A model to predict upstaging to invasive carcinoma in patients preoperatively diagnosed with ductal carcinoma in situ of the breast

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.

Validation and Clinical Utility of a Prediction Model for the Risk of Upstaging to Invasive Breast Cancer After a Biopsy Diagnosis Ductal Carcinoma In Situ

BACKGROUND

This study aimed to validate the DCIS-upstage model, a previously developed model to predict the risk of upstaging to invasive breast cancer in patients with biopsy-proven ductal carcinoma in situ (DCIS) in a more recent cohort and to assess the model's clinical utility.

METHODS

The model was validated in a registry cohort (n = 2269) and in an institution cohort (n = 302). A calibration plot was made, followed by a decision curve analysis (DCA). The model's area under the curve (AUC) was compared with the AUC of another published model and with the AUCs of new models using the risk factors of the DCIS-upstage model and additional risk factors.

RESULTS

The DCIS-upstage model had an AUC of 0.67 at development; in the validation, the AUC was 0.65 in the registry cohort and 0.73 in the institution cohort. The DCA showed that the model has clinical utility. The other published model had an AUC of 0.66 in the institution cohort. Adding risk factors to the DCIS-upstage model slightly increased the AUC.

CONCLUSIONS

The DCIS-upstage prediction model is valid in other cohorts. The model has clinical utility and may be used to select patients with biopsy-proven DCIS for sentinel lymph node biopsy.

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.

High rate of postoperative upstaging of ductal carcinoma in situ when prioritizing ultrasound evaluation of mammography-detected lesions: a single-center retrospective cohort study

BACKGROUND

The initial diagnosis of ductal carcinoma in situ (DCIS) can be upstaged to invasive cancer after definitive surgery. This study aimed to identify risk factors for DCIS upstaging using routine breast ultrasonography and mammography (MG) and to propose a prediction model.

METHODS

In this single-center retrospective study, patients initially diagnosed with DCIS (January 2016-December 2017) were enrolled (final sample size = 272 lesions). Diagnostic modalities included ultrasound-guided core needle biopsy (US-CNB), MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy. Breast ultrasonography was routinely performed for all patients. US-CNB was prioritized for lesions visible on ultrasound. Lesions initially diagnosed as DCIS on biopsy with a final diagnosis of invasive cancer at definitive surgery were defined as "upstaged."

RESULTS

The postoperative upstaging rates were 70.5%, 9.7%, and 4.8% in the US-CNB, MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy groups, respectively. US-CNB, ultrasonographic lesion size, and high-grade DCIS were independent predictive factors for postoperative upstaging, which were used to construct a logistic regression model. Receiver operating characteristic analysis showed good internal validation (area under the curve = 0.88).

CONCLUSIONS

Supplemental screening breast ultrasonography possibly contributes to lesion stratification. The low upstaging rate for ultrasound-invisible DCIS diagnosed by MG-guided procedures suggests that it is unnecessary to perform sentinel lymph node biopsy for lesions invisible on ultrasound. Case-by-case evaluation of DCIS detected by US-CNB can help surgeons determine if repeating biopsy with vacuum-assisted breast biopsy is necessary or if sentinel lymph node biopsy should accompany breast-preserving surgery.

TRIAL REGISTRATION

This single-center retrospective cohort study was conducted with the approval of the institutional review board of our hospital (approval number 201610005RIND). As this was a retrospective review of clinical data, it was not registered prospectively.

Pathological underestimation and biomarkers concordance rates in breast cancer patients diagnosed with ductal carcinoma in situ at preoperative biopsy

