.020 T6 1.35 (0.51) VAS T0 74.70 (17.10) 0.152 T6 78.20 (17.95) Utility index T0 0.81 (0.19) 0.031 T6 0.86 (0.16) Pretreatment (T0) and 6 months after treatment (T6). EQ‑5D‑3L EuroQol 5‑Dimension 3‑Level, VAS Visual Analogue Scale Changes over time in EQ 5D 3L dimensions Pretreatment (T0) and 6 months after treatment (T6). EQ‑5D‑3L EuroQol 5‑Dimension 3‑Level, VAS Visual Analogue Scale The mean (and SD) MQB and SAMANTA scores for women with AD non-structural HMB were 7.55 (2.20) and 28.8 (10.5), respectively (Table  7 ). The patients experienced reduced menstrual bleeding and an improved HRQoL following the treatment. Statistically significantly lower mean MQB and SAMANTA scores were observed after 6 months of treatment. Table 7 Changes over time in MBQ and SAMANTA and scores Score Time Value P MBQ T0 28.8 (10.5) <0.001 T6 20.1 (11.1) SAMANTA T0 7.55 (2.20) <0.001 T6 4.64 (3.18) Pretreatment (T0) and 6 months after treatment (T6). Values are means (with standard deviations). SAMANTA questionnaire SAngrado Menstrual AbundaNTe en ginecología, MBQ Menstrual Bleeding Questionnaire Changes over time in MBQ and SAMANTA and scores Pretreatment (T0) and 6 months after treatment (T6). Values are means (with standard deviations). SAMANTA questionnaire SAngrado Menstrual AbundaNTe en ginecología, MBQ Menstrual Bleeding Questionnaire To further explore potential sources of attrition bias and treatment effects, we conducted additional analyses of baseline characteristics and outcomes according to follow-up status and type of medical therapy. Supplementary Table S2 compares baseline characteristics between women who completed the T6 HRQoL assessment ( completers , n  = 60) and those who did not ( non-completers , n  = 40). No significant differences were observed in age, age at menarche, menstrual bleeding duration, hemoglobin, hematocrit, platelet count, ferritin, or SF-12 ® v2 summary scores. Similarly, the prevalence of hereditary bleeding disorders (HBD) did not differ between groups (28.3% vs. 35.0%, p  = 0.627). However, completers reported significantly higher baseline PBAC scores (395 ± 269 vs. 284 ± 231, p  = 0.036), MBQ scores (31.1 ± 10.2 vs. 25.2 ± 9.9, p  = 0.005), and SAMANTA scores (8.0 ± 1.7 vs. 6.7 ± 2.5, p  = 0.004). These differences suggest that women with more severe baseline symptoms were more likely to provide follow-up data, which may introduce a potential response bias in the interpretation of T6 outcomes. Therefore, we performed sensitivity analyses to evaluate whether study conclusions were affected (Supplementary Table S3). Specifically, we compared results from complete-case analyses with those obtained after multiple imputation of missing data using chained equations (MICE), incorporating baseline clinical and sociodemographic variables as well as initial questionnaire scores. Predictive mean matching was applied for continuous variables, and 40 imputed datasets were generated to ensure stable estimates. In this table S3, we showed that the direction and magnitude of p-values obtained from complete-case analyses and from multiple imputation are consistent. We have also studied the improvement in symptoms and quality of life according to the type of medical treatment received. Among the 60 patients who completed the HRQoL questionnaires at T6, 38 received hormonal therapy, 19 received non-hormonal therapy (tranexamic acid), and 3 received only supportive therapy (iron supplementation or transfusion). When comparing