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Obstet Gynecol Sci > Volume 68(6); 2025 > Article
Simanjuntak, Priyanto, and Azis: Red blood cell indices as predictor for severity of endometriosis

Abstract

Objective

Endometriosis is the presence of endometrial tissue outside of the uterine cavity. Certain markers have been used to evaluate the severity of endometriosis. This study aimed to explore the correlation between red blood cell (RBC) indices and the severity of endometriosis.

Methods

This was a cross-sectional study including 200 patients with endometriosis (stage I-II and stage III-IV groups) and 100 patients with other benign ovarian tumors who underwent laparotomy at the Department of Obstetrics and Gynaecology, Margono Regional Public Hospital, between 2021 and 2024. Blood tests were evaluated before surgery and the severity of endometriosis was determined during surgery using the revised American Society for Reproductive Medicine classification.

Results

Among the obtained RBC indices, mean hemoglobin (Hb), hematocrit (Hct), mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) values were significantly lower in subjects with stage III-IV endometriosis than in those with stage I-II endometriosis and the control group (P=0.000, P=0.000, P=0.006, and P=0.010, respectively). The mean red cell distribution width (RDW) was significantly higher in the stage III-IV group than in the stage I-II and control groups (P=0.000). In addition, univariate analysis indicated that lower preoperative RBC indices (Hb ≤11.9 g/dL, Hct ≤37.1%, MCV ≤82.6 fL, MCH ≤26.6 pg) and higher RDW ≥14.9% were independent risk factors for stage III/IV endometriosis.

Conclusion

Lower RBC indices, including pre-operative Hb, Hct, MCV, and MCH, were significantly associated with the severity of endometriosis, which is potentially caused by dysregulation of iron metabolism and inflammation.

Introduction

Endometriosis indicates the presence of an ectopic implantation of endometrial glands and stroma-like lesions, which represent the functional tissue lining of the uterus outside of the uterine cavity. It is found in 10% to 15% of women between menarche and menopause at a peak age between 25 years and 45 years. The lesions may appear as peritoneal lesions, superficial implants, cysts, or deep infiltration. Around 70% of patients have chronic pelvic pain but also experience fatigue, weakness, malaise, or menorrhagia, which may also be symptoms of anemia [1-4].
Several theories explain the etiology and pathogenesis of endometriosis, but none of these theories addresses a clear underlying cause of endometriosis. The most famous theory states that retrograde menstruation results in the displacement of menstrual blood into the uterine cavity, where it can implant, grow, and infiltrate [5]. As a result, an anemic condition may occur in women with endometriosis, which then causes low red blood cell (RBC) indices and complete blood count rates [1,6,7].
In endometriosis, the cellular immunity and inflammatory cytokines of the immune system are altered. Inflammatory markers that are increased in severe endometriosis are the neutrophil-lymphocyte ratio, interleukin (IL)-6, tumor necrosis factor-α, IL-1β, and IL-8. In addition, a high reactive oxygen species level, along with high iron concentrations, has been found in the early development of endometriosis [6,8-10].
Other markers have also been studied to assess the presence and severity of endometriosis. RBC indices have been reported to be lower in endometriosis patients, suggesting an effect of iron metabolism dysregulation and inflammation, which may inhibit erythropoiesis [6,9,10]. Therefore, in this study we aimed to evaluate the correlation between RBC indices (hemoglobin [Hb], hematocrit [Hct], mean corpuscular volume [MCV], mean corpuscular hemoglobin [MCH], mean corpuscular hemoglobin concentration [MCHC], red cell distribution width [RDW]) and the severity of endometriosis.

Materials and methods

We did not include individuals as subjects in this study; therefore, ethical clearance was obtained from the university as enclosed. Sample size was determined to reach a level of confidence of 95%. According to the prevalence of endometriosis (18%), the estimated minimal sample size was 227. Therefore, we included 300 patients. Potential biases included differences in the menstrual cycle between subjects, hormonal medication, and potential other causes of anemia.
This study was a cross-sectional study that included premenopausal women with benign ovarian tumors who underwent laparotomy for management at the Department of Obstetrics and Gynecology, Margono Regional Public Hospital, between 2021 and 2024. Pregnant women and those with leiomyoma, pelvic inflammatory diseases, tuberculosis, hematemesis/melena, and diseases such as endocrine diseases, abnormal liver, heart diseases, diabetes, kidney diseases, malignancy, or immune system diseases were not included in this study. The women’s age, body weight, body height, and body mass index (BMI) were considered as characteristics.
The total number of patients included in this study were 300 women, of which 200 were confirmed with endometriosis (study group), and 100 were confirmed with other types of benign ovarian tumors (control group), including serous cystadenoma, mucinous adenoma, or teratoma. The 200 patients with endometriosis were divided into two groups, 100 women with stage I-II endometriosis and another 100 women with stage III-IV endometriosis (Fig. 1). The severity of endometriosis was defined according to the revised American Society for Reproductive Medicine classification score, which was determined during surgery. Before surgery, blood tests were evaluated for the RBC indices Hb, Hct, MCV, MCH, MCHC, and RDW.
One-way analysis of variance was used to evaluate mean differences within each group. The optimal cut-off was calculated using Youden’s index. The odds ratio and 95% confidence intervals were also calculated. Univariate analysis was performed using binominal logistic regression to evaluate the relationship between variables and the severity of endometriosis. The accuracy of RBC indices in the discrimination of stage III-IV from stage I-II endometriosis was calculated using the receiver operating characteristic (ROC). All statistical analyses were performed using SPSS version 26.0 (SPSS Inc., Chicago, IL, USA), with a P-value <0.05 considered statistically significant.

