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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
The ability to accurately predict a population's long-term survival has important implications for quantifying the benefits of transplantation. To identify a model that can accurately predict a kidney transplant population's long-term graft survival, we retrospectively studied the United Network of Organ Sharing data from 13,111 kidney-only transplants completed in 1988- 1989. Nineteen-year death-censored graft survival (DCGS) projections were calculated and compared with the population's actual graft survival. The projection curves were created using a two-part estimation model that (1) fits a Kaplan-Meier survival curve immediately after transplant (Part A) and (2) uses truncated observational data to model a survival function for long-term projection (Part B). Projection curves were examined using varying amounts of time to fit both parts of the model. The accuracy of the projection curve was determined by examining whether predicted survival fell within the 95% confidence interval for the 19-year Kaplan-Meier survival, and the sample size needed to detect the difference in projected versus observed survival in a clinical trial. The 19-year DCGS was 40.7% (39.8-41.6%). Excellent predictability (41.3%) can be achieved when Part A is fit for three years and Part B is projected using two additional years of data. Using less than five total years of data tended to overestimate the population's long-term survival, accurate prediction of long-term DCGS is possible, but requires attention to the quantity data used in the projection method.
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Source |
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http://dx.doi.org/10.4103/1319-2442.98112 | DOI Listing |
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