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.
Ontology highlight
ABSTRACT: 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 ).
SUBMITTER: Meurs CJC
PROVIDER: S-EPMC6219477 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description: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.
| S-EPMC8760307 | biostudies-literature
Project description:Importance:Recent recognition of the overdiagnosis and overtreatment of ductal carcinoma in situ (DCIS) detected by mammography has led to the development of clinical trials randomizing women with non-high-grade DCIS to active surveillance, defined as imaging surveillance with or without endocrine therapy, vs standard surgical care. Objective:To determine the factors associated with underestimation of invasive cancer in patients with a clinical diagnosis of non-high-grade DCIS that would preclude active surveillance. Design, Setting, and Participants:A retrospective cohort study was conducted using records from the National Cancer Database from January 1, 1998, to December 31, 2012, of female patients 40 to 99 years of age with a clinical diagnosis of non-high-grade DCIS who underwent definitive surgical treatment. Data analysis was conducted from November 1, 2015, to February 4, 2017. Exposures:Patients with an upgraded diagnosis of invasive carcinoma vs those with a diagnosis of DCIS based on final surgical pathologic findings. Main Outcomes and Measures:The proportions of cases with an upgraded diagnosis of invasive carcinoma from final surgical pathologic findings were compared by tumor, host, and system characteristics. Results:Of 37?544 women (mean [SD] age, 59.3 [12.4] years) presenting with a clinical diagnosis of non-high-grade DCIS, 8320 (22.2%) had invasive carcinoma based on final pathologic findings. Invasive carcinomas were more likely to be smaller (>0.5 to ?1.0 cm vs ?0.5 cm: odds ratio [OR], 0.73; 95% CI, 0.67-0.79; >1.0 to ?2.0 cm vs ?0.5 cm: OR, 0.42; 95% CI, 0.39-0.46; >2.0 to ?5.0 cm vs ?0.5 cm: OR, 0.19; 95% CI, 0.17-0.22; and >5.0 cm vs ?0.5 cm: OR, 0.11; 95% CI, 0.08-0.15) and lower grade (intermediate vs low: OR, 0.75; 95% CI, 0.69-0.80). Multivariate logistic regression analysis demonstrated that younger age (60-79 vs 40-49 years: OR, 0.84; 95% CI, 0.77-0.92; and ?80 vs 40 to 49 years: OR, 0.76; 95% CI, 0.64-0.91), negative estrogen receptor status (positive vs negative: OR, 0.39; 95% CI, 0.34-0.43), treatment at an academic facility (academic vs community: OR, 2.08; 95% CI, 1.82-2.38), and higher annual income (>$63?000 vs <$38?000: OR, 1.14; 95% CI, 1.02-1.28) were significantly associated with an upgraded diagnosis of invasive carcinoma based on final pathologic findings. Conclusions and Relevance:When selecting patients for active surveillance of DCIS, factors other than tumor biology associated with invasive carcinoma based on final pathologic findings may need to be considered. At the time of randomization to active surveillance, a significant proportion of patients with non-high-grade DCIS will harbor invasive carcinoma.
| S-EPMC5710412 | biostudies-other
Project description:BackgroundWe aimed to develop a multivariable model for prediction of underestimated invasiveness in women with ductal carcinoma in situ at stereotactic large core needle biopsy, that can be used to select patients for sentinel node biopsy at primary surgery.MethodsFrom the literature, we selected potential preoperative predictors of underestimated invasive breast cancer. Data of patients with nonpalpable breast lesions who were diagnosed with ductal carcinoma in situ at stereotactic large core needle biopsy, drawn from the prospective COBRA (Core Biopsy after RAdiological localization) and COBRA2000 cohort studies, were used to fit the multivariable model and assess its overall performance, discrimination, and calibration.Results348 women with large core needle biopsy-proven ductal carcinoma in situ were available for analysis. In 100 (28.7%) patients invasive carcinoma was found at subsequent surgery. Nine predictors were included in the model. In the multivariable analysis, the predictors with the strongest association were lesion size (OR 1.12 per cm, 95% CI 0.98-1.28), number of cores retrieved at biopsy (OR per core 0.87, 95% CI 0.75-1.01), presence of lobular cancerization (OR 5.29, 95% CI 1.25-26.77), and microinvasion (OR 3.75, 95% CI 1.42-9.87). The overall performance of the multivariable model was poor with an explained variation of 9% (Nagelkerke's R(2)), mediocre discrimination with area under the receiver operating characteristic curve of 0.66 (95% confidence interval 0.58-0.73), and fairly good calibration.ConclusionThe evaluation of our multivariable prediction model in a large, clinically representative study population proves that routine clinical and pathological variables are not suitable to select patients with large core needle biopsy-proven ductal carcinoma in situ for sentinel node biopsy during primary surgery.
