A multicenter observational study of the association between systemic immune inflammation index and adenomyosis

Conceptualization, C.Y.Y. and Y.W.; data curation, Y.W.; formal analysis, C.Y.Y., Y.Z., S.Q., and Y.W.; funding acquisition, F.Y.S., F.X., and Y.W.; investigation, C.Y.Y., Y.Z., and S.Q.; methodology, C.Y.Y., Y.Z., and W.H.W.; project administration, Y.W.; resources, C.Y.Y., F.Y.S., F.X., and Y.W.; supervision, F.Y.S., F.X., and Y.W.; validation, C.Y.Y. and Y.W.; visualization, C.Y.Y.; writing – original draft, C.Y.Y., Y.Z., and Y.W.; writing – review and editing, C.Y.Y. and Y.W. All authors reviewed and approved the final version of the manuscript.

Baseline characteristics of participants stratified by SII quartiles are presented in Table 1 . Participant distribution across the quartiles was generally balanced. With the exception of alanine transaminase, diabetes mellitus, and BMI, baseline characteristics demonstrated significant differences among the four groups. An increased incidence of adenomyosis was observed among participants with elevated SII levels relative to those with lower levels. Table 1 Baseline characteristics of participants Characteristic SII Q1 SII Q2 SII Q3 SII Q4 p value n = 18,850 n = 18,747 n = 18,685 n = 18,618 Age (years) 41.58 ± 12.38 40.85 ± 11.27 40.73 ± 10.58 40.88 ± 10.10 <0.001 SII 292.45 ± 61.97 453.82 ± 42.97 628.44 ± 62.29 1093.20 ± 353.50 <0.001 Neutrophils (×10 9 /L) 2.66 ± 0.73 3.36 ± 0.83 3.99 ± 1.00 5.38 ± 1.79 <0.001 Lymphocytes (×10 9 /L) 1.97 ± 0.53 1.85 ± 0.50 1.74 ± 0.48 1.51 ± 0.46 <0.001 Platelet (×10 9 /L) 217.25 ± 50.53 252.14 ± 53.06 276.85 ± 60.26 305.34 ± 77.33 <0.001 Triglycerides (mmol/L) 1.19 ± 0.96 1.26 ± 1.04 1.28 ± 0.95 1.29 ± 0.99 <0.001 Total cholesterol (mmol/L) 4.83 ± 0.91 4.81 ± 0.89 4.80 ± 0.89 4.75 ± 0.89 <0.001 Creatinine (μmol/L) 53.09 ± 8.26 52.26 ± 8.00 51.79 ± 8.01 51.31 ± 8.46 <0.001 Alanine transaminase (U/L) 17.63 ± 12.98 17.43 ± 12.83 17.64 ± 13.92 17.38 ± 13.14 0.134 Glucose (mmol/L) 5.08 ± 0.67 5.11 ± 0.71 5.16 ± 0.76 5.22 ± 0.82 <0.001 Adenomyosis (%)  No 16,696 (88.57%) 16,601 (88.55%) 16,325 (87.37%) 15,945 (85.64%) <0.001  Yes 2,154 (11.43%) 2,146 (11.45%) 2,360 (12.63%) 2,673 (14.36%) IUD (%)  No 18,294 (97.05%) 18,110 (96.60%) 18,011 (96.39%) 17,933 (96.32%) <0.001  Yes 556 (2.95%) 637 (3.40%) 674 (3.61%) 685 (3.68%) Cesarean section history (%)  No 16,791 (89.08%) 16,505 (88.04%) 16,176 (86.57%) 16,208 (87.06%) <0.001  Yes 2,059 (10.92%) 2,242 (11.96%) 2,509 (13.43%) 2,410 (12.94%) Hypertension history (%)  No 17,145 (90.95%) 17,012 (90.75%) 16,957 (90.75%) 16,645 (89.40%) <0.001  Yes 1,705 (9.05%) 1,735 (9.25%) 1,728 (9.25%) 1,973 (10.60%) Diabetes mellitus (%)  No 18,384 (97.53%) 18,280 (97.51%) 18,179 (97.29%) 18,115 (97.30%) 0.294  Yes 466 (2.47%) 467 (2.49%) 506 (2.71%) 503 (2.70%) BMI ≥ 24kg/m 2 (%)  No 18,762 (99.53%) 18,642 (99.44%) 18,564 (99.35%) 18,517 (99.46%) 0.131  Yes 88 (0.47%) 105 (0.56%) 121 (0.65%) 101 (0.54%) Q1 = 22.75–380.15, Q2 = 380.15–529.09, Q3 = 529.09–747.41, Q4 = 747.41–2555.95. SII, systemic immune inflammation index; Q, quartile; BMI, body mass index; IUD, intrauterine device. Baseline characteristics of participants Q1 = 22.75–380.15, Q2 = 380.15–529.09, Q3 = 529.09–747.41, Q4 = 747.41–2555.95. SII, systemic immune inflammation index; Q, quartile; BMI, body mass index; IUD, intrauterine device. The results of the multivariable regression analysis examining the association between SII and adenomyosis are presented in Table 2 . In the crude model, significant associations were observed for SII Q3 and Q4 compared to Q1. Furthermore, in the model adjusted for IUD use, cesarean history, hypertension, diabetes, age, BMI, total