Individualized Prediction of Survival Benefit From Locoregional Surgical Treatment for Patients With Metastatic Breast Cancer

Survival Benefit from Cancer-Directed Surgery for Metastatic Head and Neck Cancer

OBJECTIVES

This study aimed to gather evidence for the survival benefit of cancer-directed surgery (CDS) in metastatic head and neck cancer (M1 HNC) and identify which patients will benefit most from CDS.

METHODS

Patients with M1 HNC were identified within the SEER database. According to whether received CDS, patients were divided into the CDS and non-CDS groups. The bias between the two groups was minimized using Propensity Score Matching (PSM), and the prognostic role of CDS was investigated using Kaplan-Meier analysis, log-rank test, and Cox proportional hazard models. The primary endpoint was overall survival (OS), and the secondary endpoint was cancer-specific survival (CSS).

RESULTS

A total of 3215 patients with M1 HNC were extracted, including 566 patients who received CDS that were 1:1 propensity score-matched with patients who did not receive CDS. In the matched dataset, the median OS and CSS in CDS groups were significantly higher than in non-CDS groups (OS: 19.0 vs. 9.0 months, p < 0.001; CSS: 21.0 vs. 9.0 months, p < 0.001). Meanwhile, multivariable Cox regression analysis also revealed that CDS was a favorable prognostic factor for both OS and CSS. Furthermore, subgroups of patients with M1 HNC (younger age, being married, grade I-II, oropharynx site, earlier T/N stage, radiotherapy) were inclined to benefit from CDS, while those patients who received chemotherapy failed to benefit from CDS.

CONCLUSIONS

This study indicated that CDS was associated with improved survival in M1 HNC, especially for those subpopulations that benefit more from CDS treatment.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:1288-1298, 2024.

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning

Up to 30% of breast cancer (BC) patients will develop distant metastases (DM), for which there is no cure. Here, statistical and machine learning (ML) models were developed to estimate the risk of site-specific DM following local-regional therapy. This retrospective study cohort included 175 patients diagnosed with invasive BC who later developed DM. Clinicopathological information was collected for analysis. Outcome variables were the first site of metastasis (brain, bone or visceral) and the time interval (months) to developing DM. Multivariate statistical analysis and ML-based multivariable gradient boosting machines identified factors associated with these outcomes. Machine learning models predicted the site of DM, demonstrating an area under the curve of 0.74, 0.75, and 0.73 for brain, bone and visceral sites, respectively. Overall, most patients (57%) developed bone metastases, with increased odds associated with estrogen receptor (ER) positivity. Human epidermal growth factor receptor-2 (HER2) positivity and non-anthracycline chemotherapy regimens were associated with a decreased risk of bone DM, while brain metastasis was associated with ER-negativity. Furthermore, non-anthracycline chemotherapy alone was a significant predictor of visceral metastasis. Here, clinicopathologic and treatment variables used in ML prediction models predict the first site of metastasis in BC. Further validation may guide focused patient-specific surveillance practices.

Nomogram Predicts the Role of Primary Tumor Surgery on De Novo Stage-IV Breast Cancer Patients: A SEER-Based Competing Risk Analysis Model

Objective

The efficacy of primary tumor surgery on survival in female patients with de novo stage IV breast cancer (BC) remains unclear. Our study endeavored to develop comprehensive competing risk nomograms to predict clinical outcomes and guide precision treatment in these patients.

Participants and Methods

A total of 12281 patients who had distant metastasis at initial BC diagnosis between 2010 and 2017 in the Surveillance Epidemiology and End Results (SEER) database, were enrolled in this study. First, we assessed the impacts of primary tumor surgery on overall survival (OS) and breast cancer-specific survival (BCSS) using the Kaplan-Meier curves. Then subgroup analyses stratified by different metastatic patterns were performed using Cox and competing risk models (CRM). Based on the filtered independent prognostic parameters by CRM, we established two nomograms to predict the probability of breast cancer-specific death (BCSD) at 1-,2- and 3-year intervals. Furthermore, calibration curves and area under the curves (AUC) were conducted for validation.