Ductal carcinoma in situ (DCIS) often upgrade to invasive breast cancer at surgery. The current study aimed to identify factors associated with pathological underestimation and evaluate concordance rates of biomarkers between biopsy and surgery. Patients diagnosed with DCIS at needle biopsy from 2009 to 2020 were retrospectively reviewed. Univariate and multivariate analyses were performed to identify factors associated with pathological underestimation. Concordance rates between paired biopsy samples and surgical specimens were evaluated. A total of 735 patients with pure DCIS at biopsy were included, and 392 patients (53.3%) underwent pathological underestimation at surgery. Multivariate analysis demonstrated that tumor size > 5.0 cm [odds ratio (OR) 1.79], MRI BI-RADS ≥ 5 categories (OR 2.03), and high nuclear grade (OR 2.01) were significantly associated with pathological underestimation. Concordance rates of ER, PR, HER2 status and Ki-67 between biopsy and surgery were 89.6%, 91.9%, 94.8%, and 76.4% in lesions without pathological underestimation, and were 86.4%, 93.2%, 98.2% and 76.3% for in situ components in lesions with pathological underestimation. Meanwhile, in situ components and invasive components at surgery had concordance rates of 92.9%, 93.8%, 97.4%, and 86.5% for those biomarkers, respectively. In conclusion, lesions diagnosed as DCIS at biopsy have a high rate of pathological underestimation, which was associated with larger tumor size, higher MRI BI-RADS category, and higher nuclear grade. High concordances were found in terms of ER, PR, and HER2 status evaluation between biopsy and surgery, regardless of the pathological underestimation.

Ductal carcinoma in situ: a risk prediction model for the underestimation of invasive breast cancer

Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) may be diagnosed with invasive breast cancer after excision. We evaluated the preoperative clinical and imaging predictors of DCIS that were associated with an upgrade to invasive carcinoma on final pathology and also compared the diagnostic performance of various statistical models. We reviewed the medical records; including mammography, ultrasound (US), and magnetic resonance imaging (MRI) findings; of 644 patients who were preoperatively diagnosed with DCIS and who underwent surgery between January 2012 and September 2018. Logistic regression and three machine learning methods were applied to predict DCIS underestimation. Among 644 DCIS biopsies, 161 (25%) underestimated invasive breast cancers. In multivariable analysis, suspicious axillary lymph nodes (LNs) on US (odds ratio [OR], 12.16; 95% confidence interval [CI], 4.94-29.95; P < 0.001) and high nuclear grade (OR, 1.90; 95% CI, 1.24-2.91; P = 0.003) were associated with underestimation. Cases with biopsy performed using vacuum-assisted biopsy (VAB) (OR, 0.42; 95% CI, 0.27-0.65; P < 0.001) and lesion size <2 cm on mammography (OR, 0.45; 95% CI, 0.22-0.90; P = 0.021) and MRI (OR, 0.29; 95% CI, 0.09-0.94; P = 0.037) were less likely to be upgraded. No significant differences in performance were observed between logistic regression and machine learning models. Our results suggest that biopsy device, high nuclear grade, presence of suspicious axillary LN on US, and lesion size on mammography or MRI were independent predictors of DCIS underestimation.

Prediction of Underestimation Using Contrast-Enhanced Spectral Mammography in Patients Diagnosed as Ductal Carcinoma In Situ on Preoperative Core Biopsy

BACKGROUND

To assess the performance of contrast-enhanced spectral mammography (CESM) for the prediction of DCIS underestimation in comparison with mammography, breast US, and breast MRI.

PATIENTS AND METHODS

We prospectively enrolled patients diagnosed with DCIS on preoperative core biopsy. Visibility, lesion type, and extent on each imaging modality, CESM gray values (CGV) were evaluated. Pathologic features of core biopsy and surgery were recorded. Chi-square or Fisher's exact test were used for univariate analysis. Multivariate logistic regression analysis was used to find independent predictors for DCIS underestimation and receiver operating characteristic (ROC) curve analysis was performed.

RESULTS

A total of 113 lesions in 108 patients were analyzed (50 pure DCIS; 63 underestimated DCIS). Visibility on mammography, breast US, CESM, and breast MRI were 44%, 76%, 58%, and 80% for pure DCIS, and 73%, 81%, 86%, and 92% for underestimated DCIS. Tumor extents on surgical pathology of pure and underestimated DCIS were 1.11 ± 1.35 cm and 2.61 ± 2.09 cm. On multivariate analysis, nuclear grade and suspected invasion on core biopsy, visibility on mammography, and extent on breast MRI were independent factors for the model 1, whereas nuclear grade on core biopsy, extent on CESM, and mean CGV on MLO-recombined image were independent factors for the model 2. Area under ROC curve (AUC) was 0.843 for model 1 including breast MRI, whereas AUC was 0.823 for model 2 including CESM, which didn't show a significant difference (P = .968).

