Positive margins prediction in breast cancer conservative surgery: Assessment of a preoperative web-based nomogram

External validation of a multivariable prediction model for positive resection margins in breast-conserving surgery

OBJECTIVES

Positive resection margins after breast-conserving surgery (BCS) most often demands a repeat surgery. To preoperatively identify patients at risk of positive margins, a multivariable model has been developed that predicts positive margins after BCS with a high accuracy. This study aimed to externally validate this prediction model to explore its generalizability and assess if additional preoperatively available variables can further improve its predictive accuracy. The validation cohort included 225 patients with invasive breast cancer who underwent BCS at Aarhus University Hospital, Aarhus, Denmark during 2020-2022. Receiver operating characteristic (ROC) and calibration analysis were used to validate the prediction model. Univariable logistic regression was used to evaluate if additional variables available in the validation cohort were associated with positive margins and backward elimination to explore if these variables could further improve the model´s predictive accuracy.

RESULTS

The AUC of the model was 0.60 (95% CI: 0.50-0.70) indicating a lower discriminative capacity in the external cohort. We found weak evidence for an association between increased preoperative breast density on mammography and positive resection margins after BCS (p = 0.027), but the AUC of the model did not improve, when mammographic breast density was included as an additional variable in the model.

Is the Number or Proximity of Margins Less than 2 mm Associated with an Increased Mastectomy Rate in Patients Attempting Breast Conservation Therapy for Ductal Carcinoma In Situ?

BACKGROUND

Consensus guidelines recommend ≥ 2 mm margins in patients undergoing partial mastectomy (PM) for ductal carcinoma in situ (DCIS). It is unknown whether the number or proximity of margins less than 2 mm is associated with an increased mastectomy rate in patients attempting breast conservation therapy (BCT) for DCIS. The aim of this study is to examine this relationship.

PATIENTS AND METHODS

An institutional database review identified 208 patients with DCIS who underwent PM at a tertiary referral center and community hospitals from July 2020 to June 2023. Patients with a history of breast cancer, previous surgery for breast cancer, ipsilateral invasive carcinoma, papillary carcinoma, Paget's disease, more lobular carcinoma in situ (LCIS) than DCIS present, initial mastectomy, no DCIS present, routine shave margins (of all vectors), and ≥ 2 mm margins of all six vectors were excluded. Selective intraoperative margin re-excisions were included.

RESULTS

A total of 208 patients who met inclusion criteria were retrospectively reviewed. 122 (25%) had one close/positive (< 2 mm) margin and 86 (18%) had two or more close/positive margins. Of the patients with one close/positive margin, 7% (9/122) eventually underwent mastectomy. Of the patients with two or more close/positive margins, 20% (17/86) eventually underwent mastectomy. Overall, no patients with opposing margins underwent mastectomy.

CONCLUSIONS

Patients undergoing PM for DCIS have a mastectomy rate that is increased threefold, with two or more close/positive margins at initial PM, when compared with those with only one close/positive margin. The presence of opposing close/positive margins at initial PM did not increase the mastectomy rate and most were cleared with re-excision.

MRI-based radiomic models to predict surgical margin status and infer tumor immune microenvironment in breast cancer patients with breast-conserving surgery: a multicenter validation study

OBJECTIVES

Accurate preoperative estimation of the risk of breast-conserving surgery (BCS) resection margin positivity would be beneficial to surgical planning. In this multicenter validation study, we developed an MRI-based radiomic model to predict the surgical margin status.

METHODS

We retrospectively collected preoperative breast MRI of patients undergoing BCS from three hospitals (SYMH, n = 296; SYSUCC, n = 131; TSPH, n = 143). Radiomic-based model for risk prediction of the margin positivity was trained on the SYMH patients (7:3 ratio split for the training and testing cohorts), and externally validated in the SYSUCC and TSPH cohorts. The model was able to stratify patients into different subgroups with varied risk of margin positivity. Moreover, we used the immune-radiomic models and epithelial-mesenchymal transition (EMT) signature to infer the distribution patterns of immune cells and tumor cell EMT status under different marginal status.

RESULTS

The AUCs of the radiomic-based model were 0.78 (0.66-0.90), 0.88 (0.79-0.96), and 0.76 (0.68-0.84) in the testing cohort and two external validation cohorts, respectively. The actual margin positivity rates ranged between 0-10% and 27.3-87.2% in low-risk and high-risk subgroups, respectively. Positive surgical margin was associated with higher levels of EMT and B cell infiltration in the tumor area, as well as the enrichment of B cells, immature dendritic cells, and neutrophil infiltration in the peritumoral area.

