Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Pancreatic ductal adenocarcinoma (PDAC) is prone to relapse even after radical pancreaticoduodenectomy (PD) (including robotic, laparoscopic and open approach). This study aimed to develop an online nomogram calculator to predict early recurrence (ER) (within one year after surgery) and long-term survival in patients with PDAC.
Methods: Patients with PDAC after radical PD were included. Univariate and multivariate logistic regression analysis was used to identify independent risk factors. An online nomogram calculator was developed based on independent risk factors in the training cohort and then tested in the internal and external validation cohorts.
Results: Of the 569 patients who met the inclusion criteria, 310, 155, and 104 patients were in the training, internal and external validation cohorts, respectively. Multivariate analysis revealed that preoperative carbohydrate antigen19-9 (CA19-9) [Odds Ratio (OR) 1.002; 95% confidence interval (CI) 1.001-1.003; P = 0.001], fibrinogen/albumin (FAR) (OR 1.132; 95% CI 1.012-1.266; P = 0.029), N stage (OR 2.291; 95% CI 1.283-4.092; P = 0.005), and tumor differentiation (OR 3.321; 95% CI 1.278-8.631; P = 0.014) were independent risk factors for ER. Nomogram based on the above four factors achieved good C-statistics of 0.772, 0.767 and 0.765 in predicting ER in the training, internal and external validation cohorts, respectively. Time-dependent ROC analysis (timeROC) and decision curve analysis (DCA) revealed that the nomogram provided superior diagnostic capacity and net benefit compared with other staging systems.
Conclusion: This multi-center study developed and validated an online nomogram calculator that can predict ER and long-term survival in patients with PDAC with high degrees of stability and accuracy.
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http://dx.doi.org/10.1016/j.ijsu.2022.106891 | DOI Listing |