Development of a 5-year Recurrence Risk Prediction Model After Conservative Surgery for Adenomyosis Based on Clinical and Imaging Features

Dysmenorrhea and menorrhagia are common consequences of adenomyosis. While conservative surgery can ef- fectively preserve fertility in women with adenomyosis, they are still vulnerable to postoperative recurrence, for which a reliable long-term predictive tool is lacking. This study aimed to develop and validate a 5-year recurrence predictive model for adeno- myosis patients after conservative surgery based on their clinical and imaging features.

In this retrospective study, 150 women aged 18–50 years who underwent uterus-preserving surgery for adenomyosis were analyzed. Clinical data, including imaging parameters, surgical characteristics, and postoperative management, were col- lected. Recurrence was defined as either a ≥3-point increase in Visual Analog Scale score for dysmenorrhea or a ≥50% increase in Pictorial Blood Assessment Chart score within five years. Multivariate Cox regression was used to construct a nomogram, with its predictive performance evaluated using concordance index (C-index), time-dependent receiver operating characteristic curves, calibration, and decision curve analysis (DCA).

Four independent predictors were identified: older age, larger uterine volume, shorter duration of postoperative hor- monal therapy, and concomitant endometriosis. The nomogram demonstrated good discriminative ability (C-index 0.766; AUCs 0.68, 0.73, 0.76 at 15, 24, and 48 months, respectively), along with reliable calibration and evident clinical net benefit. Kaplan– Meier analysis revealed that the nomogram effectively distinguished risk groups, with five-year recurrence-free survival rates of 78% in the low-risk group and 17% in the high-risk group.

By integrating clinical and imaging variables, the nomogram developed in this study demonstrates strong clinical applicability, accurately predicting recurrence risk in adenomyosis patients after conservative surgery and guiding personalized postoperative management.

adenomyosis; conservative surgery; recurrence; nomogram; risk prediction

Adenomyosis is a common gynecological disorder characterized by the presence of ectopic endometrial glands and stroma within the myometrium, leading to progressive uterine enlargement, chronic pelvic pain, dysmenorrhea, and menorrhagia [ 1,2]. The condition affects up to 20– 30% of women of reproductive age, imposing a substantial clinical and social burden due to impaired quality of life, infertility, and the need for repeated interventions [ 3]. Al- though hysterectomy remains the definitive treatment, most patients of childbearing age who wish to preserve fertility and maintain uterine integrity opt for conservative surgical approaches [4]. Conservative surgery is an important uterus-sparing treatment option for adenomyosis, effectively relieving pain and menorrhagia while preserving fertility in patients of reproductive age [ 4]. However, symptomatic recurrence remains a major clinical challenge in patients receiving sur- gical intervention, with approximately one-third of the pa- tients experiencing symptom relapse within five years, de- pending on surgical technique, disease extent, and postop- erative management [ 5,6]. Identifying patients at higher risk of recurrence is therefore essential to optimize post- operative hormonal therapy and follow-up strategies. Previous studies have explored the predictive value of various clinical and surgical factors for adenomyosis recur- rence, such as age, parity, coexistence of endometriosis, extent of excision, and duration of postoperative hormonal suppressive therapy [ 7,8]. In recent years, a growing body of studies have increasingly established imaging-derived parameters, including junctional zone (JZ) thickness, uter- ine volume, and adenomyosis phenotype, as objective in- 3065 dicators of disease burden and myometrial involvement [9,10]. Nevertheless, most of these studies are limited by small sample sizes, heterogeneous inclusion criteria, rela- tively short follow-up durations, and inconsistent incorpo- ration of imaging indicators, thereby diminishing the clini- cal applicability of the identified factors [ 11,12]. Currently, there is no long-term predictive model that incorporates imaging variables to assess postoperative re- currence in adenomyosis patients following conservative surgery. Therefore, the present study aimed to develop and internally validate a 5-year recurrence predictive model that combines clinical and imaging features, including JZ thick- ness, uterine volume, and adenomyosis phenotype, together with key clinical parameters such as age, coexistence of en- dometriosis, and postoperative hormonal suppressive ther- apy duration. This model is expected to provide a practi- cal tool for personalized postoperative risk assessment and management.

