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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This multicenter retrospective cohort study evaluated the prognostic value of the modified weight loss grading system (mWLGS) in patients with lung cancer by analyzing data from 3601 individuals. The investigation demonstrated that mWLGS effectively stratified patient outcomes, with median overall survival progressively declining from 35.5 months for grade 0 to 26.0 months for grade 4. Multivariate Cox regression showed grades 1, 2, 3, and 4 were independently associated with reduced survival, showing incrementally worsening hazard ratios (HR) (HR 1.56, 95% CI: 1.03-2.37, P = 0.037; HR 1.87, 95% CI: 1.24-2.84, P = 0.003; HR 1.94, 95% CI: 1.27-2.96, P = 0.003; HR: 1.95, 95% CI: 1.27-3.00, P = 0.002, respectively). Sensitivity analyses, in which we excluded patients who died within 30 days, showed that mWLGS remained an independent prognostic indicator. The system significantly enhanced prognostic discrimination when combined with TNM staging, as evidenced by improved C-statistics, continuous net reclassification improvement (NRI), and integrated discriminant improvement (IDI). These findings establish that the mWLGS can better stratification the prognosis of patients with lung cancer and is an effective indicator to predict the survival time and quality of life of lung cancer patients.
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http://dx.doi.org/10.1002/jpen.2775 | DOI Listing |