Management of Granulomatous Lobular Mastitis and Risk Factors Associated with Recurrence

A new stage for predicting the prognosis of granulomatous lobular mastitis

INTRODUCTION

The prognosis of granulomatous lobular mastitis (GLM) had been poor, primarily due to the lack of a unified disease assessment standard.

OBJECTIVE

The purpose of this cohort study was to establish a staging system for GLM to more accurately evaluate the prognosis of patients.

METHODS

This study retrospectively collected data from 264 GLM patients who visited our hospital between January 2017 and December 2023. Through logistic regression analysis, factors associated with prognosis were identified, which served as the basis for creating a new staging system.

RESULTS

Univariate and multivariate logistic regression analysis revealed that hyperlipidemia (HR: 2.031; 95% CI: 1.100-3.750) and microabscesses (HR: 2.087; 95% CI = 1.138-3.827) were significant independent risk factors affecting the prognosis of GLM patients. Based on the results of logistic analysis, three different stages were ultimately established, and it was found that stage C had the highest AUC value (AUC: 0.642), followed by stage B (AUC: 0.628), with stage A (AUC: 0.614) having the lowest. The Delong test revealed no significant difference in AUC values between stage A and stage B (P =  0.255), nor between stage B and stage C (P =  0.263). However, the AUC value of the stage C was found to be higher than that of stage A (P <  0.001). Given that stage C has the highest AUC value, this study selected stage C as the final stage for evaluating the prognosis of GLM patients and named it the 1st edition of GLM stage.

CONCLUSIONS

This study constructed a rigorous and widely applicable GLM staging system (the 1st edition of GLM stage). The system demonstrated good predictive outcomes and provided strong support for clinical decision-making.

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.

The Predictive Value of Preoperative Systemic Immune-Inflammation Index in Patients with Granulomatous Mastitis

Purpose

The systemic immune-inflammation index (SII) comprehensively reflects the balance between immune status and host inflammation. We aimed to investigate the potential predictive value of the SII in the prognosis of granulomatous mastitis (GM).

Patients and Methods

We enrolled 245 patients with GM who underwent surgery between 2015 and 2020 in this study. Using the receiver operating characteristic (ROC) curve, we divided the patients into low SII groups (SII≤836×109/L) and high SII groups (SII>836×109/L). The associations between SII and clinical parameters were assessed using chi-squared or Fisher's exact tests. Kaplan-Meier plots and Log rank tests were performed to investigate the clinical outcomes of cumulative no-recurrence rates. Risk factors were analyzed by using logistic regression analysis.

Results

We found a correlation between the recurrence of GM and the preoperative level of SII, and the high SII group exhibited a higher recurrence rate than the low SII group. To further explore the factors affecting the risk of recurrence, we found that young age at disease onset, skin rupture, and the postoperative use of corticosteroids could increase the risk of GM recurrence. Multivariate logistic regression analysis suggested that young age and postoperative corticosteroid use were the risk factors for disease recurrence.

Conclusion

As a noninvasive and readily available clinical parameter, the preoperative SII level has great significance in evaluating the efficacy and prognosis of surgical treatment for GM combined with age and postoperative corticosteroid use, which provides valuable insights for making treatment decisions.

Long-Term Outcomes of Traditional Chinese Medicine in the Treatment of Granulomatous Lobular Mastitis: A Two-Year Follow-Up Study on Recurrence and New Occurrence Rates with Analysis of Risk Factors

Background

Patients with clinically cured granulomatous lobular mastitis (GLM) still face a high probability of recurrence and new occurrence.

Purpose

To evaluate the long-term efficacy of traditional Chinese medicine (TCM) in treating GLM and to hypothesize potential risk factors for recurrence or new occurrence.

Patients and Methods

A retrospective analysis was conducted on GLM patients treated with TCM at Longhua Hospital affiliated with Shanghai University of Traditional Chinese Medicine from January 2016 to July 2021. We analyzed general data, two-year recurrence and new occurrence rates, and 12 risk factors associated with recurrence or new occurrence.

Results

This cross-sectional study included 261 GLM patients with an average age at onset of 31.95 years (primarily aged 31-40). The two-year recurrence rate for GLM was 1.53%, and the new occurrence rate was 4.21%. Univariate and multivariate conditional logistic regression analyses revealed that a history of inverted nipples was associated with the risk of both recurrence and new occurrence of GLM (HR = 8.672, 5.375, P < 0.05), and menstrual irregularity was related to a higher risk of recurrence (HR = 13.172, P < 0.001).

Conclusion

A history of inverted nipples is identified as a potential risk factor associated with the long-term recurrence and new occurrence of GLM, while menstrual irregularity is associated with recurrence. Despite this, patients with GLM undergoing TCM demonstrate low rates of long-term recurrence and new occurrence after achieving clinical cure, underscoring the effectiveness of TCM. This study lays the groundwork for a long-term effectiveness strategy to guide future GLM treatments.

