Survival of invasive breast cancer according to the Nottingham Prognostic Index in cases diagnosed in 1990-1999

The functional TNF-α-308G > a single-nucleotide polymorphism (rs1800629): association with the predictive indices of breast cancer carcinogenesis

BACKGROUND

Compared with all other cancer types, Breast cancer (BC) among women has now exceeded them all as the primary reason for cancer worldwide. The BC represents 11.7% of all cancer cases and accounts for a predestined 2.3 million new cases. It is the fourth primary reason for cancer-associated deaths in women. With a staggering 200-400% increase in the relative incidence of BC in Egypt, there is an urgent need for new diagnostic or predictive markers.

PURPOSE

The current investigation aims to explore the connection of the functional TNF-α-308G > A (rs1800629) single-nucleotide polymorphism (SNP) with different breast cancer predictive indices.

METHODS

The ARMS-PCR method was used for genotyping TNF-α-308G > A SNP. Three groups were recruited for the study: 79 patients with benign breast inflammation (BBI); 163 with breast cancer (BC) and 144 controls (C).

RESULTS

The TNF-α-308G > A SNP was distributed among different groups in a unique pattern; in the control group 63.9% of cases were in the GG, 34% were in the GA, and 2.1% were in the AA. The BC group had 14% GG, 79% GA, and 7% AA, while the BBI group had 24% GG, 76% GA, and 0% AA. The AA genotype and A allele represented a strong significant correlation with risk factors in the BC group (ORAA: 14.67 [95% CI = 3.78-56.91] and ORA: 0.27 [95% CI = 0.19-0.39], respectively; P < 0.0001) in contrast to the control group. However, in the BBI group, a strong significant correlation was noted with the GA genotype (ORGA: 5.93 [95% CI = 3.18-11.04] P < 0.0001). In the BC group, the AA genotype shows a significant increase in Nottingham Prognostic Index (NPI) in positive ER and PR in contrast to the relevant negative ones (P = 0.02 and 0.002, respectively). However, the GA genotype significantly increased NPI in positive Her2 and metastatic patients (P = 0.03 and 0.01, respectively).

CONCLUSION

This research is the first to correlate TNF-α-308G > A (rs1800629) SNP in Egyptian BC patients. The A allele, GA & AA genotypes, and the Overdominant model of the TNF-α-308G > A gene variants were recorded as prognostic risk factors for BC carcinogenesis.

The prognostic value of histological grade determined after neoadjuvant chemotherapy of breast cancer

Histological grade is a validated prognostic factor of breast cancer but may show alterations following neoadjuvant chemotherapy (NACT). Its reporting after NACT is recommended by several guidelines, but evidence of its retained prognostic impact is scarce. Patients treated with NACT followed by surgery and having sufficient residual tumour for the determination of grade were analysed for the survival effects of posttreatment grade (yG). Kaplan-Meier analyses and the log-rank test were applied, followed by the univariable and multivariable Cox proportional hazards models. The cohort comprised 355 patients with known yG, and 320 of them had also a pretreatment grade available. Pretreatment grade changed in 99/320 (31 %) cases following NACT, and downgrading was more common (n=78/320, 24 %) than upgrading (21/320, 7 %). Among 355 breast cancer patients, those with yG3 (poorly differentiated) tumours (n=155) had worse 5-year relapse-free and overall survival estimates than those with yG2 (n=169) or yG1 (n=31) tumours. This was also substantiated by univariable analysis; however, yG lost its significance in the multivariable model. Post-NACT histological grade has a prognostic impact, but does not seem to be an independent prognosticator in the post-NACT setting; however, these results lend support for its reporting by pathologists after primary systemic treatment.

Preoperative plasma fibrinogen level is a risk factor for the long-term survival of postmenopausal women after surgery for breast cancer

BACKGROUND

Studies have indicated an association between fibrinogen levels and the prognosis of breast cancer patients. However, fibrinogen levels are notably susceptible to fluctuations due to the menstrual cycle. This study explored the relationship between preoperative plasma fibrinogen levels and the prognosis of postmenopausal breast cancer women after surgery.

METHOD

855 patients with postmenopausal breast cancer were monitored for 10 years. Cox proportional hazards regression models were used to perform univariate and multivariate analyses to identify factors that are of substantial prognostic value.

RESULTS

The median follow-up was 77 months (51-105 months), and the maximum 142 months. Over the follow-up period, 65 deaths (7.6 %) were recorded. Multivariate Cox regression results show that preoperative plasma fibrinogen level (hazard ratio [HR] =1.615, 95 % confidence interval [CI]: 1.233-2.115) and age (HR = 1.626, 95%CI: 1.250-2.116) were independent risk factors for 10-year overall survival after surgery in postmenopausal breast cancer patients, while endocrine therapy (HR = 0.414, 95%CI: 0.202-0.846) was an independent protective factor. Multivariate Cox regression results also show preoperative plasma fibrinogen level was an independent risk factor for 10-year disease-free survival (HR = 1.398, 95 % CI: 1.137-1.719) and 10-year distant metastasis-free survival (HR = 1.436, 95%CI: 1.153-1.787).

CONCLUSION

Elevated pretreatment plasma fibrinogen levels are associated with a poorer long-term prognosis in postmenopausal breast cancer patients following surgical treatment.

Association between pathological characteristics and recurrence score by OncotypeDX in resected T1-3 and N0-1 breast cancer: a real-life experience of a North Hungarian regional center

Introduction: The 21-gene analysis (OncotypeDX) is validated test for pT1-3, pN0-1 with hormone receptor (HR) positive and normal expression of human epidermal growth factor receptor-2 (HER2) breast cancer (BC) to determine the aggressiveness of the disease based on the calculation of Recurrence Score (RS). Methods: In this retrospective study the authors correlated pathological characteristics and Recurrence Score (RS) by traditional statistical methods and Observed Oriented Modeling (OOM) in a realistic cohort of BC patients. Results: OncotypeDX tests were performed in 94 tumour specimens of 90 BC patients. >83% of node-negative (pN0) and >72% of node-positive (pN1) cases could avoid chemotherapy. For pN0 cases, non-parametric correlation and tests demonstrated significant association in eight types of characteristics [progesterone receptor (PR) expression, Ki-67 value, Ki-67 group, PR group, grade, estrogen receptor (ER) expression, Nottingham Prognostic Index (NPI) and Clinical Risk]. For pN1 cases, parametric correlation and tests showed significant association in six characteristic types (number of positive nodes, ER and PR expression, PR group, Ki-67 group and NPI). Based on OOM for pN0 cases, significant associations were established in three characteristics (Ki-67 group, grade and NPI group). For pN1 cases OOM found significant associations in seven characteristics (PR group, PNI, LVI, Ki-67 group, grade, NPI group and number of positive nodes). Conclusion: First in oncology, OOM was applied, which found some other significant characteristics associated with RS than traditional statistical methods. There were few patients, where no clinical associations were found between characteristics and RS contrary to statistically significant differences. Therefore, the results of these statistical analyses can be neither applied for individual cases nor able to provide the bases for screening patients, i.e., whether they need for OncotypeDX testing or not. OncotypeDX still provides a personalised approach in BC.

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multigene prognostic signature associated with metastasis

BACKGROUND

Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumors at high risk of metastasis would have a significant impact on management.

OBJECTIVE

To develop a robust and validated gene expression profile signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach.

METHODS

Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 nonmetastasizing and 86 metastasizing) were collected retrospectively from four centers. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets.

RESULTS

A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk.

LIMITATIONS

This was a retrospective 4-center study and larger prospective multicenter studies are now required.

CONCLUSION

The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC.

Expression Patterns of ER, PR, HER-2/neu and p53 in Association with Nottingham Tumour Grade in Breast Cancer Patients

Objectives

Recent molecular studies show that breast cancer (BC) is a heterogeneous disease, and several molecular changes may accumulate over time to influence treatment response. As a result, employing reliable molecular biomarkers to monitor these modifications may help deliver personalised treatment. However, this may be unrealistic in the resource-limited parts of the world. Thus, this study aimed to investigate the expression pattern of hormone receptors and p53 tumour suppressor using immunohistochemistry (IHC) in BC compared to the traditional tumour grade.