CONCLUSION

For detecting underestimated DCIS, CESM was superior to mammography and breast US, and comparable to breast MRI.

Breast Lesions Diagnosed as Ductal Carcinoma In Situ by Ultrasound-Guided Core Needle Biopsy: Risk Predictors for Concomitant Invasive Carcinoma and Axillary Lymph Node Metastasis

Background

The major concern over preoperatively diagnosed ductal carcinoma in situ (DCIS) of breast via ultrasound-guided core needle biopsy (US-CNB) is the risk of missing concomitant invasive carcinoma. It is crucial to identify risk predictors for such a phenomenon and evaluate its impact on axillary conditions to help surgeons determine which patients should receive appropriate axillary lymph node management.

Methods

Medical records of 260 patients preoperatively diagnosed with DCIS via 14-gauge CNB were retrospectively analyzed. All of them underwent subsequent surgery at our institution and were successively divided into invasive and non-invasive groups, and metastatic and non-metastatic groups according to pathology of resected specimens and metastasis of axillary lymph nodes (ALNs). Predictive value of preoperative physical examinations, imaging findings, histopathological findings, and hematological indexes for pathological underestimation and metastasis of ALN was assessed by logistic regression analysis.

Results

The concomitant invasive carcinoma was overlooked in 75 out of 260 patients (29.3%). Multivariate analysis revealed that presence of microinvasion, presence of abnormal lymph node on ultrasound, and absent linear or segmental distributed calcification on mammography were independent risk predictors for invasive carcinoma. Fourteen patients had lymph node metastasis, and five of them were in the non-invasive group. The presence of abnormal lymph node on ultrasound and increased ratio of platelet distribution width to platelet crit (PDW/PCT) (>52.85) were identified as independent risk predictors for ALN metastasis.

Conclusion

For patients diagnosed with DCIS preoperatively, appropriate ALN management is necessary if they have risk predictors for concomitant invasive carcinoma and ALN metastasis.

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.

Preoperative Nomogram for Predicting Sentinel Lymph Node Metastasis Risk in Breast Cancer: A Potential Application on Omitting Sentinel Lymph Node Biopsy

Background

Sentinel lymph node (SLN) biopsy is feasible for breast cancer (BC) patients with clinically negative axillary lymph nodes; however, complications develop in some patients after surgery, although SLN metastasis is rarely found. Previous predictive models contained parameters that relied on postoperative data, thus limiting their application in the preoperative setting. Therefore, it is necessary to find a new model for preoperative risk prediction for SLN metastasis to help clinicians facilitate individualized clinical decisions.

Materials and Methods

BC patients who underwent SLN biopsy in two different institutions were included in the training and validation cohorts. Demographic characteristics, preoperative tumor pathological features, and ultrasound findings were evaluated. Multivariate logistic regression was used to develop the nomogram. The discrimination, accuracy, and clinical usefulness of the nomogram were assessed using Harrell’s C-statistic and ROC analysis, the calibration curve, and the decision curve analysis, respectively.

Results

A total of 624 patients who met the inclusion criteria were enrolled, including 444 in the training cohort and 180 in the validation cohort. Young age, high BMI, high Ki67, large tumor size, indistinct tumor margins, calcifications, and an aspect ratio ≥1 were independent predictive factors for SLN metastasis of BC. Incorporating these parameters, the nomogram achieved a robust predictive performance with a C-index and accuracy of 0.92 and 0.85, and 0.82 and 0.80 in the training and validation cohorts, respectively. The calibration curves also fit well, and the decision curve analysis revealed that the nomogram was clinically useful.

Conclusions

We established a nomogram to preoperatively predict the risk of SLN metastasis in BC patients, providing a non-invasive approach in clinical practice and serving as a potential tool to identify BC patients who may omit unnecessary SLN biopsy.

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

Background

We conducted a prospective study with the intention to omit surgery for patients with ductal carcinoma in situ (DCIS) of the breast. We aimed to identify clinicopathological predictors of postoperative upstaging to invasive ductal carcinoma (IDC) in patients preoperatively diagnosed with DCIS.

Patients and methods

We retrospectively analyzed patients with DCIS diagnosed through biopsy between April 1, 2010 and December 31, 2014, from 16 institutions. Clinical, radiological, and histological variables were collected from medical records.