cholesterol (TCHO), creatinine (CR), alanine aminotransferase (ALT), and glucose (GLU), the risk of adenomyosis increased progressively with higher SII quartiles. Compared to Q1, the risk was 48% higher in Q4 (OR = 1.48, 95% CI: 1.38–1.59, p < 0.0001). There was a difference in the trend test between the rising trend of SII and the overall incidence rate of adenomyosis ( p < 0.0001). Further threshold analysis using a piecewise regression model identified a saturation effect at an SII of 1500. When SII was below 1500, each 100-unit increase in SII was associated with a 5% higher risk of adenomyosis (OR = 1.05, 95% CI: 1.04–1.06, p < 0.0001). However, when SII reached or exceeded 1500, the risk curve entered a plateau phase, with no further significant increase in risk observed with continued SII elevation (Likelihood ratio test for nonlinearity: p < 0.001; Table 3 ). Figure 1 A presents the SII as a categorical variable, demonstrating a stepwise increase in the risk of adenomyosis across its quartiles. Correspondingly, Figure 1 B displays the dose-response relationship between SII as a continuous variable and adenomyosis risk using smoothing splines, visually confirming the nonlinear, S-shaped association. The curve shows a rising risk trend that becomes moderate when SII reaches or exceeds 1500. As shown in Tables 2 and 3 , this relationship was quantified by the adjusted logistic regression model, which estimated a 4% increase in the odds of adenomyosis for each 100-unit increment in SII (OR = 1.04, 95% CI: 1.03–1.05, p < 0.0001). Table 2 Independent association of elevated SII with adenomyosis risk Outcome: adenomyosis No. of adenomyosis (%) Crude model p value Adjust model p value OR (95% CI) Adjusted OR (95% CI) SII Q1 2,154 (11.43%) Ref. Ref. SII Q2 2,146 (11.45%) 1.00 (0.94, 1.07) 0.9512 1.09 (1.02, 1.17) 0.011 SII Q3 2,360 (12.63%) 1.12 (1.05, 1.19) 0.0003 1.25 (1.17, 1.34) <0.0001 SII Q4 2,673 (14.36%) 1.30 (1.22, 1.38) <0.0001 1.48 (1.38, 1.58) <0.0001 Continuous SII per 100 9,333(12.46%) 1.03 (1.02, 1.04) <0.0001 1.04 (1.03, 1.05) <0.0001 p value for trend <0.0001 <0.0001 Crude model: no covariates were adjusted. Adjust model: adjusted for IUD; history of cesarean section; hypertension; diabetes; age; BMI ≥ 24 kg/m 2 (Yes/No); TCHO; CR; ALT; GLU. SII, systemic immune inflammation index; Q, quartile; OR, odds ratio; CI, confidence interval. Table 3 Threshold effect analysis for the relationship between SII and adenomyosis Models Risk of adenomyosis adjusted OR (95% Cl) p value Model I One line slope 1.04 (1.03, 1.05) <0.0001 Model II Turning point 1,500 <1,500 slope 1 1.05 (1.04, 1.06) 1,500 slope 2 0.97 (0.96, 1.01) 0.1 Slope 2 – Slope 1 0.93 (0.89, 0.96) <0.0001 Predicted at 1,500 −1.62 (−1.69, −1.54) Likelihood ratio test <0.001 Model I, linear analysis; model II, non-linear analysis. Likelihood ratio test: p value < 0.05 means model II is significantly different from model I, which indicates a non-linear relationship; adjusted for IUD; history of cesarean section; hypertension; diabetes; age; BMI ≥ 24 kg/m 2 (yes/no); TCHO; CR; ALT; GLU. OR, odds ratio; CI, confidence interval. Figure 1 Relationship between SII and the risk of adenomyosis (A) Risk of adenomyosis according to SII quartiles. Data are represented as mean ± SE. (B) Dose-response relationship between SII and adenomyosis assessed using smooth curve fitting. The solid red line indicates the estimated association, and the blue band represents the 95% CI. The overall relationship between SII and the risk of adenomyosis based on SII quartiles. SII, systemic immune inflammation index; Q, quartile; CI, confidence interval; SE, std. error. Independent association of elevated SII