Nomogram for predicting survival of patients with metastatic nonfunctioning pancreatic neuroendocrine tumors: A SEER based study.

ABSTRACT: More attention has been placed on nonfunctioning pancreatic neuroendocrine tumors due to the increase in its incidence in recent years. Whether tumor resection at the primary site of metastatic NFpNET is effective remains controversial. Moreover, clinicians need a more precise prognostic tool to estimate the survival of these patients.Patients with metastatic NFpNET were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Significant prognostic factors were identified using a multivariate Cox regression model and included in the nomogram. Coarsened exact matching analysis was used to balance the clinical variables between the non-surgical and surgical groups in our study.A total of 1464 patients with metastatic nonfunctioning pancreatic neuroendocrine tumors (NFpNETs) were included in our cohort. Multivariate analysis identified age, sex, tumor size, differentiated grade, lymph node metastases, resection of primary tumors, and marital status as independent predictors of metastatic NFpNET. The nomogram showed excellent accuracy in predicting 1-, 3-, and 5-year overall survival, with a C-index of 0.812. The calibration curve revealed good consistency between the predicted and actual survival.Coarsened exact matching analysis using SEER data indicated the survival advantages of resection of primary tumors. Our study is the first to build a nomogram model for patients with metastatic NFpNETs. This predictive tool can help clinicians identify high-risk patients and more accurately assess patient survival times.

Hypoxia-inducible factor 1α in breast cancer prognosis.

BACKGROUND: Recent studies have assessed the relationship between hypoxia-inducible factor 1α (HIF-1α) expression and prognosis in breast cancer patients with inconsistent conclusions. To comprehensively and quantitatively summarize the evidence on the survival of patients with breast cancer, a meta-analysis was performed. METHODS: Systematic literature searching was applied to the databases of PubMed, Embase and Web of science until April 1, 2013. Pooled HR with 95% CI was used to evaluate the association between HIF-1α expression and survival in breast cancer patients. RESULTS: Fourteen papers including 2933 patients were subjected to the final analysis. Of these, 7 provided data on overall survival (OS), 8 on disease-free survival (DFS), 3 on distant metastasis-free survival (DMFS) and 3 on relapse-free survival (RFS). We observed that high expression of HIF-1α in breast cancer patients was an indicator of poor prognosis on OS (HR = 1.46, 95% CI: 1.12-1.92, P = 0.006), DFS (HR = 1.91, 95% CI: 1.43-2.57, P<0.001), DMFS (HR=2.17 95% CI: 1.16-4.05, P=0.015) and RFS (HR=1.33 95% CI: 1.09-1.61, P=0.005). Significant heterogeneity was observed in the analyses of OS and DFS. Subgroup analyses by the cut-off value and antibody for IHC were conducted. CONCLUSION: High expression of HIF-1α indicated a poor prognosis for patients with breast cancer.