Applying the Nottingham Prognostic Index to a Swedish breast cancer population. South East Swedish Breast Cancer Study Group

Identification of Glandular (Acinar)/Tubule Formation in Invasive Carcinoma of the Breast: A Study to Determine Concordance Using the World Health Organization Definition

CONTEXT.—

The Nottingham Grading System (NGS) developed by Elston and Ellis is used to grade invasive breast cancer (IBC). Glandular (acinar)/tubule formation is a component of NGS.

OBJECTIVE.—

To investigate the ability of pathologists to identify individual structures that should be classified as glandular (acinar)/tubule formation.

DESIGN.—

A total of 58 hematoxylin-eosin photographic images of IBC with 1 structure circled were classified as tubules (41 cases) or nontubules (17 cases) by Professor Ellis. Images were sent as a PowerPoint (Microsoft) file to breast pathologists, who were provided with the World Health Organization definition of a tubule and asked to determine if a circled structure represented a tubule.

RESULTS.—

Among 35 pathologists, the κ statistic for assessing agreement in evaluating the 58 images was 0.324 (95% CI, 0.314-0.335). The median concordance rate between a participating pathologist and Professor Ellis was 94.1% for evaluating 17 nontubule cases and 53.7% for 41 tubule cases. A total of 41% of the tubule cases were classified correctly by less than 50% of pathologists. Structures classified as tubules by Professor Ellis but often not recognized as tubules by pathologists included glands with complex architecture, mucinous carcinoma, and the "inverted tubule" pattern of micropapillary carcinoma. A total of 80% of participants reported that they did not have clarity on what represented a tubule.

CONCLUSIONS.—

We identified structures that should be included as tubules but that were not readily identified by pathologists. Greater concordance for identification of tubules might be obtained by providing more detailed images and descriptions of the types of structures included as tubules.

An MRI-based Radiomics Approach to Improve Breast Cancer Histological Grading

RATIONALE AND OBJECTIVES

Nottingham histological grade (NHG) 2 breast cancer has an intermediate risk of recurrence, which is not informative for therapeutic decision-making. We sought to develop and independently validate an MRI-based radiomics signature (Rad-Grade) to improve prognostic re-stratification of NHG 2 tumors.

MATERIALS AND METHODS

Nine hundred-eight subjects with invasive breast cancer and preoperative MRI scans were retrospectively obtained. The NHG 1 and 3 tumors were randomly split into training and independent test cohort, with the NHG 2 as the prognostic validation set. From MRI image features, a radiomics-based signature predictive of the histological grade was built by use of the LASSO logistic regression algorithm. The model was developed for identifying NHG 1 and 3 radiological patterns, followed with re-stratification of NHG 2 tumors into Rad-Grade (RG)2-low (NHG 1-like) and RG2-high (NHG 3-like) subtypes using the learned patterns, and the prognostic value was assessed in terms of recurrence-free survival (RFS).

RESULTS

The Rad-Grade showed independent prognostic value for re-stratification of NHG 2 tumors, where RG2-high had an increased risk for recurrence (HR 2.20, 1.10-4.40, p = 0.026) compared with RG2-low after adjusting for established risk factors. RG2-low shared similar phenotypic characteristics and RFS outcomes with NHG 1, and RG2-high with NHG 3, revealing that the model captures radiomic features in NHG 2 that are associated with different aggressiveness. The prognostic value of Rad-Grade was further validated in the NHG2 ER+ (HR 2.53, 1.13-5.56, p = 0.023) and NHG 2 ER+LN- (HR 5.72, 1.24-26.44, p = 0.025) subgroups, and in specific treatment contexts.

CONCLUSION

The radiomics-based re-stratification of NHG 2 tumors offers a cost-effective promising alternative to gene expression profiling for tumor grading and thus may improve clinical decisions.

"Diagnostic and Prognostic Biomarkers of Luminal Breast Cancer: Where are We Now?"

Luminal breast cancers are hormone receptor (estrogen and/or progesterone) positive that are further divided into HER2-negative luminal A and HER2-positive luminal B subtypes. According to currently accepted convention, they represent the most common subtypes of breast cancer, accounting for approximately 70% of cases. Biomarkers play a critical role in the functional characterization, prognostication, and therapeutic prediction, rendering them indispensable for the clinical management of invasive breast cancer. Traditional biomarkers include clinicopathological parameters, which are increasingly extended by genetic and other molecular markers, enabling the comprehensive characterization of patients with luminal breast cancer. Liquid biopsies capturing and analyzing circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are emerging technologies that envision personalized management through precision oncology. This article reviews key biomarkers in luminal breast cancer and ongoing developments.

Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological images

Computer-aided Invasive Ductal Carcinoma (IDC) grading classification systems based on deep learning have shown that deep learning may achieve reliable accuracy in IDC grade classification using histopathology images. However, there is a dearth of comprehensive performance comparisons of Convolutional Neural Network (CNN) designs on IDC in the literature. As such, we would like to conduct a comparison analysis of the performance of seven selected CNN models: EfficientNetB0, EfficientNetV2B0, EfficientNetV2B0-21k, ResNetV1-50, ResNetV2-50, MobileNetV1, and MobileNetV2 with transfer learning. To implement each pre-trained CNN architecture, we deployed the corresponded feature vector available from the TensorFlowHub, integrating it with dropout and dense layers to form a complete CNN model. Our findings indicated that the EfficientNetV2B0-21k (0.72B Floating-Point Operations and 7.1 M parameters) outperformed other CNN models in the IDC grading task. Nevertheless, we discovered that practically all selected CNN models perform well in the IDC grading task, with an average balanced accuracy of 0.936 ± 0.0189 on the cross-validation set and 0.9308 ± 0.0211on the test set.

On the Additional Information Provided by 3T-MRI ADC in Predicting Tumor Cellularity and Microscopic Behavior

BACKGROUND

to evaluate whether Apparent Diffusion Coefficient (ADC) values of invasive breast cancer, provided by 3T Diffusion Weighted-Images (DWI), may represent a non-invasive predictor of pathophysiologic tumor aggressiveness.

METHODS

100 Patients with histologically proven invasive breast cancers who underwent a 3T-MRI examination were included in the study. All MRI examinations included dynamic contrast-enhanced and DWI/ADC sequences. ADC value were calculated for each lesion. Tumor grade was determined according to the Nottingham Grading System, and immuno-histochemical analysis was performed to assess molecular receptors, cellularity rate, on both biopsy and surgical specimens, and proliferation rate (Ki-67 index). Spearman's Rho test was used to correlate ADC values with histological (grading, Ki-67 index and cellularity) and MRI features. ADC values were compared among the different grading (G1, G2, G3), Ki-67 (<20% and >20%) and cellularity groups (<50%, 50-70% and >70%), using Mann-Whitney and Kruskal-Wallis tests. ROC curves were performed to demonstrate the accuracy of the ADC values in predicting the grading, Ki-67 index and cellularity groups.

