Variability in grading of ductal carcinoma in situ among an international group of pathologists

Deintensification of Radiotherapy Use in Treatment of Ductal Carcinoma In Situ in the Netherlands-A Nationwide Overview From 2008 Until 2022

AIMS

Ductal Carcinoma In Situ (DCIS) treated by breast-conserving surgery followed by radiotherapy aims to decrease the probability of locally recurrent disease. The role of whole breast irradiation, specifically in DCIS having low recurrence risk and low risk of becoming invasive, is increasingly debated. Also, the added value of applying boost irradiation in DCIS has been questioned. Hence, we evaluated the nationwide radiotherapy use in DCIS treatment in the Netherlands.

MATERIALS AND METHODS

Women diagnosed with DCIS in 2008-2022 were identified in the Netherlands Cancer Registry. Their primary treatment was presented over time and for age groups, stratified for DCIS grade I-II and III. Factors associated with radiotherapy use after breast-conserving surgery and boost irradiation use in whole breast irradiation after breast-conserving surgery were identified.

RESULTS

In women with DCIS grade I-II (N = 16,653), the use of breast-conserving surgery without radiotherapy increased from ∼11% in 2008-2013 to ∼26% in 2017-2022. Furthermore, post-breast-conserving surgery radiotherapy increasingly concerned whole breast irradiation without a boost or partial breast irradiation. Moreover, surgery was omitted more often in recent years (30% in 2022). In DCIS grade III (N = 13,534), the use of breast-conserving surgery without radiotherapy only slightly increased in the most recent years in older patients, while boost irradiation was increasingly omitted. Whole breast irradiation and boost irradiation following breast-conserving surgery were more often applied in case of a higher risk of recurrences: young age, larger lesions, or irradical resection. Variation was observed for hospital-characteristics but not for regions.

CONCLUSION

In DCIS, the process of omitting breast irradiation after breast-conserving surgery is clearly ongoing. Boost irradiation was administered less frequently. Furthermore, the use of partial breast irradiation was introduced in recent years. These effects are more prominent in older women and those with grade I-II DCIS.

A morphometric signature to identify ductal carcinoma in situ with a low risk of progression

Ductal carcinoma in situ (DCIS) may progress to ipsilateral invasive breast cancer (iIBC), but often never will. Because DCIS is treated as early breast cancer, many women with harmless DCIS face overtreatment. To identify features associated with progression, we developed an artificial intelligence-based DCIS morphometric analysis pipeline (AIDmap) on hematoxylin-eosin-stained (H&E) tissue sections. We analyzed 689 digitized H&Es of pure primary DCIS of which 226 were diagnosed with subsequent iIBC and 463 were not. The distribution of 15 duct morphological measurements was summarized in 55 morphometric variables. A ridge regression classifier with cross validation predicted 5-years-free of iIBC with an area-under the curve of 0.67 (95% CI 0.57-0.77). A combined clinical-morphometric signature, characterized by small-sized ducts, a low number of cells and a low DCIS/stroma ratio, was associated with outcome (HR = 0.56; 95% CI 0.28-0.78). AIDmap has potential to identify harmless DCIS that may not need treatment.

Conquering Overtreatment of DCIS: Lessons from PRECISION

As we cannot reliably distinguish indolent, low-risk ductal carcinoma in situ (DCIS) from potentially progressive, high-risk DCIS, all women with DCIS diagnosis undergo intensive treatment without any benefit. The PREvent ductal Carcinoma In Situ Invasive Overtreatment Now team was established to unravel DCIS biology and develop new multidisciplinary approaches for accurate risk stratification to tackle the global problem of DCIS overdiagnosis and overtreatment. See related article by Bressan et al., p. 16 See related article by Stratton et al., p. 22 See related article by Goodwin et al., p. 34.

A Nomogram Using Imaging Features to Predict Ipsilateral Breast Tumor Recurrence After Breast-Conserving Surgery for Ductal Carcinoma In Situ

OBJECTIVE

To develop a nomogram that integrates clinical-pathologic and imaging variables to predict ipsilateral breast tumor recurrence (IBTR) in women with ductal carcinoma in situ (DCIS) treated with breast-conserving surgery (BCS).