with adenomyosis risk Crude model: no covariates were adjusted. Adjust model: adjusted for IUD; history of cesarean section; hypertension; diabetes; age; BMI ≥ 24 kg/m 2 (Yes/No); TCHO; CR; ALT; GLU. SII, systemic immune inflammation index; Q, quartile; OR, odds ratio; CI, confidence interval. Threshold effect analysis for the relationship between SII and adenomyosis Model I, linear analysis; model II, non-linear analysis. Likelihood ratio test: p value < 0.05 means model II is significantly different from model I, which indicates a non-linear relationship; adjusted for IUD; history of cesarean section; hypertension; diabetes; age; BMI ≥ 24 kg/m 2 (yes/no); TCHO; CR; ALT; GLU. OR, odds ratio; CI, confidence interval. Relationship between SII and the risk of adenomyosis (A) Risk of adenomyosis according to SII quartiles. Data are represented as mean ± SE. (B) Dose-response relationship between SII and adenomyosis assessed using smooth curve fitting. The solid red line indicates the estimated association, and the blue band represents the 95% CI. The overall relationship between SII and the risk of adenomyosis based on SII quartiles. SII, systemic immune inflammation index; Q, quartile; CI, confidence interval; SE, std. error. Further subgroup analyses, presented in Table 4 , showed that the association between SII and adenomyosis was not uniform. Variation in the relationship across SII quartiles was observed among subgroups categorized by BMI, cesarean section history, and IUD utilization. Importantly, following covariate adjustment, a statistically significant positive correlation was consistently observed in each of the following subgroups independently: women with BMI <24 kg/m 2 , those without a history of cesarean delivery, and non-IUD users. Stratified analyses demonstrated consistent risk elevation in SII Q4 versus Q1: Women with BMI <24 kg/m 2 exhibited 49% higher adenomyosis risk (OR = 1.49, 95% CI: 1.39–1.59, p < 0.0001), those without cesarean section history showed 48% increased risk (OR = 1.48, 95% CI: 1.37–1.59, p < 0.0001), and non-IUD users had 49% greater risk (OR = 1.49, 95% CI: 1.39–1.59, p < 0.0001). These findings collectively indicate that elevated SII levels are consistently and more strongly associated with adenomyosis in each of the following subgroups independently: individuals with BMI <24 kg/m 2 , those without a cesarean section history, and non-IUD users. Interaction analyses indicated that the positive SII-adenomyosis association was not significantly modified by BMI category, history of cesarean section, IUD use, or across the participating centers (all p for interaction >0.05). Table 4 Subgroup and center analysis of SII and adenomyosis Subgroup/center No. of adenomyosis (%) Crude model OR (95% CI) p value p value for interaction Adjust model Adjusted OR (95% CI) p value p value for interaction BMI (kg/m 2 ) 0.0742 0.4212  <24 9,235 (12.40%)  SII Q1 2,127 (11.34%) Ref. Ref.  SII Q2 2,121 (11.38%) 1.00 (0.94, 1.07) 0.9011 1.10 (1.02, 1.17) 0.0094  SII Q3 2,334 (12.57%) 1.12 (1.06, 1.20) 0.0002 1.26 (1.18, 1.35) <0.0001  SII Q4 2,653 (14.33%) 1.31 (1.23, 1.39) <0.0001 1.49 (1.39, 1.59) <0.0001  ≥24 98 (23.61%)  SII Q1 27 (30.68%) Ref. Ref.  SII Q2 25 (23.81%) 0.71 (0.37, 1.34) 0.2848 0.78 (0.39, 1.58) 0.4878  SII Q3 26 (21.49%) 0.62 (0.33, 1.16) 0.133 0.75 (0.38, 1.47) 0.3954  SII Q4 20 (19.80%) 0.56 (0.29, 1.09) 0.0863 0.76 (0.36, 1.61) 0.4799 Cesarean section history 0.0526 0.2228  No 7,894 (12.02%)  SII Q1 1,861 (11.08%) Ref. Ref.  SII Q2 1,855 (11.24%) 1.02 (0.95, 1.09) 0.6519 1.12 (1.04, 1.21) 0.0028  SII Q3 1,967 (12.16%) 1.11 (1.04, 1.19) 0.0023 1.27 (1.18, 1.36) <0.0001  SII Q4 2,211 (13.64%) 1.27 (1.19, 1.35) <0.0001 1.48 (1.37, 1.59) <0.0001  Yes 1,439 (15.61%)  SII Q1 293 (14.23%) Ref. Ref.  