RESULTS

ADC values correlated significantly with grading, ER receptor status, Ki-67 index and cellularity rates. ADC values were significantly higher for G1 compared with G2 and for G1 compared with G3 and for Ki-67 < 20% than Ki-67 > 20%. The Kruskal-Wallis test showed that ADC values were significantly different among the three grading groups, the three biopsy cellularity groups and the three surgical cellularity groups. The best ROC curves were obtained for the G3 group (AUC of 0.720), for G2 + G3 (AUC of 0.835), for Ki-67 > 20% (AUC of 0.679) and for surgical cellularity rate > 70% (AUC of 0.805).

CONCLUSIONS

3T-DWI ADC is a direct predictor of cellular aggressiveness and proliferation in invasive breast carcinoma, and can be used as a supporting non-invasive factor to characterize macroscopic lesion behavior especially before surgery.

Improved breast cancer histological grading using deep learning

BACKGROUND

The Nottingham histological grade (NHG) is a well-established prognostic factor for breast cancer that is broadly used in clinical decision making. However, ∼50% of patients are classified as grade 2, an intermediate risk group with low clinical value. To improve risk stratification of NHG 2 breast cancer patients, we developed and validated a novel histological grade model (DeepGrade) based on digital whole-slide histopathology images (WSIs) and deep learning.

PATIENTS AND METHODS

In this observational retrospective study, routine WSIs stained with haematoxylin and eosin from 1567 patients were utilised for model optimisation and validation. Model generalisability was further evaluated in an external test set with 1262 patients. NHG 2 cases were stratified into two groups, DG2-high and DG2-low, and the prognostic value was assessed. The main outcome was recurrence-free survival.

RESULTS

DeepGrade provides independent prognostic information for stratification of NHG 2 cases in the internal test set, where DG2-high showed an increased risk for recurrence (hazard ratio [HR] 2.94, 95% confidence interval [CI] 1.24-6.97, P = 0.015) compared with the DG2-low group after adjusting for established risk factors (independent test data). DG2-low also shared phenotypic similarities with NHG 1, and DG2-high with NHG 3, suggesting that the model identifies morphological patterns in NHG 2 that are associated with more aggressive tumours. The prognostic value of DeepGrade was further assessed in the external test set, confirming an increased risk for recurrence in DG2-high (HR 1.91, 95% CI 1.11-3.29, P = 0.019).

CONCLUSIONS

The proposed model-based stratification of patients with NHG 2 tumours is prognostic and adds clinically relevant information over routine histological grading. The methodology offers a cost-effective alternative to molecular profiling to extract information relevant for clinical decisions.

Altona Prognostic Index: A New Prognostic Index for ER-Positive and Her2-Negative Breast Cancer of No Special Type

Simple Summary

Breast cancer is the most common tumor-related cause of death in women in Europe and worldwide. The aim of our retrospective study, including 6654 women, was on the one hand to verify the validity of the worldwide known Nottingham prognostic index (NPI), and on the other hand to create a new model with even more prognostic validity. Our newly developed Altona prognostic index (API) shows significantly superior outcome in calculating progression free survival. In contrast to the NPI, the API considers characteristics such as subtypes of breast cancer, as this disease is heterogenous involving different entities, and patient’s age. Evaluating progression free survival in different subgroups, our study shows that both these prognostic indices should only be applied on a patient collective that is ≤70 years old with first primary, unifocal, unilateral breast cancer that is of no special type (NST), estrogen receptor-positive and Her2-negative to get valid prediction data.

Abstract

Breast cancer is a heterogeneous disease representing a number of different histopathologic and molecular types which should be taken into consideration if prognostic or predictive models are to be developed. The aim of the present study was to demonstrate the validity of the long-known Nottingham prognostic index (NPI) in a large retrospective study (n = 6654 women with a first primary unilateral and unifocal invasive breast cancer diagnosed and treated between April 1996 and October 2018; median follow-up time of breast cancer cases was 15.5 years [14.9–16.8]) from a single pathological institution. Furthermore, it was intended to develop an even superior risk stratification model considering an additional variable, namely the patient’s age at the time of diagnosis. Heterogeneity of these cases was addressed by focusing on estrogen receptor-positive as well as Her2-negative cases and taking the WHO-defined different tumor types into account. Calculating progression free survival Cox-regression and CART-analysis revealed significantly superior iAUC as well as concordance values in comparison to the NPI based stratification, leading to an alternative, namely the Altona prognostic index (API). The importance of the histopathological tumor type was corroborated by the fact that when calculated separately and in contrast to the most frequent so-called “No Special Type” (NST) carcinomas, neither NPI nor API could show valid prognostic stratification.

Grading of invasive breast carcinoma: the way forward

Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identifying patients at risk for adverse outcomes, who may be eligible for (neo)adjuvant therapies. Histologic grading needs to be performed accurately, on properly fixed specimens, and by adequately trained dedicated pathologists that take the time to diligently follow the protocol methodology. In this paper, we review the history of histologic grading, describe the basics of grading, review prognostic value and reproducibility issues, compare performance of grading to gene expression profiles, and discuss how to move forward to improve reproducibility of grading by training, feedback and artificial intelligence algorithms, and special stains to better recognize mitoses. We conclude that histologic grading, when adequately carried out, remains to be of important prognostic value in breast cancer patients.

Prediction models for breast cancer prognosis among Asian women

BACKGROUND

Robust and reliable prognosis prediction models have not been developed and validated for Asian patients with breast cancer, a rapidly growing yet understudied population in the United States.

METHODS

We used longitudinal data from the Shanghai Breast Cancer Survival Study, a population-based prospective cohort study (n = 5042), to develop prediction models for 5- and 10-year disease-free survival (DFS) and overall survival (OS). The initial models considered age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, and estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status. We then evaluated whether the addition of modifiable lifestyle factors (physical activity, soy isoflavones intake, and postdiagnostic weight change) improved the models. All final models have been validated internally and externally in the National Cancer Database when applicable.

RESULTS

Our final models included age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, ER status, PR status, 6-month postdiagnostic weight change, interaction between ER status and tamoxifen therapy, and interaction between age and TNM stage. The internal validation yielded C-statistics of 0.76, 0.74, 0.78, and 0.75 for 5-year DFS, 10-year DFS, 5-year OS, and 10-year OS, respectively. The external validation yielded C-statistics of 5- and 10-year OS both at 0.78 for Chinese ethnicity, 0.79 for East Asian ethnicity, and 0.75 and 0.76 for all ethnic groups combined.

CONCLUSION

We developed prediction models for breast cancer prognosis from a large prospective study. Our prognostic models performed very well in women from the United States-particularly in Asian American women-and demonstrated high prediction accuracy and generalizability.

In situ breast cancer incidence patterns in Iceland and differences in ductal carcinoma in situ treatment compared to Sweden

The purpose was to review the incidence of in situ carcinoma in Iceland after initiating population-based mammography screening in 1987 and to compare management of ductal carcinoma in situ (DCIS) between Iceland and the Uppsala-Örebro region (UÖR) in Central Sweden. The Icelandic Cancer Registry provided data on in situ breast carcinomas for women between 1957 and 2017. Clinical data for women with DCIS between 2008 and 2014 was extracted from hospital records and compared to women diagnosed in UÖR. In Iceland, in situ carcinoma incidence increased from 7 to 30 per 100 000 women per year, following the introduction of organised mammography screening. The proportion of in situ carcinoma of all breast carcinomas increased from 4 to 12%. More than one third (35%) of women diagnosed with DCIS in Iceland were older than 70 years versus 18% in UÖR. In Iceland, 49% of all DCIS women underwent mastectomy compared to 40% in UÖR. The incidence of in situ carcinoma in Iceland increased four-fold after the uptake of population-based mammography screening causing considerable risk of overtreatment. Differences in treatment of DCIS were seen between Iceland and UÖR, revealing the importance of quality registration for monitoring patterns of management.