Study Design and Setting This study was designed as a retrospective cohort anal- ysis conducted at The Fourth Affiliated Hospital of Soo- chow University (Suzhou Dushu Lake Hospital), a tertiary referral center specializing in gynecological surgery. A to- tal of 150 patients diagnosed with adenomyosis who un- derwent conservative surgical treatment between February 2018 and February 2023 were screened for eligibility. The study period was defined to guarantee a minimum follow- up of 12 months for all patients by the database lock, with a subset of patients followed for up to five years. All rel- evant clinical, surgical, imaging, and follow-up data were extracted from the institutional electronic medical record system and imaging archives. Study Population Participants were women aged 18–50 years who had a confirmed diagnosis of adenomyosis. The diagnosis was established on the basis of either clinical manifestations combined with imaging findings according to the Morpho- logical Uterus Sonographic Assessment (MUSA) criteria or magnetic resonance imaging (MRI), or histopathologi- cal evidence when available [ 13,14]. Both diffuse and fo- cal types of adenomyosis were included. Eligible patients underwent conservative uterus-preserving surgery without hysterectomy, including focal adenomyotic lesion excision or uterine reconstructive repair. Furthermore, only those with standardized postoperative follow-up records from outpatient visits or structured telephone interviews, and with sufficient documentation of symptom changes for at least 12 months, were included in the analysis. Patients were excluded if they had a prior hysterec- tomy or underwent hysterectomy during index admission. Additional exclusion criteria include: (1) diagnosis of ma- lignancy or severe systemic disease during follow-up; (2) missing data exceeding 40% in any of the key variables, including age, body mass index (BMI), coexistence of en- dometriosis, JZ thickness, uterine volume, adenomyosis phenotype, and duration of postoperative hormonal sup- pressive therapy; and (3) the need for re-intervention within three months after conservative surgery for reasons other than perioperative complications, such as suspected resid- ual adenomyotic lesions confirmed by imaging, uncon- trolled symptoms unresponsive to early medical therapy, or newly developed severe uterine bleeding unrelated to sur- gical complications. Data Collection and V ariables Data were extracted from the institutional electronic medical record system, operative notes, imaging archives, and follow-up records. V ariables were selected for analy- sis based on their clinical significance, previously reported associations with adenomyosis recurrence, and availability within the dataset. Clinical variables (e.g., age, BMI, re- productive history [pregnancy and parity], concomitant en- dometriosis, and postoperative hormonal therapy duration) were chosen because they have been widely reported to in- fluence disease recurrence or response to treatment. Imag- ing variables, including JZ thickness, uterine volume, and adenomyosis phenotype, were incorporated as objective in- dicators of disease burden and myometrial involvement ac- cording to published imaging studies [ 5,9]. All imaging assessments were independently performed by two expe- rienced radiologists, and discrepancies were resolved by a third reviewer to ensure consistency. Surgical variables included the extent of lesion ex- cision (categorized as localized or extensive), the number of myometrial repair layers, and the method of hemosta- sis (categorized as suture, energy-based, or combined techniques). Data on postoperative management encom- passed the type of hormonal suppressive therapy, such as gonadotropin-releasing hormone agonists, dienogest, levonorgestrel-releasing intrauterine system, or combined oral contraceptives, as well as the total duration of treat- ment in months. Outcome Definition The primary outcome of this study was symptom re- currence within five years after conservative surgery for adenomyosis. Recurrence was defined using standardized clinical criteria. Dysmenorrhea severity was assessed using the Visual Analogue Scale (V AS), a validated and widely used scoring system for pain intensity [ 15]. Menstrual blood loss was quantified using the Pictorial Blood Assess- ment Chart (PBAC), originally developed for objective es- timation of menstrual blood volume [ 16]. Recurrence was defined as an increase of ≥3 points in V AS score or ≥50% increase in PBAC score from the patient’s lowest postoper- ative score during follow-up. Time to recurrence was cal- 3066 Fig. 1. Nomogram for predicting postoperative recurrence after conservative surgery for adenomyosis. The nomogram includes six variables: age, junctional zone (JZ) thickness, uterine volume (UterusV ol), adenomyosis phenotype (AM type; 