Results

We identified 2,293 patients diagnosed with DCIS through biopsy, including 1,663 DCIS (72.5%) cases and 630 IDC (27.5%) cases. In multivariate analysis, the presence of a palpable mass (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.2–2.6), mammography findings (≥ category 4; OR 1.8; 95% CI 1.2–2.6), mass formations on ultrasonography (OR 1.8; 95% CI 1.2–2.5), and tumor size on MRI (> 20 mm; OR 1.7; 95% CI 1.2–2.4) were independent predictors of IDC. Among patients with a tumor size on MRI of ≤ 20 mm, the possibility of postoperative upstaging to IDC was 22.1%. Among the 258 patients with non-palpable mass, nuclear grade 1/2, and positive for estrogen receptor, the possibility was 18.1%, even if the upper limit of the tumor size on MRI was raised to ≤ 40 mm.

Conclusion

We identified four independent predictive factors of upstaging to IDC after surgery among patients with DCIS diagnosed by biopsy. The combined use of various predictors of IDC reduces the possibility of postoperative upstaging to IDC, even if the tumor size on MRI is larger than 20 mm.

Application of deep learning to predict underestimation in ductal carcinoma in situ of the breast with ultrasound

Background

To develop an ultrasound-based deep learning model to predict postoperative upgrading of pure ductal carcinoma in situ (DCIS) diagnosed by core needle biopsy (CNB) before surgery.

Methods

Of the 360 patients with DCIS diagnosed by CNB and identified retrospectively, 180 had lesions upstaged to ductal carcinoma in situ with microinvasion (DCISM) or invasive ductal carcinoma (IDC) postoperatively. Ultrasound images obtained from the hospital database were divided into a training set (n=240) and validation set (n=120), with a ratio of 2:1 in chronological order. Four deep learning models, based on the ResNet and VggNet structures, were established to classify the ultrasound images into postoperative upgrade and pure DCIS. We obtained the area under the receiver operating characteristic curve (AUROC), specificity, sensitivity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) to estimate the performance of the predictive models. The robustness of the models was evaluated by a 3-fold cross-validation.

Results

Clinical features were not significantly different between the training set and the test set (P value >0.05). The area under the receiver operating characteristic curve of our models ranged from 0.724 to 0.804. The sensitivity, specificity, and accuracy of the optimal model were 0.733, 0.750, and 0.742, respectively. The three-fold cross-validation results showed that the model was very robust.

Conclusions

The ultrasound-based deep learning prediction model is effective in predicting DCIS that will be upgraded postoperatively.

Predictors of invasive disease in patients preoperatively diagnosed with ductal carcinoma without stromal invasion, with breast magnetic resonance imaging (MRI) and ultrasound (US)

BACKGROUND

A preoperative diagnosis of ductal carcinoma in situ (DCIS) is sometimes upstaged to invasive disease postoperatively. Our objective was to clarify the predictive factors of invasive disease using preoperative imaging and to investigate the positive ratio of sentinel lymph nodes (SLN) and the incidence of invasive disease.

METHODS

The subjects were 402 patients with preoperatively diagnosed ductal carcinoma without stromal invasion who underwent breast surgery with concomitant SLN surgery in January 2007 to December 2016. Of the 306 included patients, all 306 patients underwent preoperative MRI and US assessment. Outcomes were analyzed for significance using univariate and multivariate analyses.

RESULTS

Of the 306 patients, 115 (37.6%) had invasive disease and 191 (62.4%) had DCIS only. Of the 115 patients with invasive disease, 5 (4.4%) and 4 (3.5%) had macro- and micrometastases in SLN. On the other hand, of the 191 patients with DCIS, only 1 (0.5%) had a micrometastasis. Predictors of invasive disease in the univariate analysis included having a palpable mass, were varied by biopsy method, having a US hypoechoic mass, MRI enhancement, or MRI large enhanced lesion; the size of the mass enhancement ≥ 1.1 cm or a spread of non-mass enhancement ≥ 3.1 cm (P = 0.003). Predictors of invasive disease in the multivariate analysis included US hypoechoic mass and MRI large enhanced lesion.

CONCLUSION

We need to perform SLN biopsy for preoperatively diagnosed DCIS when patients have predictors of invasive disease, but SLN biopsy will no longer be essential for patients when they have no predictors of invasive disease.

