Prediction of outcome of patients with metastatic breast cancer: evaluation with prognostic factors and Nottingham prognostic index

Clinicopathological characteristics and prognostic risk factors of breast cancer patients with bone metastasis

Background

A retrospective study was performed to summarize the clinicopathological characteristics of breast cancer patients with bone metastasis, to clarify the metastasis sites, and to explore the risk factors affecting prognosis.

Methods

Breast cancer patients with bone metastasis diagnosed in our hospital from January 2008 to January 2019 were included. Through follow-up by telephone call or return visit, the metastasis sites and clinicopathological characteristics were summarized. The risk factors influencing prognosis were analyzed by univariate and multivariate regression analyses.

Results

Multifocal bone metastases were dominant in the 150 patients, and the metastatic rates in the spine, chest, pelvis, limbs, and skull were 75.3%, 74.0%, 56.0%, 46.7%, and 28.7%, respectively, with significant differences (P<0.01). Kaplan-Meier univariate analysis showed that age, menstrual status, number of metastatic lymph nodes, clinical stage, endocrine therapy, alkaline phosphatase level, visceral metastasis, and number of bone metastasis sites affected the overall survival. Cox multivariate regression analysis revealed that endocrine therapy, number of metastatic lymph nodes, visceral metastasis, number of bone metastasis sites, and c-erbB-2 expression were independent prognostic factors.

Conclusions

Middle-aged and elderly patients with breast cancer, mainly aged 40–60 years old, are prone to bone metastasis. The incidence rate of bone metastasis is high within 3 years after surgery, involving the spine, chest, pelvis, limbs, and skull in descending order. The number of metastatic lymph nodes, endocrine therapy, visceral metastasis, number of bone metastasis lesions at the first onset, and c-erbB-2 expression are independent prognostic factors influencing the survival rate of breast cancer patients with bone metastasis.

Real-world clinical profile, treatment patterns and patient-reported outcomes in a subset of HR+/HER2- advanced breast cancer patients with poor prognostic factors: data from an international study

Background

Patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2−) advanced breast cancer (ABC) and disease-related poor prognostic factors are not well characterized. We aimed to describe patient demographics, disease characteristics, treatment patterns and patient-reported outcomes in a subset of HR+/HER2− ABC patients with these factors [at the time when cyclin-dependent kinase (CDK) 4 and 6 inhibitors were being introduced] and understand how these factors informed treatment decisions at the time of the survey.

Methods

Real-world data were derived from a large, multinational, point-in-time survey of oncologists and their consulting patients with HR+/HER2− ABC in the EU5 and USA over March-June 2017, at the start of the changing treatment landscape. Analysis focused on four poor prognostic factors: visceral metastases, liver metastases (subset of visceral metastases), progesterone receptor-negative status and high tumor grade.

Results

In total, 2259 patients with HR+/HER2− ABC had records eligible for this analysis. At least one poor prognostic factor was present in 63% of patients (most common visceral metastases; least common progesterone receptor-negative status), with varying degrees of overlap between factors. For physician-reported outcomes, pain increased, whereas performance status and activities of daily living declined with presence of poor prognostic factors, especially liver metastases. No clear trends were observed for patient-reported outcomes. Treatment with combined endocrine therapy plus CDK4 and 6 inhibitors was infrequent, as these agents were entering the market.

Conclusions

More than 60% of the HR+/HER2− ABC Adelphi Real World Disease Specific Programme™ sample had ≥1 disease-related poor prognostic factor, and patients appeared to be heterogeneous regarding occurrence and distribution of these factors. These patients typically have increased pain and reduced performance status, highlighting the importance of implementing effective therapy with CDK4 and 6 inhibitors. Future studies could inform how the treatment landscape has evolved over time with respect to patients with poor prognostic factors.

•

Some 63% of HR+/HER2− ABC patients in this sample had ≥1 disease-related factors more likely to confer a poorer prognosis

•

Patients with these factors typically had increased pain and reduced performance status

•

Chemotherapy was prescribed more frequently in patients with poor prognostic factors

•

Introduction of CDK4 and 6 inhibitors saw more patients with poor prognostic factors receive endocrine therapy-based regimens

•

This study is a baseline to understand the impact of these new treatments on prognosis and aggressive disease

Prognostic Model for De Novo and Recurrent Metastatic Breast Cancer

PURPOSE

Metastatic breast cancer (MBC) has a heterogeneous clinical course. We sought to develop a prognostic model for overall survival (OS) that incorporated contemporary tumor and clinical factors for estimating individual prognosis.

