Preoperative Fibrinogen and Hematological Indexes in the Differential Diagnosis of Idiopathic Granulomatous Mastitis and Breast Cancer

A recurrence model for non-puerperal mastitis patients based on machine learning

OBJECTIVE

Non-puerperal mastitis (NPM) is an inflammatory breast disease affecting women during non-lactation periods, and it is prone to relapse after being cured. Accurate prediction of its recurrence is crucial for personalized adjuvant therapy, and pathological examination is the primary basis for the classification, diagnosis, and confirmation of non-puerperal mastitis. Currently, there is a lack of recurrence models for non-puerperal mastitis. The aim of this research is to create and validate a recurrence model using machine learning for patients with non-puerperal mastitis.

METHODS

We retrospectively collected laboratory data from 120 NPM patients, dividing them into a non-recurrence group (n = 59) and a recurrence group (n = 61). Through random allocation, these individuals were split into a training cohort and a testing cohort in a 90%:10% ratio for the purpose of building the model. Additionally, data from 25 NPM patients from another center were collected to serve as an external validation cohort for the model. Univariate analysis was used to examine differential indicators, and variable selection was conducted through LASSO regression. A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. The finally selected model was interpreted and evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, Decision curve analysis (DCA), and Shapley Additive Explanations (SHAP) plots.

RESULTS

The logistic regression model emerged as the optimal model for predicting recurrence of NPM with machine learning, primarily utilizing three variables: FIB, bacterial infection, and CD4+ T cell count. The model showed an AUC of 0.846 in the training cohort and 0.833 in the testing cohort. The calibration curve indicated excellent calibration of the model. DCA revealed that the model possessed favorable clinical utility. Furthermore, the model effectively achieved in the external validation group, with an AUC of 0.825.

CONCLUSION

The machine learning model developed in this study, serving as an effective tool for predicting NPM recurrence, aids doctors in making more individualized treatment decisions, thereby enhancing therapeutic efficacy and reducing the risk of recurrence.

Promoting Standardization of Clinical Evidence With Severity-Guided Treatments for Idiopathic Granulomatous Mastitis: A Narrative Review

Idiopathic granulomatous mastitis (IGM) is a benign disease of the breast which causes a great deal of discomfort for patients. More comparable data and greater consensus in treatment are needed to better understand the disease and help with evidence-based clinical decision making. This narrative review aims to discuss the literature available on IGM and illustrate the need for consensus on treatment. We highlight the existing severity scores for this disease in the literature and discuss the value of severity-guided treatment. In our review, 81 studies out of 319 reviewed publications met established criteria. With the selected results from our search results, the available research on IGM etiology, risk factors, diagnosis, and treatment is summarized with an emphasis on the existing severity scores. A total of four proposed severity scores were found in our review. Consensus on the treatment of IGM must be established. There are varying severity scores on IGM severity. We suggest using an established standardized severity score to guide treatment and recommend one such score.

Diagnostic role of the neutrophil‑to‑lymphocyte ratio and the platelet‑to‑lymphocyte ratio in breast cancer: A systematic review and meta‑analysis

Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) may be indicative of breast cancer (BC); however, this remains inconclusive. With the aim to assess the current literature to evaluate the diagnostic roles of NLR PLR and LMR in BC, a systematic literature search was performed using the PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, VIP database and China Biology Medicine disc databases up to August 29, 2023. The standardized mean deviation and 95% confidence intervals (CI) for each outcome was reported, and heterogeneity and publication bias were assessed. Overall, 39 studies were included in the present study. Pooled analysis with the random-effects model demonstrated that patients with BC had significantly higher NLR and PLR, and a lower LMR, compared with non-BC subjects. The pooled sensitivities of the NLR and PLR were 0.68 (95% CI, 0.59-0.75) and 0.55 (95% CI, 0.36-0.72), respectively, and the pooled specificities of the NLR and PLR were 0.75 (95% CI, 0.68-0.81) and 0.80 (95% CI, 0.51-0.94), respectively. However, the limited number of studies included hindered the evaluation of the diagnostic role of LMR. In summary, a higher NLR and PLR and lower LMR were associated with the presence of BC. NLR and PLR may be potential blood-based biomarkers for the differentiation of BC. Despite these findings, further studies are needed to validate their clinical applicability and practicality. International Prospective Register of Systematic Reviews registration no. CRD42024522226.

Comparison of Hematological Parameters and the Associated Factors Among Women with and without Breast Cancer: A Case-Control Study

Background

Breast cancer (BC) is the most popular and dangerous cancer, with a high mortality rate. Hematological parameters are often used in routine diagnosis of numerous disorders. Therefore, the study aimed to evaluate hematological parameters amongst women with and without BC.

Methodology

Briefly, 200 blood samples (100 cases and 100 controls) were collected at Life Center of Breast Cancer Control, Ibb City, Yemen. The whole blood samples were tested immediately for complete blood count (CBC) parameters. Socio-demographic and reproductive characteristics were collected by using a standardized questionnaire. Kolmogorov-Smirnov test, Unpaired t-test, Mann-Whitney test, Fisher's exact test and chi-square test for trends were calculated using GraphPad Prism 8.0.1. P-values ≤0.05 were statistically significant.

