Regardless of the research design, statistics are a crucial component of research since it allows the researchers to summarize the collected data and give it to others for interpretation.
So, when drafting a plan for data analysis, we must consider it. Data analytics and data analysis are closely related processes that involve extracting insights from data to make informed decisions. We need a defined analytic plan before we start collecting data. The SAP (statistical analysis plan) will direct us from the beginning to the conclusion, help us summarize and describe the data, and test our hypotheses.
The statistical analysis plan (SAP) describes the intended clinical trial analysis. The SAP is a technical document that describes the statistical methods of research analysis, as opposed to the protocol, which represents the analysis.
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The clinical trial report will contain all the statistical outputs that are defined in the SAP. The most popular documents utilized by statistical programmers to build their deliverables are the SAP and annotated CRFs. Practical business intelligence relies on the synergy between analytics and reporting, where analytics uncovers valuable insights, and reporting communicates these findings to stakeholders.
What is a statistical analysis plan?
A statistical analysis plan, or SAP, outlines the analytical approach of the quantitative or qualitative data you will gather. It can be used to supplement your protocol.
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An SAP contains comprehensive instructions for carrying out statistical analyses and is a more technical document than the study protocol. Although an SAP was initially designed for clinical trials, it can also be helpful in other sorts of research designs.
For instance, a documented plan defining the underlying (philosophical) approach and including specifics such as triangulation, saturation criteria, and quotation selection is likely beneficial for qualitative data analysis.
In SAP, the proposed statistical analysis must be specified in advance. This should contain the following:
- Endpoints, both primary and secondary.
- Methods of analysis
- Set of primary analysis
- Comparisons and significance levels are predefined.
- Exploratory data analyses.
- Test your maturity.
How to develop a statistical analysis plan?
An SAP or Statistical Analysis Plan is more challenging to prepare than a clinical trial protocol, requiring a solid grasp of statistical methods, medical language, and visualization power. It gives comprehensive instructions on statistical programming and reporting of clinical trial outcomes.
The four forms of SAP listed below are used in a clinical experiment:
- Data monitoring
- interim statistical analysis
- Integrated statistical analysis strategy
- Plan for statistical analysis of a clinical research
Identifying the need for an SAP
A qualified statistician who has never worked on research should be able to undertake the related analysis if the statistical approach is described in sufficient detail in the study protocol. This is frequently true for non-CTIMPs that use a quick set of analyses.
However, an SAP(Statistical Analysis Plan) would be necessary for high-risk studies (like CTIMPs) that use complex statistical methods, as it would include more technical and in-depth explanations of the methods described in the protocol as well as specific instructions for carrying out the statistical analysis of the primary and secondary variables and other subsequent data.
When an initial application is made to the Trust to act as a study sponsor, the CI, Statistician, and a suitably competent sponsor representative will determine whether an SAP is necessary.
Suppose an SAP(Statistical Analysis Plan) is necessary. In such a situation, the trial statistician and CI must prepare and approve it before distributing the randomization code and any interim analysis for blinded trials (or before the start of analysis in an unblinded trial).
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Version control should be used throughout the SAP development process to make it easier to identify the final SAP (which will be included in the Clinical Study Report: CSR).
Information in the SAP
The SAP(Statistical Analysis Plan) should be based on the statistical considerations part of the trial protocol and should include the following:
- Statistics on who wrote the SAP, its version number, when it was approved, and who signed it.
- The sample size calculation’s relevant assumptions and the anticipated number of participants.
- A thorough explanation of the main and any interim analyses used in the data analysis technique. This comprises:
- The goals of the study were outlined in the trial protocol.
- To fulfill the trial’s intended objectives outlined in the protocol, the primary and secondary hypotheses must be specified, and any parameters that need to be estimated must be specified.
- A precise description of the cohorts to be utilized in the clinical trial’s final analysis, such as Intention-To-Treat (ITT), as randomized, etc.
- A summary of every trial’s primary and secondary outcomes. It is anticipated that only one main primary consequence would be found. The SAP should specify how each outcome measure will be measured. The statistical tests are used to analyze the outcome measures and the method for accounting for missing data.
- The SAP(Statistical Analysis Plan) should also thoroughly explain the procedures used to analyze and display the study results.
- The level of statistical significance to be employed, as well as whether one-tailed or two-tailed tests will be used.
- Methods for dealing with missing data.
- Methods for dealing with outliers.
- Procedures for dealing with protocol variations, noncompliance, and withdrawals.
- Methods for estimating points and intervals.
- Rules for calculating composite or derived variables, including data-driven definitions and any additional details required to minimize ambiguity.
- Baseline and covariate data are used.
- Inclusion of randomization factors (if applicable).
- Methods for dealing with data from several locations.
- Methods for dealing with treatment interactions
- Methods for multiple comparisons and subgroup analysis
- Interim or sequential analyses are planned.
- Procedures for terminating a clinical trial and accounting for this in the analysis
- Computer systems and statistical software packages used to analyze data are specified.
- Critical analysis assumptions and sensitivity analyses are checked using these methods.
- Tables and figures for presenting study data
- The safe population is defined.
- The SAP must include provisions for testing the statistical model and information on alternative methods if the test assumptions are unmet.
Making Modifications to SAP
- Any modifications to the statistical analysis procedures indicated in the research setting and/or SAP must be well regulated, fully justified, and recorded in the Statistical Report. The Trial Statistician and Chief Investigator should also agree upon them.
- Because protocol compliance is a legal necessity, the SAP should correspond with the statistical considerations part of the study protocol.
- Any statistical analyses in the SAP that are not following the research protocol should be reported to the sponsor to determine whether a protocol revision is required.
Conclusion
A well-written and detailed Statistical Analysis Plan (SAP) is essential for improving the validity and generalizability of clinical trials and other specific research.
The SAP is a clear framework of the anticipated statistical basic/advanced procedures for clinical trial analysis, written in the study protocol and independently. SAP is critical in creating a clinical trial and is one of the essential regulatory private papers.
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