METHODS

We identified patients with MBC from our institution diagnosed between 1998 and 2017. We developed OS prognostic models by Cox regression using demographic, tumor, and treatment variables. We assessed model predictive accuracy and estimated annual OS probabilities. We evaluated model discrimination and prediction calibration using an external validation data set from the National Comprehensive Cancer Network.

RESULTS

We identified 10,655 patients. A model using age at diagnosis, race or ethnicity, hormone receptor and human epidermal growth factor receptor 2 subtype, de novo versus recurrent MBC categorized by metastasis-free interval, Karnofsky performance status, organ involvement, frontline biotherapy, frontline hormone therapy, and the interaction between variables significantly improved predictive accuracy (C-index, 0.731; 95% CI, 0.724 to 0.739) compared with a model with only hormone receptor and human epidermal growth factor receptor 2 status (C-index, 0.617; 95% CI, 0.609 to 0.626). The extended Cox regression model consisting of six independent models, for < 3, 3-14, 14-20, 20-33, 33-61, and ≥ 61 months, estimated up to 5 years of annual OS probabilities. The selected multifactor model had good discriminative ability but suboptimal calibration in the group of 2,334 National Comprehensive Cancer Network patients. A recalibration model that replaced the baseline survival function with the average of those from the training and validation data improved predictions across both data sets.

CONCLUSION

We have generated and validated a robust prognostic OS model for MBC. This model can be used in clinical decision making and stratification in clinical trials.

Prognosis and Genomic Landscape of Liver Metastasis in Patients With Breast Cancer

Objective

The prognosis of breast cancer liver metastasis (BCLM) is poor, and its molecular mechanism is unclear. We aimed to determine the factors that affect the prognosis of patients with BCLM and investigate the genomic landscape of liver metastasis (LM).

Methods

We described the prognosis of patients with BCLM and focused on prognosis prediction for these patients based on clinicopathological factors. Nomogram models were constructed for progression-free survival (PFS) and overall survival (OS) by using a cohort of 231 patients with BCLM who underwent treatment at Shandong Cancer Hospital and Institute (SCHI). We explored the molecular mechanism of LM and constructed driver genes, mutation signatures by using a targeted sequencing dataset of 217 samples of LM and 479 unpaired samples of primary breast cancer (pBC) from Memorial Sloan Kettering Cancer Center (MSKCC).

Results

The median follow-up time for 231 patients with BCLM in the SCHI cohort was 46 months. The cumulative incidence of LM at 1, 2, and 5 years was 17.5%, 45.0%, and 86.8%, respectively. The median PFS and OS were 7 months (95% CI, 6-8) and 22 months (95% CI, 19-25), respectively. The independent factors that increased the progression risk of patients with LM were Karnofsky performance status (KPS) ≤ 80, TNBC subtype, grade III, increasing trend of CA153, and disease-free interval (DFS) ≤ 1 year. Simultaneously, the independent factors that increased the mortality risk of patients with LM were Ki-67 ≥ 30%, grade III, increasing trend of CA153, pain with initial LM, diabetes, and DFI ≤ 1 year. In the MSKCC dataset, the LM driver genes were ESR1, AKT1, ERBB2, and FGFR4, and LM matched three prominent mutation signatures: APOBEC cytidine deaminase, ultraviolet exposure, and defective DNA mismatch repair.

Conclusion

This study systematically describes the survival prognosis and characteristics of LM from the clinicopathological factors to the genetic level. These results not only enable clinicians to assess the risk of disease progression in patients with BCLM to optimize treatment options, but also help us better understand the underlying mechanisms of tumor metastasis and evolution and provide new therapeutic targets with potential benefits for drug-resistant patients.

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.

