Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Objective: Gastric cancer (GC) is one of the leading causes of death in China and other Asian countries. Recently, gastric endoscopy has become the main approach for GC screening, but the identification of high-risk individuals remains a challenge in GC screening programs.
Methods: There were 7,302 patients with chronic gastritis involved in this study. Endoscopic examinations were performed, and their demographic characteristics and lifestyle data were collected. Each possible associated factor of GC/premalignant and precursor lesions was evaluated by univariate and multivariate logistic regressions. Nomograms were used for visualization of those models, and receiver operating characteristic (ROC) curve analysis was used to present the predictive accuracy.
Results: We detected 8 (0.11%) gastric adenocarcinomas, 17 (0.23%) dysplasia cases, 14 (0.19%) hyperplasia cases, 52 (0.71%) intestinal metaplasia cases, 217 (2.97%) inflammatory lesions, 141 (1.93%) gastric ulcers, 10 (0.14%) atrophic gastritis cases, 1,365 (18.69%) erosive gastritis cases, and 5,957 (81.58%) superficial gastritis cases in 7,302 patients. The age (P<0.001), gender (P=0.086), labor intensity (P=0.018) and leek food intake (P=0.143) were identified as independent predictive factors of GC/premalignant lesions possibility. The corresponding nomogram exhibited an area under the curve (AUC) [95% confidence interval (95% CI)] of 0.82 (0.74-0.89) for the modeling group and 0.80 (0.75-0.85) for the validation group. The age (P=0.002), gender (P=0.024), smoking (P=0.002) and leek food intake (P=0.039) were independent predictive factors of precursor lesions possibility. The corresponding nomogram exhibited an AUC (95% CI) of 0.62 (0.60-0.65) for the modeling group and 0.61 (0.59-0.63) for the validation group.
Conclusions: We identified several potential associated factors and provided a preclinical nomogram with the potential to predict the possibility of GC/premalignant and precursor lesions.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5592822 | PMC |
http://dx.doi.org/10.21147/j.issn.1000-9604.2017.04.07 | DOI Listing |
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