Identification of diagnostic blood indicators associated with adenomyosis: a retrospective cohort study.
AI interpretation is pending for this paper.
Open original publication →What the AI sees
Not AI summarized yet.
Research significance
Pending deeper interpretation.
Source abstract
BACKGROUND: Adenomyosis (AM) is described as a benign invasion of the endometrium into the myometrium, which impacts a large number of childbearing age women. The diagnosis of AM relies on imaging and histological examinations. Although carbohydrate antigen 125 (CA125) has served as a blood indicator for AM diagnosis, its utility is limited to being effective in only approximately half of patients. Currently, there are no reliable blood diagnostic indicators available for AM. METHODS: Data of 23 blood indicators examined for 143 patients with AM and 143 age-matched healthy women were collected, including six sex hormones, two tumor biomarkers, nine routine data, two inflammatory and coagulation indicators, and four lipid-related indicators. Wilcoxon rank-sum test was applied to identify differentially changed indicators (DCIs) for AM versus controls. Similarly, Wilcoxon rank-sum test was conducted to determine the DCIs associated with the MRI subtypes of AM. Univariate and multivariate analyses were performed to select the DCIs that might differentiate severe from mild AM. Least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVMRFE) were used to determine the key DCIs for AM. Logistic regression was carried out to develop a diagnostic model, and the area under the receiver operating characteristic (ROC) curve (AUC) was calculated to evaluate the performance of the model. A nomogram was constructed to predict the risk of AM. RESULTS: We identified 15 DCIs for AM. Four DCIs were found in all three MRI subtypes. CA125 and estradiol could distinguish severe from mild AM. The hemoglobin (HGB) concentration, lymphocyte percentage, neutrophil count, neutrophil percentage, and testosterone were different between diffuse AM and adenomyoma. Based on these DCIs, neutrophil count, HGB concentration, and high-density lipoprotein (HDL) were selected using the LASSO and SVMRFE methods, which could discriminate AM cases with CA125<35 and ≥35 U/ml from the controls with AUCs of 0.812 and 0.928, respectively. Similarly, CA125, neutrophil count, HGB concentration, and HDL were screened and a diagnostic model built for AM, which could differentiate all AM cases from the controls with an AUC of 0.935 (sensitivity = 0.902, specificity = 0.888). CONCLUSION: To our knowledge, these indicators are reported here for the first time as combined biomarkers for the diagnosis of AM. Our findings might provide clues for the pathogenesis research of AM and supply potential blood indicators to assist in its diagnosis.