Survival Outcomes Among Patients with Metastatic Breast Cancer: Review of 47,000 Patients

Approach to Bone Health in the Patient With Breast Cancer

Treatment for breast cancer, including endocrine therapies, can contribute to bone loss and increase the risk of osteoporosis and fractures. Management of bone health in patients with cancer is often coordinated between oncologists, endocrinologists, and primary care physicians. In this article, we discuss the approach to screening for fracture risk among patients initiating treatments for breast cancer and recommendations for lifestyle modifications to optimize bone health. We will review 3 indications for pharmacologic bone-targeted therapies: prevention of cancer treatment-induced bone loss, adjuvant therapy to reduce recurrence, and management of bone metastases.

Clinical genetics in breast cancer

As genetic testing becomes increasingly more accessible and more applicable with a broader range of clinical implications, it may also become more challenging for breast cancer providers to remain up-to-date. This review outlines some of the current clinical guidelines and recent literature surrounding germline genetic testing, as well as genomic testing, in the screening, prevention, diagnosis, and treatment of breast cancer, while identifying potential areas of further research.

Survival among patients with untreated metastatic breast cancer: "What if I do nothing?"

PURPOSE

We sought to assess survival outcomes of patients with de novo metastatic breast cancer (dnMBC) who did not receive treatment irrespective of the reason.

METHODS

Adults with dnMBC were selected from the NCDB (2010-2016) and stratified based on receipt of treatment (treated = received at least one treatment and untreated = received no treatments). Overall survival (OS) was estimated using the Kaplan-Meier method, and groups were compared. Cox proportional hazards models were used to identify factors associated with OS.

RESULTS

Of the 53,240 patients with dnMBC, 92.1% received at least one treatment (treated), and 7.9% had no documented treatments, irrespective of the reason (untreated). Untreated patients were more likely to be older (median 68 y vs 61 y, p < 0.001), have higher comorbidity scores (p < 0.001), have triple-negative disease (17.8% vs 12.6%), and a higher disease burden (≥ 2 metastatic sites: 38.2% untreated vs 29.2% treated, p < 0.001). The median unadjusted OS in the untreated subgroup was 2.5 mo versus 36.4 mo in the treated subgroup (p < 0.001). After adjustment, variables associated with a worse OS in the untreated cohort included older age, higher comorbidity scores, higher tumor grade, and triple-negative (vs HR + /HER2-) subtype (all p < 0.05), while the number of metastatic sites was not associated with survival.

CONCLUSIONS

Patients with dnMBC who do not receive treatment are more likely to be older, present with comorbid conditions, and have clinically aggressive disease. Similar to those who do receive treatment, survival in an untreated population is associated with select patient and disease characteristics. However, the prognosis for untreated dnMBC is dismal.

Expression of nuclear receptor co‑activator 7 protein is associated with poor prognosis of breast cancer

Nuclear receptor coactivator 7 (NCOA7) is an estrogen receptor binding protein. Its role in breast cancer progression has so far remained elusive. The present study aimed to determine the expression levels of NCOA7 in breast tumor samples and confirmed its potential utility as a breast cancer prognostic biomarker. The expression of NCOA7 was detected by immunohistochemical staining in 241 breast cancer tumor samples and 163 adjacent normal tissue samples. The association of NCOA7 expression with the clinicopathological characteristics and overall survival were statistically analyzed. Cell proliferation was determined by Cell Counting Kit-8 and colony-formation assays. Cell migration was detected using wound-healing and Transwell assays. NCOA7 was positively expressed in 44% of breast tumor tissues. The expression of NCOA7 was positively associated with tumor size (T-stage; P=0.005) and lymph node metastasis (N-stage; P=0.008). Additional statistical analysis indicated that the expression of NCOA7 was associated with patient age, tumor size and lymph node metastasis in patients with triple-negative breast cancer (TNBC) compared with that in patients with non-TNBC. The overall survival of patients with NCOA7-positive breast cancer was significantly lower than that of patients with NCOA7-negative breast cancer (P=0.006). Among the patients with lymph node metastasis, the overall survival was reversely associated with the expression of NCOA7 (P=0.042). Furthermore, knockdown of NCOA7 expression in breast cancer T47D and MCF7 cells significantly inhibited both cell proliferation and migration, suggesting that this protein may exert a role in driving breast cancer progression. Taken together, these results indicate that the expression of NCOA7 is associated with poor prognosis of breast cancer and suggest that this protein may be a driver for metastasis and a potential therapeutic target for advanced breast cancer.

A new paradigm for classifying and treating HER2-positive breast cancer

BACKGROUND

Because of the phenomenal success of treatment with monoclonal antibodies and antibody-drug conjugates targeting human epidermal growth factor receptor 2 (HER2), most patients with early-stage HER2-positive breast cancer (HER2+ BC) and some with limited metastatic diseases have been cured, and those who have not been cured have achieved significant improvements in overall survival, which has weakened the role of the TNM staging system in the prognosis of HER2+ BC today. Given that the disease is now highly curable, treatment conception, classification, and modalities should differ from those of cancer types with a poor prognosis. It is warranted to build a new paradigm for classifying and treating HER2+ BC.

RECENT FINDINGS

In our personal view, we suggest that the classification system should be based not only on traditional anatomy and cancer biology but also on available treatment regimens, their exceptional outcomes, and their toxicities. In this regard, we developed a new concise classification of HER2+ BC based on the TNM staging system, a review of the literature, research results, and our clinical experience, dividing the patients into four distinct groups: curable (lymph-node negative and small (≤3 cm) early breast cancer), do our best to cure (locally advanced or tumors >3 cm early breast cancer), hope for cure (local-regional recurrent, limited metastases, and exceptional responders), and incurable (metastatic breast cancer with poor performance status or non-exceptional responders).