these groups, no statistically significant differences were observed in SF-12v2 scores, EQ-5D-3 L scores, PBAC, MBQ, or SAMANTA outcomes. Table  8 summarizes the changes in outcome measures (SF-12 ® v2, EQ-5D-3 L, PBAC, SAMANTA, and MBQ) between the groups with HBD ( n  = 17) and non-HBD ( n  = 43), assessed six months after treatment initiation (T6). Table 8 Changes in SF-12®v2, EQ-5D-3L, SAMANTA and MBQ between the HBD and non-HBD groups at T6 Outcome measure HBD group (n=17) Non-HBD group     (n= 43) Unadjusted p-value ANCOVA  (T0 covariate) F(dF) / p value Cohen´s D SF‑12®v2 PCS 65.2 ± 28.7 82.4 ± 19.2 0.009 F(1,57) = 4.74 / p = 0.035 0.72 SF‑12®v2 MCS 49.8 ± 18.5 53.9 ± 15.1 0.382 F(1,57) = 0.73 / p = 0.395 0.24 EQ-5D-index 0.797 ± 0.166 0.887 ± 0.148 0.037 F(1,57) = 5.36 / p = 0.024 0.57 PBAC 247.82 ± 220.48 147.12 ± 151.78 0.047 F(1,57) = 4.06 / p = 0.049 0.55 MBQ 25.18 ± 14.17 18.16 ± 9.04 0.026 F(1,57) = 5.06 / p = 0.028 0.58 SAMANTA 6.00 ± 3.64 4.10 ± 2.84 0.036 F(1,57) = 3.84 / p = 0.055 0.58 Pretreatment (T0) and 6 months after treatment (T6). Values are means (and standard deviations). SF‑12®v2 Short Form‑12 Health Survey, version 2, PCS Physical component score, MCS Mental component score, EQ‑5D‑3L EuroQol 5‑Dimension 3‑Level, PBAC Pictorial Blood Assessment Chart, SAMANTA questionnaire SAngrado Menstrual AbundaNTe en ginecología, MBQ Menstrual Bleeding Questionnaire, HBD Hereditary bleeding disorders Changes in SF-12®v2, EQ-5D-3L, SAMANTA and MBQ between the HBD and non-HBD groups at T6 Pretreatment (T0) and 6 months after treatment (T6). Values are means (and standard deviations). SF‑12®v2 Short Form‑12 Health Survey, version 2, PCS Physical component score, MCS Mental component score, EQ‑5D‑3L EuroQol 5‑Dimension 3‑Level, PBAC Pictorial Blood Assessment Chart, SAMANTA questionnaire SAngrado Menstrual AbundaNTe en ginecología, MBQ Menstrual Bleeding Questionnaire, HBD Hereditary bleeding disorders For the PCS of the SF-12 ® v2, significant differences were observed, with lower scores in the HBD group (65.2 ± 28.7) compared to the non-HBD group (82.4 ± 19.2). ANCOVA, using baseline (T0) scores as covariate, confirmed this difference (F(1,57) = 4.74; p  = 0.035), with a moderate-to-large effect size (Cohen’s D = 0.72). In contrast, the MCS did not show relevant differences between groups ( p  = 0.395). The EQ-5D-3 L index was significantly lower in the HBD group (0.797 ± 0.166) compared to the non-HBD group (0.887 ± 0.148; p  = 0.024), with a moderate effect size (D = 0.57). Regarding menstrual bleeding measures, both the PBAC and the MBQ showed significantly higher values in the HBD group, indicating greater bleeding burden (PBAC: 247.82 ± 220.48 vs. 147.12 ± 151.78; p  = 0.049; MBQ: 25.18 ± 14.17 vs. 18.16 ± 9.04; p  = 0.028). Both outcomes were associated with moderate effect sizes (D = 0.55 and D = 0.58, respectively). The SAMANTA, also showed higher scores in the HBD group (6.00 ± 3.64 vs. 4.10 ± 2.84; p  = 0.055), with a moderate effect size (D = 0.58), although the difference did not reach statistical significance in the adjusted analysis. In order to explore whether treatment heterogeneity could explain the differences observed between groups, we performed a sub-analysis of the therapies received. Overall, the distribution of treatments was broadly comparable between HBD and non-HBD groups, with no systematic differences that could account for the lower responsiveness observed in the HBD group ( p  = 0.453).