Assessment of tumour proliferation by use of the mitotic activity index, and Ki67 and phosphohistone H3 expression, in early-stage luminal breast cancer

AIMS

Phosphohistone H3 (PhH3) has been proposed as a novel proliferation marker in breast cancer. This study compares the interobserver agreement for assessment of the mitotic activity index (MAI), Ki67 expression, and PhH3 in a cohort of oestrogen receptor (ER)-positive breast cancer patients.

METHODS AND RESULTS

Tumour samples of 159 luminal breast cancer patients were collected. MAI and PhH3 scores were assessed by three breast cancer pathologists. Ki67 scores were assessed separately by two of the three pathologists. PhH3-positive cells were counted in an area of 2 mm2 , with a threshold of ≥13 positive cells being used to discriminate between low-proliferative and high-proliferative tumours. Ki67 expression was assessed with the global scoring method. Ki67 percentages of <20% were considered to be low. The intraclass correlation coefficient (ICC) and Cohen's κ statistics were used to evaluate interobserver agreement. The impact on histological grading of replacing the MAI with PhH3 was assessed. Counting PhH3-positive cells was highly reproducible among all three observers (ICC of 0.86). The κ scores for the categorical PhH3 count (κ = 0.78, κ = 0.68, and κ = 0.80) reflected substantial agreement among all observers, whereas agreement for the MAI (κ = 0.38, κ = 0.52, and κ = 0.26) and Ki67 (κ = 0.55) was fair to moderate. When PhH3 was used to determine the histological grade, agreement in grading increased (PhH3, κ = 0.52, κ = 0.48, and κ = 0.52; MAI, κ = 0.43, κ = 0.35, and κ = 0.32), and the proportion of grade III tumours increased (14%, 18%, and 27%).

CONCLUSION

PhH3 seems to outperform Ki67 and the MAI as a reproducible means to measure tumour proliferation in luminal-type breast cancer. Variation in the assessment of histological grade might be reduced by using PhH3, but would result in an increase in the proportion of high-grade cancers.

Comparison of Nottingham Prognostic Index, PREDICT and PrognosTILs in Triple Negative Breast Cancer -a Retrospective Cohort Study

Triple-negative breast cancer (TNBC) represents a heterogenous subtype of breast cancer with generally poor prognosis. The prediction of its prognosis remains essential to clinicians in their therapeutical decision-making process. The aim of our study was to compare the validity of three multivariable analysis derived prognostic systems, the Nottingham Prognostic Index (NPI), PREDICT and PrognosTILs (a prognosticator including tumor infiltrating lymphocytes, TILs) in a series of TNBCs. Patients operated on with TNBC at the Department of Surgery, Bács-Kiskun County Teaching Hospital, Kecskemét between 2005 and 2016 were included. Clinical and pathological parameters and follow-up data were collected from medical charts. TILs were assessed retrospectively, following international recommendations. Estimated survivals of PrognosTILs, PREDICT and NPI were recorded and compared with real outcomes. Altogether 136 patients were included in this retrospective study. In univariate Cox analysis, type of surgery, pT, pN, stage, NPI and type of adjuvant therapy were the significant prognostic variables. The multivariate Cox-regression strengthened that NPI is an independent predictor of overall and disease-free survivals in TNBCs. The NPI, PREDICT and PrognosTILs could be compared directly only in a ROC curve analysis: the sensitivities and specificities of these predicting systems are rather similar with area under the curve values falling between 0.7 and 0.8, and NPI having the highest values. Our findings reflect the diverse prognosis of TNBC and highlight the difficulties of predicting its outcome. None of the three multivariable prognosticators is inferior to the others, the NPI can reliably be used for TNBCs.

Significant inter- and intra-laboratory variation in grading of invasive breast cancer: A nationwide study of 33,043 patients in the Netherlands

Accurate, consistent and reproducible grading by pathologists is of key-importance for identification of individual patients with invasive breast cancer (IBC) that will or will not benefit from adjuvant systemic treatment. We studied the laboratory-specific grading variation using nationwide real-life data to create insight and awareness in grading variation. Synoptic pathology reports of all IBC resection-specimens, obtained between 2013 and 2016, were retrieved from the nationwide Dutch Pathology Registry (PALGA). Absolute differences in laboratory-proportions of Grades I-III were compared to the national reference. Multivariable logistic regression provided laboratory-specific odds ratios (ORs) for high- vs. low-grade IBC. 33,792 IBC pathology reports of 33,043 patients from 39 laboratories were included, of which 28.1% were reported as Grade I (range between laboratories 16.3-43.3%), 47.6% as Grade II (38.4-57.8%), and 24.3% as Grade III (15.5-34.3%). Based on national guidelines, the indication for adjuvant chemotherapy was dependent on histologic grade in 29.9% of patients. After case-mix correction, 20 laboratories (51.3%) showed a significantly deviant OR. Significant grading differences were also observed among pathologists within laboratories. In this cohort of 33,043 breast cancer patients, we observed substantial inter- and intra-laboratory variation in histologic grading. It can be anticipated that this has influenced outcome including exposure to unnecessary toxicity, since choice of adjuvant chemotherapy was dependent on grade in nearly a third of patients. Better standardization and training seems warranted.

Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.

Prognostic models for breast cancer: a systematic review

BACKGROUND

Breast cancer is the most common cancer in women worldwide, with a great diversity in outcomes among individual patients. The ability to accurately predict a breast cancer outcome is important to patients, physicians, researchers, and policy makers. Many models have been developed and tested in different settings. We systematically reviewed the prognostic models developed and/or validated for patients with breast cancer.

METHODS

We conducted a systematic search in four electronic databases and some oncology websites, and a manual search in the bibliographies of the included studies. We identified original studies that were published prior to 1st January 2017, and presented the development and/or validation of models based mainly on clinico-pathological factors to predict mortality and/or recurrence in female breast cancer patients.

RESULTS

From the 96 articles selected from 4095 citations found, we identified 58 models, which predicted mortality (n = 28), recurrence (n = 23), or both (n = 7). The most frequently used predictors were nodal status (n = 49), tumour size (n = 42), tumour grade (n = 29), age at diagnosis (n = 24), and oestrogen receptor status (n = 21). Models were developed in Europe (n = 25), Asia (n = 13), North America (n = 12), and Australia (n = 1) between 1982 and 2016. Models were validated in the development cohorts (n = 43) and/or independent populations (n = 17), by comparing the predicted outcomes with the observed outcomes (n = 55) and/or with the outcomes estimated by other models (n = 32), or the outcomes estimated by individual prognostic factors (n = 8). The most commonly used methods were: Cox proportional hazards regression for model development (n = 32); the absolute differences between the predicted and observed outcomes (n = 30) for calibration; and C-index/AUC (n = 44) for discrimination. Overall, the models performed well in the development cohorts but less accurately in some independent populations, particularly in patients with high risk and young and elderly patients. An exception is the Nottingham Prognostic Index, which retains its predicting ability in most independent populations.

