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BACKGROUND: Despite the low recurrence rate of resected nonfunctional pancreatic neuroendocrine tumors (NF-pNETs), nearly all patients undergo long-term surveillance. A prediction model for recurrence may help select patients for less intensive surveillance or identify patients for adjuvant therapy. The objective of this study was to assess the external validity of a recently published model predicting recurrence within 5 years after surgery for NF-pNET in an international cohort. This prediction model includes tumor grade, lymph node status and perineural invasion as predictors. METHODS: Retrospectively, data were collected from 7 international referral centers on patients who underwent resection for a grade 1-2 NF-pNET between 1992 and 2018. Model performance was evaluated by calibration statistics, Harrel's C-statistic, and area under the curve (AUC) of the receiver operating characteristic curve for 5-year recurrence-free survival (RFS). A sub-analysis was performed in pNETs >2 cm. The model was improved to stratify patients into 3 risk groups (low, medium, high) for recurrence. RESULTS: Overall, 342 patients were included in the validation cohort with a 5-year RFS of 83% (95% confidence interval [CI]: 78-88%). Fifty-eight patients (17%) developed a recurrence. Calibration showed an intercept of 0 and a slope of 0.74. The C-statistic was 0.77 (95% CI: 0.70-0.83), and the AUC for the prediction of 5-year RFS was 0.74. The prediction model had a better performance in tumors >2 cm (C-statistic 0.80). CONCLUSIONS: External validity of this prediction model for recurrence after curative surgery for grade 1-2 NF-pNET showed accurate overall performance using 3 easily accessible parameters. This model is available via www.pancreascalculator.com.

Background: Despite the low recurrence rate of resected nonfunctional pancreatic neuroendocrine tumors (NF-pNETs), nearly all patients undergo long-term surveillance. A prediction model for recurrence may help select patients for less intensive surveillance or identify patients for adjuvant therapy. The objective of this study was to assess the external validity of a recently published model predicting recurrence within 5 years after surgery for NF-pNET in an international cohort. This prediction model includes tumor grade, lymph node status and perineural invasion as predictors. Methods: Retrospectively, data were collected from 7 international referral centers on patients who underwent resection for a grade 1-2 NF-pNET between 1992 and 2018. Model performance was evaluated by calibration statistics, Harrel's C-statistic, and area under the curve (AUC) of the receiver operating characteristic curve for 5-year recurrence-free survival (RFS). A sub-analysis was performed in pNETs >2 cm. The model was improved to stratify patients into 3 risk groups (low, medium, high) for recurrence. Results: Overall, 342 patients were included in the validation cohort with a 5-year RFS of 83% (95% confidence interval [CI]: 78-88%). Fifty-eight patients (17%) developed a recurrence. Calibration showed an intercept of 0 and a slope of 0.74. The C-statistic was 0.77 (95% CI: 0.70-0.83), and the AUC for the prediction of 5-year RFS was 0.74. The prediction model had a better performance in tumors >2 cm (C-statistic 0.80). Conclusions: External validity of this prediction model for recurrence after curative surgery for grade 1-2 NF-pNET showed accurate overall performance using 3 easily accessible parameters. This model is available via www.pancreascalculator.com. © 2021

Introduction: hepatocellular carcinoma (HCC) is by far the leading malignant indication for liver transplantation (LT). Few other malignancies, including cholangiocellular carcinoma (CCC), metastases from neuroendocrine tumors (NET), and sarcomas of the liver (LSAR), also are commonly accepted indications for LT. However, there is limited information on their outcome after LT. Methods: graft and patient survival in 14,623 LTs performed in patients with hepatocellular carcinoma, CCC, NET, and LSAR from 1988 to 2017 and reported to the Collaborative Transplant Study were analyzed. Results: the study group consisted of 13,862 patients who had HCC (94.8%), 498 (3.4%) who had CCC, 100 (0.7%) who had NET, and 163 (1.1%) who had LSAR. CCC patients showed a 5-year graft survival rate of 32.1%, strikingly lower than the 63.2% rate in HCC, 51.6% rate in NET, and 64.5% rate in LSAR patients (P < 0.001 for all vs. CCC). Multivariable Cox regression analysis revealed a significantly higher risk of graft loss and death due to cancer during the first five post-transplant years in CCC vs. HCC patients (HR 1.77 and 2.56; P < 0.001 for both). The same risks were increased also in NET and LSAR patients but did not reach statistical significance. Conclusion: among patients with rare malignant indications for LT, CCC patients showed significantly impaired graft as well as patient survival compared to HCC patients. The observed differences might challenge traditional decision-making processes for LT indication and palliative treatment in specific hepatic malignancies., NA

Purpose: Altered FGFR1 signaling has emerged as a therapeutic target in epithelial malignancies. In contrast, the role of FGFR1 in soft-tissue sarcoma (STS) has not been established. Prompted by the detection and subsequent therapeutic inhibition of amplified FGFR1 in a patient with metastatic leiomyosarcoma, we investigated the oncogenic properties of FGFR1 and its potential as a drug target in patients with STS. Experimental Design: The frequency of FGFR1 amplification and overexpression, as assessed by FISH, microarray-based comparative genomic hybridization and mRNA expression profiling, SNP array profiling, and RNA sequencing, was determined in three patient cohorts. The sensitivity of STS cell lines with or without FGFR1 alterations to genetic and pharmacologic FGFR1 inhibition and the signaling pathways engaged by FGFR1 were investigated using viability assays, colony formation assays, and biochemical analysis. Results: Increased FGFR1 copy number was detected in 74 of 190 (38.9%; cohort 1), 13 of 79 (16.5%; cohort 2), and 80 of 254 (31.5%; cohort 3) patients. FGFR1 overexpression occurred in 16 of 79 (20.2%, cohort 2) and 39 of 254 (15.4%; cohort 3) patients. Targeting of FGFR1 by RNA interference and small-molecule inhibitors (PD173074, AZD4547, BGJ398) revealed that the requirement for FGFR1 signaling in STS cells is dictated by FGFR1 expression levels, and identified the MAPK-ERK1/2 axis as critical FGFR1 effector pathway. Conclusions: These data identify FGFR1 as a driver gene in multiple STS subtypes and support FGFR1 inhibition, guided by patient selection according to the FGFR1 expression and monitoring of MAPK-ERK1/2 signaling, as a therapeutic option in this challenging group of diseases. (C)2016 AACR.