MATERIALS AND METHODS

This retrospective study included consecutive women with DCIS who underwent BCS at two hospitals. Patients who underwent BCS between 2003 and 2016 in one hospital and between 2005 and 2013 in another were classified into development and validation cohorts, respectively. Twelve clinical-pathologic variables (age, family history, initial presentation, nuclear grade, necrosis, margin width, number of excisions, DCIS size, estrogen receptor, progesterone receptor, radiation therapy, and endocrine therapy) and six mammography and ultrasound variables (breast density, detection modality, mammography and ultrasound patterns, morphology and distribution of calcifications) were analyzed. A nomogram for predicting 10-year IBTR probabilities was constructed using the variables associated with IBTR identified from the Cox proportional hazard regression analysis in the development cohort. The performance of the developed nomogram was evaluated in the external validation cohort using a calibration plot and 10-year area under the receiver operating characteristic curve (AUROC) and compared with the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram.

RESULTS

The development cohort included 702 women (median age [interquartile range], 50 [44-56] years), of whom 30 (4%) women experienced IBTR. The validation cohort included 182 women (48 [43-54] years), 18 (10%) of whom developed IBTR. A nomogram was constructed using three clinical-pathologic variables (age, margin, and use of adjuvant radiation therapy) and two mammographic variables (breast density and calcification morphology). The nomogram was appropriately calibrated and demonstrated a comparable 10-year AUROC to the MSKCC nomogram (0.73 vs. 0.66, P = 0.534) in the validation cohort.

CONCLUSION

Our nomogram provided individualized risk estimates for women with DCIS treated with BCS, demonstrating a discriminative ability comparable to that of the MSKCC nomogram.

Invasive recurrence after breast conserving treatment of ductal carcinoma in situ of the breast in the Netherlands: time trends and the association with tumour grade

BACKGROUND

The first aim of this study was to examine trends in the risk of ipsilateral invasive breast cancer (iIBC) after breast-conserving surgery (BCS) of ductal carcinoma in situ (DCIS). A second aim was to analyse the association between DCIS grade and the risk of iIBC following BCS.

PATIENTS AND METHODS

In this population-based, retrospective cohort study, the Netherlands Cancer Registry collected information on 25,719 women with DCIS diagnosed in the period 1989-2021 who underwent BCS. Of these 19,034 received adjuvant radiotherapy (RT). Kaplan-Meier analyses and Cox regression models were used.

RESULTS

A total of 1135 patients experienced iIBC. Ten-year cumulative incidence rates of iIBC for patients diagnosed in the periods 1989-1998, 1999-2008 and 2009-2021 undergoing BCS without RT, were 12.6%, 9.0% and 5.0% (P < 0.001), respectively. For those undergoing BCS with RT these figures were 5.7%, 3.7% and 2.2%, respectively (P < 0.001). In the multivariable analyses, DCIS grade was not associated with the risk of iIBC.

CONCLUSION

Since 1989 the risk of iIBC has decreased substantially and has become even lower than the risk of invasive contralateral breast cancer. No significant association of DCIS grade with iIBC was found, stressing the need for more powerful prognostic factors to guide the treatment of DCIS.

Systematic assessment of HER2 status in ductal carcinoma in situ of the breast: a perspective on the potential clinical relevance