Results

The mean and standard deviation (SD) revealed significant differences between BC group and the healthy control group attributed to the variables of age (P<0.0001), weight (P<0.0001), residence (P=0.0218), employment state (P<0.0001), economic state (P=0.0003), education levels (P<0.0001), regular exercise (P<0.0001) and a strict diet (P<0.0008). Marital state, marital age, number of births, and use of contraceptives demonstrated statistical significance (P<0.0001, P=0.0008, P=0.0009, and P<0.0001, respectively). Additionally, Hb, RBCs, WBCs count, neutrophils, lymphocytes and monocytes displayed significant differences (P=0.0393, P=0.0045, P=0.0327, P=0.0441, P=0.0098 and P<0.0001, respectively).

Conclusion

Hb, RBCs, WBCs, neutrophils, lymphocytes, monocytes and other parameters scored high points of evidence for BC surveillance. Further studies are required to evaluate hematological parameter differences and biochemical parameters after or during chemotherapy or mastectomy.

Cornus Officinalis Total Glycosides Alleviate Granulomatous Lobular Mastitis via the B7-CD28/CTLA-4 Costimulatory Pathway

Cornus officinalis total glycosides (COTG) derived from the traditional Chinese medicine Cornus officinalis, is a natural immunosuppressant and has been extensively studied in immunomodulation and immunosuppression. This study aimed to explore the effects of COTG on granulomatous lobular mastitis (GLM) and its associated mechanisms. Compared to the model group, COTG effectively ameliorated histopathological damage to breast tissue, reduced mammary gland suppuration, and enhanced the blood-milk barrier. Additionally, COTG treatment reduced the total number of T cells and B cells in GLM rats, significantly improving clinical indicators such as P-selectin, E-selectin, and intercellular cell adhesion molecule-1. We also observed downregulation of CD28 and B7 expression levels, an upregulation of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) expression, and a significant decrease in inflammatory marker levels in the COTG group. COTG exerts an anti-inflammatory effect in GLM by stimulating CTLA-4, inhibiting the B7-CD28 signaling pathway affecting T cell activation, and promoting the blood-milk barrier. These findings suggest that COTG could be a promising therapeutic option for managing GLM, potentially improving patient outcomes by modulating immune responses and reinforcing the blood-milk barrier.

Risk Factors and the Role of the Albumin-to-Globulin Ratio in Predicting Recurrence Among Patients with Idiopathic Granulomatous Mastitis

Background

Idiopathic granulomatous mastitis (IGM) is a rare inflammatory disease of the breast with a high recurrence rate. The serum albumin to globulin ratio (AGR) is a relatively novel biomarker in inflammatory diseases, and one whose role in the recurrence of IGM remains unknown. This study primarily investigated the potential risk factors for IGM recurrence and whether AGR can be used as a predictive factor.

Methods

Patients diagnosed with IGM from pathology reports between 2016 and 2021 were enrolled in the study, and their medical records were analyzed retrospectively. The patients were divided into two groups – recurrence and non-recurrence. Clinical, demographic characteristics, and laboratory parameters were compared.

Results

Eighty-five patients were included in the study, recurrence being detected in 16 (18.8%) of these, with a median follow-up time of 39.99±18.93 months. No relationship was determined between childbearing, breastfeeding, disease severity, or therapeutic approaches and IGM recurrence. While AGR was significantly lower in the recurrence group (p < 0.001), neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) results were comparable in the two groups (p = 0.472 and p = 0.421, respectively). Multivariate analysis identified low AGR (odds ratio (OR): 50.7, 95% CI 5.93–434.1 P < 0.001) and smoking (OR: 4.45, 95% CI 1.04–18.9 P = 0.044) as independent risk factors for IGM recurrence.

Conclusion

The study findings indicated that AGR at a cut-off value of ≤1.179 at diagnosis and smoking exhibited a remarkable performance in predicting the recurrence of IGM. Developing new risk stratification systems for IGM recurrences and using AGR in these classifications may increase the success of treatment.

Trial Registration

This study was registered with ClinicalTrials.gov, NCT05409586.

Diagnostic Value of Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte, and Monocyte-to-Lymphocyte Ratios for the Assessment of Rheumatoid Arthritis in Patients with Undifferentiated Inflammatory Arthritis

Background: To investigate the diagnostic performance of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) in the diagnosis of rheumatoid arthritis (RA) in subjects with undifferentiated inflammatory arthritis (UIA). Methods: This retrospective cohort study investigated 201 female patients with UIA (≥1 swollen joint) and 280 age-matched, healthy female controls. “Clinical RA” was defined based on the clinical judgment of a rheumatologist and “disease-modifying anti-rheumatic drugs (DMARDs) RA” was defined as a case of initiating DMARDs treatment within 6 months after the first visit. “Classified RA” was defined as fulfilling the 2010 classification criteria for RA. Receiver operating characteristics were used to determine the optimal cut-off value. Results: UIA patients had a significantly higher NLR, PLR, and MLR than the controls. Among the 201 UIA patients, 65 (32.3%), 63 (31.3%), and 61 (30.3%) subjects were classified as clinical RA, DMARDs RA, and classified RA, respectively. At a cut-off of 0.24, MLR showed moderate accuracy for the diagnosis of DMARDs RA (sensitivity, 65.1%; specificity, 62.3%; area under the curve [AUC], 0.701; p < 0.001). However, the diagnostic accuracies of NLR and PLR were low. Conclusions: MLR may be used as a complementary diagnostic indicator for RA diagnosis in patients with UIA.