Multicentre study of the risk of invasive cancer and use of sentinel node biopsy in women with a preoperative diagnosis of ductal carcinoma in situ

Background

Ductal carcinoma in situ (DCIS) in the breast that is diagnosed by biopsy implies a risk of upstaging to invasive carcinoma (IC) on final pathology. These patients require a sentinel lymph node biopsy (SLNB) for axillary staging. A two-stage procedure is not always feasible and precise selection of patients who should be offered SLNB is crucial. The aims were: to determine the rate of upstaging, and use of redundant and required SLNB in women with a preoperative diagnosis of DCIS; and to identify patient and tumour characteristics that increase the risk of upstaging.

Methods

Patients with DCIS treated between 2008 and 2016 were identified using Orbit operation planning system software, and those suitable for the study were selected based on review of the medical records. Upstaging rates and proportions of redundant and required SLNBs were calculated. Associations between clinicopathological characteristics and upstaging were analysed using univariable and multivariable logistic regression analyses.

Results

Of 1368 patients initially identified, 975 women with a preoperative diagnosis of DCIS were included in the study. Tumours in 246 of these patients (25·2 per cent) were upstaged to IC. Redundant SLNB was performed in 392 of 975 women (40·2 per cent). Forty-four patients (4·5 per cent) with a final diagnosis of IC were not offered SLNB and thus potentially undertreated. In adjusted analysis, DCIS size, palpability and mass formation identified by breast imaging were associated with increased risk of upstaging. The Van Nuys classification was not associated with upstaging.

Conclusion

Most patients with IC on final pathology underwent SLNB, but a considerable number of patients with DCIS had a redundant SLNB. Lesion size, palpability and mass formation, but not Van Nuys classification group, are suggested risk factors for upstaging.

Axillary evaluation is not warranted in patients preoperatively diagnosed with ductal carcinoma in situ by core needle biopsy

Background

Patients diagnosed with ductal carcinoma in situ (DCIS) by core needle biopsy (CNB) have a great chance of upstaging to invasive cancer. Positive axillary status can be found in these patients. This study sought to identify clinicopathological factors associated with upstaging and axillary metastasis in patients preoperatively diagnosed with DCIS by CNB.

Materials and Methods

This study identified 604 patients (cT1‐3N0M0) with preoperative diagnosis of pure DCIS by CNB who had undergone axillary evaluation from August 2006 to December 2015 at Fudan University Shanghai Cancer Center (FUSCC). Predictors of upstaging and axillary lymph nodes metastasis were analyzed, respectively.

Results

Of all 604 patients, 121 (20.03%) and 193 (31.95%) patients were upstaged to DCIS with microinvasion (DCISM) and invasive breast cancer (IBC). Positive axillary lymph nodes were identified in 41 (6.79%) patients. Predictors of upstaging included tumor size on ultrasonography (>2 cm) (OR 1.786, P = .002) and ER+HER2+ status (OR 1.874, P = .022) in multivariate analysis. Factors associated with axillary lymph nodes metastasis included tumor size on pathology (OR 2.336, P = .038) and number of lesions (OR 3.354, P = .039) in multivariate analysis. In addition, upstaging on final pathology had a significant influence on axillary lymph nodes status (P < .001).

Conclusion

Axillary evaluation was recommended in patients with larger tumor size (>2 cm), multifocal lesions or ER+HER2+ status. Despite of a 51.98% upstaging rate, the rate of axillary metastasis in these patients was relatively low, supporting the omission of axillary evaluation in selected patients with low risk of upstaging or axillary metastasis.

Predictive factors of axillary positive sentinel lymph node biopsy in extended ductal carcinoma in situ treated by simple mastectomy at once

BACKGROUND

The incidence of positive sentinel lymph node biopsy (SLNB) in ductal carcinoma in situ (DCIS) ranged from 0 to 14%. The main hypothesis would be the presence of an invasive contingent on the final histology. The objective was to identify predictive factors of sentinel lymph node positivity in the management of extended ductal carcinoma in situ treated by simple mastectomy.

METHODS

This was a retrospective study carried out at the Lorraine Cancer Institute from January 2003 to December 2017. Women with DCIS on core-needle biopsy whose management consisted of simple mastectomy and SLNB procedure were included.

