Prognostic value of intrinsic subtypes in hormone-receptor-positive metastatic breast cancer: systematic review and meta-analysis

Neoadjuvant therapy in hormone Receptor-Positive/HER2-Negative breast cancer

Neoadjuvant therapy is commonly used in patients with locally advanced or inoperable breast cancer (BC). Neoadjuvant chemotherapy (NACT) represents an established treatment modality able to downstage tumours, facilitate breast-conserving surgery, yet also achieve considerable pathologic complete response (pCR) rates in HER2-positive and triple-negative BC. For patients with HR+/HER2- BC, the choice between NACT and neoadjuvant endocrine therapy (NET) is still based on clinical and pathological features and not guided by biomarkers of defined clinical utility, differently from the adjuvant setting where gene-expression signatures have been widely adopted to drive decision-making. In this review, we summarize the evidence supporting the choice of NACT vs NET in HR+/HER2- BC, discussing the issues surrounding clinical trial design and proper selection of patients for every treatment. It is time to question the binary paradigm of responder vs non-responders as well as the "one size fits all" approach in luminal BC, supporting the utilization of continuous endpoints and the adoption of tissue and plasma-based biomarkers at multiple timepoints. This will eventually unleash the full potential of neoadjuvant therapy which is to modulate patient treatment based on treatment sensitivity and surgical outcomes. We also reviewed the current landscape of neoadjuvant studies for HR+/HER2- BC, focusing on antibody-drug conjugates (ADCs) and immunotherapy combinations. Finally, we proposed a roadmap for future neoadjuvant approaches in HR+/HER2- BC, which should be based on a staggered biomarker-driven treatment selection aiming at impacting long-term relevant endpoints.

Survival nomogram for patients with de novo metastatic breast cancer based on the SEER database and an external validation cohort

Background

On average, 5-10% of patients are diagnosed with metastatic breast cancer (MBC) at the initial diagnosis. This study aimed to develop a nomogram to predict the overall survival (OS) in these patients.

Methods

The nomogram was based on a retrospective study of 9435 patients with de novo MBC from the Surveillance, Epidemiology, and End Results (SEER) database. The predictive accuracy and discriminative ability of the nomogram were determined using the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), and calibration curve. Decision curve analysis (DCA) was employed to evaluate the benefits and advantages of our new predicting model over the 8th edition of the American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) staging system. The results were validated in a retrospective study of 103 patients with de novo MBC from January 2013 to June 2022 at an institution in northwest China.

Results

Multivariate analysis of the primary cohort revealed that independent factors for survival were age at diagnosis, pathological type, histological grade, T stage, N stage, molecular subtype, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery, chemotherapy, and radiotherapy. The nomogram achieved a C-index of 0.688 (95% confidence interval [CI], 0.682-0.694) in the training cohort and 0.875 (95% CI, 0.816-0.934) in the validation cohort. The AUC of the nomograms indicated good specificity and sensitivity in the training and validation cohorts, respectively. Calibration curves showed favorable consistency between the predicted and actual survival probabilities. Additionally, the DCA curve produced higher net gains than by the AJCC-TNM staging system. Finally, risk stratification can accurately identify groups of patients with de novo MBC at different risk levels.

Conclusions

The nomogram showed favorable predictive and discriminative abilities for OS in patients with de novo MBC. Other populations from different countries or prospective studies are needed to further validate the nomogram.