SII Q2 291 (12.98%) 0.90 (0.76, 1.07) 0.2318 0.95 (0.79, 1.14) 0.5672  SII Q3 393 (15.66%) 1.12 (0.95, 1.32) 0.1774 1.18 (0.99, 1.40) 0.0647  SII Q4 462 (19.17%) 1.43 (1.22, 1.68) <0.0001 1.48 (1.25, 1.76) <0.0001 IUD 0.7437 0.6791  No 8,915 (12.32%)  SII Q1 2,075 (11.34%) Ref. Ref.  SII Q2 2,046 (11.30%) 1.00 (0.93, 1.06) 0.8925 1.09 (1.02, 1.17) 0.0136  SII Q3 2,243 (12.45%) 1.11 (1.04, 1.18) 0.0011 1.25 (1.16, 1.34) <0.0001  SII Q4 2,551 (14.23%) 1.30 (1.22, 1.38) <0.0001 1.49 (1.39, 1.59) <0.0001  Yes 418 (16.38%)  SII Q1 79 (14.21%) Ref. Ref.  SII Q2 100 (15.70%) 1.12 (0.82, 1.55) 0.4724 1.11 (0.79, 1.55) 0.5527  SII Q3 117 (17.36%) 1.27 (0.93, 1.73) 0.1335 1.39 (1.00, 1.93) 0.0501  SII Q4 122 (17.81%) 1.31 (0.96, 1.78) 0.0874 1.35 (0.97, 1.87) 0.0738  Center 1 1,813 (11.22%) 0.8416 0.7236  SII Q1 405 (10.32%) Ref. Ref.  SII Q2 406 (10.11%) 0.98 (0.84, 1.13) 0.7499 1.01 (0.87, 1.18) 0.8834  SII Q3 477 (11.48%) 1.13 (0.98, 1.30) 0.0959 1.18 (1.01, 1.37) 0.0354  SII Q4 525 (12.92%) 1.29 (1.12, 1.48) 0.0003 1.42 (1.22, 1.65) <0.0001  Center 2 5,174 (11.19%)  SII Q1 1,228 (10.36%) Ref. Ref.  SII Q2 1,182 (10.25%) 0.99 (0.91, 1.08) 0.7810 1.08 (0.98, 1.18) 0.1034  SII Q3 1,281 (11.51%) 1.09 (1.00, 1.18) 0.0507 1.24 (1.13, 1.35) <0.0001  SII Q4 1,483 (13.03%) 1.30 (1.20, 1.41) <0.0001 1.49 (1.36, 1.63) <0.0001  Center 3 2,346 (18.79%)  SII Q1 521 (16.95%) Ref. Ref.  SII Q2 558 (17.45%) 1.04 (0.91, 1.18) 0.6002 1.19 (1.03, 1.37) 0.0200  SII Q3 602 (19.78%) 1.21 (1.06, 1.38) 0.0043 1.37 (1.18, 1.58) <0.0001  SII Q4 665 (20.94%) 1.30 (1.14, 1.47) <0.0001 1.49 (1.29, 1.72) <0.0001 In the BMI subgroup, the adjust model adjusted for: IUD, history of cesarean section, hypertension, diabetes, age, TCHO, CR, ALT, and GLU; in the cesarean section history subgroup, the adjust model adjusted for: IUD, hypertension, diabetes, age, TCHO, CR, ALT, GLU, and BMI ≥ 24 kg/m 2 (yes/no); in the IUD subgroup, the adjust model adjusted for: hypertension, diabetes, age, TCHO, CR, ALT, GLU, BMI ≥ 24 kg/m 2 (yes/no) and cesarean section history. Center 1: Huangpu Branch of Fudan University Obstetrics and Gynecology Hospital; Center 2: Yangpu Branch of Fudan University Obstetrics and Gynecology Hospital; Center 3: Tenth People’s Hospital Affiliated to Tongji University. In the center analysis, the adjust model adjusted for: hypertension, diabetes, age, TCHO,CR, ALT, GLU, BMI ≥ 24 kg/m 2 (yes/no), IUD, and cesarean section history. SII, systemic immune inflammation index; Q, quartile; BMI, body mass index; IUD, intrauterine device; OR, odds ratio; CI, confidence interval. Subgroup and center analysis of SII and adenomyosis In the BMI subgroup, the adjust model adjusted for: IUD, history of cesarean section, hypertension, diabetes, age, TCHO, CR, ALT, and GLU; in the cesarean section history subgroup, the adjust model adjusted for: IUD, hypertension, diabetes, age, TCHO, CR, ALT, GLU, and BMI ≥ 24 kg/m 2 (yes/no); in the IUD subgroup, the adjust model adjusted for: hypertension, diabetes, age, TCHO, CR, ALT, GLU, BMI ≥ 24 kg/m 2 (yes/no) and cesarean section history. Center 1: Huangpu Branch of Fudan University Obstetrics and Gynecology Hospital; Center 2: Yangpu Branch of Fudan University Obstetrics and Gynecology Hospital; Center 3: Tenth People’s Hospital Affiliated to Tongji University. In the center analysis, the adjust model adjusted for: hypertension, diabetes, age, TCHO,CR, ALT, GLU, BMI ≥ 24 kg/m 2 (yes/no), IUD, and cesarean section history. SII, systemic immune inflammation index; Q, quartile; BMI, body mass index; IUD, intrauterine device; OR, odds ratio; CI, confidence interval.

