Prognosis of Patients With Triple-negative Breast Cancer: A Population-based Study From SEER Database

A nomogram for predicting overall survival in young triple-negative breast cancer patients: a population-based study

BACKGROUND

Young triple negative breast cancer (YTNBC) patients often face poor survival outcomes. Given the high-risk nature of YTNBC, there is an urgent need for tools that can accurately predict patient outcomes and guide personalized treatment strategies. Prognostic models, particularly those in the form of nomograms, have gained popularity in oncology for their ability to integrate multiple clinical variables to estimate individual patient survival. Our study aimed to investigate independent prognostic factors in YTNBC patients and develop a nomogram to predict OS, thereby helping patients choose a better therapeutic approach.

METHODS

Patients diagnosed with YTNBC between January 2010 and December 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into training and validation cohorts at a ratio of 7:3. Univariate and multivariate Cox analyses were conducted to identify significant factors associated with prognosis, which were then used to construct a nomogram for predicting 1-, 3-, and 5-year OS.

RESULTS

Nine survival predictors (marital status, tumor grade, AJCC stage, T stage, N stage, M stage, surgery, bone metastases, brain metastases) were selected for nomogram construction. The concordance indexes (C-index), in the training and validation cohorts were 0.749 and 0.745, respectively. The nomogram model demonstrated good calibration, and time-dependent receiver operating characteristic (ROC) curves confirmed its superiority for clinical utility. Additionally, Kaplan-Meier survival curves of various independent prognostic factors validated the model.

CONCLUSIONS

The novel nomogram serves as a reliable tool for predicting survival, aiding clinicians in identifying high-risk patients and devising individualized treatments.

Patterns of presentation, treatment, and survival among older adults with metastatic breast cancer: Results from a large prospective registry

INTRODUCTION

Older adults with breast cancer experience worse survival than their younger counterparts. However, data are limited on the patterns of presentation, treatment, and outcomes for older patients with metastatic breast cancer (MBC) outside of registry studies and selected clinical trial populations.

MATERIALS AND METHODS

We identified patients aged ≥60 years from a single, NCI-designated cancer center with MBC diagnosed between 1999 and 2022. Using Chi-square testing, we compared clinicopathologic characteristics by age. We also examined treatment patterns and reasons for treatment discontinuation; overall survival (OS) was examined by subtype and age using Kaplan-Meier methods.

RESULTS

The final analytic cohort included 1115 patients with a median follow-up of 2.9 years (1.0-18.5); median age at metastatic diagnosis was 66.3 (60.0-95.4). Disease subtypes included: 70.7 % hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-), 11.9 % any HR/HER2+, 17.4 % triple negative (TN). In those with HR+/HER2- disease receiving first-line (1 L) therapy (n = 783), 1 L endocrine-based therapy was frequent (79.3 % for ages 60-65, 94.7 % for >80), and administration of 1 L chemotherapy varied by age (21.0 % in ages 60-65, 5.3 % in >80). Among those with TN and HER2+ disease, ≥84 % received a 1 L chemotherapy or trastuzumab-containing regimen. Across subtypes, most patients (80.5 %) discontinued 1 L therapy for progression, not toxicity. Among patients ages 60-65, 16.5 % stopped treatment after 1 L therapy; 42.2 % of those >age 80 received treatment after 1 L. Clinical trial enrollment declined with age (40 % in 60-65 vs. 13 % for >80; p = 0.0004), as did median OS (4.4 years in ages 60-65 vs. 2.7 years for >80; p < 0.005). For ages 60-65, 37.8 %, 17.1 %, and 40.3 % with HR + HER2-, TN, and HER2+ disease, respectively, were alive at two years. For ages >80, 23.7 %, 0 %, and 33.3 % with HR + HER2-, TN, and HER2+ disease, respectively, were alive at two years.

DISCUSSION

In a unique, large prospective cohort of older adults with MBC, the number of treatment lines decreased with increasing age, and OS outcomes were poor, particularly for those >80 years where most patients were not alive at two years after MBC diagnosis. Therapeutic approaches, with improved supportive care, are urgently needed to optimize outcomes in the oldest patients with MBC.

Saikosaponin A induces cellular senescence in triple-negative breast cancer by inhibiting the PI3K/Akt signalling pathway

Background

Breast cancer has now become the most prevalent cancer worldwide. Existing therapeutic agents are generally accompanied by significant side effects. Here, we highlight Saikosaponin A (SSA), a promising natural metabolite characterized by low toxicity, demonstrating significant efficacy against breast cancer through the induction of cellular senescence.