Geriatric assessment and biomarkers in patients with metastatic breast cancer receiving first-line mono-chemotherapy: Results from the randomized phase III PELICAN trial

OBJECTIVES

To determine predictive/prognostic factors for patients with metastatic breast cancer (MBC) receiving first-line monochemotherapy using biomarker analysis and geriatric assessment (GA).

MATERIALS AND METHODS

Karnofsky Performance Status (KPS) and GA as clinical parameters, and prognostic inflammatory and nutritional index (PINI), and Glasgow prognostic score (GPS) as biomarkers were analyzed for association with clinical outcome within the randomized phase III PEg-LIposomal Doxorubicin vs. CApecitabin iN MBC (PELICAN) trial of first-line pegylated liposomal doxorubicin (PLD) or capecitabine.

RESULTS

Of 210 patients, 38% were >65years old. GA (n=152) classified 74% as fit, 10% as compromised, and 16% as frail. Biomarkers showed no age dependency. In multivariate analysis (n=70) KPS, GA, cumulative illness rating scale-geriatrics (CIRS-G), and GPS were significantly associated with time to progression, and KPS, CIRS-G, and instrumental activities of daily living (IADL) from GA, and PINI showed a significant correlation with overall survival.

CONCLUSION

GA evaluation was feasible. KPS significantly correlated with efficacy outcomes. Items of a GA and biomarkers of inflammation and nutrition may have prognostic significance in patients with MBC.

Features of aggressive breast cancer

BACKGROUND

Aggressive breast cancer is a term commonly used in literature to describe breast cancer with a poor prognosis. Identifying and understanding the factors associated with aggressiveness could be helpful to the management of patients with breast cancer. Breast cancer is a heterogeneous disease, both clinically and biologically, which may be responsible for the wide range of survival durations for patients with metastatic disease.

AIM

The goal of this study was to identify the factors most often described in association with aggressive metastatic breast cancer (MBC).

METHODS

A systematic review was performed by querying PubMed from January 1, 2012 to June 1, 2014 for "metastatic breast cancer" ("aggressive" or "poor prognosis" or "high risk"). The level of evidence to support each potential prognostic factor of aggressive MBC was also reviewed.

RESULTS

The identified factors were grouped into 3 principle categories: clinical, biological, and patient related. Because patient-related factors may not be indicative of inherent cancer aggressiveness, this review focused only on clinical and biological factors. The factors with the highest levels of evidence to support associations with survival in metastatic breast cancer were visceral metastases, number of metastatic sites, disease-free interval, presence of CTCs, triple-negative disease, and tumour grade.

CONCLUSION

Identification of these factors and understanding their contribution to the aggressiveness of MBC and disease progression may lead to more personalized treatment in this patient population.

Phenethyl isothiocyanate upregulates death receptors 4 and 5 and inhibits proliferation in human cancer stem-like cells

Background

The cytokine TRAIL (tumor necrotic factor-related apoptosis-inducing ligand) selectively induces apoptosis in cancer cells, but cancer stem cells (CSCs) that contribute to cancer-recurrence are frequently TRAIL-resistant. Here we examined hitherto unknown effects of the dietary anti-carcinogenic compound phenethyl isothiocyanate (PEITC) on attenuation of proliferation and tumorigenicity and on up regulation of death receptors and apoptosis in human cervical CSC.

Methods

Cancer stem-like cells were enriched from human cervical HeLa cell line by sphere-culture method and were characterized by CSC-specific markers’ analyses (flow cytometry) and Hoechst staining. Cell proliferation assays, immunoblotting, and flow cytometry were used to assess anti-proliferative as well as pro-apoptotic effects of PEITC exposure in HeLa CSCs (hCSCs). Xenotransplantation study in a non-obese diabetic, severe combined immunodeficient (NOD/SCID) mouse model, histopathology, and ELISA techniques were further utilized to validate our results in vivo.

Results

PEITC attenuated proliferation of CD44^high/+/CD24^low/–, stem-like, sphere-forming subpopulations of hCSCs in a concentration- and time-dependent manner that was comparable to the CSC antagonist salinomycin. PEITC exposure-associated up-regulation of cPARP (apoptosis-associated cleaved poly [ADP-ribose] polymerase) levels and induction of DR4 and DR5 (death receptor 4 and 5) of TRAIL signaling were observed. Xenotransplantation of hCSCs into mice resulted in greater tumorigenicity than HeLa cells, which was diminished along with serum hVEGF-A (human vascular endothelial growth factor A) levels in the PEITC-pretreated hCSC group. Lung metastasis was observed only in the hCSC-injected group that did not receive PEITC-pretreatment.