CONCLUSIONS

Many prognostic models have been developed for breast cancer, but only a few have been validated widely in different settings. Importantly, their performance was suboptimal in independent populations, particularly in patients with high risk and in young and elderly patients.

Prognostic indices predictive of short-term disease-free survival of breast carcinoma patients receiving primary surgical treatment in Sri Lanka

Background

Breast carcinoma (BCa) is the commonest malignancy among women worldwide and in Sri Lanka. Several prognostic indices are described for BCa.

Aims

To assess clinicopathological features and prognostic indices derived from routine clinical, histopathological and immunohistochemical (IHC) data, in a cohort of patients undergoing primary surgery for BCa and to determine their prognostic impact on short-term disease free survival.

Setting and Design

: This is a bidirectional cohort study of 208 women undergoing primary surgery for BCa at the National Hospital of Sri Lanka, from 2012-2014, excluding post-neoadjuvant chemotherapy cases.

Material and Methods

Clinical details, tumor size and nodal status were obtained from histopathology reports. Histopathology and estrogen/progesterone receptor and HER2 status were reviewed. Molecular subtype based on IHC was determined. Nodal ratio (number of positive nodes/total number retrieved) and Nottingham prognostic index were calculated. Follow up information was obtained by patient interviews and record review.

Statistical Analysis

Data was analyzed by univariate and multivariate Cox regression using SPSS19.0.

Results

Mean follow-up duration was 27.16 months (0.5-52 months, s = 9.35 months). 174 (82.9%) remained disease free with 19 (9%) deaths. Thirteen (6.2%) survived with metastasis and 4 (1.9%) with recurrences. On univariate Cox regression, tumor, nodal and TNM stages, nodal ratio and lymphovascular invasion (LVI) were predictive of disease free survival (DFS) (P = 0.001, P = 0.021, P = 0.022, P = 0.002, P = 0.018). On multivariate analysis TNM stage and LVI were predictive of DFS.

Conclusion

TNM stage and LVI were the most important predictors of short-term disease free survival in this study population, confirming that early detection of BCa at a lower stage has a significant impact on short-term outcomes.

Survival estimates stratified by the Nottingham Prognostic Index for early breast cancer: a systematic review and meta-analysis of observational studies

BACKGROUND

Estimates of survival for women diagnosed with early staged breast cancer are available based on stratification into prognostic categories defined using the Nottingham Prognostic Index (NPI). This review aimed to identify and summarize the estimated survival statistics from separate sources in the literature and to explore the extent of between-study heterogeneity in survival estimates.

METHODS

Observational studies in women diagnosed with early and locally advanced breast cancer reporting overall survival by NPI category were identified using a systematic literature search. An exploratory meta-analysis was conducted to describe survival estimates and assess between-study heterogeneity.

RESULTS

Twenty-eight studies were identified. Nineteen studies with sufficient data on overall survival were included in meta-analysis. A high level of heterogeneity in survival estimates was evident with I² values in the range of 90 to 98%.

CONCLUSIONS

The substantial differences between studies in the relationship between NPI categories and survival at 5 and 10 years poses challenges for use of this prognostic score in both clinical settings and in decision-analytic model-based economic evaluations.

Correlation between minimum apparent diffusion coefficient values and the histological grade of breast invasive ductal carcinoma

The present study aimed to investigate the correlation between the minimum apparent diffusion coefficient (ADC_min) value and the histological grade of breast invasive ductal carcinoma (IDC). In total, 129 pathologically verified lesions that were subjected to dynamic breast magnetic resonance imaging and diffusion weighted imaging prior to biopsy were included. The ADC_min value was calculated and its correlation with the tumor histological grade was investigated. Tumors of lower grades demonstrated significantly higher ADC_min values as compared with tumors of higher grades (F=33.49; P<0.01). The mean ADC_min values for IDC of grades I, II and III were (1.14±0.11)×10^-3, (0.99±0.12)×10^-3 and (0.86±0.13)×10^-3 mm²/sec, respectively. Statistically significant differences were detected in the mean ADC_min value between tumors of grades II and III (P<0.01), as well as between tumors of grades I and II (P<0.01). In addition, the mean ADC_min values for the less aggressive (grades I and II) and more aggressive (grade III) groups were (1.01±0.13)×10^-3 and (0.86±0.13)×10^-3 mm²/sec, respectively (t=5.76, P<0.01). In conclusion, these data indicated that the ADC_min value was correlated with the IDC histological grade, and lower ADC_min values were associated with a higher histological grade and more aggressiveness. Thus, the ADC_min value may be considered as a promising prognostic parameter in identifying tumor aggressiveness.

Evaluation of the prognostic stage in the 8th edition of the American Joint Committee on Cancer in locally advanced breast cancer: An analysis based on SEER 18 database

BACKGROUND

The new "prognostic stage" in the 8th edition of the American Joint Committee on Cancer (AJCC) incorporated important biologic factors such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), histologic grade and TNM stage into one system. The objective of this study was to evaluate the "prognostic stage" in locally advanced breast cancer (LABC) based on the Surveillance, Epidemiology, and End Results (SEER) 18 database.

METHODS

10053 LABCs diagnosed between 2010 and 2013 were enrolled. TNM stage was based on AJCC 7th edition. Comparisons of biologic factor proportions among stage changes were performed using Pearson's chi-square test. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated using the Kaplan-Meier method and log rank testing with pairwise comparisons between different stages was conducted. Cox models were fitted to assess the independent prognostic factors.

RESULTS

The prognostic stage grouped LABC into six stages: IB-IIIC among which IB-IIIA had a relatively better survival. It reassigned 74% LABCs to a different tumor stage. 60.4% cases in grade III and 68.3% cases with triple negative breast cancer were upstaged while 57.1% cases with ER/PR dual positivity were down staged. It was an independent prognostic factor of LABC. There were statistically significant survival differences among stage IB-IIIA, IIIB and IIIC. Among each TNM stage, there were statistically significant survival differences among stage changes.

CONCLUSIONS

The prognostic stage provided accurate prognostic information for LABC compared with anatomic TNM stage. It will lead to accuracy in prognosis prediction and optimal treatment selection, and therefore, better outcomes.