CONCLUSIONS

This MRI-based predictive model can be used as a reliable tool to predict the risk of margin positivity of BCS. Tumor immune-microenvironment alteration was associated with surgical margin status.

CLINICAL RELEVANCE STATEMENT

This study can assist the pre-operative planning of BCS. Further research on the tumor immune microenvironment of different resection margin states is expected to develop new margin evaluation indicators and decipher the internal mechanism.

KEY POINTS

• The MRI-based radiomic prediction model (CSS model) incorporating features extracted from multiple sequences and segments could estimate the margin positivity risk of breast-conserving surgery. • The radiomic score of the CSS model allows risk stratification of patients undergoing breast-conserving surgery, which could assist in surgical planning. • With the help of MRI-based radiomics to estimate the components of the immune microenvironment, for the first time, it is found that the margin status of breast-conserving surgery is associated with the infiltration of immune cells in the microenvironment and the EMT status of breast tumor cells.

Blood flow on ultrasound imaging is a predictor of lump margin status in breast-conserving patients: a retrospective matching study

PURPOSE

This study investigated the relationship between breast ultrasound features and lump margin status in breast-conserving patients.

METHODS

A single-institution database and medical records system were searched to identify patients who had undergone breast-conserving surgery between 2015 and 2022. Patients were divided into case and control groups based on their postoperative margin status, and different matching methods [case-control matching (CCM) and propensity score matching (PSM)] were used to match the cases and controls at a ratio of 1:1.

RESULTS

Before matching, patients with positive margins were more likely to have a tumor with increased blood flow (OR = 2.90, 95% CI 1.83-4.61, p < 0.001) and microcalcifications (OR = 2.22, 95% CI 1.44-3.42, p < 0.001). Among the 83 pairs of CCM subjects, patients with positive margins were prone to increased blood flow (p = 0.007) and crab sign (p = 0.040). In addition, there was a significant difference in blood flow (p = 0.030) among PSM subjects. After adjusting for the unbalanced factors, the same results were obtained.

CONCLUSIONS

Ultrasound blood flow significantly predicts the status of breast-conserving margins, but further studies are required to verify our findings.

A predictive web-based nomogram for the early death of patients with lung adenocarcinoma and bone metastasis: a population-based study

Objective

To identify risk factors and develop predictive web-based nomograms for the early death of patients with bone metastasis of lung adenocarcinoma (LUAD).

Methods

Patients in the Surveillance, Epidemiology, and End Results database diagnosed with bone metastasis of LUAD between 2010 and 2016 were included and randomly divided into training and validation sets. Early death-related risk factors (survival time ≤7 months) were evaluated by logistic regression. Two predictive nomograms were established and validated by calibration curves, receiver operating characteristic curves, and decision curve analysis.

Results

A total of 9189 patients (56.59%) died from all causes within 7 months of being diagnosed, including 8585 patients (56.67%) who died from cancer-specific causes. Age >65 years, sex (men), T stage (T3 and T4), N stage (N2 and N3), brain metastasis, and liver metastasis were risk factors for all-cause and cancer-specific early death. The area under the curves of the nomograms for all-cause and cancer-specific early death prediction were 0.754 and 0.753 (training set) and 0.747 and 0.754 (validation set), respectively. Further analysis showed that the two nomograms performed well.

Conclusions

Our two web-based nomograms for all-cause and cancer-specific early death provide valuable tools for predicting early death in these patients.

Validated prediction model for positive resection margins in breast-conserving surgery based exclusively on preoperative data

Background

Positive margins after breast-conserving surgery (BCS) and subsequent second surgery are associated with increased costs and patient discomfort. The aim of this study was to develop a prediction model for positive margins based on risk factors available before surgery.

Methods

Patients undergoing BCS for in situ or invasive cancer between 2015 and 2016 at site A formed a development cohort; those operated during 2017 in site A and B formed two validation cohorts. MRI was not used routinely. Preoperative radiographic and tumour characteristics and method of operation were collected from patient charts. Multivariable logistic regression was used to develop a prediction model for positive margins including variables with discriminatory capacity identified in a univariable model. The discrimination and calibration of the prediction model was assessed in the validation cohorts, and a nomogram developed.

