Analysis of dysmenorrhea-related factors in adenomyosis and development of a risk prediction model

Archives of Gynecology and Obstetrics https://doi.org/10.1007/s00404-025-07967-y GENERAL GYNECOLOGY Analysis of dysmenorrhea‑related factors in adenomyosis and development of a risk prediction model Yudan Fu1 · Xin Wang1 · Xinchun Yang1 · Ruihua Zhao1 Received: 17 September 2024 / Accepted: 19 January 2025 © The Author(s) 2025 Abstract Objective To explore factors related to dysmenorrhea in adenomyosis and construct a risk prediction model. Methods A cross-sectional survey involving 1636 adenomyosis patients from 37 hospitals nationwide (November 2019– February 2022) was conducted. Data on demographics, disease history, menstrual and reproductive history, and treatment history was collected.Patients were categorized into dysmenorrhea and non-dysmenorrhea groups. Multivariate logistic regression analyzed factors influencing dysmenorrhea, and a risk prediction model was created using a nomogram. The model’s performance was evaluated through ROC curve analysis, C-index, Hosmer–Lemeshow test, and bootstrap method The nomogram function was used to establish a nomogram model. The model was evaluated using the area under the ROC curve (AUC), C-index, Hosmer–Lemeshow goodness-of-fit test, and bootstrap method. Patients were scored based on the nomogram, and high-risk groups were delineated. Results Dysmenorrhea was present in 61.31% (1003/1636) of the patients. Univariate analysis showed significant differences (P < 0.05) between groups in age at onset, course of disease, oligomenorrhea, menorrhagia, number of deliveries, pelvic inflammatory disease, family history of adenomyosis, exercise, and excessive menstrual fatigue. Significant factors included menorrhagia, multiple deliveries, pelvic inflammatory disease, and family history of adenomyosis as risk factors. Older age at onset, oligomenorrhea, and exercise were identified as protective factors. The model’s accuracy, discrimination, and reliability were acceptable, and a risk score > 88.5 points indicated a high-risk group. Conclusion Dysmenorrhea is prevalent among adenomyosis patients. Identifying and mitigating risk factors, while leveraging protective factors, can aid in prevention and management. The developed model effectively predicts dysmenorrhea risk, facilitating early intervention and treatment. Keywords Adenomyosis · Dysmenorrhea · Related factors · Logistic · Clinical prediction model What does this study add to the clinical work Yudan Fu and Xin Wang shared first authorship. * Ruihua Zhao 1 Our study identifies multiple deliveries, menorrhagia, pelvic inflammatory disease, and family history of adenomyosis as significant risk factors for dysmenorrhea in adenomyosis patients, while older age at onset, infrequent menstruation, and regular exercise are protective factors. The developed risk prediction model effectively stratifies high-risk populations, facilitating early intervention and management strategies to mitigate dysmenorrhea in clinical practice. Department of Gynecology, Guang ‘Anmen Hospital, Chinese Academy of Chinese Medical Sciences, No. 5, North Line Ge Street, Beijing 10053, Xicheng District, PR China Vol.:(0123456789) Archives of Gynecology and Obstetrics Introduction Adenomyosis (AM) is a refractory, benign, estrogen-dependent disease characterized by the invasion of endometrium tissue into the myometrium and stroma. It affects 10–57% of women of reproductive age and commonly presents with dysmenorrhea, pelvic pain, abnormal uterine bleeding, and infertility [1–3]. Symptoms are recurrent and persistent, with long-term, progressively worsening pain, difficult-to-treat infertility, and significant economic burdens leading to depression and anxiety in patients, impacting their physical and mental health, social relationships, and work ability.Research has reported that the public health costs of endometriosis (EM) and adenomyosis are high and can be comparable to those of chronic diseases like diabetes and rheumatoid arthritis [4]. Among the AM population, 63.0% present with dysmenorrhea or pelvic pain as the main symptoms, 72% of patients require painkillers, and 37.6% use themlong-term [5]. Dysmenorrhea can significantly impacts women of reproductive age at different stages, resulting in high absenteeism, decreased learning quality and work capacity, poor sleep quality, and mental health issues [6–8]. Research has found that dysmenorrhea can negatively impact women's emotional regulation and even cause anxiety or depression [9]. Other studies have pointed out that anxiety and depression can further exacerbate the progression of endometriosis-related diseases. Furthermore, long-term dysmenorrhea can increase women's pain sensitivity and the likelihood of developing other chronic pain conditions [10]. Therefore, exploring the related factors of dysmenorrhea in AM and constructing a risk prediction model can aid in preventing and controlling the condition. Current research has noted that associations between dysmenorrhea and factors such as age, smoking, early menarche, prolonged menstruation, heavy menstrual flow, high BMI, alcohol consumption, nulliparity, and family history [11–14]. This study aims to explore dysmenorrhea-related factors in AM through a cross-sectional survey. By identifying and monitoring risk factors, we seek to prevent or mitigate the development of dysmenorrhea in AM. Furthermore, this study aims to establish a nomogram model based on identified risk factors to predict dysmenorrhea in adenomyosis. The model will facilitate risk stratification, enabling early prevention, detection, and treatment of the disease through quantified scoring. Methods Study population and data collection A cross-sectional survey was conducted on 1636 AM patients treated from November 2019 to February 2022, covering 37 hospitals across 18 provinces, municipalities, and autonomous regions, including Beijing, Anhui, Sichuan, Fujian, Guangdong, Guangxi, Xinjiang, Hainan, Hebei, Henan, Shandong, Heilongjiang, Jiangsu, Jiangxi, and Yunnan. Diagnosed as AM by clinical specialists based on symptoms, signs, and auxiliary examination results, patients were divided into a dysmenorrhea group and a non-dysmenorrhea group, with 1,003 patients in the dysmenorrhea group and 633 in the non-dysmenorrhea group. Diagnostic criteria: The diagnostic criteria for adenomyosis were established based on the “Guidelines for the Diagnosis and Treatment of Endometriosis (2015 Edition)” [15]. Inclusion criteria: Clinical symptoms and auxiliary examination results (ultrasound, MRI) consistent with AM; women of reproductive age; complete clinical data. Exclusion criteria were pregnancy, menopause, malignant tumors, liver or kidney dysfunction, and history of hysterectomy. All patients signed informed consent forms, and this study was approved by the Ethics Committee of Guang'anmen Hospital (cross-sectional survey study approval number 2020–040-KY). Clinical data collection A cross-sectional survey study was conduc (...truncated)