Results

Kaplan-Meier analysis revealed that surgery was associated with better OS and BCSS (P<0.001). Subgroup analyses demonstrated that in bone-only metastases pattern, relative to breast-conserving surgery (BCS), patients receiving mastectomy had worse prognosis and the poorest survival belonged to non-surgery individuals (BCSS: mastectomy: HR=1.35; 95%CI=1.15-1.60; non-surgery: 2.42; 2.08-2.82; OS: mastectomy: 1.44; 1.23-1.68; non-surgery: 2.40; 2.08-2.78). Additionally, no survival difference was observed between BCS and reconstruction recipients (BCSS: HR=1.10; 95%CI=0.85-1.43; OS: 1.11; 0.86-1.44). Furthermore, patients undergoing BCS possessed similar BCSS with mastectomy recipients as well as reconstruction recipients in viscera metastases pattern, whereas non-surgery individuals had a worse survival (mastectomy: HR=1.04; 95%CI=0.92-1.18; reconstruction: 0.86; 0.69-1.06; non-surgery: 1.83; 1.63-2.05). Two competing risk nomograms of distinct metastatic patterns were established to comprehensively predict the survival of patients. Calibration curves indicated the terrific consistency of the models. Moreover, the AUC values in the training and validation sets were in the range of 0.70–0.80, exhibiting good specificity and sensitivity.

Conclusion

The surgery implementation was associated with a lower probability of BCSD in de novo stage-IV BC patients. Our nomograms could offer a relatively accurate and individualized prediction of the cumulative incidence rate of BCSD after primary tumor resection.

Metastasis patterns and prognosis of octogenarians with metastatic breast cancer: A large-cohort retrospective study

Background

Breast cancer may differ biologically in patients aged over 80 years. The objective of the current study was to analyze the metastasis patterns and prognosis of elderly patients with metastatic breast cancer (MBC) and compare it to patients of other ages.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was utilized to select MBC patients from 2010 to 2015. Chi-squared test was used to compare clinicopathological characteristics among different aged groups. The Kaplan-Meier method and multivariate Cox model were utilized for survival analysis.

Results

A total of 10479 MBC patients were included, among which 1036 (9.9%) patients were aged over 80 years. Compared with other aged group, the elderly patients tended to have a higher proportion of HR+/Her2- subtype, white race, lower tumor differentiation, and receive less treatment, including surgery, chemotherapy and radiotherapy (P< 0.001). MBC patients with different age presented with distinctive metastatic patterns. The older patients were more likely to have lung metastasis, but less likely to have bone, brain, liver and multiple sites metastasis than the younger group (P <0.001). The proportion of TNBC subtype increased substantially in the older patients with brain metastasis, compared to the younger and middle-aged group. The old age was demonstrated to significantly associate with worse prognosis of MBC patients. Additionally, our findings also showed that older MBC patients could achieve dramatical overall survival benefit from surgery (HR = 0.58; P <0.001) and chemotherapy (HR = 0.59; P <0.001), but not the radiotherapy (HR = 0.96; P = 0.097).

Conclusion

The elderly MBC patients presented with distinctive metastatic patterns, clinical characteristics, and prognostic outcomes compared with younger patients. Our findings could assist clinicians in making appropriate therapeutic decision.

Postoperative radioiodine therapy impact on survival in poorly differentiated thyroid carcinoma: a population-based study

PURPOSE

The true impact of postoperative radioiodine therapy on survival has been controversial for patients with poorly differentiated thyroid carcinoma (PDTC). We aimed to determine the impact of postoperative radioiodine on survival in PDTC through a population-based study.

METHODS

Data on patients with PDTC were collected from the US SEER database (2004 to 2015). Patients were divided into the radioiodine group and nonradioiodine group. Survival comparison between groups was evaluated by Kaplan-Meier curves, log-rank test and multivariate Cox regression analysis. Akaike information criterion was used to select variables in the nomogram. The performance of the nomogram was assessed by discrimination (C-index) and calibration plots.

RESULTS

The radioiodine group had more aggressive features, such as advanced tumor node metastasis stage and radical surgery, compared to the nonradioiodine group. PDTC patients receiving radioiodine therapy had a significant survival advantage in terms of overall survival (OS) (P = 0.001) but not in terms of cancer-specific survival (P = 0.083). Multivariate analysis revealed radioiodine therapy was an independent favorable factor for OS in PDTC patients (hazard ratio = 0.57; 95% CI, 0.44-0.75, P < 0.001). Subgroup analysis identified patients' characteristics favoring radioiodine therapy. The nomogram (age, tumor size, extension, neck lymph nodes metastasis and radioiodine therapy) of OS for predicting 3-, 5- and 10-year OS probability showed good discrimination (C-index, 0.797) and calibration power.

CONCLUSION

Postoperative radioiodine therapy can prolong the long-term OS in patients with PDTC, and is an independent favorable prognostic factor for those patients. Further prospective studies are warranted.

Development and Validation of Prognostic Nomogram for Elderly Breast Cancer: A Large-Cohort Retrospective Study

Purpose

Our research aims to study the bone metastatic patterns and prognostic outcomes in elderly breast cancer (BC) and to develop elder-specific nomograms.