Predictive Value of Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in Early Breast Cancer

BACKGROUND Sentinel lymph node biopsy (SLNB) is one of the preferred treatments for breast cancer including clinically negative lymph node breast cancer. However, for 60-70% of patients this invasive axilla surgery is unnecessary. Our study aimed to identify the predictors for sentinel lymph node (SLN) metastasis in early breast cancer patients and provide evidence for rational decision-making in specified clinical situations. MATERIAL AND METHODS Medical records of 417 breast cancer patients who were treated with a breast surgical procedure and SLNB in Ningbo Medical Center Lihuili Eastern Hospital were retrospectively reviewed. Univariate analysis and multivariate logistic regression analysis were used to analyze the correlation between SLN metastasis and clinicopathological characteristics, including patient age, menstrual status, body mass index (BMI), family history, tumor size, laterality of tumor, histological grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), Ki67 index, and molecular subtypes of the tumor. RESULTS In the cohort of 417 cases, the ratio of SLNM was 23.0%. Univariate analysis found that age, tumor size, histological grade, and Ki67 index were associated with SLN metastasis. However, age, tumor size, and histological grade were the only three independent predictors for SLN metastasis by multivariate logistic regression analysis. When these three factors were considered together, three different levels of SLN metastasis groups could be classified: low-risk group with the ratio of 14.3%, moderate-risk group with the ratio of 31.4%, and high-risk group with the ratio of 66.7%. CONCLUSIONS Our study demonstrated that age, tumor size, and histological grade were three independent predictive factors for SLN metastasis in early breast cancer patients. This finding may help surgeons in the decision-making process for early breast cancer patients before considering axilla surgical procedure.

Improved survival in metastatic breast cancer 1985-2016

PURPOSE

In the last 25 years new treatment options in breast cancer have evolved. We wanted to determine whether the survival of; patients with metastatic breast cancer have improved during this period.

METHODS

Patients consecutively diagnosed with disseminated breast cancer 1985-2014 in the County of Kalmar, Sweden, were identified and followed to 2016. Survival was calculated for each successive 5 year interval. Separate analyses were performed for pts with ER and/or PR and HER2 positive tumours resp.

RESULTS

Median survival of the 784 patients increased successively from 13 to 33 months. Five year survival increased from 10 to 27%. Patients with high grade primary tumours had the shortest post recurrence survival time but their median survival increased significantly by time from 12 to 30 months, 3 year survival from 16 to 38% and 5 year from 5 to 20%. Median survival for patients with grade 2 tumours was 2 years and did not improve. Only 47 patients had grade 1 tumours and their median survival of 4 years did not change. Median survival for HER2 positive patients treated before the introduction of trastuzumab in year 2000 was 14 months and after 2000 29 months, 5 year survival improved from 2 to 31%.

CONCLUSIONS

Survival in metastatic breast cancer improved 1985-2016. For the first time a significant increase in survival time for patients with metastasis from fast-growing grade 3 tumours was seen. The most striking improvement was achieved in the HER2 positive subset.

Prognostic contribution of mammographic breast density and HER2 overexpression to the Nottingham Prognostic Index in patients with invasive breast cancer

Background

To investigate whether very low mammographic breast density (VLD), HER2, and hormone receptor status holds any prognostic significance within the different prognostic categories of the widely used Nottingham Prognostic Index (NPI). We also aimed to see whether these factors could be incorporated into the NPI in an effort to enhance its performance.

Methods

This study included 270 patients with newly diagnosed invasive breast cancer. Patients with mammographic breast density of <10 % were considered as VLD. In this study, we compared the performance of NPI with and without VLD, HER2, ER and PR. Cox multivariate analysis, time-dependent receiver operating characteristic curve (tdROC), concordance index (c-index) and prediction error (0.632+ bootstrap estimator) were used to derive an updated version of NPI.

Results

Both mammographic breast density (VLD) (p < 0.001) and HER2 status (p = 0.049) had a clinically significant effect on the disease free survival of patients in the intermediate and high risk groups of the original NPI classification. The incorporation of both factors (VLD and HER2 status) into the NPI provided improved patient outcome stratification by decreasing the percentage of patients in the intermediate prognostic groups, moving a substantial percentage towards the low and high risk prognostic groups.

Conclusions

Very low density (VLD) and HER2 positivity were prognostically significant factors independent of the NPI. Furthermore, the incorporation of VLD and HER2 to the NPI served to enhance its accuracy, thus offering a readily available and more accurate method for the evaluation of patient prognosis.

The prognostic performance of Adjuvant! Online and Nottingham Prognostic Index in young breast cancer patients

Background:

Limited data are available on the prognostic performance of Adjuvant! Online (AOL) and Nottingham Prognostic Index (NPI) in young breast cancer patients.

Methods:

This multicentre hospital-based retrospective cohort study included young (⩽40 years) and older (55–60 years) breast cancer patients treated from January 2000 to December 2004 at four large Belgian and Italian institutions. Predicted 10-year overall survival (OS) and disease-free survival (DFS) using AOL and 10-year OS using NPI were calculated for every patient. Tools ability to predict outcomes (i.e., calibration) and their discriminatory accuracy was assessed.

Results:

The study included 1283 patients, 376 young and 907 older women. Adjuvant! Online accurately predicted 10-year OS (absolute difference: 0.7% P=0.37) in young cohort, but overestimated 10-year DFS by 7.7% (P=0.003). In older cohort, AOL significantly underestimated both 10-year OS and DFS by 7.2% (P<0.001) and 3.2% (P=0.04), respectively. Nottingham Prognostic Index significantly underestimated 10-year OS in both young (8.5% P<0.001) and older (4.0% P<0.001) cohorts. Adjuvant! Online and NPI had comparable discriminatory accuracy.

Conclusions:

In young breast cancer patients, AOL is a reliable tool in predicting OS at 10 years but not DFS, whereas the performance of NPI is sub-optimal.

Prognostic models in male breast cancer

PURPOSE

Breast cancer in men is uncommon; it accounts for 1 % of all patients with primary breast cancer. Its treatment is mostly extrapolated from its female counterpart. Accurate predictions are essential for adjuvant systemic treatment decision-making and informing patients. Several predictive models are available for female breast cancer (FBC) including the Morphometric Prognostic Index (MPI), Nottingham Prognostic Index (NPI), Adjuvant! Online and Predict. The aim of this study was to examine and compare the prognostic performance of these models for male breast cancer (MBC).

METHODS

The population of this study consists of 166 MBC patients. The prognostic scores of the patients are categorized by good, (moderate) and poor, defined by the test itself (MPI and NPI) or based on tertiles (Adjuvant! Online and Predict). Survival according to prognostic score was compared by Kaplan-Meier analysis and differences were tested by logRank. The prognostic performances were evaluated with C-statistics. Calibration was done with the aim to estimate to what extent the survival rates predicted by Predict were similar to the observed survival rates.

RESULTS

All prediction models were capable of discriminating between good, moderate and poor survivors. P-values were highly significant. Comparison between the models using C-statistics (n = 88) showed equal performance of MPI (0.67), NPI (0.68), Adjuvant! Online (0.69) and Predict (0.69). Calibration of Predict showed overestimation for MBC patients.

CONCLUSION

In conclusion, MPI, NPI, Adjuvant! and Predict prognostic models, originally developed and validated for FBC patients, also perform quite well for MBC patients.