| S-EPMC3795649 | biostudies-literature
Project description:BackgroundMicroinvasive breast cancer is an uncommon pathological entity. Owing to the rarity of this condition, its surgical axillary management and overall prognosis remain controversial.MethodsA database was analysed to identify patients with microinvasive ductal carcinoma in situ (DCIS) who had surgery for invasive breast cancer at the European Institute of Oncology, Milan, between 1998 and 2010. Women who had undergone axillary staging by sentinel lymph node biopsy were included in the study.ResultsOf 257 women with microinvasive breast cancer who underwent sentinel lymph node biopsy (SLNB), 226 (87·9 per cent) had negative sentinel lymph nodes (SLNs) and 31 had metastatic SLNs. Twelve patients had isolated tumour cells (ITCs), 14 had micrometastases and five had macrometastases in sentinel nodes. Axillary lymph node dissection was performed in 16 of the 31 patients with positive SLNs. After a median follow-up of 11?years, only one regional first event was observed in the 15 patients with positive SLNs who did not undergo axillary lymph node dissection. There were no regional first events in the 16 patients with positive SLNs who had axillary dissection.ConclusionGood disease-free and overall survival were found in women with positive SLNs and microinvasive DCIS. This study is in line with studies showing that SLNB in microinvasive DCIS may not be useful, and supports the evidence that less surgery can provide the same level of overall survival with better quality of life.
| S-EPMC6393177 | biostudies-literature
Project description:BACKGROUND:The upgrade rate of biopsy-confirmed ductal carcinoma in situ (DCIS) to invasive carcinoma is up to 50% on final pathology. We investigated MRI and clinicopathologic predictors of the invasive components of DCIS diagnosed by preoperative biopsy and then compared MRI features between patients with DCIS, microinvasive ductal carcinoma (mIDC), and invasive ductal carcinoma (IDC) diagnosed on final pathology. METHODS:Two hundred and one patients with 206 biopsy-confirmed DCIS lesions were enrolled. MRI and clinicopathologic features were used to predict either mIDC or IDC via a cumulative logistic regression analysis. For the lesions detected on MRI, morphologic and kinetic analyses were performed using the Chi-square, Fisher's exact, and Kruskal-Wallis tests. RESULTS:Of all the lesions, 112 (54.4%) were diagnosed as DCIS, 50 (24.3%) were upgraded to mIDC, and 44 (21.4%) to IDC. The detection on MRI as mass (Odds ratio (OR)?=?8.84, 95% confidence interval (CI)?=?1.05-74.04, P?=?0.045) or non-mass enhancement (NME; OR?=?11.17, 95% CI?=?1.35-92.36, P?=?0.025), negative progesterone receptor (PR; OR?=?2.40, 95% CI?=?1.29-4.44, P?=?0.006), and high Ki-67 level (OR?=?2.42, 95% CI?=?1.30-4.50, P?=?0.005) were significant independent predictors of histologic upgrade. On MRI, 87 (42.2%) lesions appeared as mass and 107 (51.9%) as NME. Irregularly shaped, not-circumscribed, heterogeneous, or rim-enhancing masses with intratumoral high signal intensity or peritumoral edema, clumped or clustered ring-enhancing NMEs, and high peak enhancement were significantly associated with histologic upgrade (P?<?0.001). CONCLUSION:MRI detection, negative PR, and high Ki-67 levels are associated with a histologic upgrade in patients with biopsy-confirmed DCIS. Suspicious MRI features are more frequent in such patients.
