Clinicopathological predictors of postoperative upstaging to invasive ductal carcinoma (IDC) in patients preoperatively diagnosed with ductal carcinoma in situ (DCIS): a multi-institutional retrospective cohort study

Radiological and pathological predictors of post-operative upstaging of breast ductal carcinoma in situ (DCIS) to invasive ductal carcinoma and lymph-nodes metastasis; a potential algorithm for node surgical de-escalation

BACKGROUND/AIM

Ductal carcinoma in situ is considered a local disease with no metastatic potential, thus sentinel lymph node biopsy (SLNB) may be deemed an overtreatment. SLNB should be reserved for patients with invasive cancer, even though the risk of upstaging rises to 25 %. We aimed to identify clinicopathological predictors of post-operative upstaging in invasive carcinoma.

METHODS

We retrospectively analyzed patients with a pre-operative diagnosis of DCIS subjected to breast surgery between January 2017 to December 2021, and evaluated at the Breast Unit of PTV (Policlinico Tor Vergata, Rome).

RESULTS

Out of 267 patients diagnosed with DCIS, 33(12.4 %) received a diagnosis upstaging and 9(3.37 %) patients presented with sentinel lymph node (SLN) metastasis. In multivariate analysis, grade 3 tumor (OR 1.9; 95 % CI 1.2-5.6), dense nodule at mammography (OR 1.3; 95 % CI 1.1-2.6) and presence of a solid nodule at ultrasonography (OR 1.5; 95 % CI 1.2-2.6) were independent upstaging predictors. Differently, the independent predictors for SLNB metastasis were: upstaging (OR 2.1.; 95 % CI 1.2-4.6; p = 0.0079) and age between 40 and 60yrs (OR 1.4; 95 % CI 1.4-2.7; p = 0.027). All 9 patients with SLN metastasis received a diagnosis upstaging and were aged between 40 and 60 years old.

CONCLUSION

We identified pre-operative independent predictors of upstaging to invasive ductal carcinoma. The combined use of different predictors in an algorithm for surgical treatments of DCIS could reduce the numbers of unnecessary SLNB.

AI analytics can be used as imaging biomarkers for predicting invasive upgrade of ductal carcinoma in situ

OBJECTIVES

To evaluate whether the quantitative abnormality scores provided by artificial intelligence (AI)-based computer-aided detection/diagnosis (CAD) for mammography interpretation can be used to predict invasive upgrade in ductal carcinoma in situ (DCIS) diagnosed on percutaneous biopsy.

METHODS

Four hundred forty DCIS in 420 women (mean age, 52.8 years) diagnosed via percutaneous biopsy from January 2015 to December 2019 were included. Mammographic characteristics were assessed based on imaging features (mammographically occult, mass/asymmetry/distortion, calcifications only, and combined mass/asymmetry/distortion with calcifications) and BI-RADS assessments. Routine pre-biopsy 4-view digital mammograms were analyzed using AI-CAD to obtain abnormality scores (AI-CAD score, ranging 0-100%). Multivariable logistic regression was performed to identify independent predictive mammographic variables after adjusting for clinicopathological variables. A subgroup analysis was performed with mammographically detected DCIS.

RESULTS

Of the 440 DCIS, 117 (26.6%) were upgraded to invasive cancer. Three hundred forty-one (77.5%) DCIS were detected on mammography. The multivariable analysis showed that combined features (odds ratio (OR): 2.225, p = 0.033), BI-RADS 4c or 5 assessments (OR: 2.473, p = 0.023 and OR: 5.190, p < 0.001, respectively), higher AI-CAD score (OR: 1.009, p = 0.007), AI-CAD score ≥ 50% (OR: 1.960, p = 0.017), and AI-CAD score ≥ 75% (OR: 2.306, p = 0.009) were independent predictors of invasive upgrade. In mammographically detected DCIS, combined features (OR: 2.194, p = 0.035), and higher AI-CAD score (OR: 1.008, p = 0.047) were significant predictors of invasive upgrade.

CONCLUSION

The AI-CAD score was an independent predictor of invasive upgrade for DCIS. Higher AI-CAD scores, especially in the highest quartile of ≥ 75%, can be used as an objective imaging biomarker to predict invasive upgrade in DCIS diagnosed with percutaneous biopsy.

CRITICAL RELEVANCE STATEMENT

Noninvasive imaging features including the quantitative results of AI-CAD for mammography interpretation were independent predictors of invasive upgrade in lesions initially diagnosed as ductal carcinoma in situ via percutaneous biopsy and therefore may help decide the direction of surgery before treatment.

KEY POINTS

• Predicting ductal carcinoma in situ upgrade is important, yet there is a lack of conclusive non-invasive biomarkers. • AI-CAD scores-raw numbers, ≥ 50%, and ≥ 75%-predicted ductal carcinoma in situ upgrade independently. • Quantitative AI-CAD results may help predict ductal carcinoma in situ upgrade and guide patient management.

