Development and External Validation of a Model to Predict Overall Survival in Patients With Resected Gallbladder Cancer.

OBJECTIVE: The aim of this study was to develop and validate a clinical prediction model to predict overall survival in patients with nonmetastatic, resected gallbladder cancer (GBC). BACKGROUND: Although several tools are available, no optimal method has been identified to assess survival in patients with resected GBC. METHODS: Data from a Dutch, nation-wide cohort of patients with resected GBC was used to develop a prediction model for overall survival. The model was internally validated and a cohort of Australian GBC patients who underwent resection was used for external validation. The performance of the American Joint Committee on Cancer (AJCC) staging system and the present model were compared. RESULTS: In total, 446 patients were included; 380 patients in the development cohort and 66 patients in the validation cohort. In the development cohort median survival was 22 months (median follow-up 75 months). Age, T/N classification, resection margin, differentiation grade, and vascular invasion were independent predictors of survival. The externally validated C-index was 0.75 (95%CI: 0.69-0.80), implying good discriminatory capacity. The discriminative ability of the present model after internal validation was superior to the ability of the AJCC staging system (Harrell C-index 0.71, [95%CI: 0.69-0.72) vs. 0.59 (95% CI: 0.57-0.60)]. CONCLUSION: The proposed model for the prediction of overall survival in patients with resected GBC demonstrates good discriminatory capacity, reasonable calibration and outperforms the authoritative AJCC staging system. This model can be a useful tool for physicians and patients to obtain information about survival after resection and is available from https:// gallbladderresearch.shinyapps.io/Predict_GBC_survival/.

Identifying Biomarkers in Lymph Node Metastases of Esophageal Adenocarcinoma for Tumor-Targeted Imaging.

INTRODUCTION: Tumor-targeted imaging is a promising technique for the detection of lymph node metastases (LNM) and primary tumors. It remains unclear which biomarker is the most suitable target to distinguish malignant from healthy tissue in esophageal adenocarcinoma (EAC). OBJECTIVE: We performed an immunohistochemistry study to identify viable tumor markers for tumor-targeted imaging of EAC. METHODS: We used samples from 72 patients with EAC to determine the immunohistochemical expression of ten potential tumor biomarkers for EAC (carbonic anhydrase IX [CA-IX], carcinoembryonic antigen [CEA], hepatic growth factor receptor, epidermal growth factor receptor, epithelial membrane antigen [EMA], epithelial cell adhesion molecule [EpCAM], human epidermal growth factor receptor 2 [HER-2], urokinase plasminogen activator receptor, vascular endothelial growth factor-A [VEGF-A], and VEGF receptor 2). Immunohistochemistry was performed on tissue microarrays of LNM (n = 48), primary EACs (n = 62), fibrotic tissues (n = 11), nonmalignant lymph nodes (n = 24), and normal esophageal and gastric tissues (n = 40). Tumor marker staining was scored on intensity and percentage of positive cells. RESULTS: EMA and EpCAM showed strong expression in LNM (> 95%) and primary EACs (> 95%). Significant expression was also observed for LNM and EAC using VEGF-A (85 and 92%), CEA (68 and 54%), and CA-IX (4 and 34%). The other tumor biomarkers showed expression of 0-15% for LNM and primary EAC. Except for VEGF-A, nonmalignant lymph node staining was scored as slight or absent. CONCLUSIONS: High expression rates and correlation between LNM in EAC combined with low expression rates in healthy lymph nodes and esophagus tissues were observed for EpCAM and CEA, meaning these are promising targets for tumor-targeted imaging approaches for lymph nodes in patients with EAC.

The diagnostic accuracy of CT and MRI for the detection of lymph node metastases in gallbladder cancer: A systematic review and meta-analysis.

BACKGROUND: Lymph node metastases (LNM) are an ominous prognostic factor in gallbladder cancer (GBC) and, when present, should preclude surgery. However, uncertainty remains regarding the optimal imaging modality for pre-operative detection of LNM and international guidelines vary in their recommendations. The purpose of this study was to systematically review the diagnostic accuracy of computed tomography (CT) versus magnetic resonance imaging (MRI) in the detection of LNM of GBC. METHODS: A literature search of studies published until November 2017 concerning the diagnostic accuracy of CT or MRI regarding the detection of LNM in GBC was performed. Data extraction and risk of bias assessment was performed independently by two reviewers. The sensitivity of CT and MRI in the detection of LNM was reviewed. Additionally, estimated summary sensitivity, specificity and diagnostic accuracy of MRI were calculated in a patient based meta-analysis. RESULTS: Nine studies including 292 patients were included for narrative synthesis and 5 studies including 158 patients were selected for meta-analysis. Sensitivity of CT ranged from 0.25 to 0.93. Estimated summary diagnostic accuracy parameters of MRI were as follows: sensitivity 0.75 (95% CI 0.6 - 0.85), specificity 0.83 (95% CI 0.74 - 0.90), LR + 4.52 (95% CI 2.55-6.48) and LR- 0.3 (95% CI 0.15 - 0.45). Small (<10 mm) LNM were most frequently undetected on pre-operative imaging. Due to a lack of data, no subgroup analysis comparing the diagnostic accuracy of CT versus MRI could be performed. CONCLUSION: The value of current imaging strategies for the pre-operative assessment of nodal status in GBC remains unclear, especially regarding the detection of small LNM. Additional research is warranted in order to establish uniformity in international guidelines, improve pre-operative nodal staging and to prevent futile surgery.