CONCLUSION

It will assist clinicians in developing an optimal treatment regimen at the outset, curing more HER2+ BC patients and improving their quality of life.

Novel Prognostic Staging System for Patients With De Novo Metastatic Breast Cancer

PURPOSE

Given the heterogeneity and improvement in outcomes for metastatic breast cancer (MBC), we developed a staging system that refines prognostic estimates for patients with metastatic cancer at the time of initial diagnosis, de novo MBC (dnMBC), on the basis of survival outcomes and disease-related variables.

METHODS

Patients with dnMBC (2010-2016) were selected from the National Cancer Database (NCDB). Recursive partitioning analysis (RPA) was used to group patients with similar overall survival (OS) on the basis of clinical T category, grade, estrogen receptor (ER), progesterone receptor, human epidermal growth factor receptor 2, histology, organ system site of metastases (bone-only, brain-only, visceral), and number of organ systems involved. Three-year OS rates were used to assign a final stage: IVA: >70%, IVB: 50%-70%, IVC: 25 to <50%, and IVD: <25%. Bootstrapping was applied with 1,000 iterations, and final stage assignments were made based on the most commonly occurring assignment. Unadjusted OS was estimated. Validation analyses were conducted using SEER and NCDB.

RESULTS

At a median follow-up of 52.9 months, the median OS of the original cohort (N = 42,467) was 35.4 months (95% CI, 34.8 to 35.9). RPA stratified patients into 53 groups with 3-year OS rates ranging from 73.5% to 5.7%; these groups were amalgamated into four stage groups: 3-year OS, A = 73.2%, B = 61.9%, C = 40.1%, and D = 17% (log-rank P < .001). After bootstrapping, the survival outcomes for the four stages remained significantly different (log-rank P < .001). This staging system was then validated using SEER data (N = 20,469) and a separate cohort from the NCDB (N = 7,645) (both log-rank P < .001).

CONCLUSION

Our findings regarding the heterogeneity in outcomes for patients with dnMBC could guide future revisions of the current American Joint Committee on Cancer staging guidelines for patients with newly diagnosed stage IV disease. Our findings should be independently confirmed.

HR+/HER2- de novo metastatic breast cancer: a true peculiar entity?

De novo metastatic breast cancer (dnMBC) accounts for ~6-10% of all breast cancers and for ~30% of MBC with increasing incidence over time. Hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR⁺/HER2^-) tumours are the most frequent subtype with a similar incidence to that observed amongst recurrent MBC (rMBC). Higher frequency of PI3KCA and ARID2 mutations and a lower frequency of ESR1 mutations and of genes involved in DNA damage, as compared with rMBC, have been reported in HR⁺/HER2^- dnMBC; however, these are not correlating with prognosis, whilst tumour mutational burden is inversely correlated with outcome. Bone represents the most frequent metastatic site, being the single site in up to 60% of patients with dnMBC. HR⁺/HER2^- dnMBC has been generally reported to have better outcomes than rMBC, with a median overall survival ranging from 26 months to nearly 5 years in patients with favourable features such as age <40 years and bone-only disease, but not when compared with patients with late recurring disease (≥2-5 years). Analyses of the de novo cohorts within randomized clinical trials and large real-world series report a better outcome after treatment with CDK4/6 inhibitors and endocrine agents as compared to rMBC. Despite the limitations of retrospective studies and controversial results of the randomized trials, locoregional treatment of the primary tumour after response to systemic therapy appears to confer a survival benefit, particularly in patients with favourable prognostic factors. Altogether genomic, biological and clinical findings highlight HR⁺/HER2^- dnMBC as a peculiar entity as compared with rMBC and deserve a dedicated treatment algorithm. This article is part of the Tackling clinical complexity in breast cancer Special Issue: https://www.drugsincontext.com/special_issues/tackling-clinical-complexity-in-breast-cancer/.

Design and Evaluation of a Computational Phenotype to Identify Patients With Metastatic Breast Cancer Within the Electronic Health Record

PURPOSE

Outcomes for patients with metastatic breast cancer (MBC) are continually improving as more effective treatments become available. Granular data sets of this unique population are lacking, and the standard method for data collection relies largely on chart review. Therefore, using electronic health records (EHR) collected at a tertiary hospital system, we developed and evaluated a computational phenotype designed to identify all patients with MBC, and we compared the effectiveness of this algorithm against the gold standard, clinical chart review.

METHODS

A cohort of patients with breast cancer were identified according to International Classification of Diseases codes, the institutional tumor registry, and SNOMED codes. Chart review was performed to determine whether distant metastases had occurred. We developed a computational phenotype, on the basis of SNOMED concept IDs, which was applied to the EHR to identify patients with MBC. Contingency tables were used to aggregate and compare results.

RESULTS

A total of 1,741 patients with breast cancer were identified using data from International Classification of Diseases codes, the tumor registry, and/or SNOMED concept identifiers. Chart review of all patients classified each patient as having MBC (n = 416; 23.9%) versus not (n = 1,325; 75.9%). The final computational phenotype successfully classified 1,646 patients (95% accuracy; 82% sensitivity; 99% specificity).

CONCLUSION

Hospital systems with robust EHRs and reliable mapping to SNOMED have the ability to use standard codes to derive computational phenotypes. These algorithms perform reasonably well and have the added ability to be run at disparate health care facilities. Better tooling to navigate the polyhierarchical structure of SNOMED ontology could yield better-performing computational phenotypes.