RESULTS

188 patients were analyzed. Preoperatively, 18 patients (9.6%) had DCIS with microinvasion, while the others had pure DCIS. Eight patients (4.2%) had positive sentinel lymph node biopsy, the majority of which were single micrometastases. Predictive factor of node invasion was microinvasion on biopsy (p<0.01). Only in cases of pure DCIS, the percentage of positive SLNB was reduced to 2.9%. Invasive carcinoma was found in the majority of patients with positive axillary SLNB procedure (75%, n=6), compared to 16.7% (n=30) without SLNB involvement (p<0.01).

CONCLUSIONS

The low rate of positive sentinel node biopsy in pure ductal carcinoma in situ suggests that in the absence of microinvasion, the sentinel procedure would seem less appropriate. New techniques for identifying sentinel lymph node biopsy could report axillary staging after definitive histologic results.

Ductal Carcinoma in situ after Core Needle Biopsy: In Which Cases Is a Sentinel Node Biopsy Necessary?

Introduction

In some hospitals it is still common practice to carry out a sentinel node biopsy (SNB) if ductal carcinoma in situ (DCIS) is determined in preoperative staging, although this is against international guidelines. The reason for this is because an infiltrative component can be demonstrated frequently in the final pathohistological examination. In this study, we wanted to investigate possible predictors for infiltrative growth, to select patients to do an SNB or to omit it.

Material and Methods

All patients with DCIS in the core needle biopsy (CNB), who were treated with surgery including an SNB, were included in a prospective data registry. Patient characteristics were collected through physical examination, mammography and ultrasonography. All characteristics of the DCIS were noted. After surgery, the pathological results were collected.

Results

From the 287 patients, 39 (13.6%) had an infiltrative component in the definitive pathological examination despite only DCIS in preoperative CNB. In total, there were only 14 (4.9%) positive SNBs, of which 11 patients had infiltrative growth in the breast tumor and 3 (1.2% of patients with DCIS alone in the final pathology) did not. In addition, characteristics of the CNB, including microcalcifications and comedonecrosis, did not show a statistically significant higher risk for infiltration.

Discussion

Considering the low rates of positive SNBs in our population, we think that an SNB should not be performed in advance when DCIS is diagnosed, because if infiltrative growth is found in the final biopsy, an SNB could always be performed afterwards. Only if an SNB cannot be performed afterwards is an SNB indicated.

A retrospective alternative for active surveillance trials for ductal carcinoma in situ of the breast

Ductal carcinoma in situ (DCIS) of the breast is a nonobligate precursor of invasive breast cancer, accounting for 20 % of screen-detected breast cancers. Little is known about the natural progression of DCIS because most patients undergo surgery upon diagnosis. Many DCIS patients are likely being overtreated, as it is believed that only around 50 % of DCIS will progress to invasive carcinoma. Robust prognostic markers for progression to invasive carcinoma are lacking. In the past, studies have investigated women who developed a recurrence after breast-conserving surgery (BCS) and compared them with those who did not. However, where there is no recurrence, the patient has probably been adequately treated. The present narrative review advocates a new research strategy, wherein only those patients with a recurrence are studied. Approximately half of the recurrences are invasive cancers, and half are DCIS. So-called "recurrences" are probably most often the result of residual disease. The new approach allows us to ask: why did some residual DCIS evolve to invasive cancers and others not? This novel strategy compares the group of patients that developed in situ recurrence with the group of patients that developed invasive recurrence after BCS. The differences between these groups could then be used to develop a robust risk stratification tool. This tool should estimate the risk of synchronous and metachronous invasive carcinoma when DCIS is diagnosed in a biopsy. Identification of DCIS patients at low risk for developing invasive carcinoma will individualize future therapy and prevent overtreatment.

Factors associated with upstaging in patients preoperatively diagnosed with ductal carcinoma in situ by core needle biopsy

Objective

Patients preoperatively diagnosed with ductal carcinoma in situ (DCIS) by core needle biopsy (CNB) exhibit a significant risk for upstaging on final pathology, which leads to major concerns of whether axillary staging is required at the primary operation. The present study aimed to identify clinicopathological factors associated with upstaging in patients preoperatively diagnosed with DCIS by CNB.