Methods

In total, 205 cases were investigated, and the Modified Bloom-Richardson score system was adopted in grading the tumours. The tissue sections of the cases were stained with specific primary antibodies at dilutions of 1:60 for oestrogen receptors (ER) and progesterone receptors (PR), 1:350 for the human epidermal growth factor (HER-2/neu) and 1:50 for p53.

Results

Invasive ductal carcinoma of no-specific type (n = 190, 92.7%) was predominant and grade II tumour (n = 146, 71.2%) was the most frequent. Hormone receptors ER (n = 127) and PR (n = 145) had 62.0% and 70.7% positive cases, respectively; 34.1% (n = 70) were positive for HER-2/neu, while 76.1% (n = 156) were positive for p53. Significant associations between Nottingham grade and expression patterns of ER (P <0.01), PR (P <0.001), HER-2/neu (P <0.001) and p53 (P = 0.001) were observed.

Conclusion

Nottingham grade had a high degree of concordance with the patterns of expression of hormone receptors, HER-2/neu and p53, suggesting that it may play an important role in connection with the predictive and prognostic biomarkers for BC.

Stromal Expression of CD10 in Breast Carcinoma and Its Association with Known Prognostic Factors-A Tissue Microarray-Based Study

Background  Breast cancer is an epithelial malignancy; however, stroma plays a key role with its stimulatory and inhibitory factors in modulating tumor invasion and metastasis. CD10, a matrix metalloproteinase, is known to regulate cell adhesion, migration and helps in determining the progression of tumor. This knowledge helps to identify specific signals that promote growth, dedifferentiation, invasion, metastasis and serve as target for better therapeutic management. Objectives  The aim of this study was to estimate frequency of expression of stromal CD10 and assess its prognostic significance in breast carcinomas by correlating with known prognostic factors. Materials and Methods  Morphological parameters of 62 cases of carcinoma breast were studied on H&E (hematoxylin and eosin) stained sections and expressions of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2/neu), and CD10 on manually constructed tissue microarray sections by immunohistochemistry (IHC). Staining pattern, percentage of stained cells, and intensity of stains were evaluated and IHC scoring of all markers was done. CD10 scores were correlated with the known prognostic factors (ER, PR, and HER2/neu). A p -value less than 0.05 was considered as significant. Results  Stromal expression of CD10 was found in 82.3% of cases and it was significantly associated with increasing tumor size ( p  = 0.012), increasing tumor grade ( p  = 0.001), lymph node metastasis ( p  = 0.018), necrosis ( p  = 0.008), lymphovascular invasion ( p  = 0.008), ER negativity ( p  = 0.001), PR negativity( p  = 0.007), HER 2 positivity ( p  = 0.012), triple-negative molecular subtypes ( p  = 0.001), and poor prognostic groups ( p  = 0.01). Conclusion  CD10 can be used as an independent prognostic stromal marker and this will help to envisage new therapeutic strategies.

Comparison of the Nottingham Prognostic Index and OncotypeDX© recurrence score in predicting outcome in estrogen receptor positive breast cancer

INTRODUCTION

Traditionally, Nottingham prognostic index (NPI) informed prognosis in patients with estrogen receptor positive, human epidermal growth factor receptor-2 negative, node negative (ER+/HER2-/LN-) breast cancer. At present, OncotypeDX© Recurrence Score (RS) predicts prognosis and response to adjuvant chemotherapy (AC).

AIMS

To compare NPI and RS for estimating prognosis in ER + breast cancer.

METHODS

Consecutive patients with ER+/HER2-/LN- disease were included. Disease-free (DFS) and overall survival (OS) were determined using Kaplan-Meier and Cox regression analyses.

RESULTS

1471 patients met inclusion criteria. The mean follow-up was 110.7months. NPI was calculable for 1382 patients: 19.8% had NPI≤2.4 (291/1471), 33.0% had NPI 2.41-3.4 (486/1471), 30.0% had NPI 3.41-4.4 (441/1471), 10.9% had NPI 4.41-5.4 (160/1471), and 0.3% had NPI>5.4 (4/1471). In total, 329 patients underwent RS (mean RS: 18.7) and 82.1% had RS < 25 (270/329) and 17.9% had RS ≥ 25 (59/329). Using multivariable Cox regression analyses (n = 1382), NPI independently predicted DFS (Hazard ratio (HR): 1.357, 95% confidence interval (CI): 1.140-1.616, P < 0.001) and OS (HR: 1.003, 95% CI: 1.001-1.006, P = 0.024). When performing a focused analysis of those who underwent both NPI and RS (n = 329), neither biomarker predicted DFS or OS. Using Kaplan Meier analyses, NPI category predicted DFS (P = 0.008) and (P = 0.026) OS. Conversely, 21-gene RS group failed to predict DFS (P = 0.187) and OS (P = 0.296).

CONCLUSION

In our focused analysis, neither NPI nor RS predicted survival outcomes. However, in the entire series, NPI independently predicted both DFS and OS. On the 40th anniversary since its derivation, NPI continues to provide accurate prognostication in breast cancer, outperforming RS in the current study.

Pathological Diagnosis, Work-Up and Reporting of Breast Cancer 1st Central-Eastern European Professional Consensus Statement on Breast Cancer

This text is based on the recommendations accepted by the 4th Hungarian Consensus Conference on Breast Cancer, modified on the basis of the international consultation and conference within the frames of the Central-Eastern European Academy of Oncology. The recommendations cover non-operative, intraoperative and postoperative diagnostics, determination of prognostic and predictive markers and the content of cytology and histology reports. Furthermore, they address some specific issues such as the current status of multigene molecular markers, the role of pathologists in clinical trials and prerequisites for their involvement, and some remarks about the future.

The projected impact of the COVID-19 lockdown on breast cancer deaths in England due to the cessation of population screening: a national estimation

BACKGROUND

Population breast screening services in England were suspended in March 2020 due to the COVID-19 pandemic. Here, we estimate the number of breast cancers whose detection may be delayed because of the suspension, and the potential impact on cancer deaths over 10 years.

METHODS

We estimated the number and length of screening delays from observed NHS Breast Screening System data. We then estimated additional breast cancer deaths from three routes: asymptomatic tumours progressing to symptomatically diagnosed disease, invasive tumours which remain screen-detected but at a later date, and ductal carcinoma in situ (DCIS) progressing to invasive disease by detection. We took progression rates, prognostic characteristics, and survival rates from published sources.

RESULTS

We estimated that 1,489,237 women had screening delayed by around 2-7 months between July 2020 and June 2021, leaving 745,277 outstanding screens. Depending on how quickly this backlog is cleared, around 2500-4100 cancers would shift from screen-detected to symptomatic cancers, resulting in 148-452 additional breast cancer deaths. There would be an additional 164-222 screen-detected tumour deaths, and 71-97 deaths from DCIS that progresses to invasive cancer.

CONCLUSIONS

An estimated 148-687 additional breast cancer deaths may occur as a result of the pandemic-related disruptions. The impact depends on how quickly screening services catch up with delays.

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.

Advancement of prognostic models in breast cancer: a narrative review

Objective

To provide a reference for clinical work and guide the decision-making of healthcare providers and end-users, we systematically reviewed the development, validation and classification of classical prognostic models for breast cancer.

Background

Patients suffering from breast cancer have different prognosis for its high heterogeneity. Accurate prognosis prediction and risk stratification for breast cancer are crucial for individualized treatment. There is a lack of systematic summary of breast cancer prognostic models.

Methods

We conducted a PubMed search with keywords "breast neoplasm", "prognostic model", "recurrence" and "metastasis", and screened the retrieved publications at three levels: title, abstract and full text. We identified the articles presented the development and/or validation of models based on clinicopathological factors, genomics, and machine learning (ML) methods to predict survival and/or benefits of adjuvant therapy in female breast cancer patients.