Premenopausal women with HMB without organic gynecological pathology were recruited. Gynecological evaluation of women presenting with HMB was conducted according to the PALM-COEIN classification system. The assessment included a detailed medical and menstrual history, physical and pelvic examination, and laboratory testing (complete blood count, coagulation profile, and iron status). Structural causes (Polyp, Adenomyosis, Leiomyoma, Malignancy and hyperplasia) were investigated using transvaginal ultrasound and, when indicated, hysteroscopy or endometrial sampling, endocrine evaluation, and review of medication use. The cause of non-structural HMB was identified and classified as coagulopathy, ovulatory dysfunction, endometrial, iatrogenic, and not yet classified according to standard criteria. A diagnosis of HBD was ascribed to von Willebrand disease (VWD) [ 12 ], congenital platelet disorder [ 13 – 14 ], congenital coagulation factor deficiency [ 15 – 16 ], hypermobility spectrum disorders [ 17 ], or bleeding disorder of unknown cause [ 18 ], according to complete clinical, laboratory assays and molecular tests [ 19 – 20 ]. Patients who did not agree to participate in the study in terms of completing questionnaires or obtaining analytical results were also excluded. HMB was defined as a bleeding duration of ≥ 8 days and/or a PBAC (Pictorial Blood Assessment Chart) score > 100 points [ 21 ]. The PBAC score, a semiquantitative tool, requires patients to record the number and degree of saturation of sanitary pads and tampons used during their menstrual cycle, as well as noting the presence of clots and episodes of flooding. Each item is assigned a score, with lightly, moderately and heavily soiled pads/tampons scoring 1, 5 and 10, respectively; small clots score 1 and large clots score 5. The total PBAC score is calculated as the sum of these values, with a score of ≥ 100 indicating HMB [ 22 ]. The package for HRQoL assessment comprised four questionnaires: the SF-12 ® v2 Health Survey [ 23 ], EuroQol’s 5D-3 L [ 24 ], the Menstrual Bleeding Questionnaire (MBQ) [ 25 ] and the SAMANTA questionnaire [ 26 ] (supplementary table S1 ). The SF-12 ® v2 questionnaire was used to measure general health-related HRQoL. The tool consists of 12 items covering eight domains of two main factors: physical health and mental health. Physical health comprises four domains: physical functioning, physical role limitations, bodily pain, and general health perception. Mental health comprises four domains: emotional role limitations, mental health, vitality, and social functioning. Each item is rated on a scale of 0–5, with higher scores indicating better health status. All item-level results were transformed to scaled scores ranging from 0 to 100, with higher values indicating better health status. To calculate PCS and MCS from the SF-12 ® v2, item responses are standardized using population norms and weighted by specific scoring coefficients. PCS and MCS reflect, respectively, physical and mental health, with higher scores indicating better health status. The EQ-5D-3 L questionnaire was used to evaluate general health-related HRQoL of participants. The EQ-5D-3 L comprises five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has three levels of severity (no problems to extreme problems). Overall health status is calculated as a single index value ranging from 0 (worst health) to 1 (best health). The Menstrual Bleeding Questionnaire (MBQ) is a comprehensive patient-reported outcome measure designed to assess the impact of HMB on women’s HRQoL. MBQ assesses aspects of menstrual bleeding, including frequency, duration, regularity, and volume, along with its impact on physical, social, emotional, and material HRQoL. Items are scored based on the severity and impact, typically with ordinal scales, e.g., from 1 to 5 or 1 to 7, depending on the specific questions asked. Higher