Survival Outcomes Based on Axillary Surgery in Ductal Carcinoma In Situ: A Nationwide Study From the Korean Breast Cancer Society

PURPOSE

In total mastectomy (TM), sentinel lymph node biopsy (SLNB) is recommended but can be omitted for breast-conserving surgery (BCS) in patients with ductal carcinoma in situ (DCIS). However, concerns regarding SLNB-related complications and their impact on quality of life exist. Consequently, further research is required to evaluate the role of axillary surgeries, including SLNB, in the treatment of TM. We aimed to explore the clinicopathological factors and outcomes associated with axillary surgery in patients with a final diagnosis of pure DCIS who underwent BCS or TM.

METHODS

We retrospectively analyzed large-scale data from the Korean Breast Cancer Society registration database, highlighting on patients diagnosed with pure DCIS who underwent surgery and were categorized into two groups: BCS and TM. Patients were further categorized into surgery and non-surgery groups according to their axillary surgery status. The analysis compared clinicopathological factors and outcomes according to axillary surgery status between the BCS and TM groups.

RESULTS

Among 18,196 patients who underwent surgery for DCIS between 1981 and 2022, 11,872 underwent BCS and 6,324 underwent TM. Both groups leaned towards axillary surgery more frequently for large tumors. In the BCS group, clinical lymph node status was associated with axillary surgery (odds ratio, 11.101; p = 0.003). However, in the TM group, no significant differences in these factors were observed. Survival rates did not vary between groups according to axillary surgery performance.

CONCLUSION

The decision to perform axillary surgery in patients with a final diagnosis of pure DCIS does not affect the prognosis, regardless of the breast surgical method. Furthermore, regardless of the breast surgical method, axillary surgery, including SLNB, should be considered for high-risk patients, such as those with large tumors. This may reduce unnecessary axillary surgery and enhance the patients' quality of life.

Treatments and Prognosis of the Breast Ductal Carcinoma In Situ

INTRODUCTION

With progress in treatments, breast ductal carcinoma in situ (DCIS) outcomes have substantially improved. However, as various treatment methods are used in different countries and institutions, consensus on the optimal treatment method is lacking. This study aimed to analyze the prognostic factors and provide a reference for optimizing the clinical treatment of DCIS.

PATIENTS AND METHODS

This retrospective clinical study collected data from DCIS patients at the Sun Yat-sen University Cancer Center from 2010 to 2017. The Kaplan-Meier method and Cox regression model were used to assess disease-free survival (DFS), overall survival (OS), and local control (LC) rates.

RESULTS

Among the 483 included patients, 83.6% (404) underwent mastectomies. The median follow-up time was 101 months. The number of patients undergoing breast-conserving surgery (BCS) with radiotherapy has gradually increased. Axillary lymph node dissection was the main surgery performed from 2010 to 2015, and the proportion of sentinel lymph node biopsies (SLNBs) has increased. LC and DFS rates with BCS without radiotherapy were significantly lower than those with mastectomy (P = .002; P < .001). Additionally, the patients who did not undergo axillary surgery had worse LC and OS rates than those who underwent SLNB (P = .028 and P = .038). Endocrine therapy (ET) or its duration had no significant effect on prognosis.

CONCLUSION

In conclusion, BCS without radiotherapy and lack of axillary surgery were independent prognostic factors. We recommend performing BCS with radiotherapy and SLNB more in clinical practice, as well as shortening the ET duration.

Prediction of Surgical Upstaging Risk of Ductal Carcinoma In Situ Using Machine Learning Models

Objective

The purpose of this study was to build machine learning models to predict surgical upstaging risk of ductal carcinoma in situ (DCIS) to invasive cancer and to compare model performance to eligibility criteria used by the Comparison of Operative versus Monitoring and Endocrine Therapy (COMET) active surveillance trial.

Methods

Medical records were retrospectively reviewed of all women with DCIS at core-needle biopsy who underwent surgery from 2007 to 2016 at an academic medical center. Multivariable regression and machine learning models were developed to evaluate upstaging-related features and their performance was compared with that achieved using the COMET trial eligibility criteria.

Results

Of 1387 women (mean age, 57 years; range, 27-89 years), the upstaging rate of DCIS was 17% (235/1387). On multivariable analysis, upstaging-associated features were presentation of DCIS as a palpable area of concern, imaging finding of a mass, and nuclear grades 2 or 3 at biopsy (P < 0.05). If COMET trial eligibility criteria were applied to our study cohort, then 496 women (42%, 496/1175) would have been eligible for the trial, with an upstaging rate of 12% (61/496). Of the machine learning models, none had a significantly lower upstaging rate than 12%. However, if using the models to determine eligibility, then a significantly larger proportion of women (56%-87%) would have been eligible for active surveillance.