Methods

The antitumor property of SSA was determined via MTT colorimetric assay, 5-ethynyl-2'-deoxyuridine (EdU) incorporation assay, colony formation, and propidium iodide (PI) staining in vitro, as well as xenograft in vivo model. A network approach was used to predict potential targets of SSA reevant for a potential anti-tumor effect and verified through senescence-associated β-galactosidase (SA-β-gal), flow-cytometry analysis, RT-PCR, Western blotting, and immuno-histochemistry assay.

Results

SSA significantly suppressed proliferation and triggered cell cycle arrest of SUM159PT and MDA-MB-231 cells. Revealed by network analysis, cellular senescence, and phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathway were implemented in the anti-tumor effects of SSA. SSA-stimulated senescence was associated with increased ROS production, distinct senescence-associated secretory phenotype (SASP), and restricted PI3K/Akt signaling, as well as p21 and p53 accumulation. Furthermore, SSA displayed inhibitory effects on tumor growth with minimal toxicity in animal studies, accompanied by activated biomarkers of cellular senescence and decreased expression of p-Akt and p-PI3K.

Conclusion

Taken together, based on the preliminary results of network analysis and further experimental validation, this study revealed that SSA significantly induced cell cycle arrest and senescence, and the inhibition of ROS-mediated PI3K/Akt pathway may be the potential mechanism in this process.

Clinical characteristics, prognosis, and prognostic factors of patients with second primary triple-negative breast cancer: a study based on Surveillance, Epidemiology, and End Results database

This study examined the characteristics of tumors, treatments, and survival outcomes, with a particular focus on the survival-related factors of second primary triple-negative breast cancer (TNBC) in comparison to first primary TNBC. The Surveillance, Epidemiology, and End Results database was utilized to identify and enroll patients diagnosed with TNBC between the years 2010 and 2015. The outcomes of this study were 3-year and 5-year breast cancer-specific survival (BCSS). The multivariate competing risk model was conducted to explore the association between the second primary cancer and BCSS and to estimate risk factors for BCSS of both first and second primary TNBC. The hazard ratio and 95% confidence interval (CI) were evaluation indices. Our study demonstrated that age, histological grade III/IV, high T stage, high N stage, and TNBC were associated with a decreased 3-year and 5-year BCSS in both first and second primary TNBC. Family income ≥$60 000 per year (hazard ratio: 0.68, 95% CI: 0.48-0.95, P = 0.026) correlated with better 3-year BCSS in patients with second primary TNBC. Breast-conserving surgery, mastectomy, and the interval between two cancer diagnoses >3 years were associated with increased 3-year and 5-year BCSS in patients with second primary TNBC (all P < 0.05). This paper reveals a worse survival of second primary TNBC. Great attention should be paid to the prognosis of patients with second primary TNBC.

Establishment of prognostic model for invasive ductal carcinoma with distant metastasis within the triple-negative breast cancer: a SEER population-based study

Triple-negative breast cancer (TNBC) is a complex and diverse group of malignancies. Invasive ductal carcinoma (IDC) is the predominant pathological subtype and is closely linked to the ominous potential for distant metastasis, a pivotal factor that significantly influences patient outcomes. In light of these considerations, the present study was conceived with the objective of developing a nomogram model. This model was designed to predict the prognosis observed in IDC with distant metastasis in TNBC. This was a retrospective study based on the SEER database. Data of 9739 IDC-TNBC patients diagnosed from 2010 to 2020 were included in our study. Independent risk factors were screened by univariate and multivariate Cox regression analyses successively, which were used to develop a nomogram model predicting for prognosis. Cox multivariable analysis showed statistical significance in bone metastasis, liver metastasis, surgery, and chemotherapy. Incorporating statistically significant variables, as well as clinically significant age, lung metastasis, and brain metastasis into the construction of the prediction model, the C-indexes of the training group and validation group were 0.702 (0.663-0.741) and 0.667 (0.600-0.734), respectively, while the calibration curves were all close to the ideal 45° reference line, and decision curve analysis curves show excellent net benefit in the predictive model. The prognostic prediction model developed in this study demonstrated enhanced predictive accuracy, enabling a more precise evaluation of mortality risks associated with IDC with distant metastasis in TNBC.

Triple-negative breast cancer survival prediction: population-based research using the SEER database and an external validation cohort

Introduction

Triple-negative breast cancer (TNBC) is linked to a poorer outlook, heightened aggressiveness relative to other breast cancer variants, and limited treatment choices. The absence of conventional treatment methods makes TNBC patients susceptible to metastasis. The objective of this research was to assess the clinical and pathological traits of TNBC patients, predict the influence of risk elements on their outlook, and create a prediction model to assist doctors in treating TNBC patients and enhancing their prognosis.