scores indicate greater impairment in health-related quality of life. The SAMANTA Questionnaire (SAngrado Menstrual AbundaNTe en ginecologíA) consists of six items that assess the severity of HMB and its impact on daily life. Items score from 0 to 3, with higher scores indicating greater severity and impact. Scores are summed to provide a total score that reflects the overall impact of HMB. The PBAC and ISTH-BAT score and the four HRQoL questionnaires (SF-12 ® v2, EQ-5D-3 L, MBQ and SAMANTA) were completed at the time of diagnosis (T0) and at 6 months (T6). In 2010, the International Society on Thrombosis and Hemostasis (ISTH) introduced a standardized Bleeding Assessment Tool (ISTH-BAT) to evaluate bleeding symptoms. The bleeding score (BS) is determined by assessing the severity of bleeding across 14 key anatomical sites, with the tool administered by a healthcare professional. Each symptom is rated on a scale from 0 (no or minimal symptoms) to 4 (symptoms requiring medical attention), and reference ranges are adjusted based on age and gender. A ISTH-BAT score is considered abnormal if it is ≥ 3 in children, ≥ 4 in adult males, or ≥ 6 in adult females [ 27 ]. At the T0 visit, blood samples were drawn for a complete blood count (CBC), iron metabolism analysis, a basic coagulation study, assessment of coagulation factor levels, and light-transmission aggregometry (LTA). The therapeutic options for treating non-structural HMB include hormonal treatments involving the use of combined oral contraceptives, progestins, or the levonorgestrel-releasing intrauterine device (LNG-IUD). Non-hormonal treatments include tranexamic acid and/or iron therapy (for ferritin levels of < 20 ng/mL). The choice of therapy was individualized, based on the underlying cause, patient preferences, and reproductive plans, thereby ensuring effective management of symptoms. The primary objective was to investigate the HRQoL (SF-12 ® v2, EQ-5D-3 L, MBQ and SAMANTA) in non-structural HMB. The secondary objectives were to determine the presence of HBDs in women with HMB and to evaluate the change in scores from the SF-12 ® v2, EQ-5D-3 L, MBQ and SAMANTA questionnaires between baseline and 6 months after medical treatment for HMB, as well as to examine the effect of a hereditary bleeding disorder diagnosis on HRQoL improvements. The test scores of the HRQoL questionnaires were recorded and analyzed using IBM SPSS Statistics version 29.0 (IBM Corp., Armonk, NY, USA; Licensed to the University of Salamanca). The χ2 and Fisher’s exact tests were used to compare patient demographic data between groups. The independent-samples t test was used to compare the HRQoL test scores between groups at different times. Paired-samples t tests were used to examine the changes over time within each group. The effect size, which was calculated by dividing the mean difference between T6 and T0 by the standard deviation at T0, was calculated to establish the magnitude of the statistical difference. Two-tailed values of p  < 0.05 were considered statistically significant. This was a prospective and longitudinal study to investigate the HRQoL in women with non-structural HMB This study was conducted in accordance with the principles of the Declaration of Helsinki and its subsequent amendments. Ethical approval was obtained from the Institutional Review Board (IRB) of the Complejo Asistencial Universitario de Salamanca (Approval Number: PI 2023-04-1280) and written informed consent was obtained from all participants.

Non-structural HMB significantly affects women’s physical and mental well-being. HBD is an important cause of HMB. Medical treatment improves mobility, moderate activities, pain perception, and anxiety/depression after 6 months, although HRQoL improvements are less pronounced in HBD patients. A larger study population is needed to validate and consolidate these preliminary results.

