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
Background: Increased blood pressure (BP) is commonly observed in patients treated with vascular endothelial growth factor pathway inhibitors, including axitinib. Ambulatory BP monitoring (ABPM) and pharmacokinetic data were collected in a randomised, double-blind phase II study of axitinib with or without dose titration in previously untreated patients with metastatic renal cell carcinoma.
Objective: Aims of these analyses were to (1) develop a population pharmacokinetic-pharmacodynamic model for describing the relationship between axitinib exposure and changes in diastolic BP (dBP) and (2) simulate changes in dBP with different axitinib dosing regimens.
Methods: We employed a three-stage modelling approach, which included development of (1) a baseline 24-h ABPM model, (2) a pharmacokinetic model from serial and sparse pharmacokinetic data, and (3) an indirect-response, maximum-effect (Emax) model to evaluate the exposure-driven effect of axitinib on dBP. Simulations (N = 1,000) were performed using the final pharmacokinetic-pharmacodynamic model to evaluate dBP changes on days 4 and 15 of treatment with different axitinib doses.
Results: Baseline ABPM data from 62 patients were best described by 24-h mean dBP and two cosine terms. The final indirect-response Emax model showed good agreement between observed 24-h ABPM data and population and individual predictions. The maximum increase in dBP was 20.8 %, and the axitinib concentration at which 50 % of the maximal increase in dBP was reached was 12.4 ng/mL.
Conclusion: Our model adequately describes the relationship between axitinib exposure and dBP increases. Results from these analyses may potentially be applied to infer dBP changes in patients administered axitinib at nonstandard doses.
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Source |
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http://dx.doi.org/10.1007/s40262-014-0207-5 | DOI Listing |
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