Conclusion

Use of machine learning models to determine eligibility for the COMET trial identified a larger proportion of women eligible for surveillance compared with current eligibility criteria while maintaining similar upstaging rates.

De-escalation of Sentinel Lymph Node Biopsy in Patients With Ductal Carcinoma In Situ

Introduction Current guidelines recommend that sentinel lymph node biopsy (SLNB) be performed in patients with ductal carcinoma in situ (DCIS) undergoing mastectomy, in patients for whom the location of excision may compromise future SLNB, or if there is a high suspicion or risk of upstaging to invasive cancer on final pathology. Whether axillary surgery should be performed in patients with DCIS remains controversial. Our study aimed to examine the factors associated with the upgrade of DCIS to invasive cancer on final pathology and sentinel lymph node (SLN) metastases to evaluate whether axillary surgery may be safely omitted in DCIS. Methods Patients with a diagnosis of DCIS on core biopsy who underwent surgery with axillary staging between 2016 and 2022 were identified from our pathology database and retrospectively reviewed. Patients who underwent surgical management of DCIS without axillary staging and those treated for local recurrence were excluded. Results Out of 65 patients, 35.3% of patients were upstaged to the invasive disease on final pathology. 9.23% of cases had a positive SLNB. Predictive factors associated with upstaging to invasive cancer included palpable mass on clinical examination (P = 0.013), presence of a mass on preoperative imaging (P = 0.040), and estrogen receptor status (P = 0.036). Conclusion Our results support ongoing opportunities for the de-escalation of axillary surgery in patients with DCIS. In a subset of patients undergoing surgery for DCIS, SLNB may be omitted as the risk of upstaging to invasive cancer is low. Patients with a mass on clinical examination or imaging and negative estrogen receptor (ER) lesions have a higher risk of upstaging to invasive cancer, where a sentinel lymph node biopsy should be performed.

Preoperative Breast MRI: Current Evidence and Patient Selection

Breast MRI is the most sensitive imaging modality for the assessment of newly diagnosed breast cancer extent and can detect additional mammographically and clinically occult breast cancers in the ipsilateral and contralateral breasts. Nonetheless, appropriate use of breast MRI in the setting of newly diagnosed breast cancer remains debated. Though highly sensitive, MRI is less specific and may result in false positives and overestimation of disease when MRI findings are not biopsied prior to surgical excision. Furthermore, improved anatomic depiction of breast cancer on MRI has not consistently translated to improved clinical outcomes, such as lower rates of re-excision or breast cancer recurrence, though there is a paucity of well-designed studies examining these issues. In addition, current treatment paradigms have been developed in the absence of this more accurate depiction of disease span, which likely has limited the value of MRI. These issues have led to inconsistent and variable utilization of preoperative MRI across practice settings and providers. In this review, we discuss the history of breast MRI and its current use and recommendations with a focus on the preoperative setting. We review the evidence surrounding the use of preoperative MRI in the evaluation of breast malignancies and discuss the data on breast MRI in the setting of specific patient factors often used to determine breast MRI eligibility, such as age, index tumor phenotype, and breast density. Finally, we review the impact of breast MRI on surgical outcomes (re-excision and mastectomy rates) and long-term breast recurrence and survival outcomes.

Upgrade Rate of Ductal Carcinoma In Situ to Invasive Carcinoma and the Clinicopathological Factors Predicting the Upgrade Following a Mastectomy: A Retrospective Study

Background The rate of upgrading ductal carcinoma in situ (DCIS) to invasive cancer varies widely in the literature with no consensus regarding sentinel lymph node biopsy (SLNB) for DCIS; however, some guidelines do recommend it in the event of a mastectomy. The primary aim of this study was to determine the upgrade rate of DCIS to invasive carcinoma (IC) in patients undergoing mastectomy for DCIS and identify the clinicopathological predicting factors for the upgrade. The secondary aim was to determine the SLNB positivity rate. Methodology We retrospectively analysed consecutive patients with DCIS diagnosed through a biopsy who then underwent mastectomy over a 10-year period (2010 to 2020). Clinical, radiological, and histological variables were collected from medical records. Results We studied 143 women (mean age = 57.4 years, range = 26-85 years) who underwent mastectomy for DCIS identified on biopsy. Almost two-thirds (62.9%, 90/143) of the patients were detected on screening mammography, while 35.6% (51/143) were diagnosed following presentation with either an area of palpable concern or nipple discharge. The most common mammographic presentation of DCIS was calcification (83.9%, 120/143), and, in 85.9% of the patients, the mammographic lesion was more than 20 mm. High-grade DCIS was noted in 76.9% of preoperative biopsy results, while the rest was either low or intermediate-grade DCIS. Overall, 24.5% (35/143) were upgraded to IC (upgraded group) on postoperative histology, whereas 108/143 remained DCIS postoperatively (pure DCIS group). The positivity rate of SLNB was 4.8%. Multifocality was the only significant predictor of IC on multivariate analyses of clinicopathological predictors (odds ratio = 3.0, 95% confidence interval = 1.0-8.7). The presence of comedonecrosis was higher in the upgraded group compared to the pure DCIS group (42.9% vs. 27.8%), but this was not statistically significant. Conclusions In our study cohort, nearly one in four (24.5%) patients were upgraded from DCIS to IC on postoperative histology, with an SLNB positivity rate of 4.8%. This is important when counselling patients regarding the risk of coincident occult IC and the importance of SLNB at the time of mastectomy. Multifocality on preoperative imaging was the only significant predictive factor. Based on this result, we recommend that SLNB should also be considered if patients have multifocal DCIS and planned for oncoplastic breast-conserving surgery. However, further studies are required to investigate the association between multifocal DCIS and the risk of upgrading to IC.