Conclusions

Combining prognostic-related variables with long-term clinical outcomes, researchers have developed a series of prognostic models based on clinicopathological parameters, genomic assays, and medical figures. The discrimination, calibration, overall performance, and clinical usefulness were validated by internal and/or external verifications. Clinicopathological models integrated the clinical parameters, including tumor size, histological grade, lymph node status, hormone receptor status to provide prognostic information for patients and doctors. Gene-expression assays deeply revealed the molecular heterogeneity of breast cancer, some of which have been cited by AJCC and National Comprehensive Cancer Network (NCCN) guidelines. In addition, the models based on the ML methods provided more detailed information for prognosis prediction by increasing the data dimension. Combined models incorporating clinical variables and genomics information are still required to be developed as the focus of further researches.

Preoperative Routine Laboratory Markers for Predicting Postoperative Recurrence and Death in Patients with Breast Cancer

Simple, convenient, and reliable preoperative prognostic indicators are needed to estimate the future risk of recurrences and guide the treatment decisions associated with breast cancer. We evaluated preoperative hematological markers related to recurrence and mortality and investigated independent risk factors for recurrence and mortality in patients after breast cancer surgery. We reviewed electronic medical records of patients with invasive breast cancer diagnosed at our tertiary institution between November 2005 and December 2010 and followed them until 2015. We compared two groups of patients classified according to recurrence or death and identified risk factors for postoperative outcomes. Data from 1783 patients were analyzed ultimately. Cancer antigen (CA) 15-3 and red cell distribution width (RDW) had the highest area under the curve values among several preoperative hematological markers for disease-free survival and overall survival (0.590 and 0.637, respectively). Patients with both preoperative CA 15-3 levels over 11.4 and RDW over 13.5 had a 1.7-fold higher risk of recurrence (hazard ratio (HR): 1.655; 95% confidence interval (CI): 1.154-2.374; p = 0.007) and mortality (HR: 1.723; 95% CI: 1.098-2.704; p = 0.019). In conclusion, relatively high preoperative RDW (>13.5) and CA 15-3 levels (>11.4) had the highest predictive power for mortality and recurrence, respectively. When RDW and CA 15-3 exceeded the cut-off value, the risk of recurrence and death also increased approximately 1.7 times.

Dynamic Effects of CAM Techniques on Inflammation and Emotional States: An Integrative Single-Case Study on a Breast Cancer Survivor

BACKGROUND

This study on a breast cancer survivor investigated how episodic practice of various complementary and alternative medicine (CAM) techniques affected the dynamics of emotional states and urinary neopterin-an inflammation marker.

METHODS

The 49-year-old female patient (diagnosis: ductal breast carcinoma 5 years before study start, suffering from chronic fatigue and depression) collected her entire urine in 12-hour intervals (from about 8 a.m. to 8 p.m. and from about 8 p.m. to 8 a.m.) for 28 days. The resulting 55 consecutive urine samples were analyzed for neopterin and creatinine levels using HPLC. Also in 12-hour intervals, the patient filled out questionnaires on emotional states and everyday routine, including CAM practice. Weekly, she was interviewed to identify emotionally meaningful everyday incidents, including use of CAM techniques. Time series analysis consisted of ARIMA modeling and cross-correlational analyses.

RESULTS

Qualitative evaluation revealed that, with the exception of Tai Chi, all CAM techniques, that is, Jin Shin Jyutsu, music, physiotherapy and energy healing, were experienced as positive. Cross-correlational analyses showed that practice of such CAM techniques was followed first by significant (P < .05) increases in positive mood and mental activity on the same day (lag 0) and then by decreases in positive mood after a total of 72 to 84 hours (+lag 6) and in mental activity after a total of 84 to 96 hours (+lag 7). Negative mood, by contrast, first decreased on the day of CAM practice (lag 0) and then increased after a total of 84 to 96 hours (+lag 7) following CAM. Moreover, urinary neopterin levels first increased on the day of CAM practice (lag 0) and then decreased after a total of 36 to 48 hours (+lag 3). Similar biphasic effects were also detected for irritation in response to CAM, although only partly significant.

CONCLUSION

Cyclic psychophysiological response patterns following CAM practice were attributable to biopsychosocial feedback mechanisms involving personally meaningful experiences. As lower neopterin levels following CAM point to a health-promoting effect, the patient of this study may have actively contributed to her healing process through episodic CAM practice.

Case Report: Dynamic Interdependencies Between Complementary and Alternative Medicine (CAM) Practice, Urinary Interleukin-6 Levels, and Fatigue in a Breast Cancer Survivor

Background: This study investigated the influence of complementary and alternative medicine (CAM) techniques (i.e., Jin Shin Jyutsu, music, physiotherapy, Tai Chi, and energy healing) on urinary interleukin-6 (IL-6) levels and fatigue in a 49-year-old breast cancer survivor suffering from cancer-related fatigue and depression. Data were sampled under conditions of "life as it is lived." Methods: For 28 days, a female breast cancer survivor collected her full urine output in 12-h intervals from about 8 a.m. to 8 p.m. and from about 8 p.m. to 8 a.m. These urine samples were used to determine urinary IL-6 levels through ELISA and creatinine concentrations via HPLC. In 12-h intervals (every morning and evening), the patient completed the DIARI, which included fatigue measurement and notes on incidents and activities such as CAM practice. In addition, the patient was interviewed weekly to identify meaningful everyday incidents. In this context, CAM practice was also discussed. Time series analysis consisted of ARIMA modeling and cross-correlational analyses (p < 0.05). Results: When each CAM technique was considered separately in time series analysis, CAM was consistently associated with increases in urinary IL-6 release and decreases in fatigue. Furthermore, when all CAM techniques experienced as positive were included in one time series, a biphasic urinary IL-6 response pattern was found in which CAM practice was first preceded by decreases in IL-6 by 12-0 h and then followed by increases in IL-6 after 108-120 h. Finally, cross-correlations between IL-6 and fatigue showed that increases in IL-6 were followed by decreases in fatigue intensity after 48-60 h and, conversely, that decreases in fatigue intensity were followed by decreases in IL-6 after 24-36 h and 48-60 h. Conclusion: IL-6 increases and fatigue decreases highlight potential health-promoting effects of CAM practice. Moreover, a cyclic IL-6 pattern in response to all CAM activities experienced as positive underscores that CAM was meaningful to the patient. Additionally, a negative feedback circuit between IL-6 and fatigue intensity was detected. Taken together, this study confirms the necessity of integrating subjective meaning and dynamic complexity into biopsychosocial research in order to understand human functioning under real-life conditions.

One-year conditional survival of dogs and cats with invasive mammary carcinomas: A concept inspired from human breast cancer

Numerous studies have described the prognostic factors of canine and feline mammary carcinomas (MCs), that is, variables that predict patient survival after diagnosis. But how does survival estimation evolve in patients that escaped early death from their cancer? In human oncology, conditional survival (CS), the probability of surviving X further years when cancer patients have already survived Y years, is used to analyse cancer outcomes in a long‐term perspective. In this cohort of 344 dogs and 342 cats with surgically removed stage I to III invasive MCs, with a minimal follow‐up of 2 years, we calculated the 1‐year CS, that is, the probability for patients that have survived 1 year, to survive or to die from cancer during the subsequent year. The 1‐year conditional specific survival probabilities were 59% and 48% at diagnosis of invasive MC respectively in dogs and cats, and 80% and 52% in 1‐year surviving dogs and cats respectively, suggesting that 1‐year surviving dogs were relatively protected from cancer‐related death, whereas feline MCs remained life‐threatening cancers for longer periods of time. Among the most significant parameters associated with CS in surviving dogs and cats were the nodal stage and lymphovascular invasion, as well as patient age, cancer stage and margin status in surviving dogs. By comparison, tumour size and the histological grade did not significantly alter CS probabilities in surviving dogs and cats. Conditional survival may be considered a very interesting tool for veterinary practitioners to estimate the likely outcome of cancer survivors.