0 = focal, 1 = diffuse, 2 = mixed), duration of postoperative hormonal suppressive therapy (TxDuration), and concomitant endometriosis (0 = no, 1 = yes). culated from the date of surgery to the first documented oc- currence of symptom relapse, regardless of whether it was dysmenorrhea or menorrhagia. Patients without recurrence at the end of follow-up were censored at their last visit. Statistical Analysis All statistical analyses were performed using IBM SPSS Statistics 26.0 (IBM Corp., Armonk, NY , USA) and R software version 4.3.2 (R Foundation for Statis- tical Computing, Vienna, Austria). Baseline character- istics were summarized descriptively. Continuous vari- ables were tested for normality using the Shapiro–Wilk test. The Mann–Whitney U test was employed to analyze inter- group data that do not follow a normal distribution, which are expressed as medians and interquartile ranges (IQRs), whereas the Chi-square test was used to compare categor- ical variables, which are presented as counts and percent- ages. Univariate Cox proportional hazards regression anal- yses were conducted to evaluate the association between each variable and the risk of recurrence. V ariables with clinical significance or p < 0.05 in the univariate analysis were subsequently entered into multivariable Cox regres- sion to identify independent predictors. A nomogram that enables individualized prediction of recurrence risk at dif- ferent postoperative time points was then developed based on the final multivariable Cox model. V ariables of clinical significance, such as JZ thickness and adenomyosis pheno- type, were retained in the final model regardless of their statistical significance, in accordance with Transparent Re- porting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis recommendations [ 17]. Model performance was assessed in terms of its dis- criminative ability, calibration, and clinical utility. Dis- criminative performance of the model was evaluated by cal- culating the concordance index (C-index) and plotting time- dependent receiver operating characteristic (ROC) curves to determine the corresponding area under the curve (AUC). Calibration was examined using bootstrap resampling with 1000 iterations, and plots were generated to compare pre- dicted and observed probabilities of recurrence. Decision curve analysis (DCA) was applied to estimate the net clini- cal benefit of the predictive model across a range of thresh- old probabilities. Finally, patients were stratified into high- and low-risk groups according to their absolute predicted recurrence risk at 24 months, and Kaplan–Meier survival curves were used to compare recurrence-free survival be- tween groups, with significance determined by the log-rank test. 3067 Table 1. Baseline characteristics. Overall (n = 150) Non-recurrence group (n = 97) Recurrence group (n = 53) Z/χ2 p Age (years) 34.00 [30.00, 37.00] 33.00 [29.00, 37.00] 34.00 [31.00, 39.00] –1.712 0.087 BMI (kg/m2) 22.10 [19.52, 24.40] 22.60 [20.00, 24.80] 21.10 [19.30, 23.20] –1.980 0.048 Duration of follow-up (months) 27.00 [18.00, 38.00] 30.00 [18.00, 42.00] 24.00 [18.00, 38.00] –0.538 0.591 JZ thickness (mm) 14.85 [12.93, 16.80] 13.90 [12.00, 15.50] 16.30 [14.90, 18.00] –5.295 <0.001 Uterine volume (mL) 178.00 [141.00, 238.00] 161.00 [128.00, 201.00] 238.00 [193.00, 304.00] –5.772 <0.001 TxDuration (months) 7.00 [2.00, 11.00] 10.00 [6.00, 12.00] 2.00 [0.00, 6.00] –5.958 <0.001 Pregnancy (%) 0.029 0.864 No 15 (10.0) 10 (10.3) 5 (9.4) Y es 135 (90.0) 87 (89.7) 48 (90.6) Cesarean section (%) 0.035 0.852 No 41 (27.3) 27 (27.8) 14 (26.4) Y es 109 (72.7) 70 (72.2) 39 (73.6) Endometriosis (%) 45.730 <0.001 No 89 (59.3) 77 (79.4) 12 (22.6) Y es 61 (40.7) 20 (20.6) 41 (77.4) Adenomyosis phenotype (%) 26.795 <0.001 Diffuse 76 (50.7) 34 (35.1) 42 (79.2) Focal 42 (28.0) 36 (37.1) 6 (11.3) Mixed 32 (21.3) 27 (27.8) 5 (9.4) Extent of lesion excision (%) 1.933 0.164 Localized 65 (43.3) 38 (39.2) 27 (50.9) Extensive 85 (56.7) 59 (60.8) 26 (49.1) Repair layers (%) 4.297 0.117 1 13 (8.7) 5 (5.2) 8 (15.1) 2 78 (52.0) 52 (53.6) 26 (49.1) ≥3 59 (39.3) 40 (41.2) 19 (35.8) Hemostasis method (%) 0.381 0.827 Suture 52 (34.7) 32 (33.0) 20 (37.7) Energy-based 31 (20.7) 21 (21.6) 10 (18.9) Combined 67 (44.7) 44 (45.4) 23 (43.4) PostopTx (%) 12.298 0.015 GnRH agonist 26 (17.3) 18 (18.6) 8 (15.1) Dienogest 33 (22.0) 24 (24.7) 9 (17.0) LNG-IUS 33 (22.0) 25 (25.8) 8 (15.1) COCs 25 (16.7) 17 (17.5) 8 (15.1) None 33 (22.0) 13 (13.4) 20 (37.7) Notes: V alues that do not conform to the normal distribution are presented as median [IQR]. Abbreviations: BMI, body mass index; COCs, combined oral contraceptives; GnRH, gonadotropin-releasing hormone; JZ, junctional zone; LNG-IUS, levonorgestrel-releasing intrauterine system; TxDuration, duration of postoperative hormonal therapy; PostopTx, post- operative treatment.