In many countries, hormone receptor status assessment of ductal carcinoma in situ (DCIS) is routinely performed, as hormone receptor-positive DCIS patients are eligible for adjuvant anti-hormonal treatment, aiming to reduce the ipsilateral and contralateral breast cancer risk. Although HER2 gene amplification and its associated HER2 protein overexpression constitute a major prognostic and predictive marker in invasive breast carcinoma, its use in the diagnosis and treatment of DCIS is less straightforward. HER2 immunohistochemistry is not routinely performed yet, as the role of HER2-positivity in DCIS biology is unclear. Nonetheless, recent data challenge this practice. Here, we discuss the value of routine HER2 assessment for DCIS. HER2-positivity correlates strongly with DCIS grade: around four in five HER2-positive DCIS show high grade atypia. As morphological DCIS grading is prone to interobserver variability, HER2 immunohistochemistry could render grading more robust. Several studies showed an association between HER2-positive DCIS and ipsilateral recurrence risk, albeit currently unclear whether this is for overall, in situ or invasive recurrence. HER2-positive DCIS tends to be larger, with a higher risk of involved surgical margins. HER2-positive DCIS patients benefit more from adjuvant radiotherapy: it substantially decreases the local recurrence risk after lumpectomy, without impact on overall survival. HER2-positivity in pure biopsy-diagnosed DCIS is associated with increased upstaging to invasive carcinoma after surgery. HER2 immunohistochemistry on preoperative biopsies might therefore provide useful information to surgeons, favoring wider excisions. The time seems right to consider DCIS subtype-dependent treatment, comprising appropriate local treatment for HER2-positive DCIS patients and de-escalation for hormone receptor-positive, HER2-negative DCIS patients.

Radiology for Ductal Carcinoma In Situ of the Breast: Updates on Invasive Cancer Progression and Active Monitoring

Ductal carcinoma in situ (DCIS) accounts for approximately 30% of new breast cancer diagnoses. However, our understanding of how normal breast tissue evolves into DCIS and invasive cancers remains insufficient. Further, conclusions regarding the mechanisms of disease progression in terms of histopathology, genetics, and radiology are often conflicting and have implications for treatment planning. Moreover, the increase in DCIS diagnoses since the adoption of organized breast cancer screening programs has raised concerns about overdiagnosis and subsequent overtreatment. Active monitoring, a nonsurgical management strategy for DCIS, avoids surgery in favor of close imaging follow-up to de-escalate therapy and provides more treatment options. However, the two major challenges in active monitoring are identifying occult invasive cancer and patients at risk of invasive cancer progression. Subsequently, four prospective active monitoring trials are ongoing to determine the feasibility of active monitoring and refine the patient eligibility criteria and follow-up intervals. Radiologists play a major role in determining eligibility for active monitoring and reviewing surveillance images for disease progression. Trial results published over the next few years would support a new era of multidisciplinary DCIS care.

Ductal carcinoma in situ of the breast: finding the balance between overtreatment and undertreatment

Ductal carcinoma in situ (DCIS) accounts for 15-25% of all breast cancer diagnoses. Its prognosis is excellent overall, the main risk being the occurrence of local breast events, as most cases of DCIS do not progress to invasive cancer. Systematic screening has greatly increased the incidence of this non-obligate precursor of invasion, lending urgency to the need to identify DCIS that is prone to invasive progression and distinguish it from non-invasion-prone DCIS, as the latter can be overdiagnosed and therefore overtreated. Treatment strategies, including surgery, radiotherapy, and optional endocrine therapy, decrease the risk of local events, but have no effect on survival outcomes. Active surveillance is being evaluated as a possible new option for low-risk DCIS. Considerable efforts to decipher the biology of DCIS have led to a better understanding of the factors that determine its variable natural history. Given this variability, shared decision making regarding optimal, personalised treatment strategies is the most appropriate course of action. Well designed, risk-based de-escalation studies remain a major need in this field.

Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

Update on Management of Ductal Carcinoma in Situ

Ductal carcinoma in situ (DCIS) represents 18% to 25% of all diagnosed breast cancers, and is a noninvasive, nonobligate precursor lesion to invasive cancer. The diagnosis of DCIS represents a wide range of disease, including lesions with both low and high risk of progression to invasive cancer and recurrence. Over the past decade, research on the topic of DCIS has focused on the possibility of tailoring treatment for patients according to their risk for progression and recurrence, which is based on clinicopathologic, biomolecular and genetic factors. These efforts are ongoing, with recently completed and continuing clinical trials spanning the continuum of cancer care. We conducted a review to identify recent advances on the topic of diagnosis, risk stratification and management of DCIS. While novel imaging techniques have increased the rate of DCIS diagnosis, questions persist regarding the optimal management of lesions that would not be identified with conventional methods. Additionally, among trials investigating the potential for omission of surgery and use of active surveillance, 2 trials have completed accrual and 2 clinical trials are continuing to enroll patients. Identification of novel genetic patterns is expanding our potential for risk stratification and aiding our ability to de-escalate radiation and systemic therapies for DCIS. These advances provide hope for tailoring of DCIS treatment in the near future.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials

BACKGROUND

Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296-2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA),  L. E. Elshof et al., Eur J Cancer, 51, 1497-510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials.

OBJECTIVE

To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance.

METHODS

In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS.

RESULTS

When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved.

CONCLUSION

For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.

Evolving Treatment Paradigms for Low-Risk Ductal Carcinoma In Situ: Imaging Needs

Ductal carcinoma in situ (DCIS) is a nonobligate precursor to invasive cancer that classically presents as asymptomatic calcifications on screening mammography. The increase in DCIS diagnoses with organized screening programs has raised concerns about overdiagnosis, while a patientcentric push for more personalized care has increased awareness about DCIS overtreatment. The standard of care for most new DCIS diagnoses is surgical excision, but nonsurgical management via active monitoring is gaining attention, and multiple clinical trials are ongoing. Imaging, along with demographic and pathologic information, is a critical component of active monitoring efforts. Commonly used imaging modalities including mammography, ultrasound, and MRI, as well as newer modalities such as contrast-enhanced mammography and dedicated breast PET, can provide prognostic information to risk stratify patients for DCIS active monitoring eligibility. Furthermore, radiologists will be responsible for closely surveilling patients on active monitoring and identifying if invasive progression occurs. Active monitoring is a paradigm shift for DCIS care, but the success or failure will rely heavily on the interpretations and guidance of radiologists.

Domain and Histopathology Adaptations-Based Classification for Malignancy Grading System

Accurate proliferation rate quantification can be used to devise an appropriate treatment for breast cancer. Pathologists use breast tissue biopsy glass slides stained with hematoxylin and eosin to obtain grading information. However, this manual evaluation may lead to high costs and be ineffective because diagnosis depends on the facility and the pathologists' insights and experiences. Convolutional neural network acts as a computer-based observer to improve clinicians' capacity in grading breast cancer. Therefore, this study proposes a novel scheme for automatic breast cancer malignancy grading from invasive ductal carcinoma. The proposed classifiers implement multistage transfer learning incorporating domain and histopathologic transformations. Domain adaptation using pretrained models, such as InceptionResNetV2, InceptionV3, NASNet-Large, ResNet50, ResNet101, VGG19, and Xception, was applied to classify the ×40 magnification BreaKHis data set into eight classes. Subsequently, InceptionV3 and Xception, which contain the domain and histopathology pretrained weights, were determined to be the best for this study and used to categorize the Databiox database into grades 1, 2, or 3. To provide a comprehensive report, this study offered a patchless automated grading system for magnification-dependent and magnification-independent classifications. With an overall accuracy (means ± SD) of 90.17% ± 3.08% to 97.67% ± 1.09% and an F1 score of 0.9013 to 0.9760 for magnification-dependent classification, the classifiers in this work achieved outstanding performance. The proposed approach could be used for breast cancer grading systems in clinical settings.

Agreement on risk assessment and chemotherapy recommendations among breast cancer specialists: A survey within the MINDACT cohort

PURPOSE

Tailored recommendation for adjuvant chemotherapy in breast cancer patients is of great importance. This survey assessed agreement among oncologists on risk assessment and chemotherapy recommendation, the impact of adding the 70-gene signature to clinical-pathological characteristics, and changes over time.