The Utility of Phosphohistone H3 in Breast Cancer Grading

The commonly used Nottingham Grading System in breast cancer takes into consideration the presence of tubular formation, nuclear pleomorphism, and the mitotic index (MI), among which the latter has been shown to be the most powerful prognostic factor. In practice, histologic grading is highly subjective, with only moderate interobserver reproducibility. Phosphorylation of histone H3 has been demonstrated to be a specific event in the mitotic phase, and is negligible during interphase. In this study, we evaluated the efficacy of Phosphohistone H3 (PHH3) in the breast cancer grading of 97 consecutive biopsy specimens. PHH3 antibodies clearly revealed discrete, strong nuclear immunoreactivity in mitotically active cells even under low magnification. The PHH3 MI showed a significant correlation with that derived by hematoxylin and eosin (H&E) staining as well as the Ki-67 proliferation index. Further, the pairwise κ-value of the MI was significantly increased, and the pairwise agreement was also markedly improved by PHH3 immunostaining, although a significant proportion of breast cancer cases were upgraded by use of the PHH3 MI. Our data showed that PHH3 provided a more sensitive and accurate MI with less interobserver variability when compared with conventional H&E staining, thus emphasizing its potentially increased value in practice. Reconsideration of breast cancer grading with integration of PHH3 should be considered if it continues to demonstrate superiorly to traditional H&E staining.

Relative Prognostic and Predictive Value of Gene Signature and Histologic Grade in Estrogen Receptor-Positive, HER2-Negative Breast Cancer

BACKGROUND

In estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, first-generation genomic signatures serve predominately as prognostic biomarkers and secondarily as predictors of response to chemotherapy. We compared both the prognostic and predictive value of histologic grades and genomic markers.

METHODS

We retrieved publicly available cDNA microarray data from 1373 primary ER(+)/HER2(-) breast cancers and developed a genomic signature simulated from Recurrence Online (http://www.recurrenceonline.com/) to calculate the recurrence score and risk using predefined sets of genes in the cDNA microarray. We then compared the prognostic and predictive information provided by histologic grade and genomic signature.

RESULTS

Based on genomic signatures, 55%, 28%, and 17% of breast cancers were classified as low, intermediate, and high risk, respectively, whereas the histologic grades were I, II, and III in 22%, 59%, and 19% of breast cancers, respectively. Univariate analysis in the untreated cohort revealed that both histologic grade (overall P = .007) and genomic signature (P < .001) could predict prognosis. Results were similar using the genomic signature, with pathologic complete response rates of 4.6%, 5.7%, and 16.5% for low-, intermediate-, and high-risk cancers, respectively. Neither biomarker was statistically significant in multivariate analysis for predictive response to neoadjuvant chemotherapy (NAC).

CONCLUSION

Genomic signature was better at identifying low-risk cases compared to histologic grade alone, but both markers had similar predictive values for NAC response. Better predictive biomarkers for NAC response are still needed.

The Nottingham Prognostic Index: five- and ten-year data for all-cause survival within a screened population

INTRODUCTION

The Nottingham Prognostic Index (NPI) is an established prognostication tool in the management of breast cancers (BCs). Latest ten-year survival data have demonstrated an improved outlook for each NPI category and the latest UK five- and ten-year survival from BC has been reported to be 85% and 77%, respectively. We compared survival of each NPI category for BCs diagnosed within the national breast screening service in Wales (Breast Test Wales (BTW)) to the latest data, and reviewed its validity in unselected cases within a screened population.

METHODS

All women screened between 1998 and 2001 within BTW were included. The NPI score for each cancer was calculated using the size, nodal status, and grade of the primary tumour. Survival data (all-cause) were calculated after ten years of follow-up.

RESULTS

In the three-year screening period, 199,082 women were screened. A total of 1,712 cancers were diagnosed, and 1,546 had data available for calculating the NPI. Overall five-year and ten-year survival was 94% and 82%, respectively.

CONCLUSIONS

Overall five-year and ten-year survival (all-cause) has improved even when compared with UK data for BC-specific survival. We found that the NPI remains valid for BC treatment, and that our data provide a reference for updating the all-cause survival of women diagnosed with BCs within a screened population.

Advances in the Molecular Analysis of Breast Cancer: Pathway toward Personalized Medicine

Background

Breast cancer is a heterogeneous disease that encompasses a wide range of clinical behaviors and histological and molecular variants. It is the most common type of cancer affecting women worldwide and is the second leading cause of cancer death.

Methods

A comprehensive literature search was performed to explore the advances in molecular medicine related to the diagnosis and treatment of breast cancer.

Results

During the last few decades, advances in molecular medicine have changed the landscape of cancer treatment as new molecular tests complement and, in many instances, exceed traditional methods for determining patient prognosis and response to treatment options. Personalized medicine is becoming the standard of care around the world. Developments in molecular profiling, genomic analysis, and the discovery of targeted drug therapies have significantly improved patient survival rates and quality of life.

Conclusions

This review highlights what pathologists need to know about current molecular tests for classification and prognostic/predictive assessment of breast carcinoma as well as their role as part of the medical team.

Comparison of Nottingham Prognostic Index and Adjuvant Online prognostic tools in young women with breast cancer: review of a single-institution experience

OBJECTIVE

Accurately predicting the prognosis of young patients with breast cancer (<40 years) is uncertain since the literature suggests they have a higher mortality and that age is an independent risk factor. In this cohort study we considered two prognostic tools; Nottingham Prognostic Index and Adjuvant Online (Adjuvant!), in a group of young patients, comparing their predicted prognosis with their actual survival.

SETTING

North East England

PARTICIPANTS

Data was prospectively collected from the breast unit at a Hospital in Grimsby between January 1998 and December 2007. A cohort of 102 young patients with primary breast cancer was identified and actual survival data was recorded. The Nottingham Prognostic Index and Adjuvant! scores were calculated and used to estimate 10-year survival probabilities. Pearson's correlation coefficient was used to demonstrate the association between the Nottingham Prognostic Index and Adjuvant! scores. A constant yearly hazard rate was assumed to generate 10-year cumulative survival curves using the Nottingham Prognostic Index and Adjuvant! predictions.

RESULTS

Actual 10-year survival for the 92 patients who underwent potentially curative surgery for invasive cancer was 77.2% (CI 68.6% to 85.8%). There was no significant difference between the actual survival and the Nottingham Prognostic Index and Adjuvant! 10-year estimated survival, which was 77.3% (CI 74.4% to 80.2%) and 82.1% (CI 79.1% to 85.1%), respectively. The Nottingham Prognostic Index and Adjuvant! results demonstrated strong correlation and both predicted cumulative survival curves accurately reflected the actual survival in young patients.

CONCLUSIONS

The Nottingham Prognostic Index and Adjuvant! are widely used to predict survival in patients with breast cancer. In this study no statistically significant difference was shown between the predicted prognosis and actual survival of a group of young patients with breast cancer.

Correlation between 3T apparent diffusion coefficient values and grading of invasive breast carcinoma

PURPOSE

The aim of this study was to evaluate whether the apparent diffusion coefficient (ADC) provided by 3.0T (3T) magnetic resonance diffusion-weighted imaging (DWI) varied according to the grading of invasive breast carcinoma.

MATERIALS AND METHODS

A total of 92 patients with 96 invasive breast cancer lesions were enrolled; all had undergone 3T magnetic resonance imaging (MRI) for local staging. All lesions were confirmed by histological analysis, and tumor grade was established according to the Nottingham Grading System (NGS). MRI included both dynamic contrast-enhanced and DWI sequences, and ADC value was calculated for each lesion. ADC values were compared with NGS classification using the Mann-Whitney U and the Kruskal-Wallis H tests. Grading was considered as a comprehensive prognostic factor, and Rho Spearman test was performed to determine correlation between grading and tumor size, hormonal receptor status, HER2 expression and Ki67 index. Pearson's Chi square test was carried out to compare grading with the other prognostic factors.