Baseline Characteristics A total of 150 patients were included, comprising 97 (64.7%) in the non-recurrence group and 53 (35.3%) in the recurrence group (Table 1). Compared with the non- recurrence group, patients who experienced recurrence had a significantly lower BMI (21.1 vs. 22.6 kg/m 2, p = 0.048), greater JZ thickness (16.3 vs. 13.9 mm, p < 0.001), and larger uterine volume (238 vs. 161 mL, p < 0.001). The dif- fuse type of adenomyosis was significantly more common in the recurrence group (79.2% vs. 35.1%), whereas focal and mixed types predominated in the non-recurrence cases (p < 0.001). In addition, patients with recurrence showed a markedly higher prevalence of concomitant endometrio- sis (77.4% vs. 20.6%, p < 0.001) and a shorter duration of postoperative hormonal suppressive therapy (median 2 vs. 10 months, p < 0.001). The proportion of patients without postoperative treatment was also higher in the recurrence group (37.7% vs. 13.4%, p = 0.015). Other baseline char- 3068 Fig. 2. Model performance evaluation. (A–C) Time-dependent receiver operating characteristic (ROC) curves at 15, 24, and 48 months with area under the curve (AUC) values of 0.68, 0.73, and 0.76, respectively. (D–F) Calibration plots for 15-, 24-, and 48-month recurrence probabilities showing agreement between predicted and observed outcomes. acteristics, including age, parity, history of cesarean sec- tion, extent of lesion excision, number of repair layers, and hemostasis method, showed no significant differences be- tween the two groups (all p > 0.05). Univariate and Multivariate Cox Regression Analysis Univariate Cox regression showed that age (Hazard Ratio [HR] = 1.072, 95% CI = 1.015–1.132, p = 0.013), JZ thickness (HR = 1.160, 95% CI = 1.063–1.266, p < 0.001), uterine volume (HR = 1.005, 95% CI = 1.003–1.008, p < 0.001), adenomyosis phenotype (HR = 0.421, 95% CI = 0.267–0.665, p < 0.001), concomitant endometriosis (HR = 4.850, 95% CI = 2.548–9.233, p < 0.001), postoperative treatment (HR = 1.265, 95% CI = 1.035–1.547, p = 0.022), and treatment duration (HR = 0.857, 95% CI = 0.804–0.913, p < 0.001) were significantly associated with recurrence. Based on the multivariate Cox regression results, older age (HR = 1.069, 95% CI = 1.004–1.138, p = 0.037), larger uterine volume (HR = 1.003, 95% CI = 1.001–1.006, p = 0.018), a significantly shorter duration of postoperative therapy (HR = 0.905, 95% CI = 0.843–0.971, p = 0.006), and concomitant endometriosis (HR = 2.564, 95% CI = 1.27–5.178, p = 0.009) remained significantly associated with recurrence, making them the four independent predic- tors of recurrence. During the analysis, JZ thickness, ade- nomyosis phenotype, and postoperative treatment lost sta- tistical significance following adjustment (Table 2). Nomogram Development and Model Performance V ariables with statistical significance (age, uterine volume, duration of postoperative hormonal suppressive therapy, and concomitant endometriosis) in the multivari- ate Cox regression analysis were included in the nomogram (Fig. 1). In addition, JZ thickness and adenomyosis phe- notype were incorporated because of their well-recognized clinical relevance as imaging indicators of disease burden and morphological subtype, despite not reaching statistical significance in multivariate analysis. The nomogram pro- vided an individualized prediction of recurrence risk at 15, 24, and 48 months