Economic Evaluation of Population-Based BRCA1/BRCA2 Mutation Testing across Multiple Countries and Health Systems

Clinical criteria/Family history-based BRCA testing misses a large proportion of BRCA carriers who can benefit from screening/prevention. We estimate the cost-effectiveness of population-based BRCA testing in general population women across different countries/health systems. A Markov model comparing the lifetime costs and effects of BRCA1/BRCA2 testing all general population women ≥30 years compared with clinical criteria/FH-based testing. Separate analyses are undertaken for the UK/USA/Netherlands (high-income countries/HIC), China/Brazil (upper–middle income countries/UMIC) and India (low–middle income countries/LMIC) using both health system/payer and societal perspectives. BRCA carriers undergo appropriate screening/prevention interventions to reduce breast cancer (BC) and ovarian cancer (OC) risk. Outcomes include OC, BC, and additional heart disease deaths and incremental cost-effectiveness ratio (ICER)/quality-adjusted life year (QALY). Probabilistic/one-way sensitivity analyses evaluate model uncertainty. For the base case, from a societal perspective, we found that population-based BRCA testing is cost-saving in HIC (UK-ICER = $−5639/QALY; USA-ICER = $−4018/QALY; Netherlands-ICER = $−11,433/QALY), and it appears cost-effective in UMIC (China-ICER = $18,066/QALY; Brazil-ICER = $13,579/QALY), but it is not cost-effective in LMIC (India-ICER = $23,031/QALY). From a payer perspective, population-based BRCA testing is highly cost-effective in HIC (UK-ICER = $21,191/QALY, USA-ICER = $16,552/QALY, Netherlands-ICER = $25,215/QALY), and it is cost-effective in UMIC (China-ICER = $23,485/QALY, Brazil−ICER = $20,995/QALY), but it is not cost-effective in LMIC (India-ICER = $32,217/QALY). BRCA testing costs below $172/test (ICER = $19,685/QALY), which makes it cost-effective (from a societal perspective) for LMIC/India. Population-based BRCA testing can prevent an additional 2319 to 2666 BC and 327 to 449 OC cases per million women than the current clinical strategy. Findings suggest that population-based BRCA testing for countries evaluated is extremely cost-effective across HIC/UMIC health systems, is cost-saving for HIC health systems from a societal perspective, and can prevent tens of thousands more BC/OC cases.

Peritumor to tumor apparent diffusion coefficient ratio is associated with biologically more aggressive breast cancer features and correlates with the prognostication tools

PURPOSE

The apparent diffusion coefficient (ADC) is increasingly used to characterize breast cancer. The peritumor/tumor ADC ratio is suggested to be a reliable and generally applicable index. However, its overall prognostication value remains unclear. We aimed to evaluate the associations between the peritumor/tumor ADC ratio and histopathological biomarkers and published prognostic tools in patients with invasive breast cancer.

MATERIALS AND METHODS

This prospective study included 88 lesions (five bilateral) in 83 patients with primary invasive breast cancer who underwent preoperative 3.0-T magnetic resonance imaging. The lowest intratumoral mean ADC value on the slice with the largest tumor cross-sectional area was designated the tumor ADC, and the highest mean ADC value on the peritumoral breast parenchymal tissue adjacent to the tumor border was designated the peritumor ADC. The peritumor/tumor ADC ratio was then calculated. The tumor and peritumor ADC values and peritumor/tumor ADC ratios were compared with histopathological parameters using an unpaired t test, and their correlations with published prognostic tools were evaluated with Pearson's correlation coefficient.

RESULTS

The peritumor/tumor ADC ratio was significantly associated with tumor size (p<0.001), histological grade (p = 0.005), Ki-67 index (p = 0.006), axillary-lymph-node metastasis (p = 0.001), and lymphovascular invasion (p = 0.006), but was not associated with estrogen receptor status (p = 0.931), progesterone receptor status (p = 0.160), or human epidermal growth factor receptor 2 status (p = 0.259). The peritumor/tumor ADC ratio showed moderate positive correlations with the Nottingham Prognostic Index (r = 0.498, p<0.001) and mortality predicted using PREDICT (r = 0.436, p<0.001).

CONCLUSION

The peritumor/tumor ADC ratio was correlated with histopathological biomarkers in patients with invasive breast cancer, showed significant correlations with published prognostic indexes, and may provide an easily applicable imaging index for the preoperative prognostic evaluation of breast cancer.

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.

PIK3Cδ expression by fibroblasts promotes triple-negative breast cancer progression

As there is growing evidence for the tumor microenvironment's role in tumorigenesis, we investigated the role of fibroblast-expressed kinases in triple-negative breast cancer (TNBC). Using a high-throughput kinome screen combined with 3D invasion assays, we identified fibroblast-expressed PIK3Cδ (f-PIK3Cδ) as a key regulator of cancer progression. Although PIK3Cδ was expressed in primary fibroblasts derived from TNBC patients, it was barely detectable in breast cancer (BC) cell lines. Genetic and pharmacological gain- and loss-of-function experiments verified the contribution of f-PIK3Cδ in TNBC cell invasion. Integrated secretomics and transcriptomics analyses revealed a paracrine mechanism via which f-PIK3Cδ confers its protumorigenic effects. Inhibition of f-PIK3Cδ promoted the secretion of factors, including PLGF and BDNF, that led to upregulation of NR4A1 in TNBC cells, where it acts as a tumor suppressor. Inhibition of PIK3Cδ in an orthotopic BC mouse model reduced tumor growth only after inoculation with fibroblasts, indicating a role of f-PIK3Cδ in cancer progression. Similar results were observed in the MMTV-PyMT transgenic BC mouse model, along with a decrease in tumor metastasis, emphasizing the potential immune-independent effects of PIK3Cδ inhibition. Finally, analysis of BC patient cohorts and TCGA data sets identified f-PIK3Cδ (protein and mRNA levels) as an independent prognostic factor for overall and disease-free survival, highlighting it as a therapeutic target for TNBC.

Radiological audit of interval breast cancers: Estimation of tumour growth rates

INTRODUCTION

This multicentre, retrospective study aimed to establish correlation between estimated tumour volume doubling times (TVDT) from a series of interval breast cancers with their clinicopathological features. The potential impact of delayed diagnosis on prognosis was also explored.

MATERIALS AND METHODS

Interval cancers, where screening mammograms demonstrated changes that were retrospectively classified as either uncertain or suspicious, were reviewed from five screening units within the UK NHS Breast Screening Programme (NHSBSP). Data collected included the time interval between screening mammogram and cancer diagnosis, the size of the initial mammographic abnormality and of the subsequent cancer, demographics, mammographic density and tumour biology. We estimated volume doubling times and the estimated change in size and node status, which would have followed if these cancers had been detected at the previous screen.

RESULTS

306 interval cancers meeting the inclusion criteria were identified. Average time from screening to diagnosis was 644 days (SD 276 days). 19% were diagnosed in the first twelve months, 42% in the subsequent twelve months and 39% thereafter. Overall average estimated TVDT was 167 days (95% CI 151-186). Significant differences were noted with age (p = 0.01), grade (p < 0.001) and ER status (p < 0.001) with women under 60, grade 3 cancers and ER negative cancers having shorter TVDTs. HER2 positive tumours had shorter doubling times than HER2 negative, but this difference was not statistically significant. It was estimated that diagnosing these cancers at the previous screen would have increased ten-year survival from 82% to 86%.

CONCLUSION

High grade, ER negativity and younger age were associated with shorter durations of TVDT. The role of HER2 status on interval cancer growth rate requires further assessment. It is likely that the delayed diagnosis of interval cancers confers a 4% reduction in ten-year survival.

Older age and comorbidity in breast cancer: is RT alone the new therapeutic frontier?

AIM

To assess the impact of age, comorbidities and endocrine therapy (ET) in older breast cancer (BC) patients treated with hypofractionated radiotherapy (Hypo-RT).

METHODS

From June 2009 to December 2017, we enrolled in this study 735 ER-positive BC patients (stage pT1-T2, pNx-1, M0 and age ≥ 65 years) receiving hypo-RT and followed them until September 2019. Baseline comorbidities included in the hypertension-augmented Charlson Comorbidity Index were retrospectively retrieved. Logistic regression model estimated adjusted-odds ratios (ORs) of ET prescription in relation to baseline patient and tumor characteristics. Competing risk analysis estimated 5-year cumulative incidence function (CIF) of ET discontinuation due to side effects (with BC progression or death as competing events), and its effect on locoregional recurrence (LRR) and distant metastasis (DM) (with death as competing event).