METHODS

A survey consisting of 37 discordant patient cases from the MINDACT trial (T1-3N0-1M0) was sent to European breast cancer specialists for assessment of risk (high or low) and chemotherapy administration (yes or no). In 2015 the survey was sent twice (survey 1 and 2), several weeks apart, and in 2021 a third time (survey 3). Only the second and third surveys included the 70-gene signature result.

RESULTS

41 breast cancer specialists participated in all three surveys. Overall agreement between respondents decreased slightly between survey 1 and 2, but increased again in survey 3. Over time there was an increase in agreement with the 70-gene signature result on risk assessment, 23% in survey 2 versus 1 and 11% in survey 3 versus 2. With information available indicating a low risk 70-gene signature (n = 25 cases), 20% of risk assessments changed from high to low and 19% of recommendations changed from yes to no chemotherapy in survey 2 versus 1, further increasing with 18% and 21%, respectively, in survey 3 versus 2.

CONCLUSION

There is a variability in risk assessment of early breast cancer patients among breast cancer specialists. The 70-gene signature provided valuable information, resulting in fewer patients being assessed as high risk and fewer recommendations for chemotherapy, increasing over time.

Analytical validation of the 7-gene biosignature for prediction of recurrence risk and radiation therapy benefit for breast ductal carcinoma in situ

Purpose

Ductal carcinoma in situ (DCIS), is a noninvasive breast cancer, representing 20-25% of breast cancer diagnoses in the USA. Current treatment options for DCIS include mastectomy or breast-conserving surgery (BCS) with or without radiation therapy (RT), but optimal risk-adjusted treatment selection remains a challenge. Findings from past and recent clinical trials have failed to identify a 'low risk' group of patients who do not benefit significantly from RT after BCS. To address this unmet need, a DCIS biosignature, DCISionRT (PreludeDx, Laguna Hills, CA), was developed and validated in multiple cohorts. DCISionRT is a molecular assay with an algorithm reporting a recurrence risk score for patients diagnosed with DCIS intended to guide DCIS treatment. In this study, we present results from analytical validity, performance assessment, and clinical performance validation and clinical utility for the DCISionRT test comprised of multianalyte assays with algorithmic analysis.

Methods

The analytical validation of each molecular assay was performed based on the Clinical and Laboratory Standards Institute (CLSI) guidelines Quality Assurance for Design Control and Implementation of Immunohistochemistry Assays and the College of American Pathologists/American Society of Clinical Oncology (CAP/ASCO) recommendations for analytic validation of immunohistochemical assays.

Results

The analytic validation showed that the molecular assays that are part of DCISionRT test have high sensitivity, specificity, and accuracy/reproducibility (≥95%). The analytic precision of the molecular assays under controlled non-standard conditions had a total standard deviation of 6.6 (100-point scale), where the analytic variables (Lot, Machine, Run) each contributed <1% of the total variance. Additionally, the precision in the DCISionRT test result (DS) had a 95%CI ≤0.4 DS units under controlled non-standard conditions (Day, Lot, and Machine) for molecular assays over a wide range of clinicopathologic factor values. Clinical validation showed that the test identified 37% of patients in a low-risk group with a 10-year invasive IBR rate of ~3% and an absolute risk reduction (ARR) from RT of 1% (number needed to treat, NNT=100), while remaining patients with higher DS scores (elevated-risk) had an ARR for RT of 9% (NNT=11) and 96% clinical sensitivity for RT benefit.

Conclusion

The analytical performance of the PreludeDx DCISionRT molecular assays was high in representative formalin-fixed, paraffin-embedded breast tumor specimens. The DCISionRT test has been analytically validated and has been clinically validated in multiple peer-reviewed published studies.

AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trials

Clinical trials in nonalcoholic steatohepatitis (NASH) require histologic scoring for assessment of inclusion criteria and endpoints. However, guidelines for scoring key features have led to variability in interpretation, impacting clinical trial outcomes. We developed an artificial intelligence (AI)-based measurement (AIM) tool for scoring NASH histology (AIM-NASH). AIM-NASH predictions for NASH Clinical Research Network (CRN) grades of necroinflammation and stages of fibrosis aligned with expert consensus scores and were reproducible. Continuous scores produced by AIM-NASH for key histological features of NASH correlated with mean pathologist scores and with noninvasive biomarkers and strongly predicted patient outcomes. In a retrospective analysis of the ATLAS trial, previously unmet pathological endpoints were met when scored by the AIM-NASH algorithm alone. Overall, these results suggest that AIM-NASH may assist pathologists in histologic review of NASH clinical trials, reducing inter-rater variability on trial outcomes and offering a more sensitive and reproducible measure of patient therapeutic response.

Should low-risk DCIS lose the cancer label? An evidence review

BACKGROUND

Population mammographic screening for breast cancer has led to large increases in the diagnosis and treatment of ductal carcinoma in situ (DCIS). Active surveillance has been proposed as a management strategy for low-risk DCIS to mitigate against potential overdiagnosis and overtreatment. However, clinicians and patients remain reluctant to choose active surveillance, even within a trial setting. Re-calibration of the diagnostic threshold for low-risk DCIS and/or use of a label that does not include the word 'cancer' might encourage the uptake of active surveillance and other conservative treatment options. We aimed to identify and collate relevant epidemiological evidence to inform further discussion on these ideas.

METHODS

We searched PubMed and EMBASE databases for low-risk DCIS studies in four categories: (1) natural history; (2) subclinical cancer found at autopsy; (3) diagnostic reproducibility (two or more pathologist interpretations at a single time point); and (4) diagnostic drift (two or more pathologist interpretations at different time points). Where we identified a pre-existing systematic review, the search was restricted to studies published after the inclusion period of the review. Two authors screened records, extracted data, and performed risk of bias assessment. We undertook a narrative synthesis of the included evidence within each category.

RESULTS

Natural History (n = 11): one systematic review and nine primary studies were included, but only five provided evidence on the prognosis of women with low-risk DCIS. These studies reported that women with low-risk DCIS had comparable outcomes whether or not they had surgery. The risk of invasive breast cancer in patients with low-risk DCIS ranged from 6.5% (7.5 years) to 10.8% (10 years). The risk of dying from breast cancer in patients with low-risk DCIS ranged from 1.2 to 2.2% (10 years). Subclinical cancer at autopsy (n = 1): one systematic review of 13 studies estimated the mean prevalence of subclinical in situ breast cancer to be 8.9%. Diagnostic reproducibility (n = 13): two systematic reviews and 11 primary studies found at most moderate agreement in differentiating low-grade DCIS from other diagnoses. Diagnostic drift: no studies found.

CONCLUSION

Epidemiological evidence supports consideration of relabelling and/or recalibrating diagnostic thresholds for low-risk DCIS. Such diagnostic changes would need agreement on the definition of low-risk DCIS and improved diagnostic reproducibility.

Learning to distinguish progressive and non-progressive ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) is a non-invasive breast neoplasia that accounts for 25% of all screen-detected breast cancers diagnosed annually. Neoplastic cells in DCIS are confined to the ductal system of the breast, although they can escape and progress to invasive breast cancer in a subset of patients. A key concern of DCIS is overtreatment, as most patients screened for DCIS and in whom DCIS is diagnosed will not go on to exhibit symptoms or die of breast cancer, even if left untreated. However, differentiating low-risk, indolent DCIS from potentially progressive DCIS remains challenging. In this Review, we summarize our current knowledge of DCIS and explore open questions about the basic biology of DCIS, including those regarding how genomic events in neoplastic cells and the surrounding microenvironment contribute to the progression of DCIS to invasive breast cancer. Further, we discuss what information will be needed to prevent overtreatment of indolent DCIS lesions without compromising adequate treatment for high-risk patients.

Is loss of p53 a driver of ductal carcinoma in situ progression?