Results

Differences in patients characteristics in each group are presented in Table 1. The mean BMI was slightly higher in the stage III-IV group. However, there were no significant group differences in age, body weight, body height, and BMI. Table 2 shows the mean values of RBC indices in each group, including RBCs, Hb, Hct, MCV, MCH, MCHC, and RDW. Multiple variables such as Hb, Hct, MCV, and MCH significantly differed between the groups (P=0.000, P=0.000, P=0.006, and P=0.010, respectively). These indices were significantly lower in the stage II-IV group than in the control and stage I-II groups. RBCs and MCHC were also lower in the stage III-IV group, but not significantly. In contrast, the mean RDW was significantly higher in the stage III-IV group than the control and stage I-II groups (P=0.000).
ROCs and the area under the curve (AUC) were generated for RBC indices in the stage III-IV group to determine their sensitivity and specificity relative to baseline values (Table 3). Optimal cut-off values were calculated based on Youden’s index. The AUC for Hb, Hct, MCV, MCH, and RDW was 0.66, 0.66, 0.58, 0.57, and 0.65, respectively.
Univariate regression analysis was performed to assess the relationship between RBC indices and severe endometriosis (stage III-IV group). All variables (Hb, Hct, MCV, MCH, and RDW, above or below cut-off values) were significantly associated with stage III-IV endometriosis (Table 4).

Discussion

Because endometriosis is related to local and systemic inflammatory processes, numerous inflammatory markers are found in endometriosis patients [10,11]. According to retrograde menstruation theory, which applies to 90% of women, repeated localized hemorrhage results in deposition of erythrocytes. Therefore, severe hemolysis develops as menstrual reflux increases and iron is released due to RBC degradation. This results in iron overload upon deposition of endometrial tissue, which sheds physiologically, on the peritoneal surface. In turn, iron overload fosters attachment, further growth, and neovascularization of endometrial cells in the pelvic cavity. Iron overload also increases oxidative stress due to the production of free radicals [12-16].
Many studies have reported that RBC indices may be used for predicting the severity of endometriosis. However, these previous results need further verification. Cho et al. [10] found a significant association between RBC indices (Hb, Hct, MCV, and MCH) and endometriosis, which aligns with the findings of our current study [11]. Another study by Atkins et al. [17] found that women with endometriosis have significantly decreased Hct and Hb levels. A clinical study using primate models showed that endometriosis is associated with significantly lower RBC, serum hepcidin, and hepatic and bone marrow iron levels. Iron deficiency has also been related to heavy menstrual bleeding and chronic inflammation in endometriosis patients. Iron storage depletion negatively affects hematopoiesis, while chronic inflammation affects iron regulation through reduced iron absorption [18]. The altered RBC indices in endometriosis may be explained by the dysregulation of iron metabolism [10,11,19].
Our study indicates that RDW levels were increased in severe endometriosis, in contrast to the other RBC indices, which were decreased. Similarly, Kurt et al. [20] reported a significantly higher RDW in the endometriosis group than in the control group. RDW is a parameter used to diagnose anemia and has also been related to systemic inflammation in chronic diseases. Increased RDW promotes RBC membrane deformability and thus alters erythropoiesis [21,22]. Chronic inflammation reduces the life span of RBCs through iron metabolism impairment and erythropoietin response. RBC deformability subsequently impairs the microcirculation, which promotes oxidative stress and sustains inflammation [16,19,23]. Inflammatory markers were significantly higher in severe endometriosis patients [24]. However, no previous studies have reported a relation between RBC indices and the severity of endometriosis. Higher inflammatory markers with increased severity of endometriosis may be related to iron metabolism and inflammation, which affect RBC indices.
We consider the selection of a control group as a strength of our study. We included women who were pathologically proven to have only benign ovarian tumors. This allowed us to confirm that our control subjects did not have endometriosis. A limitation of our study is its retrospective and single-center design. Other factors such as menstrual cycle phase and hormonal medication use can affect RBC parameters. This could have caused bias in our study because blood sampling data were collected irrespective of the patients’ menstrual cycle phase. In addition, there might have been other causes of anemia in our samples that we could not exclude. Several confounders, which were not included in our analytic calculation, such as age, BMI, or iron status, might have also affected the RBC indices. Therefore, our results may be partially distorted owing to the absence of multivariate regression. Our statistical comparisons indicated significant differences among RBC indices but cannot be used as a diagnostic tool because they do not have diagnostic or predictive value.
This study indicates that RBC indices, such as Hb, Hct, MCV, and MCH, and higher RDW were significantly lower in subjects within the stage III-IV group compared with those in the control group. Chronic inflammation in endometriosis, which is related to disrupted iron metabolism, may explain these findings. However, further studies are needed to better explain the mechanisms underlying the relationship between RBC indices and the severity of endometriosis.