RESULTS

ET has been prescribed in 89% patients. In multivariable analysis, the odds of ET prescription was significantly reduced in older patients (≥ 80 years, OR 0.08, 95% CI 0.03-0.20) and significantly increased in patients with moderate comorbidity. Patients ≥ 80 years discontinued the prescribed therapy earlier and more frequently than younger (65-69 years) patients (p = 0.060). Five-year CIF of LLR, DM and death from causes other that BC were 1.7%, 2.2% and 7.5%, respectively. Patients who discontinued ET had higher chance of LRR (p = 0.004). ET use did not impact on OS in any of the analyzed groups.

CONCLUSIONS

In older patients, ET did not show a benefit in terms of overall survival. Further studies focusing on tailored treatment approaches are warranted to offer the best care in terms of adjuvant treatment to these patients.

Automated volumetric radiomic analysis of breast cancer vascularization improves survival prediction in primary breast cancer

To investigate whether automated volumetric radiomic analysis of breast cancer vascularization (VAV) can improve survival prediction in primary breast cancer. 314 consecutive patients with primary invasive breast cancer received standard clinical MRI before the initiation of treatment according to international recommendations. Diagnostic work-up, treatment, and follow-up was done at one tertiary care, academic breast-center (outcome: disease specific survival/DSS vs. disease specific death/DSD). The Nottingham Prognostic Index (NPI) was used as the reference method with which to predict survival of breast cancer. Based on the MRI scans, VAV was accomplished by commercially available, FDA-cleared software. DSD served as endpoint. Integration of VAV into the NPI gave NPI_VAV. Prediction of DSD by NPI_VAV compared to standard NPI alone was investigated (Cox regression, likelihood-test, predictive accuracy: Harrell's C, Kaplan Meier statistics and corresponding hazard ratios/HR, confidence intervals/CI). DSD occurred in 35 and DSS in 279 patients. Prognostication of the survival outcome by NPI (Harrell's C = 75.3%) was enhanced by VAV (NPI_VAV: Harrell's C = 81.0%). Most of all, the NPI_VAV identified patients with unfavourable outcome more reliably than NPI alone (hazard ratio/HR = 4.5; confidence interval/CI = 2.14-9.58; P = 0.0001). Automated volumetric radiomic analysis of breast cancer vascularization improved survival prediction in primary breast cancer. Most of all, it optimized the identification of patients at higher risk of an unfavorable outcome. Future studies should integrate MRI as a "gate keeper" in the management of breast cancer patients. Such a "gate keeper" could assist in selecting patients benefitting from more advanced diagnostic procedures (genetic profiling etc.) in order to decide whether are a more aggressive therapy (chemotherapy) is warranted.

Omission of postoperative radiation after breast conserving surgery: A progressive paradigm shift towards precision medicine

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Post-operative radiotherapy is standard after breast conservation in early breast cancer.

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To de-escalate the treatment burden, indentifying a subset at very low risk of relapse is crucial.

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Clinical and pathological factors are important, but can be integrated with genomic signatures.

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Ongoing trials will provide evidence on patients at low risk for radiotherapy omission.

Radiation therapy is a standard therapeutic option in the post-operative setting for early breast cancer patients after breast conserving surgery, providing a substantial benefit in reducing the risk of local relapse with a consequent survival gain. Nevertheless, the reduction in the burden related to treatment is becoming crucial in modern oncology for both local and systemic therapies and investigational efforts are being put forward by radiations oncologists to identify a subset of women at very low risk to be potentially omitted from post-operative irradiation after breast conservation. Clinical factors, classical pathological parameters and new predictive scores derived from gene expression and next generation sequencing techniques are being integrated in the quest toward a reliable low-risk profile for breast cancer patients. We herein provide a comprehensive overview on the topic.

Pan-cancer analysis of RNA methyltransferases identifies FTSJ3 as a potential regulator of breast cancer progression

RNA methylation, catalysed by a set of RNA methyltransferases (RNMTs), modulates RNA structures, properties, and biological functions. RNMTs are increasingly documented to be dysregulated in various human diseases, particularly developmental disorders and cancer. However, the genomic and transcriptomic alterations of RNMTs, as well as their functional roles in human cancer, are limited. In this study, we utilized an unbiased approach to examine copy number alterations and mutation rates of 58 RNMTs in more than 10,000 clinical samples across 32 human cancer types. We also investigated these alterations and RNMT expression level as they related to clinical features such as tumour subtype, grade, and survival in a large cohort of tumour samples, focusing on breast cancer. Loss-of-function analysis was performed to examine RNMT candidates with important roles in growth and viability of breast cancer cells. We identified a subset of RNMTs, notably TRMT12, NSUN2, TARBP1, and FTSJ3, that were amplified or mutated in a subset of human cancers. Several RNMTs were significantly associated with breast cancer aggressiveness and poor prognosis. Loss-of-function analysis indicated FTSJ3, a 2'-O-Me methyltransferase, as a candidate RNMT with functional roles in promoting cancer growth and survival. A subset of RNMTs, like FTSJ3, represents promising novel targets for anticancer drug discovery. Our findings provide a framework for further study of the functional consequences of RNMT alterations in human cancer and for developing therapies that target cancer-promoting RNMTs in the future.

Retinoid X receptor gamma (RXRG) is an independent prognostic biomarker in ER-positive invasive breast cancer

BACKGROUND

Retinoid X Receptor Gamma (RXRG) is a member of the nuclear receptor superfamily and plays a role in tumour suppression. This study aims to explore the prognostic significance of RXRG in breast cancer.

METHODS

Primary breast cancer tissue microarrays (n = 923) were immuno-stained for RXRG protein and correlated with clinicopathological features, and patient outcome.

RESULTS

Nuclear RXRG expression was significantly associated with smaller tumour size (p = 0.036), lower grade (p < 0.001), lobular histology (p = 0.016), lower Nottingham Prognostic Index (p = 0.04) and longer breast cancer-specific survival (p < 0.001), and longer time to distant metastasis (p = 0.002). RXRG expression showed positive association with oestrogen receptor (ER)-related biomarkers: GATA3, FOXA1, STAT3 and MED7 (all p < 0.001) and a negative correlation with the Ki67 proliferation marker. Multivariate analysis demonstrated RXRG protein as an independent predictor of longer breast cancer-specific survival and distant metastasis-free survival. In the external validation cohorts, RXRG expression was associated with improved patients' outcome (p = 0.025). In ER-positive tumours, high expression of RXRG was associated with better patient outcome regardless of adjuvant systemic therapy. ER signalling pathway was the top predicted master regulator of RXRG protein expression (p = 0.005).

CONCLUSION

This study provides evidence for the prognostic value of RXRG in breast cancer particularly the ER-positive tumours.

A plea for taking all available clinical information into account when assessing the predictive value of omics data

Background

Omics data can be very informative in survival analysis and may improve the prognostic ability of classical models based on clinical risk factors for various diseases, for example breast cancer. Recent research has focused on integrating omics and clinical data, yet has often ignored the need for appropriate model building for clinical variables. Medical literature on classical prognostic scores, as well as biostatistical literature on appropriate model selection strategies for low dimensional (clinical) data, are often ignored in the context of omics research. The goal of this paper is to fill this methodological gap by investigating the added predictive value of gene expression data for models using varying amounts of clinical information.

Methods

We analyze two data sets from the field of survival prognosis of breast cancer patients. First, we construct several proportional hazards prediction models using varying amounts of clinical information based on established medical knowledge. These models are then used as a starting point (i.e. included as a clinical offset) for identifying informative gene expression variables using resampling procedures and penalized regression approaches (model based boosting and the LASSO). In order to assess the added predictive value of the gene signatures, measures of prediction accuracy and separation are examined on a validation data set for the clinical models and the models that combine the two sources of information.

Results

For one data set, we do not find any substantial added predictive value of the omics data when compared to clinical models. On the second data set, we identify a noticeable added predictive value, however only for scenarios where little or no clinical information is included in the modeling process. We find that including more clinical information can lead to a smaller number of selected omics predictors.

