Dataset Information

AMGET, an R-Based Postprocessing Tool for ADAPT 5.

ABSTRACT: ADAPT 5 is a powerful modeling software for population pharmacokinetic and pharmacodynamic systems analysis, but provides limited built-in functionality for creating pre- and post-analysis diagnostic plots. ADAPT 5 Model Evaluation Graphical Toolkit (AMGET), an external package written in the open source R programming language, was developed specifically to support efficient postprocessing of ADAPT 5 runs, as well as NONMEM and S-ADAPT runs. Using interactive navigational menus, users of AMGET are able to rapidly create informative diagnostic plots enriched by the display of numerical and graphical elements with a high degree of customization using a simple settings spreadsheet. This article describes each feature of the AMGET package and illustrates how it allows users to utilize the powerful numerical routines of the ADAPT 5 package in a more efficient manner through the use of a simulated dataset and a simple pharmacokinetic model optimized using the maximum likelihood expectation maximization (MLEM) algorithm of ADAPT 5.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e61; doi:10.1038/psp.2013.36; published online 31 July 2013.

SUBMITTER: Guiastrennec B

PROVIDER: S-EPMC3731825 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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AMGET, an R-Based Postprocessing Tool for ADAPT 5.

Guiastrennec B B Wollenberg L L Forrest A A Ait-Oudhia S S

CPT: pharmacometrics & systems pharmacology 20130731

ADAPT 5 is a powerful modeling software for population pharmacokinetic and pharmacodynamic systems analysis, but provides limited built-in functionality for creating pre- and post-analysis diagnostic plots. ADAPT 5 Model Evaluation Graphical Toolkit (AMGET), an external package written in the open source R programming language, was developed specifically to support efficient postprocessing of ADAPT 5 runs, as well as NONMEM and S-ADAPT runs. Using interactive navigational menus, users of AMGET a ...[more]

PMID: 23903464

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Project description:BackgroundThere are a growing number of mHealth tools for breast cancer patients but a lack of scientific evidence for their effects. Recent studies have shown a mix of positive and negative impacts on users. Here we will assess the impact of OWise Breast Cancer, a mobile application for self-monitoring symptoms and managing care, on the process of self-management.MethodsThis randomized controlled trial with early stage breast cancer patients will assess the effect of OWise use on patient activation at 3 months from diagnosis measured by the PAM-13 questionnaire. We will also assess differences in changes in health-related quality of life, psychological distress, health status, and National Health Service (NHS) health resource utilization over the first year from diagnosis. Participants will be randomly allocated (1:1) to standard care or standard care plus OWise. Participants will complete questionnaires before starting anti-cancer treatment and at 3, 6, and 12 months from diagnosis. Clinical and patient-reported outcome data will be linked to health resource utilization data from Discover, an integrated care record of primary, secondary, and social care in North West London. We will measure contamination in the control group and adjust the sample size to mitigate the dilution of effect estimates. A per-protocol analysis will be conducted as a sensitivity analysis to assess robustness of the primary results.DiscussionThis study aims to generate evidence for the effectiveness of OWise at improving patient activation for women with early-stage breast cancer. The results will show the impact of using the tool at the patient level and the NHS health system level. The outcomes of the study will have implications for the application of OWise across the NHS for breast cancer patients and expansion into other tumor types. Assessing publicly available mHealth tools poses a challenge to trialists due to the risk of contamination. Here we apply various methods to measure, mitigate, and assess the effects of contamination.Trial registrationThe study was registered at clincaltrials.gov (NCT03866655) on 7 March 2019.

Dataset Information

AMGET, an R-Based Postprocessing Tool for ADAPT 5.

Publications

AMGET, an R-Based Postprocessing Tool for ADAPT 5.

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