Additional resources and reagents are available from, and will be handled by her, the lead contact, Ying Wang ( [email protected] ). This study did not generate new unique reagents and materials. • All data generated or analyzed during this study are reasonably available from the corresponding author. • This paper does not report original code. • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request. All data generated or analyzed during this study are reasonably available from the corresponding author. This paper does not report original code. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

In this multicenter study, we demonstrate that elevated SII is independently associated with an increased risk of adenomyosis, exhibiting a nonlinear dose–response relationship in which the risk rises with SII below 1500 and plateaus beyond this threshold. Women in the SII Q4 had a 48% increased risk of adenomyosis compared to those in SII Q1.Subgroup analysis showed that among individuals in SII Q4, the risk was further increased by 49%, 48%, and 49% for those with BMI <24 kg/m 2 , no history of cesarean section, and no IUD use, respectively, compared to SII Q1. These findings possess originality and significant clinical relevance. The differential effects observed across subgroups underscore the complexity of adenomyosis etiology. 8 , 9 They not only highlight the potential role of SII in risk stratification but also suggest its possible association with adenomyosis. Furthermore, this study provides indications of the dominant inflammatory function in these specific populations, offering valuable directions for further research and disease prevention. Adenomyosis and endometriosis, though both categorized as endometriotic disorders, have distinct underlying mechanisms. 10 Previous studies have reported an association between SII and endometriosis, which partially supports our findings. For instance, Zhou et al. 11 studied 434 endometriosis patients, comprising 237 (55%) with cystic ovarian endometriosis, 130 (30%) with adenomyosis, and 67 (15%) with both conditions. When SII served as the indicator, the OR for endometriosis development was 19.73 (95% CI: 9.95–39.6, p < 0.001) relative to 517 controls. Additionally, Peng et al. 12 reported a significant positive association between SII levels and endometriosis risk (OR = 3.14, 95% CI: 2.22–4.45, p < 0.01). While the direction of this association of these findings was consistent with ours (OR = 1.48, 95% CI: 1.38–1.59, p < 0.0001), the magnitude of the risk increase observed by them was substantially higher. Whereas Zhou et al. explicitly included adenomyosis in their outcome definition, Peng et al. did not specify its inclusion for endometriosis. The ambiguity of the outcomes not only explains the divergence from our results but also precludes their ORs from being reliable measures of the SII-adenomyosis risk association. Furthermore, as a single-center study with a limited sample size ( n = 3,390), Peng et al. did not consider confounding factors, and the stratification method (age/education/pregnancy history) differed from ours, resulting in inconsistent subgroup results. Given the distinct pathophysiological mechanisms of adenomyosis and endometriosis, it remains unclear whether SII independently predicts the risk of either condition. Although Dong et al. 13 examined SII levels in adenomyosis patients, their analysis focused solely on identifying a nonlinear relationship between SII and the platelet-to-lymphocyte ratio (PLR), without evaluating adenomyosis as a clinical outcome. To address this gap, this multicenter study is to comprehensively evaluate the relationship between SII and adenomyosis risk. Our findings implicate SII in clinical assessment and provide evidence for targeted anti-inflammatory interventions in specific high-risk subgroups. Inflammatory responses promote the implantation and survival of ectopic endometrial tissue, ultimately facilitating disease development, 14 , 15 making them a key factor in the pathogenesis of adenomyosis. The elevation of SII is primarily driven by the synergistic pro-inflammatory effects of neutrophils and platelets, along with a relative decrease in lymphocyte counts under systemic inflammation. In adenomyosis, elevated neutrophils may directly disrupt the endometrium-myometrium interface and promote angiogenesis through the release of reactive oxygen species and matrix metalloproteinases, 16 this infiltration and activation align with the inherent inflammatory gene expression profile observed in eutopic endometrium. 17 Meanwhile, increased peripheral platelets are persistently activated and secrete abundant pro-inflammatory and pro-angiogenic factors (e.g., VEGF and TGF-β), 18 thereby accelerating disease progression. The relative reduction in lymphocyte counts, serving as the denominator, likely reflects an exhaustion of adaptive immune cells due to chronic inflammation, impairing the clearance of ectopic lesions. 19 , 20 This indicates an aggravated imbalance between pro-inflammatory effects (driven by neutrophils and platelets) and overall adaptive immune resources. However, when SII exceeds 1,500, the risk increase plateaus, likely reflecting a tissue self-limitation due to immune-inflammatory saturation. Thus, the SII, as a ratio-based index, quantifies the systemic pro-inflammatory burden and systematically captures the immune-inflammatory disequilibrium that promotes the progression of adenomyosis. Previous research has elucidated the pathogenesis of adenomyosis through several theories, including the invasion of endometrium into the myometrium and the tissue injury and repair (TIAR) mechanism. 21 Immune cells are involved throughout the disease process, which aligns with the systemic immune-inflammatory imbalance reflected by the SII. However, conclusions regarding the extent of local immune infiltration in lesions have been inconsistent across studies. For example, Wacheul et al. 22 observed reduced immune cell infiltration (particularly of T cells, NK cells, B cells, macrophages, and dendritic cells) in adenomyotic lesions, whereas Zhang et al. 3 proposed that immune cell infiltration and cytokine imbalance are central to pathogenesis. These discrepancies may arise from heterogeneity in research methodologies, study populations, and the lesional microenvironment. Notably, Liu et al. 23 identified an NKG2A + CD8 + T cell subset in ectopic lesions that correlated with disease severity, suggesting that T cell exhaustion may contribute to disease progression—a finding that provides a potential explanation for the pathological significance of decreased lymphocyte counts in the SII. Taken together, the SII, as a composite peripheral blood index, offers a complementary perspective that extends beyond localized lesion studies to characterize the systemic immune-inflammatory profile in adenomyosis and is more suitable for non-invasive assessment in clinical practice. This further underscores the necessity of our high-quality, multicenter retrospective study focusing on the SII. This study presents the groundbreaking finding that elevated SII levels in peripheral blood are consistently and positively associated with an increased risk of adenomyosis in each of the following subgroups independently: women with BMI < 24 kg/m 2 , those without a history of surgical delivery, and non-IUD users. This reveals a critical pathogenic role of systemic inflammation specifically within this demographic. Our findings suggest that in individuals who are overweight (BMI ≥ 24 kg/m 2 ), the systemic inflammatory signal reflected by SII may be obscured by more potent local inflammatory drivers. Specifically, when BMI reaches or exceeds 30, excessive visceral adipose tissue accumulation disrupts immune-related epigenetic regulatory mechanisms, thereby promoting autoimmune and inflammatory responses. 