after surgery, with higher total scores corresponding to higher recurrence probabilities. The discriminative ability of the model was accept- able, with a C-index of 0.766 in the overall cohort. Boot- strap validation with 1000 resamples confirmed robust in- ternal validity, yielding a corrected C-index of 0.767. Time- dependent ROC analyses demonstrated AUC values of 0.68 3069 Table 2. Univariate and multivariate Cox regression analysis of risk factors for recurrence after conservative surgery for adenomyosis. V ariable Univariate analysis Multivariate analysis HR (95% CI) p HR (95% CI) p Age 1.072 (1.015–1.132) 0.013 1.069 (1.004–1.138) 0.037 BMI 0.916 (0.833–1.008) 0.072 Pregnancy 1.063 (0.423–2.673) 0.896 Cesarean section 1.195 (0.648–2.203) 0.568 Endometriosis 4.850 (2.548–9.233) <0.001 2.564 (1.27–5.178) 0.009 Duration of follow-up 0.000 (0–Inf) 0.984 JZ thickness 1.160 (1.063–1.266) <0.001 1.107 (0.98–1.251) 0.102 Uterine volume 1.005 (1.003–1.008) <0.001 1.003 (1.001–1.006) 0.018 Adenomyosis phenotype 0.421 (0.267–0.665) <0.001 0.73 (0.427–1.249) 0.250 Extent of lesion excision 0.737 (0.429–1.265) 0.268 Repair layers 0.731 (0.48–1.113) 0.144 Hemostasis method 0.952 (0.702–1.29) 0.749 PostopTx 1.265 (1.035–1.547) 0.022 0.957 (0.785–1.167) 0.665 TxDuration 0.857 (0.804–0.913) <0.001 0.905 (0.843–0.971) 0.006 Abbreviations: HR, hazard ratio; CI, confidence interval; Inf, infinity. Fig. 3. Decision curve analysis (DCA) of the recurrence-prediction model. (A) DCA curves showing the net benefit of the Cox model, clinical rules, “all”, and “none” strategies across a range of threshold probabilities. (B) DCA at the fixed 24-month time point, illustrating the net benefit of the Cox model compared with clinical rules, “all”, and “none” strategies. (95% CI: 0.644–0.721), 0.73 (95% CI: 0.691–0.763), and 0.76 (95% CI: 0.719–0.795) at 15, 24, and 48 months, re- spectively (Fig. 2A–C), indicating stable predictive perfor- mance over time. Calibration plots for 15-, 24-, and 48- month predictions (Fig. 2D–F) showed close agreement be- tween predicted and observed probabilities, suggesting no significant overfitting. The numbers of patients remaining at risk at these time points were approximately 140, 125, and 100, respectively, indicating adequate sample sizes to ensure reliable calibration, particularly at the later time point. Decision curve analysis further indicated that the nomogram consistently provided a greater net clinical ben- efit than the traditional clinical rules when the threshold probability ranged between 0.15 and 0.45 (Fig. 3). Risk Stratification A 24-month predicted recurrence risk threshold of ≥30% was applied, which was selected because it falls 3070 Fig. 4. Kaplan–Meier curves of recurrence-free survival stratified by 24-month predicted recurrence risk. Patients with a predicted risk of ≥30% at 24 months (high-risk group, n = 31) had significantly higher recurrence rates than those with <30% risk (low-risk group, n = 119). within the DCA-identified optimal threshold probability range, where the model provides the greatest net clinical benefit (Fig. 3B). Using this threshold, 31 patients (20.7%) were classified as high-risk and 119 (79.3%) as low-risk. The five-year recurrence-free survival was 78% in the low- risk group and 17% in the high-risk group (Fig. 4), with a statistically significant difference between the two groups (log-rank p < 0.0001).