RESULTS

ADC values were significantly higher in G1 than in G3 tumors. No significant difference was observed when G1 and G3 were compared with G2. Tumor size, hormonal receptor status, HER2 expression and Ki67 index correlated significantly with grading but there was a significant difference only between G1 and G3 related to the ER and PR status, HER2 expression and Ki67 index. There was no statistically significant difference in lesion size between the two groups.

CONCLUSION

ADC values obtained on 3T DWI correlated with low-grade (G1) and high-grade (G3) invasive breast carcinoma. 3T ADC may be a helpful tool for identifying high-grade invasive breast carcinoma.

Classification of patients with breast cancer according to Nottingham prognostic index highlights significant differences in immunohistochemical marker expression

BACKGROUND

Prognosis and treatment of patients with breast carcinoma of no special type (NST) is dependent on a few established parameters, such as tumor size, histological grade, lymph node stage, expression of estrogen receptor, progesterone receptor, and HER-2/neu, and proliferation index. The original Nottingham Prognostic Index (NPI) employs a three-tiered classification system that stratifies patients with breast cancer into good, moderate, and poor prognostic groups. The aim of our study was to use robust immunohistochemical methodology for determination of ER, PR, HER-2/neu, Ki-67, p53, and Bcl-2, and to observe differences in the expression of these markers when patients are stratified according to the original, three-tiered Nottingham Prognostic Index.

METHODS

Paraffin blocks from 120 patients diagnosed with breast carcinoma, NST, were retrieved from our archive. Cases included in the study were female patients previously treated with modified radical mastectomy and axillary dissection.

RESULTS

Our study demonstrates that expression of markers of good prognosis, such as ER, PR, and Bcl-2, is seen with higher frequency in good and moderate NPI groups. In contrast, overexpression of HER-2/neu, a marker of adverse prognosis, is more frequent in moderate and poor NPI groups. High proliferation index, as measured by Ki-67, is seen in moderate and poor NPI groups, whereas low proliferation index is seen in good NPI groups.

CONCLUSIONS

These data confirm that the original, three-tiered NPI statistically correlates with the expression of prognostic immunohistochemical markers in breast carcinoma NST.

ß1 integrin binding phosphorylates ezrin at T567 to activate a lipid raft signalsome driving invadopodia activity and invasion

Extracellular matrix (ECM) degradation is a critical process in tumor cell invasion and requires matrix degrading protrusions called invadopodia. The Na⁺/H⁺ exchanger (NHE1) has recently been shown to be fundamental in the regulation of invadopodia actin cytoskeleton dynamics and activity. However, the structural link between the invadopodia cytoskeleton and NHE1 is still unknown. A candidate could be ezrin, a linker between the NHE1 and the actin cytoskeleton known to play a pivotal role in invasion and metastasis. However, the mechanistic basis for its role remains unknown. Here, we demonstrate that ezrin phosphorylated at T567 is highly overexpressed in the membrane of human breast tumors and positively associated with invasive growth and HER2 overexpression. Further, in the metastatic cell line, MDA-MB-231, p-ezrin was almost exclusively expressed in invadopodia lipid rafts where it co-localized in a functional complex with NHE1, EGFR, ß1-integrin and phosphorylated-NHERF1. Manipulation by mutation of ezrins T567 phosphorylation state and/or PIP2 binding capacity or of NHE1s binding to ezrin or PIP2 demonstrated that p-ezrin expression and binding to PIP2 are required for invadopodia-mediated ECM degradation and invasion and identified NHE1 as the membrane protein that p-ezrin regulates to induce invadopodia formation and activity.

Modeling of breast cancer prognostic factors using a parametric log-logistic model in Fars province, Southern Iran

In general, breast cancer is the most common malignancy among women in developed as well as some developing countries, often being the second leading cause of cancer mortality after lung cancer. Using a parametric log-logistic model to consider the effects of prognostic factors, the present study focused on the 5-year survival of women with the diagnosis of breast cancer in Southern Iran. A total of 1,148 women who were diagnosed with primary invasive breast cancer from January 2001 to January 2005 were included and divided into three prognosis groups: poor, medium, and good. The survival times as well as the hazard rates of the three different groups were compared. The log-logistic model was employed as the best parametric model which could explain survival times. The hazard rates of the poor and the medium prognosis groups were respectively 13 and 3 times greater than in the good prognosis group. Also, the difference between the overall survival rates of the poor and the medium prognosis groups was highly significant in comparison to the good prognosis group. Use of the parametric log-logistic model - also a proportional odds model - allowed assessment of the natural process of the disease based on hazard and identification of trends.

Tumor-stromal interactions in breast tumor progression--significance of histological heterogeneity of tumor-stromal fibroblasts

INTRODUCTION

Existing pathological diagnostic protocols for breast cancer do not fully reflect the biological characteristics of tumor stromata. To improve the pathological diagnosis of breast cancer, a new pathological diagnostic method capable of assessing the degree of breast cancer malignancy based on the histological features of the tumor stroma is needed.

AREAS COVERED

The presence of a fibrotic focus (FF), which consists of fibroblasts or collagen fibers, and the presence of atypical tumor-stromal fibroblasts are significantly associated with nodal metastasis or distant-organ metastasis in patients with invasive ductal carcinoma (IDC) of the breast. FF is the only factor that is significantly associated with an increase in tumor angiogenesis. The importance of FF and atypical tumor-stromal fibroblasts clearly indicates that the malignant potential of IDC does not depend only on the biological characteristics of the tumor cell, but also on those of the tumor stroma.

EXPERT OPINION

The biological characteristics of fibroblasts forming an FF or atypical tumor-stromal fibroblasts probably differ from those of fibroblasts located outside an FF or ordinary tumor-stromal fibroblasts. Thus, similar to tumor cells, the heterogeneity of tumor-stromal fibroblasts probably influences the outcome of patients with IDC of the breast.

Asymptomatic Breast Cancer in Non-Participants of the National Screening Programme in Norway: A Confounding Factor in Evaluation?

Objective

To evaluate the extent and histopathological characteristics of asymptomatic breast cancer detected outside the Norwegian Breast Cancer Screening Program (NBCSP) in women targeted by the programme.

Methods

Our study included 568 primary breast cancers (523 invasive and 45 ductal carcinoma in situ) diagnosed in 553 women aged 50–70, residing in Møre og Romsdal County, 2002–2008. The cancers were divided into screening-detected cancers in the NBCSP, interval cancers (ICs) and cancers detected in women not participating in the NBCSP (never participated and lapsed attendees), and further into asymptomatic and symptomatic cancers. Nottingham Prognostic Index (NPI) was used for comparisons across the groups and the distributions were compared using chi-square tests for statistical significance.

