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
Background: Simulation models analyzing the impact of treatment interventions and screening on the level of breast cancer mortality require an input of mortality from causes other than breast cancer, or competing risks.
Methods: This chapter presents an actuarial method of creating cohort life tables using published data that removes breast cancer as a cause of death.
Results: Mortality from causes other than breast cancer as a percentage of all-cause mortality is smallest for women in their forties and fifties, as small as 85% of the all-cause rate, although the level and percentage of the impact varies by birth cohort.
Conclusion: This method produces life tables by birth cohort and by age that are easily included as a common input by the various CISNET modeling groups to predict mortality from other causes. Attention to removing breast cancer mortality from all-cause mortality is worthwhile, because breast cancer mortality can be as high as 15% at some ages.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1093/jncimonographs/lgj004 | DOI Listing |
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