Methods

We downloaded the data of BC patients between 2010 and 2016 from the Surveillance, Epidemiology, and End Results database. The differences in clinical features and prognosis between young (age < 65) and elderly (age ≥ 65) BC patients were compared. The univariate and multivariate Cox analyses were used to determine the overall survival (OS)- and cancer-specific survival (CSS)-related variables and establish two nomograms of BC patients with bone metastasis (BCBM). The receiver operating characteristic (ROC) curve with area under the curve (AUC), calibration curve, decision curve analysis (DCA), and Kaplan–Meier survival curve were selected to evaluate nomograms.

Results

A total of 230,177 BC patients were enrolled in our research, including 142,025 young and 88,152 elderly patients. The prognosis of elderly BCBM patients was significantly worse than young patients. Age, race, breast subtype, tumor size, tumor grade, brain metastasis, liver metastasis, surgery, and chemotherapy were independent prognostic variables for elderly BCBM patients, including OS and CSS. The AUC values at 12, 18, and 24 months were 0.750, 0.751, and 0.739 for OS nomogram and 0.759, 0.762, and 0.752 for CSS nomogram in the training cohort, which were higher than the AUC values of all single independent prognostic variables. The survival curve showed a distinct prognosis between low-, median- and high-risk groups (p < 0.001). Finally, calibration curves and DCA indicated that both nomograms have favorable performance.

Conclusion

Elderly and young patients presented with different bone metastatic frequencies, clinical features, and prognostic outcomes. Two elder-specific nomograms incorporating nine clinical variables were established and validated to be a valuable predictor for elderly BCBM patients.

Metastatic breast cancer: Who benefits from surgery?

BACKGROUND

We sought to identify characteristics of metastatic breast cancer (MBC) patients who may benefit most from primary tumor resection.

METHODS

Recursive partitioning analysis (RPA) was used to categorize non-surgical patients with de novo MBC in the NCDB (2010-2015) into 3 groups (I/II/III) based on 3-year overall survival (OS). After bootstrapping (BS), group-level profiles were applied, and the association of surgery with OS was estimated using Cox proportional hazards models.

RESULTS

All patients benefitted from surgery (median OS, surgery vs no surgery): 72.7 vs 42.9 months, 47.3 vs 30.4 months, 23.8 vs 14.4 months (all p < 0.001) in BS-groups I, II, and III, respectively. After adjustment, surgery remained associated with improved OS (HR 0.52, 95% CI 0.50-0.55). The effect of surgery on OS differed quantitatively across groups.

CONCLUSION

Prognostic groups may inform the degree of benefit from surgery, with the greatest benefit seen in those with the most favorable survival.

A System Pharmacology Model for Decoding the Synergistic Mechanisms of Compound Kushen Injection in Treating Breast Cancer

Breast cancer (BC) is one of the most common malignant tumors among women worldwide and can be treated using various methods; however, side effects of these treatments cannot be ignored. Increasing evidence indicates that compound kushen injection (CKI) can be used to treat BC. However, traditional Chinese medicine (TCM) is characterized by “multi-components” and “multi-targets”, which make it challenging to clarify the potential therapeutic mechanisms of CKI on BC. Herein, we designed a novel system pharmacology strategy using differentially expressed gene analysis, pharmacokinetics synthesis screening, target identification, network analysis, and docking validation to construct the synergy contribution degree (SCD) and therapeutic response index (TRI) model to capture the critical components responding to synergistic mechanisms of CKI in BC. Through our designed mathematical models, we defined 24 components as a high contribution group of synergistic components (HCGSC) from 113 potentially active components of CKI based on ADME parameters. Pathway enrichment analysis of HCGSC targets indicated that Rhizoma Heterosmilacis and Radix Sophorae Flavescentis could synergistically target the PI3K-Akt signaling pathway and the cAMP signaling pathway to treat BC. Additionally, TRI analysis showed that the average affinity of HCGSC and targets involved in the key pathways reached -6.47 kcal/mmol, while in vitro experiments proved that two of the three high TRI-scored components in the HCGSC showed significant inhibitory effects on breast cancer cell proliferation and migration. These results demonstrate the accuracy and reliability of the proposed strategy.

Surgery for primary tumor benefits survival for breast cancer patients with bone metastases: a large cohort retrospective study

BACKGROUND

The role of surgery for the primary tumor in breast cancer patients with bone metastases (BM) remains unclear. The purpose of this study was to determine the impact of surgery for the primary tumor in breast cancer patients with BM and to develop prognostic nomograms to predict the overall survival (OS) of breast cancer patients with BM.

METHODS

A total of 3956 breast cancer patients with BM from the Surveillance, Epidemiology, and End Results database between 2010 and 2016 were included. Propensity score matching (PSM) was used to eliminate the bias between the surgery and non-surgery groups. The Kaplan-Meier analysis and the log-rank test were performed to compare the OS between two groups. Cox proportional risk regression models were used to identify independent prognostic factors. Two nomograms were constructed for predicting the OS of patients in the surgery and non-surgery groups, respectively. In addition, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the performance of nomograms.