Methods

The present study enrolled 604 patients (cN0M0) with a preoperative diagnosis of pure DCIS by CNB, who underwent axillary staging between August 2006 and December 2015, at Fudan University Shanghai Cancer Center (Shanghai, China). Predictive factors of upstaging were analyzed retrospectively.

Results

Of the 604 patients, 20.03% (n = 121) and 31.95% (n = 193) were upstaged to DCIS with microinvasion (DCISM) and invasive breast cancer (IBC) on final pathology, respectively. Larger tumor size on ultrasonography (> 2 cm) was independently associated with upstaging [odds ratio (OR) 1.558,P = 0.014]. Additionally, patients in lower breast imaging reporting and data system (BI-RADS) categories were less likely to be upstaged (4B vs. 5: OR 0.435, P = 0.002; 4C vs. 5: OR 0.502, P = 0.001). Overall, axillary metastasis occurred in 6.79% (n = 41) of patients. Among patients with axillary metastasis, 1.38% (4/290), 3.31% (4/121) and 17.10% (33/193) were in the DCIS, DCISM, and IBC groups, respectively.

Conclusions

For patients initially diagnosed with DCIS by CNB, larger tumor size on ultrasonography (> 2 cm) and higher BI-RADS category were independent predictive factors of upstaging on final pathology. Thus, axillary staging in patients with smaller tumor sizes and lower BI-RADS category may be omitted, with little downstream risk for upstaging.

A prediction model for underestimation of invasive breast cancer after a biopsy diagnosis of ductal carcinoma in situ: based on 2892 biopsies and 589 invasive cancers

Background

Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) might be diagnosed with invasive breast cancer at excision, a phenomenon known as underestimation. Patients with DCIS are treated based on the risk of underestimation or progression to invasive cancer. The aim of our study was to expand the knowledge on underestimation and to develop a prediction model.

Methods

Population-based data were retrieved from the Dutch Pathology Registry and the Netherlands Cancer Registry for DCIS between January 2011 and June 2012.

Results

Of 2892 DCIS biopsies, 21% were underestimated invasive breast cancers. In multivariable analysis, risk factors were high-grade DCIS (odds ratio (OR) 1.43, 95% confidence interval (CI): 1.05–1.95), a palpable tumour (OR 2.22, 95% CI: 1.76–2.81), a BI-RADS (Breast Imaging Reporting and Data System) score 5 (OR 2.36, 95% CI: 1.80–3.09) and a suspected invasive component at biopsy (OR 3.84, 95% CI: 2.69–5.46). The predicted risk for underestimation ranged from 9.5 to 80.2%, with a median of 14.7%. Of the 596 invasive cancers, 39% had unfavourable features.

Conclusions

The risk for an underestimated diagnosis of invasive breast cancer after a biopsy diagnosis of DCIS is considerable. With our prediction model, the individual risk of underestimation can be calculated based on routinely available preoperatively known risk factors (https://www.evidencio.com/models/show/1074).

Is sentinel lymph node biopsy indicated in patients with a diagnosis of ductal carcinoma in situ? A systematic literature review and meta-analysis

BACKGROUND

Recent discussion has suggested that some cases of ductal carcinoma in situ (DCIS) with high risk of invasive disease may require sentinel lymph node biopsy (SLNB).

METHODS

Systematic literature review identified 48 studies (9,803 DCIS patients who underwent SLNB). Separate analyses for patients diagnosed preoperatively by core sampling and patients diagnosed postoperatively by specimen pathology were conducted to determine the percentage of patients with axillary nodal involvement. Patient factors were analyzed for associations with risk of nodal involvement.

RESULTS

The mean percentage of positive SLNBs was higher in the preoperative group (5.95% vs 3.02%; P = .0201). Meta-regression analysis showed a direct association with tumor size (P = .0333) and grade (P = .00839) but not median age nor tumor upstage rate.

CONCLUSIONS

The SLNB should be routinely considered in patients with large (>2 cm) high-grade DCIS after a careful multidisciplinary discussion. In the context of breast conserving surgery, the SLNB is not routinely indicated for low- and intermediate-grade DCIS, high-grade DCIS smaller than 2 cm, or pure DCIS diagnosed by definitive surgical excision.