Large trials and studies generate many analysis results in the form of tables, figures and written reports. Historically, a typical workflow for producing analysis results involves the end user generating the display in a static format such as RTF or PDF from the Analysis Data Model (ADaM) dataset (Figure 1). The Analysis Results Metadata (ARM) for Define-XML (add reference) is then created retrospectively to provide high-level documentation about metadata relating to the analysis displays and results; however. However, there is no formal model or structures to describe analysis results and associated metadata, leaving a gap in standardization. The current process is expensive, time-consuming, lacks automation and traceability, leading to unnecessary variation in analysis results reporting.
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Figure 1: Example of Current Workflow
The goal for the future state of analysis results reporting is where we can have a standard that will support the following objectives:
- Use analysis results metadata prospectively to drive the automation of results
- Support storage, access, processing and reproducibility of results
- Improved navigation and reusability of analyses and results
- Traceability to Protocol/SAP and to input ADaM data
are that they are machine-readable, easily navigable, and highly reusable. We envision the following:
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Our aim was to create a logical model that fully described analysis results and associated metadata to support the following objectives:
- Automated generation of machine-readable results data
- Improved navigation and reusability of analysis and results data
- Support for the storage, access, processing, and reproducibility of results data
- Traceability to the study protocol/, statistical analysis plan (SAP), and to the input ADaM data
•Use analysis results metadata to drive the automation of results
•Support storage, access, processing and reproducibility of results
•Improved navigation and reusability of analyses and results
•Traceability to Protocol/SAP and to input ADaM data
- dataset
The Analysis Results Standard (ARS) Model has several potential implementations including: leveraging analysis results metadata to aid in automation as well as representing analysis results as data in a dataset structure. The creation of an ARS technical specification could be used To achieve these goals, a logical model to fully describe analysis results metadata has been developed. This logical model will enable the implementation of an Analysis Results Metadata Technical Specification and an Analysis Results Data framework. ARM-TS can be used to support automation, traceability, and the creation of data displays while the ARD framework will . An analysis results dataset couldl support reuse and reproducibility of results data.
To address the current limitations of analysis results and associated metadata reporting, we are proposing a new workflow that shifts the focus from retrospective reporting to prospective planning. Specifically, we propose that end-users generate the a technical specification to l prior to generating a display, rather than after the display has been created. This approach will allow for better planning and standardization of the analysis process, resulting in more consistent and traceable reporting.
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Overall, this new workflow will enable end-users to generate analysis results metadata prospectively, with greater standardization, consistency, and traceability of analysis results reporting, enabling better decision-making and regulatory submissions. By shifting the focus from retrospective reporting to prospective planning, we believe that this approach will help to address many of the current limitations of analysis results reporting and support the development of more efficient and effective analysis standards.In our vision for the future state, we anticipate the availability of open-source or community tools, such as the TFL Designer Community [1], in the industry. These tools will empower users to create machine-readable analysis metadata, which can automate the generation of analysis results data and displays. We also hope that such a tool can seamlessly integrate with existing analysis programs and report creation tools, enabling an end-to-end automation of the analysis and reporting process.
Use of LinkML for the development of the ARS Logical Model
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