Our findings highlight the positive impact of medical intervention on HRQoL measures in women with non-structural HMB. The SF-12 ® v2 scores demonstrated significant improvements in both physical (PCS) and mental (MCS) components with notable enhancements in mobility, moderate activities, and pain perception. Likewise, the EQ-5D-3 L evaluations showed a reduction in anxiety and depression, reflecting emotional well-being improvements. Furthermore, the MBQ and SAMANTA scores indicated statistically significant reductions in menstrual bleeding, reinforcing the efficacy of treatment in symptom management and overall health. However, for the first time, we have documented that women diagnosed with HBD experienced less pronounced improvements compared with those without HBD, suggesting that additional tailored interventions may be necessary for this subgroup. HMB is a common gynecological condition affecting a significant proportion of women worldwide. Approximately 32% of women experience HMB, the prevalence varying by age and region [ 2 ]. In a survey conducted in Spain, 32.7% of participants reported excessive menstrual bleeding, and this was associated with a higher frequency and intensity of menstrual symptoms and a greater impact on daily life [ 28 ]. Research also shows that HMB can lead to reduced physical and mental well-being, limiting social and professional activities and negatively affecting overall health-related quality of life. Despite its prevalence, many women do not seek medical assistance, highlighting the need for increased awareness and better treatment options. Several studies have evaluated the impact of HMB on HRQoL using standardized tools. A study conducted in Sweden assessed HRQoL in women with HMB using the SF-36 Health Survey questionnaire, a more detailed version of the SF-12 ® v2, showed that, on average, women with HMB had significantly lower HRQoL scores than those with normal menstrual bleeding, particularly with respect to the mental health domains [ 29 ]. Additional research focused on developing a brief menstrual HRQoL measure for women with HMB. The study introduced the PERIOD-QoL, which demonstrated that women with HMB reported significantly lower menstrual HRQoL scores than those without HMB [ 30 ]. These findings align with the results of our study, reinforcing the conclusion that HMB has a negative impact on physical and mental well-being, and highlighting the importance of effective treatment strategies to improve HRQoL. There is a lack of evidence in the field of HRQoL and HMB without organic pathology. Weisberg et al. focused on the decrease in HRQoL related to pain [ 31 ]. Coinciding with the findings of our study, they concluded that HMB has an important effect not only on the physical, but above all on the emotional aspect, since women reported feeling more depressed, having less energy, and that their leisure activities were influenced by pain, to the extent that they were unable to undertake activities during their menstrual period. The most frequent cause of abnormal post-menarche uterine bleeding is the immaturity of the hypothalamic–pituitary–ovarian axis, which leads to anovulatory cycles. However, there is increasing awareness that HBDs play an important role in HMB, and hemostatic disorders may be present in 5–36% of women [ 11 ]. Platelet dysfunction was the most common entity in our series ( n  = 11). Hypermobility spectrum disorders were the second cause of hemostatic disorder. A systematic investigation using LTA test and the Beighton score could be carried out to try to explain these results. In the meantime, our findings emphasize the need to implement systematic screening for HBDs, particularly for women presenting with non-structural HMB. Treatment of HMB has proved to be effective for reducing the volume of bleeding and improving some aspects affecting patients’ HRQoL, as evidenced by the scores obtained from the questionnaires used. Specifically, a statistically significant improvement was observed in the domain of anxiety and depression after 6 months of treatment. This result underscores the critical role that effective management of HMB plays in alleviating the emotional and psychological distress associated with the condition. Anxiety and depression are frequently reported by individuals with HMB due to the chronic nature of the symptoms and their interference with daily life. Dealing with them is therefore a crucial aspect of patient care. Our findings on symptom improvement and HRQoL are consistent with previous reports showing that women with structural causes of HMB (e.g., fibroids, adenomyosis, polyps) experience significant impairment in quality of life, which improves after appropriate treatment [ 32 ]. Although our study focused on non-structural causes, the magnitude of HRQoL improvement we observed parallels that reported in structural pathology once effective therapy is instituted. The attenuated response in HBD patients may be multifactorial. In platelet dysfunction, hormonal therapy does not correct the underlying hemostatic defect, leading to persistent bleeding despite treatment [ 33 ]. In hypermobility spectrum disorders, musculoskeletal symptoms such as joint pain and fatigue—unaddressed by HMB therapy—may further limit improvements in HRQoL [ 34 ]. An importan limitation of our study is the relatively small sample size available for the comparative analysis between HBD and non-HBD groups at T6, with 60% of the initial cohort completing the T6 assessment. Baseline analyses showed that completers had significantly higher bleeding burden scores compared to non-completers, suggesting that women with more severe symptoms were more likely to provide follow-up data. However, sensitivity analyses using multiple imputation showed results consistent with complete-case analyses, supporting the robustness of our findings despite missing data. Other limitation of the present study is that treatments were not standardized but rather prescribed according to routine clinical practice. Although our sub-analysis indicates that treatment regimens were broadly similar between HBD and non-HBD groups, the absence of a uniform therapeutic protocol may have introduced confounding effects and should be considered when interpreting the comparative outcomes. In the same line, treatment adherence was assessed indirectly through patient self-reports using a simple self-rating question during medical visits. This approach may be subject to recall bias and social desirability bias, potentially leading to an overestimation of adherence. In addition, the analysis of the PBAC score focused exclusively on the use of pads and tampons, although information on menstrual cup use awaits validation. These limitations may have influenced the borderline p-values observed and increased the potential impact of confounding factors, for which reason we must consider our results to be preliminary.