Notes

Conflict of interest

No potential conflict of interest relevant to this article was reported.

Ethical approval

The study was approved by the Ethics Committee of Soekarjo University (021/KEPK/PE/II/2025).

Patient consent

Not applicable.

Funding information

None.

Fig. 1
Flow diagram of selection of included patients.
ogs-25080f1.jpg
Table 1
Group differences in patient characteristics
Control (n=100) Stage I-II (n=100) Stage III-IV (n=100) P-value
Age (yr) 39.08 (37.28-40.88) 39.16 (37.67-40.65) 39.10 (37.77-40.43) 0.997
Body weight (kg) 55.95 (53.66-58.23) 57.22 (54.75-59.68) 58.97 (56.55-61.38) 0.207
Height (cm) 152.59 (151.42-153.76) 152.04 (150.87-153.21) 152.34 (151.11-153.57) 0.810
BMI (kg/m2) 23.688 (23.096-24.880) 24.665 (23.734-25.974) 25.419 (24.440-26.394) 0.101

Values are presented as mean (95% confidence interval). P-values were obtained using one-way analysis of variance.

BMI, body mass index.

Table 2
RBC index count in each group
Control (n=100) Stage I-II (n=100) Stage III-IV (n=100) P-value
Preoperative RBC indices
 RBCs (106/μL) 4.587 (4.459-4.416) 4.498 (4.386-4.610) 4.403 (4.302-4.503) 0.111
 Hb (g/dL) 12.275 (12.047-12.503) 11.905 (11.662-12.148) 11.237 (10.957-11.517) 0.000b
 Hct (%) 36.477 (35.482-37.472) 36.533 (35.732-37.334) 33.735 (32.685-34.785) 0.000b
 MCV (fL) 83.066 (81.532-84.600) 82.194 (80.811-83.577) 79.589 (77.837-81.341) 0.006a
 MCH (pg) 27.114 (26.459-27.769) 26.709 (26.111-27.307) 25.741 (25.059-26.423) 0.010a
 MCHC (%) 32.395 (32.101-32.689) 32.487 (32.196-32.778) 32.256 (31.957-32.555) 0.543
 RDW (%) 15.506 (14.861-16.151) 14.616 (14.192-15.040) 16.316 (15.621-17.011) 0.000b

Values are presented as mean (95% confidence interval). P-values were obtained using one-way analysis of variance.

RBC, red blood cells; Hb, hemoglobin; Hct, hematocrit; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; RDW, red cell distribution width.

a P<0.05.

b P<0.0001.

Table 3
ROC-AUC and optimal cut-off of RBC ondices
Variable Cut-off AUC Youden index Sensitivity (%) Specificity (%)
Hb 11.9 0.66 0.29 54.0 75.0
Hct 37.1 0.66 0.28 49.0 79.0
MCV 82.6 0.58 0.19 59.0 60.0
MCH 26.6 0.57 0.18 58.0 60.0
RDW 14.9 0.65 0.23 61.0 62.0

ROC-AUC, receiver operating characteristics and area under the curve; RBC, red blood cells; Hb, hemoglobin; Hct, hematocrit; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; RDW, red cell distribution width.

Table 4
Univariate binominal logistic regression analysis
Variable B-value OR (95% CI) P-value
Hb ≤11.9 g/dL 1.25±0.30 3.52 (1.93-6.41) 0.000b
Hct ≤37.1% 1.28±0.31 3.61 (1.94-6.72) 0.000b
MCV ≤82.6 fL 0.76±0.28 2.15 (1.22-3.79) 0.008a
MCH ≤26.6 pg 0.72±0.28 2.07 (1.17-3.64) 0.011a
RDW ≥14.9% 0.85±0.28 2.34 (1.33-4.13) 0.003a

Values are presented as mean±standard deviation unless otherwise indicated.

OR, odds ratio; CI, confidence interval; Hb, hemoglobin; Hct, hematocrit; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; RDW, red cell distribution width.

a P<0.05.

b P<0.0001.

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