pathologic lymph node
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Oral Oncology ◽  
2021 ◽  
Vol 123 ◽  
pp. 105625
Author(s):  
Roman O. Kowalchuk ◽  
Kathryn M. Van Abel ◽  
Linda X. Yin ◽  
Joaquin Garcia ◽  
William S. Harmsen ◽  
...  

Cancer ◽  
2020 ◽  
Vol 126 (13) ◽  
pp. 2991-3001 ◽  
Author(s):  
Arnav Srivastava ◽  
Zorimar Rivera‐Núñez ◽  
Sinae Kim ◽  
Joshua Sterling ◽  
Nicholas J. Farber ◽  
...  

2019 ◽  
Vol 229 (4) ◽  
pp. e54
Author(s):  
Gabriella T. Capolupo ◽  
Sara Lauricella ◽  
Gianluca Mascianà ◽  
Erica Mazzotta ◽  
Filippo Carannante ◽  
...  

HPB ◽  
2018 ◽  
Vol 20 (5) ◽  
pp. 470-476 ◽  
Author(s):  
David G. Brauer ◽  
Ryan C. Fields ◽  
Benjamin R. Tan ◽  
M.B. Majella Doyle ◽  
Chet W. Hammill ◽  
...  

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 171-171
Author(s):  
Jinho Hwang ◽  
Jung Jun Kim ◽  
Jong Jin Oh ◽  
Chang Wook Jeong ◽  
Sang Eun Lee ◽  
...  

171 Background: To evaluate the accuracy of preoperative magnetic resonance imaging (MRI) in patients who underwent pelvic lymph node dissection (PLND). Methods: The data of 1528 patients who underwent radical prostatectomy and PLND from 2003 to 2017 in our institution were retrospectively reviewed. We evaluated the various clinicopathologic variables including preoperative MRI and pathologic lymph node metastasis (LNmet). The prediction model for pathologic lymph node (LNmet) was assessed using logistic regression analyses and the areas under receiver operating characteristic curves (AUCs) were evaluated. Results: The mean age of our cohort was 66.4 ± 6.7 years. Positive preoperative MRI finding was observed in 9.4% (145/1528) of patients. 5.3% (81/1528) of patients accompanied confirmed final pathologic LNmet. Sensitivity and specificity of preoperative MRI were 30.8% and 91.7%, respectively. Multivariate analysis showed that preoperative MRI findings, clinical stage, and biopsy Gleason score were independent predictors for pathologic LNmet. Preoperative PSA, which was significantly related to pathologic LNmet in univariate analysis, failed to achieve independent predictor status in multivariate analysis. A better prediction model with greater accuracy was achieved by applying multivariate ROC analysis that included MRI findings, clinical stage, and biopsy Gleason score (AUC: 0.799 vs 0.613, p<0.01). The corresponding newer prediction model showed better sensitivity(77.78%) and specificity(70.74%) within threshold value range when it was compared with the predictor model using conventional Partin triad. Conclusions: Preoperative MRI findings for pathologic LNmet showed limited prediction power, yet the predicting power was significantly increased when additional factors such as clinical stage, and biopsy Gleason score were included in the analysis. [Table: see text]


Surgery ◽  
2017 ◽  
Vol 162 (4) ◽  
pp. 846-856 ◽  
Author(s):  
Kotaro Sugawara ◽  
Hiroharu Yamashita ◽  
Yukari Uemura ◽  
Takashi Mitsui ◽  
Koichi Yagi ◽  
...  

Oncotarget ◽  
2017 ◽  
Vol 8 (37) ◽  
pp. 62231-62239 ◽  
Author(s):  
Yuming Zhao ◽  
Shengyi Zhong ◽  
Zhenhua Li ◽  
Xiaofeng Zhu ◽  
Feima Wu ◽  
...  

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 382-382
Author(s):  
Douglas S. Swords ◽  
Chong Zhang ◽  
Angela P. Presson ◽  
Matthew A. Firpo ◽  
Sean J. Mulvihill ◽  
...  

382 Background: Clinical nodal staging in PDAC is inaccurate. Most pts are cN0, but > 70% are pN+. We hypothesize that preoperative variables are associated with pN+ and could be used to create a predictive nomogram. Methods: The NCDB was reviewed from 2010-13 for pts with clinical stage I-II PDAC. Exclusions were neoadjuvant therapy, < 12 nodes examined, and missing data for clinical/pathologic stage, size, and number of nodes examined/positive. Logistic regression assessed factors associated with pN+ and an interaction was included for extrapancreatic extension and cN stage. A logistic regression based nomogram was constructed and 10-fold cross validation evaluated model discrimination. Results: Of 7,475 pts, 28% were cN+ but 74% were pN+ (P < 0.001). Associations of preoperative factors with pN+ are shown. Size was pathology based. We recommend multiplying imaging based size estimates by 1.33 for use in the nomogram based on studies showing that imaging underestimates size by 25%. Interestingly, extrapancreatic extension was protective for cN0 pts but associated with increased odds of pN+ for cN1 relative to cN0 ps. A nomogram was created to predict pN+ using these variables. The 10-fold cross validated AUC was 0.77. Conclusions: Our nomogram has good discrimination to preoperatively predict lymph node positivity for patients with resectable PDAC. It could potentially be useful in identifying biologically aggressive resectable PDAC pts at higher risk of pN+ in order to select pts for neoadjuvant therapy. [Table: see text]


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