Results

There were 432 patients in the development cohort, and 190 and 157 in site A and B validation cohorts respectively. Positive margins were identified in 77 patients (17.8 per cent) in the development cohort. A non-linear transformation of mammographic tumour size and six variables (visible on mammography, ductal carcinoma in situ, lobular invasive cancer, distance from nipple–areola complex, calcification, and type of surgery) were included in the final prediction model, which had an area under the curve of 0.80 (95 per cent c.i. 0.75 to 0.85). The discrimination and calibration of the prediction model was assessed in the validation cohorts, and a nomogram developed.

Conclusion

The prediction model showed good ability to predict positive margins after BCS and might, after further validation, be used before surgery in centres without the routine use of preoperative MRI.

Presented in part to the San Antonio Breast Cancer Symposium, San Antonio, Texas, USA, December 2018 and the Swedish Surgical Society Annual Meeting, Helsingborg, Sweden, August 2018.

Factors associated with locoregional and metastatic breast cancer at diagnosis in a Southern Portuguese registry in the period 2005-2012

Breast cancer (BC) is the most frequent malignancy in Portuguese women, and more than half of the registered cases live in the south of the country. The main of this study was to characterize patients with locoregional and metastatic incident BC living in the Southern Portuguese and Madeira regions in 2005-2012 according to demographic, clinical and contextual characteristics. Additionally it aimns to find the associations and relative influences of these factors with locoregional or metastatic disease at diagnosis. After a descriptive approach, binary logistic regression models were used to estimate factors related to the presence of metastatic disease at diagnosis. A final multiple regression model was developed and presented graphically as a nomogram. The median age at diagnosis was 60.84 years, being statistically lower in locoregional cases (P < 0.001). Most patients presented a locoregional disease (78.4%) of unspecified location (44.5%) and had a ductal carcinoma (73.1%). The Lisbon region represented 50.5% of the analyzed cases. Metastatic disease significantly decreased over the period under analysis ( ≈ 7%/year). Demographic (age at diagnosis ≥ 50 years), clinical (lobular and 'other' morphologies, unspecified location) and contextual (residence in Portalegre) characteristics were statistically correlated with the presence of metastatic disease at the time of BC diagnosis in univariate logistic regression, with all but the last maintaining their significance in a multivariate model. Cases with metastatic BC disease at diagnosis are decreasing; however, additional information on their characteristics can improve the alignment of public health strategies, thus strengthening this trend, and contributing to the development of a graphically tailored screening tool.

Predicting initial margin status in breast cancer patients during breast-conserving surgery

Background

We sought to develop and validate a model for prediction of initial margin status during breast-conserving surgery (BCS).

Methods

We included eligible breast cancer patients receiving BCS in Sun Yat-sen Memorial Hospital from January 2003 to December 2014. All patients received intraoperative frozen-section analysis for initial margin assessment. We used univariate and multivariate logistic regression analyses to screen for predictors. A nomogram was developed in the training cohort (n=1,193) from the south branch of the hospital and externally validated in the validation cohort (n=499) from the north branch. We used the area under the receiver-operating characteristic curve and Hosmer–Lemeshow tests to assess the discrimination and accuracy of the nomogram.

Results

The initial margin-positivity rates were 19.5% and 25.2% in the training and validation cohorts, respectively. Preoperative tumor size, preoperative lymph-node status, suspicion of multifocality, hormone-receptor status, and HER2 status were significantly associated with margin status. The model included these five variables. The discrimination and calibration of the model were considered acceptable in both cohorts.

Conclusion

The nomogram can predict the likelihood of having positive initial margins during BCS and may be useful for clinical decision-making in the surgical treatment of breast cancer patients.

The promising impact of molecular profiling on treatment strategies in oral cancers

Oral squamous cell carcinoma (OSCC) is a major cause of cancer-associated morbidity and mortality. Although OSCC may develop from easily accessible oral preneoplastic lesions (OPLs), no intervention has been reported so far that reduces the rate of malignant transformation. A comprehensive molecular characterization of oral carcinogenesis may help refining treatment strategies both in patients with OPLs and OSCC. Herein, we review main molecular alterations occurring at different steps during oral carcinogenesis and show how molecularly-based medicine and surgery may impact the outcome of OSCC in the future.