Methods

We included 23,394 individuals with complete baseline clinical data and survival information who were diagnosed with primary TNBC between 2010 and 2015 based on the SEER database. External validation utilised a group from The Affiliated Lihuili Hospital of Ningbo University. Independent risk factors linked to TNBC prognosis were identified through univariate, multivariate, and least absolute shrinkage and selection operator regression methods. These characteristics were chosen as parameters to develop 3- and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) nomogram models. Model accuracy was assessed using calibration curves, consistency indices (C-indices), receiver operating characteristic curves (ROCs), and decision curve analyses (DCAs). Finally, TNBC patients were divided into groups of high, medium, and low risk, employing the nomogram model for conducting a Kaplan-Meier survival analysis.

Results

In the training cohort, variables such as age at diagnosis, marital status, grade, T stage, N stage, M stage, surgery, radiation, and chemotherapy were linked to OS and BCSS. For the nomogram, the C-indices stood at 0.762, 0.747, and 0.764 in forecasting OS across the training, internal validation, and external validation groups, respectively. Additionally, the C-index values for the training, internal validation, and external validation groups in BCSS prediction stood at 0.793, 0.755, and 0.811, in that order. The findings revealed that the calibration of our nomogram model was successful, and the time-variant ROC curves highlighted its effectiveness in clinical settings. Ultimately, the clinical DCA showcased the prospective clinical advantages of the suggested model. Furthermore, the online version was simple to use, and nomogram classification may enhance the differentiation of TNBC prognosis and distinguish risk groups more accurately.

Conclusion

These nomograms are precise tools for assessing risk in patients with TNBC and forecasting survival. They can help doctors identify prognostic markers and create more effective treatment plans for patients with TNBC, providing more accurate assessments of their 3- and 5-year OS and BCSS.

Assessing of case-cohort design: a case study for breast cancer patients in Xinjiang, China

Objective

To assess the effectiveness and clinical value of case-cohort design and determine prognostic factors of breast cancer patients in Xinjiang on the basis of case-cohort design.

Methods

The survival data with different sample characteristics were simulated by using Cox proportional risk models. To evaluate the effectiveness for the case-cohort, entire cohort, and simple random sampling design by comparing the mean, coefficient of variation, etc., of covariate parameters. Furthermore, the prognostic factors of breast cancer patients in Xinjiang were determined based on case-cohort sampling designs. The models were comprehensively evaluated by likelihood ratio test, the area under the receiver operating characteristic curve (AUC), and Akaike Information Criterion (AIC).

Results

In a simulations study, the case-cohort design shows better stability and improves the estimation efficiency when the censored rate is high. In the breast cancer data, molecular subtypes, T-stage, N-stage, M-stage, types of surgery, and postoperative chemotherapy were identified as the prognostic factors of patients in Xinjiang. These models based on the different sampling designs both passed the likelihood ratio test (p<0.05). Moreover, the model constructed under the case-cohort design had better fitting effect (AIC=3,999.96) and better discrimination (AUC=0.807).

Conclusion

Simulations study confirmed the effectiveness of case-cohort design and further determined the prognostic factors of breast cancer patients in Xinjiang based on this design, which presented the practicality of case-cohort design in actual data.

Postmarketing Safety of Sacituzumab Govitecan: A Pharmacovigilance Study Based on the FDA Adverse Event Reporting System

Sacituzumab govitecan is widely used for the treatment of breast cancer and urothelial carcinoma, but available information regarding adverse events (AEs) is limited. We aim to explore the AE induced by sacituzumab govitecan by mining the FDA Adverse Event Reporting System (FAERS) database. The association between sacituzumab govitecan and AEs was evaluated using the information component. A multivariate logistic regression analysis was conducted for all identified signals to explore the risk factors associated with AEs leading to hospitalization. In total, 1,884 reports related to sacituzumab govitecan were retrieved, and 114 AE signals involving 20 systems were identified. The median time for onset of AEs was ~ 6-7 days after initiating treatment with sacituzumab govitecan, with over 80% of AEs occurring within 30 days. Subgroup analysis revealed that 14 signals were reported in men and 110 in women. There were 58 signals reported in patients under 65 following the use of sacituzumab govitecan, 59 signals in patients over 65, and 31 signals were present in both groups. Multivariable analysis showed that being male and the occurrence of colitis, pneumonitis, febrile neutropenia, pyrexia, sepsis, dehydration, and diarrhea were risk factors leading to hospitalization with an area under the curve (AUC) of 0.89. Additionally, sensitivity analysis revealed that this study had good robustness. This is the first retrospective analysis based on FAERS to review the safety of sacituzumab govitecan. The results highlight the need to closely monitor adverse reactions such as neutropenia, diarrhea, colitis, and sepsis when using sacituzumab govitecan.