Conclusions

New research using omics data should include all available established medical knowledge in order to allow an adequate evaluation of the added predictive value of omics data. Including all relevant clinical information in the analysis might also lead to more parsimonious models. The developed procedure to assess the predictive value of the omics data can be readily applied to other scenarios.

Electronic supplementary material

The online version of this article (10.1186/s12874-019-0802-0) contains supplementary material, which is available to authorized users.

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.

The Global and Regional Survival Rate of Women With Breast Cancer: A Systematic Review and Meta-analysis

Breast cancer is the most common cancer among women in the world. The aim of this study was to measure the global and regional survival rates of women with breast cancer. We searched Medline/PubMed, Web of Science, Scopus, and Google Scholar to identify cohort studies on the survival rate of women with primary invasive breast cancer until the end of June 2017. We used random effect models to estimate the pooled 1-, 3-, 5-, and 10-year survival rates. Subgroup analysis and meta-regression models were used to investigate the potential sources of heterogeneity. One hundred twenty-six studies were included in the meta-analysis. Between-study heterogeneities in the 1-, 3-, 5-, and 10-year survival rates were significantly high (all I²s > 50%; P = .001). The global 1-, 3-, 5-, and 10-year pooled survival rates in women with breast cancer were 0.92 (95% confidence interval [CI], 0.90-0.94), 0.75 (95% CI, 0.71-0.79), 0.73 (95% CI, 0.71-0.75), and 0.61% (95% CI, 0.54-0.67), respectively. Subgroup analysis revealed that survival rates varied in different World Health Organization regions, age and stage at diagnosis, year of the studies, and degree of development of countries. Meta-regression indicated that year of the study (β = 0.07; P = .002) and development of country (β = -0.1; P = .0001) were potential sources of heterogeneity. The survival rate was improved in recent decades; however, it is lower in developing regions than developed ones.

Nottingham Prognostic Index is an Applicable Prognostic Tool in Non-Metastatic Triple-Negative Breast Cancer

Introduction:

Triple-negative breast cancer (TNBC) is characterized by a poor prognosis due to high mortality and early relapse, requiring the study of its prognostic factors. Tumor size, histological grade and lymph node status represent important parameters that are widely studied in breast cancer, and are retained as prognostic factors by several international guidelines. The Nottingham team combined these parameters into a prognostic score called the Nottingham prognostic index (NPI). In this study, we investigated the influence of NPI on outcomes in non metastatic TNBC.

Methodology:

This retrospective cohort study included all female patients with non metastatic TNBC who received treatment at the Regional Oncology Center Hassan II Oujda - Morocco, between January 2009 and December 2011. The prognostic impact of the NPI on the survival curves at 5 years was studied using multivariate Cox proportional hazards models.

Results:

The analysis of the data involved 98 patients, 39 patients (39.8%) were classed in the poor prognosis group with a NPI > 5.4. The Overall survival (OS) and Disease free survival (DFS) rates at 5 years, in this group, were 70 and 55.6 % respectively. After adjusting for clinic-pathological variables, a NPI > 5.4 was associated with mortality (HR: 2.598, 95% CI: 1.423 – 4.744, p = 0.002) and disease progression (HR: 2.512, CI to 95%: 1.496 – 4.219, p <0.001) in patients with non-metastatic TNBC.

Conclusion:

This retrospective cohort analysis showed that NPI was an independent prognostic factor for OS and DFS at 5 years in women with non metastatic TNBC. Once validated, the impact of this score on survival outcomes could be considered in the clinical management of TNBC.

Assessing the prognostic factors, survival, and recurrence incidence of triple negative breast cancer patients, a single center study in Iran

Background

Breast cancer is the second leading cause of death due to cancer in women. Triple negative breast cancer (TNBC) is a subgroup with unique behavior. There is a controversy in organ involvement in metastasis. In this study, we planned to define the prognostic factors, survival, and recurrence incidence of patients.

Materials and method

Among the 583 patients with breast mass referred to hematology and oncology clinic in Shariati hospital, Tehran, Iran from March 2005 to March 2015, fifty four patients entered the survival analysis whom we followed for two years until March 2017. Overall survival (OS) and disease-free survival (DFS) and Cumulative recurrence incidences (RI) were estimated. Univariate and multivariate Cox proportional hazards regression was performed to assess risk factors in predicting OS and DFS.

Results

Median follow up for the patients was 5.00 years. The five-year OS, DFS and RI were 86.13% (95% CI (71.42–93.59), 63.09% (95% CI (47.04–75.49) and 32.15% (95% CI (19.52–47.43) respectively. Among the factors studied OS, DFS and RI differed significantly only between patients with and without nodal involvement (P = 0.004, P = 0.003, and P = 0.02 respectively). On the other hand, based on the univariate modeling, patients with nodal involvement had a higher risk of breast cancer-specific death (HR: 17.99, P = 0.004). Furthermore, patients with nodal involvement had a higher risk of breast cancer-specific death or recurrence (HR = 5.64, P = 0.008). In Multivariate model, just the nodal involvement significantly changed the hazard for OS (HR = 23.91, P = 0.001). As the nodal involvement was the only significant risk factor at the 0.2 level of significance, we can consider the hazard ratio of lymph node positivity in DFS univariate models as adjusted hazard.

Conclusion

The only factor with significant effect on OS, DFS and RI was nodal involvement in the pathology report.

KLP-PI: a new prognostic index for luminal B HER-2-negative breast cancer

Luminal B HER-2-negative (LBHN) subtype is one of the major subtypes of breast cancer according to different features, clinical behaviors, and treatment response. The LBHN subtype shows a poor prognosis and is insensitive to endocrine therapy. Our work aim is to investigate the prognostic factor in the LBHN subgroup and, meanwhile, try to obtain an optimal prognostic index (PI) contrapose LBHN subgroup which helps to guide chemotherapy. A total of 515 female LBNH patients who underwent diagnosis and surgery at our hospitals from August 2008 to August 2018 were enrolled. Clinical-pathological information was obtained and immunohistochemistry result was available. From these cases, a 30% Ki-67 LI was employed to divide LBHN into two groups with low and high levels; high Ki-67 LI was associated with GIII tumor grade (P < 0.001), positive axillary lymph nodes (ALN) status (P = 0.018) and negative PR status (P = 0.016), and also seemed to be related to T2-T3 tumor size (P = 0.058). High Ki-67 level (HR = 3.30; P < 0.011), positive ALN (HR = 7.29; P < 0.001) and PR negative (HR = 2.63; P = 0.034) significantly associated with poor 5-year DFS in multivariate Cox's proportional hazard regression model. A novel prognosis prediction model (KLP-PI), based on Ki-67 LI, ALN and PR status, showed a better discriminatory ability compared with traditional Nottingham prognostic index targeted to LBHN breast cancer. Our study highlights that high Ki-67 LI, positive ALN and negative PR status were associated with poor outcome in LBHN patients, and composed by these prognostic factors, KLP-PI improves the prognostic assessment using the Nottingham Prognostic Index when aiming at LBHN subtype.

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.

Correlations of aldehyde dehydrogenase-1 (ALDH1) expression with traditional prognostic parameters and different molecular subtypes of breast carcinoma

Background and aim

Breast cancer, a heterogeneous disease, is the most common cause of cancer-related death in women worldwide. Despite considerable developments in treatment modalities, a subset of patients with advanced-stage breast carcinoma display poor prognosis. Breast cancer heterogeneity and risk of recurrence could be explained with the help of cancer stem cell hypothesis. Stem cells have the capacity to self-renew and differentiate into multiple cell types. Aldehyde dehydrogenase-1 (ALDH1), an enzyme responsible for the oxidation of intracellular aldehydes, contributes to normal and tumor stem cell differentiation. Invasion and metastasis in breast cancer are found to be mediated by a subpopulation of tumor cells which exhibit stem cell-like features and express ALDH1.

The aim was to document ALDH1 expression in breast carcinoma and find its association with other clinico-pathologic prognostic parameters.

Study design

This was a cross-sectional observational study.

