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
This study aimed to develop and validate a nomogram using clinical variables to guide personalized treatment strategies for adenoid cystic carcinoma of the head and neck (ACCHN). Data from 1069 patients with ACCHN diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were used to construct the nomogram. External validation was performed using an independent cohort of 70 patients from Fujian Cancer Hospital. Multivariate Cox regression analysis was conducted using IBM SPSS version 26.0 and R Software version 4.2.3. The concordance index (C-index) and receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the nomogram. Age, tumor site, surgery, N stage, M stage, and TNM stage were identified as independent prognostic factors through univariate and multivariate Cox analyses. The nomogram demonstrated superior predictive performance compared to the TNM staging system, effectively stratifying patients into high-risk and low-risk groups. This nomogram offers a valuable tool for predicting overall survival in patients with ACCHN and tailoring individualized treatment approaches.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11531573 | PMC |
http://dx.doi.org/10.1038/s41598-024-77322-9 | DOI Listing |
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