Results

Twenty percent (19/97) of the ICs and 32% (69/213) of the breast cancers in non-participants were asymptomatic, with opportunistic screening as the most frequent detection method (42%, 8/19 for ICs and 54%, 37/69 for non-participants). There were no differences in distribution of NPI prognostic categories across subgroups of asymptomatic invasive cancers (screening-detected cancers in the NBCSP, asymptomatic ICs and asymptomatic cancers in non-participants) or between subgroups of symptomatic invasive cancers (symptomatic ICs and symptomatic cancers in non-participants). Asymptomatic cancers had a significantly more favourable distribution of NPI prognostic categories compared with symptomatic cancers ( P < 0.001). The proportion of invasive cancers with excellent/good NPI was 53% (164/310) for all asymptomatic and 25% (52/211) for all symptomatic invasive cancers.

Conclusions

A considerable percentage of breast cancers detected outside the organized screening programme were asymptomatic, with a prognostic profile comparable with screening-detected breast cancers in the NBCSP. Individual data regarding the detection method for all breast cancers are needed for a complete evaluation of the organized screening programme in Norway.

Molecular characteristics and prognostic features of breast cancer in Nigerian compared with UK women

Although breast cancer (BC) incidence is lower in African-American women compared with White-American, in African countries such as Nigeria, BC is a common disease. Nigerian women have a higher risk for early-onset, with a high mortality rate from BC, prompting speculation that risk factors could be genetic and the molecular portrait of these tumours are different to those of western women. In this study, 308 BC samples from Nigerian women with complete clinical history and tumour characteristics were included and compared with a large series of BC from the UK as a control group. Immunoprofile of these tumours was characterised using a panel of 11 biomarkers of known relevance to BC. The immunoprofile and patients' outcome were compared with tumour grade-matched UK control group. Nigerian women presenting with BC were more frequently premenopausal, and their tumours were characterised by large primary tumour size, high tumour grade, advanced lymph node stage, and a higher rate of vascular invasion compared with UK women. In the grade-matched groups, Nigerian BC showed over representation of triple-negative and basal phenotypes and BRCA1 deficiency BC compared with UK women, but no difference was found regarding HER2 expression between the two series. Nigerian women showed significantly poorer outcome after development of BC compared with UK women. This study demonstrates that there are possible genetic and molecular differences between an indigenous Black population and a UK-based series. The basal-like, triple negative and BRCA1 dysfunction groups of tumours identified in this study may have implications in the development of screening programs and therapies for African patients and families that are likely to have a BRCA1 dysfunction, basal like and triple negative.

A mitotically active, cellular tumor stroma and/or inflammatory cells associated with tumor cells may contribute to intermediate or high Oncotype DX Recurrence Scores in low-grade invasive breast carcinomas

Oncotype DX is an RT-PCR-based 21-gene assay validated to provide prognostic and predictive information in the form of a Recurrence Score in patients with estrogen receptor-positive, lymph node-negative breast cancer. Although the Recurrence Score was shown to correlate with several histopathological tumor features, there is a significant proportion of cases showing an apparent discrepancy between Recurrence Score and risk estimates based on the traditional clinicopathological tumor features. In this study, we tested whether a proliferating, cellular stroma and/or admixed inflammatory cells may result in an artificially increased Recurrence Score in low-grade invasive breast cancers. We analyzed the histopathological features in 141 low-grade invasive breast carcinomas, including 41 special type (tubular, cribriform and mucinous) carcinomas, with available Recurrence Score. The tumor stroma was evaluated for increased cellularity and presence of inflammatory cells. Double immunohistochemical stains for pancytokeratin and Ki-67 was performed to assess the cell proliferation in tumor vs stromal/inflammatory cells. The clinicopathological features of tumors with Recurrence Score <18 (low risk) were compared with those with Recurrence Score ≥18 (intermediate/high risk). Carcinomas associated with Recurrence Score ≥18 showed lower progesterone receptor immunoreactivity, increased stromal cellularity and presence of inflammatory cells associated with the tumor. Double immunohistochemical stains showed significantly increased proliferation in stromal/inflammatory cells compared with carcinoma cells in cases associated with Recurrence Score ≥18. A Ki-67-positive stromal/tumor cells ratio of >1 predicted Recurrence Score ≥18 with an area under the curve of 0.8967 on receiver operator curve analysis (P<0.0001). Our results suggest that the presence of increased stromal cellularity and/or associated inflammatory cells in low-grade invasive breast carcinomas may contribute to an apparently increased risk of recurrence according to Oncotype DX Recurrence Score. Careful assessment and correlation with histopathological features in such cases may help in determining the appropriate patient management.

Modified primary tumour/vessel tumour/nodal tumour classification for patients with invasive ductal carcinoma of the breast

Background:

We previously reported that the primary tumour/vessel tumour/nodal tumour (PVN) classification is significantly superior to the UICC pTNM classification and the Nottingham Prognostic Index for accurately predicting the outcome of patients with invasive ductal carcinoma of the breast in a manner that is independent of the nodal status and the hormone receptor status.

Methods:

The purpose of the present study was to compare the outcome predictive power of a modified PVN classification to that of the newly devised pathological UICC pTNM classification and the reclassified Nottingham Prognostic Index in a different group of patients with invasive ductal carcinoma (n=1042) using multivariate analyses by the Cox proportional hazard regression model.

Results:

The modified PVN classification clearly exhibited a superior significant power, compared with the other classifications, for the accurate prediction of tumour recurrence and tumour-related death among patients with invasive ductal carcinoma in a manner that was independent of the nodal status, the hormone receptor status, and adjuvant therapy status.

Conclusion:

The modified PVN classification is a useful classification system for predicting the outcome of invasive ductal carcinoma of the breast.

Correlation between mammographic and sonographic findings and prognostic factors in patients with node-negative invasive breast cancer

OBJECTIVES

The purpose of this study was to correlate sonographic and mammographic findings with prognostic factors in patients with node-negative invasive breast cancer.

METHODS

Sonographic and mammographic findings in 710 consecutive patients (age range 21-81 years; mean age 49 years) with 715 node-negative invasive breast cancers were retrospectively evaluated. Pathology reports relating to tumour size, histological grade, lymphovascular invasion (LVI), extensive intraductal component (EIC), oestrogen receptor (ER) status and HER-2/neu status were reviewed and correlated with the imaging findings. Statistical analysis was performed using logistic regression analysis and intraclass correlation coefficient (ICC).

RESULTS

On mammography, non-spiculated masses with calcifications were associated with all poor prognostic factors: high histological grade, positive LVI, EIC, HER-2/neu status and negative ER. Other lesions were associated with none of these poor prognostic factors. Hyperdense masses on mammography, the presence of mixed echogenicity, posterior enhancement, calcifications in-or-out of masses and diffusely increased vascularity on sonography were associated with high histological grade and negative ER. Associated calcifications on both mammograms and sonograms were correlated with EIC and HER-2/neu overexpression. The ICC value for the disease extent was 0.60 on mammography and 0.70 on sonography.

CONCLUSION

Several sonographic and mammographic features can have a prognostic value in the subsequent treatment of patients with node-negative invasive breast cancer. Radiologists should pay more attention to masses that are associated with calcifications because on both mammography and sonography associated calcifications were predictors of positive EIC and HER-2/neu overexpression.