Methods

A total of 62 patients with breast carcinoma undergoing mastectomy were included in this study. The tumors were classified into molecular subtypes by assessing immunohistochemical (IHC) expression of ER, PgR, HER2 and Ki-67 according to St. Gallen Consensus Conference 2013. ALDH1 expression was studied by IHC and correlated with clinicoathological parameters.

Statistical analysis

Statistical analysis was done using Graph Pad software (Prism 5 version) for Windows 7. A p-value <0.05 was considered statistically significant.

Results and analysis

Out of 62 tumors, 35 tumors (56.4%) showed ALDH1 positivity. ALDH1 expression was significantly associated with larger size, lymph node involvement, higher grade, higher stage and HER2+ or triple negative tumors.

Conclusion

This study suggests that ALDH1 expression is associated with poor prognostic parameters and aggressive tumor behavior. Larger population-based prospective trials on Indian patients are required to validate these results.

Cost-Effectiveness and Value of Information Analysis of Brief Interventions to Promote Physical Activity in Primary Care

BACKGROUND

Brief interventions (BIs) delivered in primary care have shown potential to increase physical activity levels and may be cost-effective, at least in the short-term, when compared with usual care. Nevertheless, there is limited evidence on their longer term costs and health benefits.

OBJECTIVES

To estimate the cost-effectiveness of BIs to promote physical activity in primary care and to guide future research priorities using value of information analysis.

METHODS

A decision model was used to compare the cost-effectiveness of three classes of BIs that have been used, or could be used, to promote physical activity in primary care: 1) pedometer interventions, 2) advice/counseling on physical activity, and (3) action planning interventions. Published risk equations and data from the available literature or routine data sources were used to inform model parameters. Uncertainty was investigated with probabilistic sensitivity analysis, and value of information analysis was conducted to estimate the value of undertaking further research.

RESULTS

In the base-case, pedometer interventions yielded the highest expected net benefit at a willingness to pay of £20,000 per quality-adjusted life-year. There was, however, a great deal of decision uncertainty: the expected value of perfect information surrounding the decision problem for the National Health Service Health Check population was estimated at £1.85 billion.

CONCLUSIONS

Our analysis suggests that the use of pedometer BIs is the most cost-effective strategy to promote physical activity in primary care, and that there is potential value in further research into the cost-effectiveness of brief (i.e., <30 minutes) and very brief (i.e., <5 minutes) pedometer interventions in this setting.

P2Y2 receptor promotes the migration and invasion of breast cancer cells via EMT-related genes Snail and E-cadherin

Adenosine 5'-triphosphate (ATP) is one of the most abundant biochemical constituents within the tumor microenvironment and is postulated to play critical roles in the progression of a number of types of tumors via interaction with the P2Y2 receptor. In the present study, we demonstrated that the P2Y2 receptor was highly expressed in MCF7 and Hs578T breast cancer cells. Downregulation of the P2Y2 receptor by small interfering RNA (siRNA) significantly attenuated ATP- or UTP-driven migration and invasion of the breast cancer cells as well as expression of EMT-related genes Snail and E-cadherin. Consistent with the observations in vitro, the P2Y2 receptor was found to be abundantly expressed at the invasive edge of the tumor, in infiltrating tumor cells in breast adipose tissues and/or the cancer embolus in the lymphatic sinuses compared with the tumor core areas. Furthermore, high Snail expression and weak or negative expression of E-cadherin were observed at the invasive edge of tumors. Taken together, these data indicate that the P2Y2 receptor promoted cell migration and invasion in breast cancer cells via EMT-related genes Snail and E-cadherin.

[Nomograms in routine clinical practice: Methodology, interest and limitations]

In order to help the clinician, mathematical models including several clinical and pathological variables are proposed in the literature with the aim to predict the occurrence of an event of interest. Nomograms allow individual prognosis for each patient. When they are developed, validated and correctly used, nomograms can provide important information for patients' care. But, despite the strong interest in nomograms in oncology, statistical methodologies used remain unknown from the medical community. This paper presents the major steps in the development, the validation and the clinical use of nomograms. Examples are given to illustrate these different points and the limits of this methodology. Finally, guidelines on the use of nomograms are proposed for clinicians.

Prognostic value of routine laboratory variables in prediction of breast cancer recurrence

The prognostic value of routine laboratory variables in breast cancer has been largely overlooked. Based on laboratory tests commonly performed in clinical practice, we aimed to develop a new model to predict disease free survival (DFS) after surgical removal of primary breast cancer. In a cohort of 1,596 breast cancer patients, we analyzed the associations of 33 laboratory variables with patient DFS. Based on 3 significant laboratory variables (hemoglobin, alkaline phosphatase, and international normalized ratio), together with important demographic and clinical variables, we developed a prognostic model, achieving the area under the curve of 0.79. We categorized patients into 3 risk groups according to the prognostic index developed from the final model. Compared with the patients in the low-risk group, those in the medium- and high-risk group had a significantly increased risk of recurrence with a hazard ratio (HR) of 1.75 (95% confidence interval [CI] 1.30–2.38) and 4.66 (95% CI 3.54–6.14), respectively. The results from the training set were validated in the testing set. Overall, our prognostic model incorporating readily available routine laboratory tests is powerful in identifying breast cancer patients who are at high risk of recurrence. Further study is warranted to validate its clinical application.

Do online prognostication tools represent a valid alternative to genomic profiling in the context of adjuvant treatment of early breast cancer? A systematic review of the literature

INTRODUCTION

Decision-making regarding adjuvant chemotherapy has been based on clinical and pathological features. However, such decisions are seldom consistent. Web-based predictive models have been developed using data from cancer registries to help determine the need for adjuvant therapy. More recently, with the recognition of the heterogenous nature of breast cancer, genomic assays have been developed to aid in the therapeutic decision-making.

METHODS

We have carried out a comprehensive literature review regarding online prognostication tools and genomic assays to assess whether online tools could be used as valid alternatives to genomic profiling in decision-making regarding adjuvant therapy in early breast cancer.

RESULTS AND CONCLUSIONS

Breast cancer has been recently recognized as a heterogenous disease based on variations in molecular characteristics. Online tools are valuable in guiding adjuvant treatment, especially in resource constrained countries. However, in the era of personalized therapy, molecular profiling appears to be superior in predicting clinical outcome and guiding therapy.

Identification of breast cancer recurrence risk factors based on functional pathways in tumor and normal tissues

The recurrence of breast cancer (BC) is a serious therapeutic problem, and the risk factors for recurrence urgently need to be identified. In this study, we examined the functional pathways in tumor and normal tissues to more comprehensively identify biomarkers for the risk of BC recurrence. We collected tumor and normal tissue gene expression profiles of recurrent BC patients and non-recurrent BC patients from the TCGA database.We derived an expression interval (mean ± 1.96SD) based on non-recurrent patients rather than a single value, such as a mean or median. If the expression of a gene was significantly different from its normal expression interval, it was considered a differentially expressed gene. Eight pathways that significantly distinguished recurrent and non-recurrent BC patients were obtained based on 65% accuracy, and these pathways were all associated with the immune response and sensitivity to drugs. The genes in these eight pathways were also used to analyze survival, and the significance level reached 0.003 in an independent dataset (p = 0.02 in tumor and p = 0.03 in normal tissue). Our results reveal that the integration of tumor and normal tissue functional analyses can comprehensively enhance the understanding of BC prognosis.

A Prognostic Model for Patients with Triple-Negative Breast Cancer: Importance of the Modified Nottingham Prognostic Index and Age

Purpose

Considering the distinctive biology of triple-negative breast cancer (TNBC), this study aimed to identify TNBC-specific prognostic factors and determine the prognostic value of the Nottingham Prognostic Index (NPI) and its variant indices.

Methods

A total of 233 patients with newly diagnosed stage I to III TNBC from 2003 to 2012 were reviewed. We retrospectively analyzed the patients' demographics, clinicopathologic parameters, treatment, and survival outcomes. The NPI was calculated as follows: tumor size (cm)×0.2+node status+Scarff-Bloom-Richardson (SBR) grade. The modified NPI (MNPI) was obtained by adding the modified SBR grade rather than the SBR grade.