RESULT

The survival analysis showed that the surgery of the primary tumor significantly improved the OS for breast cancer patients with BM. Based on independent prognostic factors, separate nomograms were constructed for the surgery and non-surgery groups. The calibration and ROC curves of these nomograms indicated that both two models have high predictive accuracy, with the area under the curve values ≥0.700 on both the training and validation cohorts. Moreover, DCA showed that nomograms have strong clinical utility. Based on the results of the X-tile analysis, all patients were classified in the low-risk-of-death subgroup had a better prognosis.

CONCLUSION

The surgery of the primary tumor may provide survival benefits for breast cancer patients with BM. Furthermore, these prognostic nomograms we constructed may be used as a tool to accurately assess the long-term prognosis of patients and help clinicians to develop individualized treatment strategies.

Blocking c-MET/ERBB1 Axis Prevents Brain Metastasis in ERBB2+ Breast Cancer

Simple Summary

Targeted monotherapies are ineffective in the treatment of brain metastasis of ERBB2⁺ breast cancer (BC) underscoring the need for combination therapies. The lack of robust preclinical models has further hampered the assessment of treatment modalities. We report here a clinically relevant orthotopic mouse model of ERBB2⁺ BC that spontaneously metastasizes to brain and demonstrates that targeting the c-MET/ERBB1 axis with a combination of cabozantinib and neratinib decreases primary tumor growth and prevents brain metastasis in ERBB2⁺ BC.

Abstract

Brain metastasis (BrM) remains a significant cause of cancer-related mortality in epidermal growth factor receptor 2-positive (ERBB2⁺) breast cancer (BC) patients. We proposed here that a combination treatment of irreversible tyrosine kinase inhibitor neratinib (NER) and the c-MET inhibitor cabozantinib (CBZ) could prevent brain metastasis. To address this, we first tested the combination treatment of NER and CBZ in the brain-seeking ERBB2⁺ cell lines SKBrM3 and JIMT-1-BR3, and in ERBB2⁺ organoids that expressed the c-MET/ERBB1 axis. Next, we developed and characterized an orthotopic mouse model of spontaneous BrM and evaluated the therapeutic effect of CBZ and NER in vivo. The combination treatment of NER and CBZ significantly inhibited proliferation and migration in ERBB2⁺ cell lines and reduced the organoid growth in vitro. Mechanistically, the combination treatment of NER and CBZ substantially inhibited ERK activation downstream of the c-MET/ERBB1 axis. Orthotopically implanted SKBrM3⁺ cells formed primary tumor in the mammary fat pad and spontaneously metastasized to the brain and other distant organs. Combination treatment with NER and CBZ inhibited primary tumor growth and predominantly prevented BrM. In conclusion, the orthotopic model of spontaneous BrM is clinically relevant, and the combination therapy of NER and CBZ might be a useful approach to prevent BrM in BC.

Establishing a predicted model to evaluate prognosis for initially diagnosed metastatic Her2-positive breast cancer patients and exploring the benefit from local surgery

BACKGROUND

For patients initially diagnosed with metastatic Her2-positive breast cancer (MHBC), we intended to construct a nomogram with risk stratification to predict prognosis and to explore the role of local surgery.

METHODS

We retrieved data from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier (KM) method and log-rank test were used for the selection of significant variables. Cox regression analysis and Fine-Gray test were utilized to confirm independent prognostic factors of overall survival (OS) and breast cancer-specific survival (BCSS). A nomogram predicting 1-year, 3-year, and 5-year OS was developed and validated. Patients were stratified based on the optimal cut-off values of total personal score. KM method and log-rank test were used to estimate OS prognosis and benefit from local surgery and chemotherapy.

RESULTS

There were 1680 and 717 patients in the training and validation cohort. Age, race, marriage, T stage, estrogen receptor (ER) status, visceral metastasis (bone, brain, liver and lung) were identified as independent prognostic factors for OS and BCSS, while histology was also corelated with OS. C-indexes in the training and validation cohort were 0.70 and 0.68, respectively. Calibration plots indicated precise predictive ability. The total population was divided into low- (<141 points), intermediate- (142-208 points), and high-risk (>208 points) prognostic groups. Local surgery and chemotherapy brought various degrees of survival benefit for patients with diverse-risk prognosis.

CONCLUSIONS

We constructed a model with accurate prediction and discrimination. It would provide a reference for clinicians' decision-making. Surgery on the primary lesion was recommended for patients with good physical performance status, while further study on optimal surgical opportunity was needed.