24 Furthermore, studies have confirmed that overweight or obese women are more susceptible to adenomyosis. 25 Therefore, the marked inflammatory state caused by overweight alone probably attenuates the observed relationship between SII and adenomyosis. Furthermore, Riggs et al. 26 reported a 25% prevalence of adenomyosis in women with a history of cesarean section, representing a 2.08-fold increased odds compared to those without such history. The incision into the uterine myometrium during surgery disrupts the natural barrier between the endometrium and myometrium—the endometrial-myometrial junction (EMJ). This disruption, combined with the potential iatrogenic implantation of endometrial cells, glands, and stroma during the procedure, facilitates the invasion of endometrial glands and stroma into the myometrium, potentially leading to the growth of ectopic lesions and disease development. 27 Consequently, our findings indicate that for women without a cesarean section history, spontaneous inflammation plays the predominant pathogenic role. Additionally, compelling evidence demonstrates that copper-containing IUDs induce significant local endometrial inflammatory responses, tissue damage, and dysregulation of key molecular pathways (e.g., the miR-144-3p/MT/NF-κB/MMP injury pathway and the THBS-1/TGF-β/SMAD3 repair pathway) via the release of Cu 2+ . 28 , 29 , 30 This constitutes the pathophysiological basis for IUD-associated side effects like menorrhagia, abnormal uterine bleeding, and dysmenorrhea. Although no direct evidence or widespread reports currently establish a definitive link between IUD use and adenomyosis onset, the pathophysiological parallels are striking. The persistent endometrial inflammation, injury, and impaired repair induced by IUDs share significant commonality with the core pathogenic mechanisms of adenomyosis—namely, disruption of the EMJ, abnormal invasion of endometrial tissue into the myometrium, and the establishment of a local chronic inflammatory microenvironment. 31 , 32 We therefore propose that the chronic inflammation and injury induced by IUDs (particularly copper IUDs) may account for the lack of a significant association between SII and IUD use in the subgroup analysis. This is because IUD use itself may act as a potent, independent risk factor for adenomyosis, potentially confounding the observed relationship with SII. In this study, we utilized a control group composed of women with benign gynecological conditions who presented symptoms similar to those of adenomyosis, rather than asymptomatic healthy individuals. This design enhances the clinical relevance of our findings, as it mirrors the real-world diagnostic challenge of differentiating adenomyosis from other common benign diseases with overlapping clinical manifestations, such as uterine fibroids or isolated endometriosis. Since some control conditions may involve low-grade inflammation, the observed SII-adenomyosis association likely represents a conservative estimate. Future multicenter studies should validate these findings through sensitivity analyses stratified by inflammatory burden. This study offers several key strengths. First, the primary strength lies in its multicenter design with a large sample size, which adjusted for key confounders, thereby enhancing the reliability of the findings. Second, the exposure factors utilized readily available laboratory measurements, enhancing clinical feasibility and potential for wider application. Furthermore, stratified analyses were conducted across the entire study population. This approach enabled a more precise assessment of the systemic inflammatory-immune status in women characterized by BMI < 24 kg/m 2 , absence of surgical delivery history, and no IUD use. These findings hold significant clinical implications for predicting and managing adenomyosis in this specific subgroup. In summary, this multicenter study demonstrates that the SII, while not a diagnostic tool, serves as a useful adjunct for risk stratification of adenomyosis in symptomatic outpatients. The association between SII and adenomyosis is particularly relevant in specific subgroups—including women with BMI < 24 kg/m 2 , those without a history of cesarean section, and non-IUD users—suggesting its potential for independent risk prediction and personalized management. To advance these findings, future large-scale prospective studies should not only validate the pathogenic role of SII and establish causality, but also focus on translating this knowledge into clinical practice. Key priorities will include developing integrated prediction models that combine SII with imaging and other laboratory parameters in larger multicenter cohorts, as well as defining clinically applicable SII cutoff values to enhance real-world utility. This study is subject to several inherent limitations. First, the retrospective observational design fundamentally prevents the establishment of a causal relationship between SII and adenomyosis, and the possibility of reverse causality cannot be ruled out. While prospective cohort studies or laboratory-based mechanistic investigations would be essential to clarify this direction of causality, such studies are not currently feasible due to practical constraints. Given these constraints, we have explicitly acknowledged this fundamental limitation, believing that this clarity enhances the academic integrity of our work while paving the way for future studies to resolve this important scientific question. Second, this study relied solely on a single baseline SII measurement, which precludes the assessment of temporal fluctuations in SII levels and their potential role in adenomyosis development. Third, the uniform application of a 3 standard deviation (SD) threshold across the entire cohort for extreme value exclusion, though based on the high consistency of laboratory platforms across centers, may not fully account for potential underlying differences across centers or subgroups, representing a limitation in data robustness. Fourth, due to inconsistent documentation standards and variable completeness of medical records across different centers and time periods in this multicenter retrospective study, we were unable to conduct a stratified analysis based on adenomyosis severity (e.g., imaging-based staging or symptom scores). This represents a notable gap in our descriptive characterization of the study population. Fifth, the statistical power for subgroup analyses was limited. Specifically, within the BMI ≥ 24 kg/m 2 subgroup, the restricted sample size necessitates cautious interpretation of the effect estimates, as the analysis may have been underpowered to detect true associations, increasing the risk of false-negative findings. Moreover, the overall sample size constraints, particularly in certain subgroups, rendered the data insufficient to support stable and reliable testing for higher-order interactions; therefore, we did not proceed to construct models involving triple or more interaction terms. Lastly, despite rigorous adjustment for numerous potential confounders guided by existing literature and clinical knowledge, the possibility of persistent residual confounding impacting the results cannot be fully discounted.