Conclusions

The anti-proliferative effects of PEITC in hCSCs may at least partially result from up regulation of DR4 and possibly DR5 of TRAIL-mediated apoptotic pathways. PEITC may offer a novel approach for improving therapeutic outcomes in cancer patients.

Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study

Background

In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia.

Materials and Methods

We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic).

Results

We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48–0.53) to 0.63 (95% CI, 0.60–0.66).

Conclusion

The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.

Time-dependent risk of developing distant metastasis in breast cancer patients according to treatment, age and tumour characteristics

BACKGROUND

Metastatic breast cancer is a severe condition without curative treatment. How relative and absolute risk of distant metastasis varies over time since diagnosis, as a function of treatment, age and tumour characteristics, has not been studied in detail.

METHODS

A total of 9514 women under the age of 75 when diagnosed with breast cancer in Stockholm and Gotland regions during 1990-2006 were followed up for metastasis (mean follow-up=5.7 years). Time-dependent development of distant metastasis was analysed using flexible parametric survival models and presented as hazard ratio (HR) and cumulative risk.

RESULTS

A total of 995 (10.4%) patients developed distant metastasis; the most common sites were skeleton (32.5%) and multiple sites (28.3%). Women younger than 50 years at diagnosis, with lymph node-positive, oestrogen receptor (ER)-negative, >20 mm tumours and treated only locally, had the highest risk of distant metastasis (0-5 years' cumulative risk =0.55; 95% confidence interval (CI): 0.47-0.64). Women older than 50 years at diagnosis, with ER-positive, lymph node-negative and ≤20-mm tumours, had the same and lowest cumulative risk of developing metastasis 0-5 and 5-10 years (cumulative risk=0.03; 95% CI: 0.02-0.04). In the period of 5-10 years after diagnosis, women with ER-positive, lymph node-positive and >20-mm tumours were at highest risk of distant recurrence. Women with ER-negative tumours showed a decline in risk during this period.

CONCLUSION

Our data show no support for discontinuation at 5 years of clinical follow-up in breast cancer patients and suggest further investigation on differential clinical follow-up for different subgroups of patients.

The prognostic analysis of clinical breast cancer subtypes among patients with liver metastases from breast cancer

BACKGROUND

To determine whether the inferior outcome noted with triple-negative breast cancer (TNBC) reflects a higher risk population among patients with breast cancer liver metastases.

METHODS

A total of 123 patients with breast cancer liver metastases diagnosed at Tianjin Medical University Cancer Hospital were included in this study. Breast cancer subtype was assigned using immunohistochemistry or fluorescence in situ hybridization: hormone receptor (HR) positive (+)/human epidermal growth factor receptor 2 (HER2) negative (-), HR+/HER2+, HR-/HER2+ and triple-negative subtype. Clinical features and survival were evaluated in different subtypes.

RESULTS

The median age at breast cancer diagnosis was 47 years (range, 23-67 years). Breast cancer subtype was confirmed in all patients (39.8% with HR+/HER2-, 24.4% with HR+/HER2+, 15.3% with HR-/HER2+ and 20.3% with TNBC). The median overall survival after liver metastases was 29 months (range, 4-89 months), and the overall 1-, 2- and 3-year survival rate was 68.3, 48.0 and 34.1%, respectively. Survival was found to be impacted by breast cancer subtype (P = 0.001), and was shortest for patients with TNBC. Time to liver metastases (TTLM) less than 24 months and liver metastasis lesions ≥3 were found to be important predictors of poor survival after liver metastases (P = 0.009 and 0.001, respectively).

CONCLUSIONS

The results indicate that clinical breast cancer subtype remains an independent prognostic predictor among patients with breast cancer liver metastases. Liver metastases arising from TNBC confers the worst prognosis, and novel agents capable of controlling intrahepatic and extrahepatic TNBC are needed.