Results

The median follow-up was 67.8 months. Five-year disease-free survival (DFS) and overall survival (OS) were 81.4% and 89.9%, respectively. Multivariate analyses showed that the MNPI was the most significant and common prognostic factor of DFS (p=0.001) and OS (p=0.019). Young age (≤35 years) was also correlated with poor DFS (p=0.006). A recursive partitioning for establishing the prognostic model for DFS was performed based on the results of multivariate analysis. Patients with a low MNPI (≤6.5) were stratified into the low-risk group (p<0.001), and patients with a high MNPI (>6.5) were subdivided into the intermediate (>35 years) and high-risk (≤35 years) groups. Age was not a prognostic factor in patients with a low MNPI, whereas in patients with a high MNPI, it was the second key factor in subdividing patients according to prognosis (p=0.023).

Conclusion

The MNPI could be used to stratify patients with stage I to III TNBC according to prognosis. It was the most important prognosticator for both DFS and OS. The prognostic significance of young age for DFS differed by MNPI.

A Comprehensive Model for Predicting Recurrence and Survival in Cases of Chinese Postoperative Invasive Breast Cancer

We investigated relationships between clinical pathologic data, molecular biomarkers and prognosis of invasive breast cancer based on a Chinese population. Immunohistochemistry (IHC) was used to assess the status of ER, PR, HER-2 and Ki-67, with fluorescence in situ hybridization (FISH) performed to further confirm HER-2 positivity with an equivocal result (IHC 2+). Subsequently, Kaplan-Meier univariate and multivariate COX regression analyses of ER, PR, HER-2, Ki-67, clinical features, therapeutic status and follow-up data were performed according to the establishment principle of the Nottingham prognostic index (NPI). From this study, age, tumor size, lymph node status, ER, HER-2, Ki-67 status were found to be associated with prognosis. Eventually, a prognostic model of (PI= (1.5×age) - size + (0.1×lymph node status) - (0.5×ER) + (2×HER-2) - (0.2×Ki-67)) was established with 288 randomly selected patients and verified with another 100 cases with invasive breast cancer. Pearson correlation analysis demonstrated a significant positive correlation index of 0.376 (P=0.012<0.05) between the prognostic index (PI) and actual prognosis. Remarkably, the consistency with the model predicted recurrence was 93% in the validation set. Therefore, it appears feasible to predict the prognosis of individuals with invasive breast cancer and to determine optimal therapeutic strategy with this model.

Association between age and access to immediate breast reconstruction in women undergoing mastectomy for breast cancer

BACKGROUND

National guidelines state that patients with breast cancer undergoing mastectomy in England should be offered immediate breast reconstruction (IR), unless precluded by their fitness for surgery or the need for adjuvant therapies.

METHODS

A national study investigated factors that influenced clinicians' decision to offer IR, and collected data on case mix, operative procedures and reconstructive decision-making among women with breast cancer having a mastectomy with or without IR in the English National Health Service between 1 January 2008 and 31 March 2009. Multivariable logistic regression was used to examine the relationship between whether or not women were offered IR and their characteristics (tumour burden, functional status, planned radiotherapy, planned chemotherapy, perioperative fitness, obesity, smoking status and age).

RESULTS

Of 13 225 women, 6458 (48·8 per cent) were offered IR. Among factors the guidelines highlighted as relevant to decision-making, the three most strongly associated with the likelihood of an offer were tumour burden, planned radiotherapy and performance status. Depending on the combination of their values, the probability of an IR offer ranged from 7·4 to 85·1 per cent. A regression model that included all available factors discriminated well between whether or not women were offered IR (c-statistic 0·773), but revealed that increasing age was associated with a fall in the probability of an IR offer beyond that expected from older patients' tumour and co-morbidity characteristics.

CONCLUSION

Clinicians are broadly following guidance on the offer of IR, except with respect to patients' age.

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.

OPTIMA prelim: a randomised feasibility study of personalised care in the treatment of women with early breast cancer

BACKGROUND

There is uncertainty about the chemotherapy sensitivity of some oestrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancers. Multiparameter assays that measure the expression of several tumour genes simultaneously have been developed to guide the use of adjuvant chemotherapy for this breast cancer subtype. The assays provide prognostic information and have been claimed to predict chemotherapy sensitivity. There is a dearth of prospective validation studies. The Optimal Personalised Treatment of early breast cancer usIng Multiparameter Analysis preliminary study (OPTIMA prelim) is the feasibility phase of a randomised controlled trial (RCT) designed to validate the use of multiparameter assay directed chemotherapy decisions in the NHS.

OBJECTIVES

OPTIMA prelim was designed to establish the acceptability to patients and clinicians of randomisation to test-driven treatment assignment compared with usual care and to select an assay for study in the main RCT.

DESIGN

Partially blinded RCT with adaptive design.

SETTING

Thirty-five UK hospitals.

PARTICIPANTS

Patients aged ≥ 40 years with surgically treated ER-positive HER2-negative primary breast cancer and with 1-9 involved axillary nodes, or, if node negative, a tumour at least 30 mm in diameter.

INTERVENTIONS

Randomisation between two treatment options. Option 1 was standard care consisting of chemotherapy followed by endocrine therapy. In option 2, an Oncotype DX(®) test (Genomic Health Inc., Redwood City, CA, USA) performed on the resected tumour was used to assign patients either to standard care [if 'recurrence score' (RS) was > 25] or to endocrine therapy alone (if RS was ≤ 25). Patients allocated chemotherapy were blind to their randomisation.

MAIN OUTCOME MEASURES

The pre-specified success criteria were recruitment of 300 patients in no longer than 2 years and, for the final 150 patients, (1) an acceptance rate of at least 40%; (2) recruitment taking no longer than 6 months; and (3) chemotherapy starting within 6 weeks of consent in at least 85% of patients.

RESULTS

Between September 2012 and 3 June 2014, 350 patients consented to join OPTIMA prelim and 313 were randomised; the final 150 patients were recruited in 6 months, of whom 92% assigned chemotherapy started treatment within 6 weeks. The acceptance rate for the 750 patients invited to participate was 47%. Twelve out of the 325 patients with data (3.7%, 95% confidence interval 1.7% to 5.8%) were deemed ineligible on central review of receptor status. Interviews with researchers and recordings of potential participant consultations made as part of the integral qualitative recruitment study provided insights into recruitment barriers and led to interventions designed to improve recruitment. Patient information was changed as the result of feedback from three patient focus groups. Additional multiparameter analysis was performed on 302 tumour samples. Although Oncotype DX, MammaPrint(®)/BluePrint(®) (Agendia Inc., Irvine, CA, USA), Prosigna(®) (NanoString Technologies Inc., Seattle, WA, USA), IHC4, IHC4 automated quantitative immunofluorescence (AQUA(®)) [NexCourse BreastTM (Genoptix Inc. Carlsbad, CA, USA)] and MammaTyper(®) (BioNTech Diagnostics GmbH, Mainz, Germany) categorised comparable numbers of tumours into low- or high-risk groups and/or equivalent molecular subtypes, there was only moderate agreement between tests at an individual tumour level (kappa ranges 0.33-0.60 and 0.39-0.55 for tests providing risks and subtypes, respectively). Health economics modelling showed the value of information to the NHS from further research into multiparameter testing is high irrespective of the test evaluated. Prosigna is currently the highest priority for further study.

CONCLUSIONS

OPTIMA prelim has achieved its aims of demonstrating that a large UK clinical trial of multiparameter assay-based selection of chemotherapy in hormone-sensitive early breast cancer is feasible. The economic analysis shows that a trial would be economically worthwhile for the NHS. Based on the outcome of the OPTIMA prelim, a large-scale RCT to evaluate the clinical effectiveness and cost-effectiveness of multiparameter assay-directed chemotherapy decisions in hormone-sensitive HER2-negative early breast would be appropriate to take place in the NHS.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN42400492.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 10. See the NIHR Journals Library website for further project information. The Government of Ontario funded research at the Ontario Institute for Cancer Research. Robert C Stein received additional support from the NIHR University College London Hospitals Biomedical Research Centre.

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.