Clinical features and risk factors of bilateral granulomatous lobular mastitis

Granulomatous lobular mastitis (GLM) is an idiopathic inflammatory breast disease that tends to recur on the same side. With the accumulation of clinical cases, it has been observed that GLM can also occur contralaterally. Currently, most studies on GLM focus on treatment methods and risk factors for ipsilateral recurrence, and there are few reports on bilateral GLM. The study aimed to summarize the clinical characteristics of patients with bilateral GLM by reviewing their clinical data, and to discuss the risk factors affecting the occurrence of bilateral GLM. A retrospective study of the medical records database of patients with GLM admitted between May 2019 and August 2022 was performed. Patients were divided into bilateral GLM group (bilateral GLM group) and unilateral GLM patients (unilateral GLM group). Demographic and clinical characteristics, treatment, and follow-up were collected and analyzed. In this study, by reviewing the clinical data of 59 cases of bilateral GLM, we found that the median time between the onset of bilateral GLM on both sides was 6.63 (0-18) months. Additionally, because of the simultaneous or interval onset on both sides, the duration of the disease was longer compared to unilateral cases. Regarding the history of external hospital treatment, it was found that about 57.63% of patients with bilateral GLM received 2 or more treatment modalities, with a higher involvement of herbal medicine. Meanwhile, by counting the clinical data of the 2 groups of patients with bilateral GLM and unilateral GLM, it was shown by univariate analysis that fertility, nipple development, absolute CD4 value, and CD4/CD8 ratio were associated with contralateral onset of GLM in both groups, with inverted nipple being an independent risk factor.

The Effect of Local Steroid Administration on Idiopathic Granulomatous Mastitis: A Systematic Review andMeta-Analysis

INTRODUCTION

Idiopathic granulomatous mastitis (IGM) is a rare, benign inflammatory breast disease. Corticosteroids and surgery are the primary treatment options, and a growing number of publications have shown the effectiveness of local steroid administration (intralesional injection and topical corticosteroids). However, less is known about the specific details and effects of this treatment approach. The purpose of this meta-analysis was to summarize the details and evaluate the efficacy of local steroid administration for IGM.

METHODS

The PubMed, Embase, Cochrane Library, and SinoMed databases were systematically searched from inception to July 2023 to identify relevant randomized controlled trials. The quality of the included studies was assessed, and meta-analysis and subgroup analysis were conducted to obtain the pooled effect sizes of the outcomes of interest.

RESULTS

Eight trials comprising 613 patients were included. Local steroid administration included intralesional injection and topical steroid ointment, and control groups were mainly given systemic therapy (oral steroid) and surgical treatment. The meta-analysis showed that local steroid administration had a significant effect on the response rate (risk ratio [RR] = 1.35, 95% CI = [1.14-1.59], P = 0.0004). The incidence of side effects was also lower than that of systemic treatment (RR = 0.24, 95% CI = [0.13-0.43], P＜0.0001). There was no difference in the recurrence rate (RR = 0.8, 95% CI = [1.42-1.51], P = 0.48).

CONCLUSIONS

Local steroid administration can increase the RR and decrease the incidence of side effects for IGM patients. There is no significant difference in the recurrence rate between the local steroid administration group and the control group. Further studies are needed to identify the effect in different stages and among pregnant women.

Predisposing Factors for Granulomatous Lobular Mastitis: A Case-Control Study

Background

Despite the rising incidence rate of granulomatous lobular mastitis (GLM), uncertainties persist about its etiologic and predisposing factors to guide clinical treatment and early prevention. The objective of this study is to explore the predisposing factors for GLM.

Patients and methods

This case-control study was conducted from 2018 to 2021 at Beijing Hospital of Traditional Chinese Medicine, Capital Medical University. Patients with GLM (cases) were matched with healthy examinees (controls) in a 1:1 ratio according to gender and living area. We analyzed their demographic features and investigated 75 factors that may be relevant to GLM using a standard questionnaire. Univariate and multivariable binary conditional logistic regression analyses were used to compare the differences between the two groups and evaluate the predisposing factors that may induce GLM.

Results

There were 594 female GLM patients and 594 matched controls included in the study. The average age of the cases was 32.78 years (mainly 20 to 40). The incidence was high within five years after childbirth, and lesions were mainly in the unilateral breast. Univariate and multivariable conditional logistic regression analyses obtained six relevant factors and six high-risk factors. The six relevant factors included age, marriage, emotional abnormality, high prolactin, psychiatric drug intake, and sex hormone intake. Additionally, the independent high-risk factors for GLM included gestation, nipple invagination, blunt trauma, non-iatrogenic massage, lactation disorder, and nipple discharge (odds ratio (OR)=17.378, 8.518, 4.887, 3.116, 2.522, 1.685, P<0.05). Menopause was an independent protective factor (OR=0.249, P<0.05).

Conclusion

The factors that increase milk and secretion production in the mammary duct are the main risk factors of GLM, especially when the nipples are invaginated. These factors can obstruct the duct and induce inflammation. Additionally, hormonal disorders, extrinsic trauma, and emotional abnormalities can accelerate the occurrence of GLM.