| S-EPMC7424652 | biostudies-literature
Project description:BACKGROUND:The transition from ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) is an important step during breast carcinogenesis. Understanding its molecular changes may help to identify high-risk DCIS that progress to IBC. Here, we describe a transcriptomic profiling analysis of matched formalin-fixed and paraffin-embedded (FFPE) DCIS and IBC components of individual breast tumours, containing both tumour compartments. The study was performed to validate progression-associated transcripts detected in an earlier gene profiling project using fresh frozen breast cancer tissue. In addition, FFPE tissues from patients with pure DCIS (pDCIS) were analysed to identify candidate transcripts characterizing DCIS with a high or low risk of progressing to IBC. METHODS:Fifteen laser microdissected pairs of DCIS and IBC were profiled by Illumina DASL technology and used for expression validation by qPCR. Differential expression was independently validated using further 25 laser microdissected DCIS/IBC sample pairs. Additionally, laser microdissected epithelial cells from 31 pDCIS were investigated for expression of candidate transcripts using qPCR. RESULTS:Multiple statistical calculation methods revealed 1784 mRNAs which are differentially expressed between DCIS and IBC (P?<?0.05), of which 124 have also been identified in the gene profiling project using fresh frozen breast cancer tissue. Nine mRNAs that had been selected from the gene list obtained using fresh frozen tissues by applying pathway and network analysis (MMP11, GREM1, PLEKHC1, SULF1, THBS2, CSPG2, COL10A1, COL11A1, KRT14) were investigated in tissues from the same 15 microdissected specimens and the 25 independent tissue samples by qPCR. All selected transcripts were also detected in tumour cells from pDCIS. Expression of MMP11 and COL10A1 increased significantly from pDCIS to DCIS of DCIS/IBC mixed tumours. CONCLUSION:We confirm differential expression of progression-associated transcripts in FFPE breast cancer samples which might mediate the transition from DCIS to IBC. MMP11 and COL10A1 may characterize pure DCIS with a high risk developing IDC.
| S-EPMC6147035 | biostudies-literature
Project description:Although ductal carcinoma in situ (DCIS) precedes invasive ductal carcinoma (IDC), the related genomic alterations remain unknown. To identify the genomic landscape of DCIS and better understand the mechanisms behind progression to IDC, we performed whole-exome sequencing and copy number profiling for six cases of pure DCIS and five pairs of synchronous DCIS and IDC. Pure DCIS harbored well-known mutations (e.g., TP53, PIK3CA and AKT1), copy number alterations (CNAs) and chromothripses, but had significantly fewer driver genes and co-occurrence of mutation/CNAs than synchronous DCIS-IDC. We found neither recurrent nor significantly mutated genes with synchronous DCIS-IDC compared to pure DCIS, indicating that there may not be a single determinant for pure DCIS progression to IDC. Of note, synchronous DCIS genomes were closer to IDC than pure DCIS. Among the clinicopathologic parameters, progesterone receptor (PR)-negative status was associated with increased mutations, CNAs, co-occurrence of mutations/CNAs and driver mutations. Our results indicate that although pure DCIS has already acquired some drivers, more changes are needed to progress to IDC. In addition, IDC-associated DCIS is more aggressive than pure DCIS at genomic level and should really be considered IDC. Finally, the data suggest that PR-negativity could be used to predict aggressive breast cancer genotypes.
| S-EPMC4480702 | biostudies-literature
Project description:Ductal carcinoma in situ (DCIS) is a precursor lesion that can give rise to invasive breast cancer (IBC). It has been proposed that both the nature of the lesion and the tumor microenvironment play key roles in progression to IBC. Here, laser capture microdissected tissue samples from epithelium and stroma in normal breast, pure DCIS, and pure IBC were employed to define key gene expression profiles associated with disease progression. Tumor and matching stroma were profiled for 9 DCIS patients, 10 IBC patients, and 3 normal breast. Differential gene expression was evaluated for paired normal stroma versus normal epitelium samples, paired DCIS stroma versus DCIS epitelium samples, paired IBC stroma versus IBC epitelium, IBC stroma versus DCIS stroma, and IBC epithelium versus DCIS epithelium.