Adenomyosis, characterized by ectopic endometrial tissue within the myometrium, is a common gynecological disorder affecting ∼10% of reproductive-aged women. It causes symptoms including heavy menstrual bleeding, chronic pelvic pain, and infertility, significantly reducing quality of life and imposing substantial healthcare burdens. 1 Despite its prevalence, adenomyosis remains understudied compared to conditions like endometriosis. 2 Its pathogenesis involves aberrant inflammation and immune dysregulation, 3 yet comprehensive biomarkers reflecting systemic inflammatory status are lacking. The systemic immune inflammation index (SII), calculated as (platelets × neutrophils)/lymphocytes, is an integrative biomarker derived from routine blood counts. SII quantifies systemic inflammatory/immune balance and demonstrates prognostic utility in oncologic and cardiovascular disorders. 4 , 5 , 6 However, its role in benign gynecological conditions is underexplored. Given the centrality of inflammation in adenomyosis pathogenesis, 7 , 8 SII represents a promising but unvalidated biomarker for this condition. No large-scale studies have examined SII’s relationship with adenomyosis severity or progression, creating a critical knowledge gap. To address these limitations, our multicenter analysis provides the assessment of SII concentrations in patients with diagnosed adenomyosis. SII was further stratified by quartiles, and analyses were carefully adjusted for potential confounding factors. Subgroup analyses were performed based on body mass index (BMI), history of cesarean section, and intrauterine device (IUD) use to evaluate the robustness of the association between SII and adenomyosis. These methodological enhancements allow us to more rigorously assess the relationship between SII and adenomyosis risk. These results could refine risk stratification protocols and advance targeted anti-inflammatory interventions.

The authors declare no competing interests.

REAGENT or RESOURCE SOURCE IDENTIFIER Software and algorithms R Project for Statistical Computing R Foundation https://www.r-project.org/ SPSS 28 IBM https://www.ibm.com/spss Other Hospital Information System (HIS) Participating centers N/A Laboratory Information System (LIS) Participating centers N/A This retrospective, multicenter, observational study included 74,900 participants who underwent laparoscopic surgery between January 2018 and December 2024. Among them, 9,333 were diagnosed with adenomyosis, and 65,567 had other benign gynecological conditions presenting with at least one clinical symptom similar to those of adenomyosis, such as pain or heavy menstrual bleeding. The disease control group comprised patients with conditions including ovarian cysts (simple, corpus luteum, and follicular cysts), teratomas, uterine fibroids, isolated endometriosis and ovarian fibromas. It is important to note that only cases of endometriosis coexisting with adenomyosis were excluded; isolated endometriosis was retained as part of the control group, which was entirely composed of symptomatic patients with benign gynecological diseases clinically comparable to adenomyosis. All participants underwent examination and laparoscopic surgery at one of the three centers: Huangpu Branch of Fudan University Obstetrics and Gynecology Hospital, Yangpu Branch of Fudan University Obstetrics and Gynecology Hospital, or Tenth People’s Hospital Affiliated to Tongji University. The screening procedure is visualized in figure. During the initial visit, prior to laparoscopic surgery, clinical data was compiled and laboratory tests were carried out. The Hospital Information System (HIS) and Laboratory Information System (LIS) served as the sources for all clinical records and test outcomes. The clinical laboratories of all three participating centers are accredited by the China National Accreditation Service for Conformity Assessment (CNAS) and consistently participate in and pass the External Quality Assessment (EQA) programs organized by the National Center for Clinical Laboratories and the Shanghai Center for Clinical Laboratories. Complete blood count items are included in the mutual recognition program for laboratory results within the Shanghai region. The three centers have achieved a high level of consistency in instrument platforms, quality control systems, and result traceability, ensuring strong comparability of hematological parameters and derived indices such as the SII across sites. Exclusion criteria for this study were as follows: pathological diagnosis of malignancy; endometriosis with adenomyosis; hydrosalpinx; ectopic pregnancy; missing medical history records (including BMI, cesarean section history, or IUD usage) or key laboratory indicators; absence of SII data; or SII values identified as extreme outliers based on a uniform 3SD threshold applied to the overall cohort distribution. This study received approval from the ethics committees of all participating centers, specifically: the Ethics Committee of the Obstetrics and Gynecology Hospital affiliated with Fudan University (Approval No. 2024-214) and the Ethics Committee of Shanghai Tenth People’s Hospital (Approval No. SHSY-IEC-6.0/26K64/P01). This study involved a retrospective