Prediction of the histologic upgrade of ductal carcinoma in situ using a combined radiomics and machine learning approach based on breast dynamic contrast-enhanced magnetic resonance imaging

Objective

To investigate whether support vector machine (SVM) trained with radiomics features based on breast magnetic resonance imaging (MRI) could predict the upgrade of ductal carcinoma in situ (DCIS) diagnosed by core needle biopsy (CNB) after surgical excision.

Materials and methods

This retrospective study included a total of 349 lesions from 346 female patients (mean age, 54 years) diagnosed with DCIS by CNB between January 2011 and December 2017. Based on histological confirmation after surgery, the patients were divided into pure (n = 198, 56.7%) and upgraded DCIS (n = 151, 43.3%). The entire dataset was randomly split to training (80%) and test sets (20%). Radiomics features were extracted from the intratumor region-of-interest, which was semi-automatically drawn by two radiologists, based on the first subtraction images from dynamic contrast-enhanced T1-weighted MRI. A least absolute shrinkage and selection operator (LASSO) was used for feature selection. A 4-fold cross validation was applied to the training set to determine the combination of features used to train SVM for classification between pure and upgraded DCIS. Sensitivity, specificity, accuracy, and area under the receiver-operating characteristic curve (AUC) were calculated to evaluate the model performance using the hold-out test set.

Results

The model trained with 9 features (Energy, Skewness, Surface Area to Volume ratio, Gray Level Non Uniformity, Kurtosis, Dependence Variance, Maximum 2D diameter Column, Sphericity, and Large Area Emphasis) demonstrated the highest 4-fold mean validation accuracy and AUC of 0.724 (95% CI, 0.619-0.829) and 0.742 (0.623-0.860), respectively. Sensitivity, specificity, accuracy, and AUC using the test set were 0.733 (0.575-0.892) and 0.7 (0.558-0.842), 0.714 (0.608-0.820) and 0.767 (0.651-0.882), respectively.

Conclusion

Our study suggested that the combined radiomics and machine learning approach based on preoperative breast MRI may provide an assisting tool to predict the histologic upgrade of DCIS.

Surgical upstaging rates in patients meeting the eligibility for active surveillance trials

PURPOSE

Four clinical active surveillance trials including LORIS, COMET, LORD and LORETTA, are being conducted to assess whether women with low-risk ductal carcinoma in situ can safely avoid surgery. The present study aimed to determine the rate of upstaging to invasive cancer among patients with a preoperative diagnosis of ductal carcinoma in situ and to evaluate the incidence of upstaging in patients meeting the eligibility criteria for four active surveillance clinical trials.

METHODS

The present study initially enrolled 180 patients with 183 calcifications who received the diagnosis of ductal carcinoma in situ by biopsy. Patients were classified as eligible for four clinical trials according to the respective inclusion criteria.

RESULTS

In total, 152 patients with 155 calcifications were analyzed. Of these, 32 (21%) were upstaged to invasive disease based on the final pathological analysis of surgical specimens. Of the 152 patients, 53 (35%), 90 (59%), 24 (16%) and 34 (22%) met the eligibility criteria for the LORIS, COMET, LORD and LORETTA trial, respectively. Among patients with low-risk ductal carcinoma in situ, 10 (19%), 14 (16%), 6 (25%) and 4 (12%) patients were upstaged to invasive disease in LORIS, COMET, LORD and LORETTA, respectively. The upstaging to pT1b or higher rates were 2% (1/53), 3% (3/90), 0% (0/24) and 3% (1/34) in LORIS, COMET, LORD and LORETTA, respectively.

CONCLUSIONS

The upstaging rate in patients eligible for the clinical active surveillance trials was 12-25%. Although the rate of upstaging to pT1b or higher was low, further studies are required to determine the rates of upstaging to invasive cancer and the risk factors among patients with low-risk ductal carcinoma in situ.