Heavy menstrual bleeding (HMB) is common in women and negatively affects their health-related quality of life (HRQoL). HMB is widespread among women of reproductive age, with a prevalence between 10% and 32%, being particularly common in adolescents and young women [ 1 – 2 ]. Despite its frequency, accurate prevalence estimates remain elusive due to the varied diagnostic approaches taken and the subjective nature of self-reported bleeding severity. A study conducted in Spain (SANA registry) found that fewer than half the women experiencing HMB seek medical attention on their own initiative because they often perceive their bleeding patterns to be normal [ 3 ]. Excessive menstrual blood loss not only disrupts physical health but also interferes with emotional and social well-being [ 4 ]. Many women experience limitations in daily activities, workplace productivity, and social engagement due to the unpredictability and severity of their symptoms. A significant number of women experiencing HMB do not receive an accurate diagnosis explaining its cause. Many factors contribute to this issue, including the complexity of menstrual disorders, the coincidence of symptoms with those of other gynecological conditions, and the lack of standardized diagnostic protocols. HMB can arise from both structural and non-structural causes. This distinction is formalized in the widely accepted PALM-COEIN classification system, which categorizes etiologies into structural (Polyp, Adenomyosis, Leiomyoma, Malignancy/hyperplasia) and non-structural (Coagulopathy, Ovulatory dysfunction, Endometrial, Iatrogenic, and Not yet classified) entities [ 5 – 7 ]. Among non-structural HMB, ovulatory dysfunction is the most prevalent cause, accounting for 57.7% of cases, and characterized by absent or irregular ovulation, with fewer than nine menstrual cycles per year. Of the structural causes, polyps are the most frequently diagnosed pathology (16.2%), followed by leiomyomas (12.0%) and adenomyosis (4.9%) [ 6 ]. There is a growing awareness that hereditary bleeding disorders (HBDs) play a significant role in HMB. Earlier studies of young women who sought a medical consultation due to HMB reported prevalences of 20–30% of HBDs, emphasizing the importance of thorough evaluation and appropriate referral to hematology specialists to ensure accurate diagnosis and management [ 8 – 11 ]. While physical symptoms (e.g., anemia, fatigue) are well documented, the psychological burden —including anxiety, depression, and social limitations— is often underexplored or measured inconsistently in women with HMB. Also, HBDs are frequently overlooked, leading to a gap in our understanding of how they influence HMB severity and HRQoL. Various management strategies (e.g., hormonal therapy, intrauterine devices, antifibrinolytics) have been used, making it difficult to standardize results and assess which treatments bring about the biggest improvements in HRQoL. We hypothesize that HBDs, may attenuate improvements in health-related quality of life (HRQoL) following treatment, underscoring the importance of accurate classification and individualized management. The objective of this study was to assess the HRQoL of women with non-structural HMB and its association with HBDs.

Supplementary Material 1. Supplementary Material 1.