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive carcinoma. Multiple studies have shown that DCIS lesions typically possess a driver mutation associated with cancer development. Mutation in the TP53 tumour suppressor gene is present in 15-30% of pure DCIS lesions and in ~30% of invasive breast cancers. Mutations in TP53 are significantly associated with high-grade DCIS, the most likely form of DCIS to progress to invasive carcinoma. In this review, we summarise published evidence on the prevalence of mutant TP53 in DCIS (including all DCIS subtypes), discuss the availability of mouse models for the study of DCIS and highlight the need for functional studies of the role of TP53 in the development of DCIS and progression from DCIS to invasive disease.

Unresected screen-detected ductal carcinoma in situ: Outcomes of 311 women in the Forget-Me-Not 2 study

BACKGROUND AND AIM

The natural history of ductal carcinoma in situ (DCIS) is poorly understood. The aim of this cohort study was to determine the outcomes of women who had no surgery for screen-detected DCIS in the 6 months following diagnosis.

METHODS

English breast screening databases were retrospectively searched for women diagnosed with DCIS without invasive cancer at screening and who had no record of surgery within 6 months of diagnosis. These were cross-referenced with cancer registry data. Details of the potentially eligible women were sent to the relevant breast screening units for verification and for completion of data forms detailing clinical, radiological and pathological findings, non-surgical treatment and subsequent clinical course.

RESULTS

Data for 311 eligible women (median age 62 years) were available. 60 women developed invasive cancer, 56 ipsilateral and 4 contralateral. Ipsilateral invasion risk increased approximately linearly with time for at least 10 years. The 10-year cumulative risk of ipsilateral invasion was 9% (95% CI 4-21%), 39% (24-58%) and 36% (24-50%) for low, intermediate and high grade DCIS respectively and was higher in younger women, in those with larger DCIS lesions and in those with microinvasion. Most invasive cancers that developed were grade 2 or 3.

CONCLUSION

The findings suggest that active surveillance may be a reasonable alternative to surgery in patients with low grade DCIS but that women with intermediate or high grade disease should continue to be offered surgery. This highlights the importance of reproducible grading of DCIS to ensure patients receive appropriate treatment.

Low-risk DCIS. What is it? Observe or excise?

The issue of overdiagnosis and overtreatment of lesions detected by breast screening mammography has been debated in both international media and the scientific literature. A proportion of cancers detected by breast screening would never have presented symptomatically or caused harm during the patient's lifetime. The most likely (but not the only) entity which may represent those overdiagnosed and overtreated is low-grade ductal carcinoma in situ (DCIS). In this article, we address what is understood regarding the natural history of DCIS and the diagnosis and prognosis of low-grade DCIS. However, low cytonuclear grade disease may not be the totality of DCIS that can be considered of low clinical risk and we outline the issues regarding active surveillance vs excision of low-risk DCIS and the clinical trials exploring this approach.

Ductal Carcinoma in Situ: State-of-the-Art Review

Ductal carcinoma in situ (DCIS) is a nonobligate precursor of invasive cancer, and its detection, diagnosis, and management are controversial. DCIS incidence grew with the expansion of screening mammography programs in the 1980s and 1990s, and DCIS is viewed as a major driver of overdiagnosis and overtreatment. For pathologists, the diagnosis and classification of DCIS is challenging due to undersampling and interobserver variability. Understanding the progression from normal breast tissue to DCIS and, ultimately, to invasive cancer is limited by a paucity of natural history data with multiple proposed evolutionary models of DCIS initiation and progression. Although radiologists are familiar with the classic presentation of DCIS as asymptomatic calcifications at mammography, the expanded pool of modalities, advanced imaging techniques, and image analytics have identified multiple potential biomarkers of histopathologic characteristics and prognosis. Finally, there is growing interest in the nonsurgical management of DCIS, including active surveillance, to reduce overtreatment and provide patients with more personalized management options. However, current biomarkers are not adept at enabling identification of occult invasive disease at biopsy or accurately predicting the risk of progression to invasive disease. Several active surveillance trials are ongoing and are expected to better identify women with low-risk DCIS who may avoid surgery.