In this study, a nomogram integrating clinical and imaging parameters was developed and internally validated to predict 5-year postoperative recurrence after conserva- tive surgery for adenomyosis. The model showed good discriminative ability (C-index 0.766) and calibration, with time-dependent AUCs increasing from 0.68 to 0.76 across 15–48 months, reflecting stable and reliable performance. These findings suggest that the selected variables—age, uterine volume, JZ thickness, adenomyosis phenotype, du- ration of postoperative hormonal suppressive therapy, and coexistence of endometriosis—may serve as valuable pre- dictors for long-term recurrence risk. The recurrence rate of 35.3% observed in this study aligns with previous research [5], which showed recurrence rates ranging from 30% to 40% following conservative surgery. Several studies have identified age, uterine size, and incomplete lesion resection as major risk factors influ- encing postoperative outcomes [ 5,18]. Our findings con- firm that larger uterine volume and shorter duration of post- operative hormonal suppressive therapy are independently associated with higher recurrence risk, consistent with ear- lier literature emphasizing disease burden and insufficient hormonal suppression as key contributors. Imaging indicators such as JZ thickness and adeno- myosis phenotype have been recognized as objective mark- ers of disease severity and morphological subtype [ 9]. Al- though these parameters were not statistically significant in multivariate analysis, they were retained in the final model due to their strong biological plausibility and extensive prior validation as imaging indicators of myometrial inva- sion and treatment response [ 19]. Moreover, the model’s slight improvement in discriminative performance at later follow-up time points (24–48 months) may reflect the de- layed manifestation of true recurrences, as transient post- operative inflammatory or hormonal changes could obscure early symptom differentiation [ 5,20]. The current nomogram offers a clinically practical ap- proach for individualized postoperative management. Pa- tients classified as high-risk may benefit from prolonged postoperative hormonal suppressive therapy, early imaging surveillance, or fertility counseling. By integrating both 3071 clinical and imaging markers, the model connects tradi- tional risk factor analysis with individualized recurrence prediction, thereby facilitating evidence-based follow-up planning. The main strengths of this study include its relatively large, well-characterized surgical cohort, the use of stan- dardized imaging protocols, and long-term (5-year) follow- up data, which enhance the robustness of the findings. However, several limitations should be noted. As a single- center retrospective study, potential selection bias and in- complete control of confounding factors cannot be fully ex- cluded. The model was only internally validated, and exter- nal validation in larger, multicenter prospective cohorts is needed to confirm its generalizability. In addition, hetero- geneity in surgical techniques and postoperative treatment strategies may have influenced the research outcomes, and imaging parameters could be affected by interobserver vari- ability. Furthermore, molecular biomarkers and advanced imaging features such as radiomics, which have additional predictive value, were not included in our analysis. Future research should therefore focus on multicenter prospective validation, incorporation of molecular and radiomic signa- tures, and development of dynamic predictive tools that up- date risk over time. Such efforts may refine individual- ized risk assessment and ultimately improve long-term out- comes for women undergoing conservative surgery for ade- nomyosis.

This study highlights the value of integrating clinical and imaging characteristics into a nomogram for predicting recurrence risk after conservative surgery for adenomyosis. The proposed model serves as a practical tool for individ- ualized postoperative management, supporting more accu- rate risk stratification and clinical decision-making. Availability of Data and Materials The data used to support the findings of this study are available from the corresponding author upon request. Author Contributions Study concept and design: ANS and LLH; Anal- ysis and interpretation of data: XQC; Drafting of the manuscript: ANS; Critical revision of the manuscript for important intellectual content: ANS, XQC and LLH; Sta- tistical analysis: XQC; Study supervision: all authors. All authors have read and approved the final manuscript and agreed to be accountable for all aspects of the work, ensur- ing that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Ethics Approval and Consent to Participate This study was approved by The Fourth Affiliated Hospital of Soochow University (Suzhou Dushu Lake Hos- pital) (2024-241023). Given the retrospective nature of the analysis, the requirement to obtain patients’ informed con- sent was waived by the ethics committee. All data were anonymized to protect patient confidentiality in accordance with the principles of the Declaration of Helsinki. Acknowledgment Not applicable. Funding This research received no external funding. Conflict of Interest The authors declare no conflict of interest.

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