Oncologic Outcomes of Colon Cancer Patients with Extraregional Lymph Node Metastasis: Comparison of Isolated Paraaortic Lymph Node Metastasis with Resectable Liver Metastasis

2015 ◽  
Vol 23 (5) ◽  
pp. 1562-1568 ◽  
Author(s):  
Sung Uk Bae ◽  
Yoon Dae Han ◽  
Min Soo Cho ◽  
Hyuk Hur ◽  
Byung Soh Min ◽  
...  
Author(s):  
Hui-Hua Chen ◽  
Wan-Hua Ting ◽  
Hsu-Dong Sun ◽  
Ming-Chow Wei ◽  
Ho-Hsiung Lin ◽  
...  

Background: to elucidate the predictors of progression-free survival (PFS) and overall survival (OS) in high-risk endometrial cancer patients. Methods: the medical records of all consecutivewomen with high-risk endometrial cancer were reviewed. Results: among 92 high-risk endometrial cancer patients, 30 women experienced recurrence, and 21 women died. The 5-year PFS and OS probabilities were 65.3% and 75.9%, respectively. Multivariable Cox regression revealed that body mass index (hazard ratio (HR) = 1.11), paraaortic lymph node metastasis (HR = 11.11), lymphovascular space invasion (HR = 5.61), and sandwich chemoradiotherapy (HR = 0.15) were independently predictors of PFS. Body mass index (HR = 1.31), paraaortic lymph node metastasis (HR = 32.74), non-endometrioid cell type (HR = 11.31), and sandwich chemoradiotherapy (HR = 0.07) were independently predictors of OS. Among 51 women who underwent sandwich (n = 35) or concurrent (n = 16) chemoradiotherapy, the use of sandwich chemoradiotherapy were associated with better PFS (adjusted HR = 0.26, 95% CI = 0.08–0.87, p = 0.03) and OS (adjusted HR = 0.11, 95% CI = 0.02–0.71, p = 0.02) compared with concurrent chemoradiotherapy. Conclusion: compared with concurrent chemoradiotherapy, sandwich chemoradiotherapy was associated with better PFS and OS in high-risk endometrial cancer patients. In addition, high body mass index, paraaortic lymph node metastasis, and non-endometrioid cell type were also predictors of poor OS in high-risk endometrial cancer patients.


2006 ◽  
Vol 41 (4) ◽  
pp. 391-392 ◽  
Author(s):  
Takahiro Uenishi ◽  
Osamu Yamazaki ◽  
Katsuhiko Horii ◽  
Takatsugu Yamamoto ◽  
Shoji Kubo

2020 ◽  
Author(s):  
Xiangjian Zheng ◽  
Xiaodong Chen ◽  
Min Li ◽  
Chunmeng Li ◽  
Xian Shen

Abstract Background: Surgery combined with chemo-radiotherapy is a recognized model for the treatment of gastric and colon cancers. Lymph node metastasis determines the patient's surgical or comprehensive treatment plan. This analytical study aims to compare preoperative prediction scores to better predict lymph node metastasis in gastric and colon cancer patients.Methods: This study comprised 768 patients, which included 312 patients with gastric cancer and 462 with colon cancer. Preoperative clinical tumor characteristics, serum markers, and immune indices were evaluated using single-factor analysis. Logistic analysis was designed to recognize independent predictors of lymph node metastasis in these patients. The independent risk factors were integrated into preoperative prediction scores, which were accurately assessed using receiver operating characteristic (ROC) curves.Results: Results showed that serum markers (CA125, hemoglobin, albumin), immune indices (S100, CD31, d2–40), and tumor characteristics (pathological type, size) were independent risk factors for lymph node metastasis in patients with gastric and colon cancer. The preoperative prediction scores reliably predicted lymph node metastasis in gastric and colon cancer patients with a higher area under the ROC curve (0.901). The area was 0.923 and 0.870 in gastric cancer and colon cancer, respectively. Based on the ROC curve, the ideal cutoff value of preoperative prediction scores to predict lymph node metastasis was established to be 287. Conclusion: The preoperative prediction scores is a useful indicator that can be applied to predict lymph node metastasis in gastric and colon cancer patients.


2014 ◽  
Vol 132 (1) ◽  
pp. 38-43 ◽  
Author(s):  
Sanjeev Kumar ◽  
Karl C. Podratz ◽  
Jamie N. Bakkum-Gamez ◽  
Sean C. Dowdy ◽  
Amy L. Weaver ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Aydin Eresen ◽  
Yu Li ◽  
Jia Yang ◽  
Junjie Shangguan ◽  
Yury Velichko ◽  
...  

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