analysis of fully anonymized clinical data. Given this study design, a formal waiver of informed consent was granted by the institutional review boards. The research was conducted in accordance with the Declaration of Helsinki. Flowchart of the participant selection process A total of 74,900 complete samples—including cases of cystic cysts, ovarian fibromas, simple ovarian cysts, corpus luteum cysts, follicular cysts, teratomas, uterine fibroids, and adenomyosis—were analyzed. These comprised 16,157 samples (21.57%) from the Huangpu Branch of Fudan University Obstetrics and Gynecology Hospital, 46,255 (61.76%) from the Yangpu Branch of Fudan University Obstetrics and Gynecology Hospital, and 12,488 (16.67%) from Tenth People’s Hospital Affiliated to Tongji University. SII, systemic immune inflammation index; BMI, body mass index; IUD, intrauterine device; SD, standard deviation. Flowchart of the participant selection process A total of 74,900 complete samples—including cases of cystic cysts, ovarian fibromas, simple ovarian cysts, corpus luteum cysts, follicular cysts, teratomas, uterine fibroids, and adenomyosis—were analyzed. These comprised 16,157 samples (21.57%) from the Huangpu Branch of Fudan University Obstetrics and Gynecology Hospital, 46,255 (61.76%) from the Yangpu Branch of Fudan University Obstetrics and Gynecology Hospital, and 12,488 (16.67%) from Tenth People’s Hospital Affiliated to Tongji University. SII, systemic immune inflammation index; BMI, body mass index; IUD, intrauterine device; SD, standard deviation. This study designated the SII as the exposure variable. Given that repeated preoperative laboratory testing is not part of the routine clinical protocol, only a single baseline SII measurement was available for analysis. Specifically, venous blood samples were obtained at the initial clinical visit, a mean of 0.91 (SD 0.23) months before laparoscopic surgery. Lymphocyte, neutrophil, and platelet counts (measured in 10 9 /L) were quantified using automated hematology analyzers. Results from all three centers met external quality assurance standards, ensuring comparability. SII was derived by multiplying platelet and neutrophil counts, then dividing by lymphocyte counts. The outcome of this study was the presence of adenomyosis. To guarantee diagnostic accuracy, we employed rigorous benchmark criteria necessitating histopathologic verification of laparoscopically resected entire-lesion specimens. All cases were pathologically confirmed. We stratified the SII into quartiles, spanning the lowest (Q1) to highest (Q4) values. Continuous measures are reported as mean ± SD, whereas categorical variables are expressed as percentages. Differences in covariates across SII quartiles were compared using one-way ANOVA for continuous variables and Pearson chi-square test for categorical variables. Multivariable logistic regression analyses were conducted to investigate associations between SII and adenomyosis. The crude model included no covariates, while the adjusted model accounted for: IUD use; cesarean section history; hypertension; diabetes; age; BMI; TCHO; CR; ALT; and GLU. To assess potential multicollinearity, variance inflation factors (VIFs) were calculated for all included covariates; all VIF values were below 5, indicating no substantial multicollinearity. ORs with corresponding 95% CIs quantified the SII-adenomyosis relationship. Model fit was evaluated using the Akaike Information Criterion (AIC); the AIC decreased from 47005 in the crude model to 46861 in the adjusted model, suggesting improved overall fit. The model’s discriminative ability was further assessed via ROC analysis, yielding an AUC of 0.74. To evaluate the robustness of the primary findings, multiple sensitivity analyses were performed, which confirmed that the direction and magnitude of the association between SII and adenomyosis remained consistent. We used trend testing to evaluate the relationship between SII and the risk of adenomyosis. Furthermore, to specifically examine the nonlinear dose-response relationship and identify potential inflection points, we conducted a threshold analysis using piecewise linear regression, with the threshold value determined by testing a series of candidate points based on the smoothing spline curve. The Likelihood ratio test was used to compare the piecewise model with the standard linear model, and a p -value <0.05 was considered to indicate a significant improvement in fit, confirming nonlinearity. Additionally, a generalized additive model was applied to fit a smooth curve to visually and quantitatively assess the nonlinear relationship between SII levels and adenomyosis risk. Subgroup analyses evaluated effect modifications by BMI status, cesarean section history, and IUD usage. Interaction tests were performed across subgroups and among the three centers, with a p -value >0.05 indicating no significant interaction effect.

This study was supported by the 10.13039/501100001809 National Natural Science Foundation of China (grant nos. 82372701 and 81930066 ), the Key Medical Disciplines of Xuhui District , Shanghai ( SHXHZDXK202322 ), and the Tongji University Medicine-X Interdisciplinary Research Initiative ( 2025-0553-ZD-08 ).