2012-03-31 | E-GEOD-33692 | biostudies-arrayexpress
Project description:BackgroundThe value of screen detection and treatment of ductal carcinoma in situ (DCIS) is a matter of controversy. At present, the extent to which the diagnosis and treatment of DCIS could prevent the occurrence of invasive breast cancer in the future is not clear. We sought to estimate the association between detection of DCIS at screening and invasive interval cancers subsequent to the relevant screen.MethodsWe obtained aggregate data for screen-detected cancers from 84 local screening units within 11 regional Quality Assurance Reference Centres in England, Wales, and Northern Ireland from the National Health Service Breast Screening Programme. Data for DCIS diagnoses were obtained for women aged 50-64 years who were invited to and attended mammographic breast screening from April 1, 2003, to March 31, 2007 (4 screening years). Patient-level data for interval cancer arising in the 36 months after each of these were analysed by Poisson regression with invasive interval cancer screen detection rate as the outcome variable; DCIS detection frequencies were fitted first as a continuous and then as a categorical variable. We repeated this analysis after adjustment with both small size and high-grade invasive screen-detected cancers.FindingsWe analysed data for 5,243,658 women and on interval cancers occurring in the 36 months after the relevant screen. The average frequency of DCIS detected at screening was 1·60 per 1000 women screened (median 1·50 [unit range 0·54-3·56] [corrected to] per 1000 women). There was a significant negative association of screen-detected DCIS cases with the rate of invasive interval cancers (Poisson regression coefficient -0·084 [95% CI -0·13 to -0·03]; p=0·002). 90% of units had a DCIS detection frequency within the range of 1·00 to 2·22 per 1000 women; in these units, for every three screen-detected cases of DCIS, there was one fewer invasive interval cancer in the next 3 years. This association remained after adjustment for numbers of small screen-detected invasive cancers and for numbers of grade 3 invasive screen-detected cancers.InterpretationThe association between screen-detected DCIS and subsequent invasive interval cancers suggests that detection and treatment of DCIS is worthwhile in prevention of future invasive disease.FundingUK Department of Health Policy Research Programme and NHS Cancer Screening Programmes.
| S-EPMC4691349 | biostudies-literature
Project description:Here, we show that SOX11, an embryonic mammary marker that is normally silent in postnatal breast cells, is expressed in many oestrogen receptor-negative preinvasive ductal carcinoma in situ (DCIS) lesions. Mature mammary epithelial cells engineered to express SOX11 showed alterations in progenitor cell populations, including an expanded basal-like population with increased aldehyde dehydrogenase (ALDH) activity, and increased mammosphere-forming capacity. DCIS.com cells engineered to express SOX11 showed increased ALDH activity, which is a feature of cancer stem cells. The CD44+/CD24-/ALDH+ cell population was increased in DCIS.com cells that expressed SOX11. Upregulating SOX11 expression in DCIS.com cells led to increased invasive growth both in vitro and when they were injected intraductally in a mouse model of DCIS that recapitulates human disease. Invasive lesions formed sooner and tumour growth was augmented in vivo, suggesting that SOX11 contributes to the progression of DCIS to invasive breast cancer. We identified potential downstream effectors of SOX11 during both microinvasive and invasive tumour growth stages, including several with established links to regulation of progenitor cell function and prenatal developmental growth. Our findings suggest that SOX11 is a potential biomarker for DCIS lesions containing cells harbouring distinct biological features that are likely to progress to invasive breast cancer. © 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
| S-EPMC5637904 | biostudies-literature