Quanticate's Medical Writing Team have summarized tips for the preparation of comprehensive, well-written, and focused integrated summary documentation.
Integrated Summary Tips:
Worst practices for producing an integrated summary
- Not providing one!
- Being too brief
- Excluding data that do not support the effectiveness conclusions
- Excluding pertinent safety data
- Pooling data that should not be pooled
- Replying on results from post hot meta analyses
- Discussing experimental endpoints, rather than focusing on primary and co-primary endpoints
- Including datasets without explaining how they were derived
Initial preparation for authors, contributors and reviewers
- Always ensure most up-to-date templates and relevant regulatory guidelines are consulted and used throughout the project life cycle
- Use professional approved style guides, and detail how to cover items not covered in style guides upfront
- Use standardized methods for citation/referencing
- Train authors to write granular documents
- Train reviewers to review electronically
Planning for Lifecycle Management
- Employ methods and tools for information sharing and knowledge management early in the process
- Reviewers need to know what has changed and why
- Consider impact of changes on future documents
- Incorporate best practices for change history
Improved Reviewability
- User effective hyperlinks and bookmarks; all documents from protocol through to summary should be hyperlinked and bookmarked at time of preparation rather than at the end
- Write with electronic review in mind – FDA Good Review Practices
- Create an efficient work flow
- Produce submission-ready documents at all stages – employ a consistent QC checklist to make this happen
Get the Basics Right - Writing
- Clear, concise, objective statements
- Acceptable grammar and punctuation
- Consistent writing style and Quality Control (QC) checklists to ensure intra and inter document consistency
- Accurately crafted key messages; no mixed messages; same message throughout; focus on label claims
- Ensure scientific interpretation, not regurgitation
- Easy-to-read layout: 100% zoom, 12 pt font, Times New Roman
- Easy to navigate - sufficient and accurate hyperlinks and bookmarks
- Find the right balance between content re-use and avoid redundant repitition. Content does not mean simply copying and pasting from one document to another
- Avoid repeating detail already given in the individual summaries of clinical trials; Don't cut and paste - hyperlink instead
- For legacy trials, use the body of the Clinical Study Report (CSR) as the source, not the CSR sypnosis
Get the Basics Right - Statistics
- Don't use secondary data unless they support label claims or reveal an issue
- Provide comprehensive, detailed, in-depth analysis of results in aggregate with a clear rationale for the methods used
- Utilise both positive and negative trials
- Compare trials of similar designs: Weighting of sample size; Examine by common covariates or stratifications; Consider controls, durations, parent populations, endpoints, dropouts, statistical analyses
- Consider inconsistencies in the data
- Consider areas needing further exploration
Safety Summaries
- Choose a single dictionary, and include dictionary and version in the methods. If older dictionaries used and re-coding is not possible, include details and/or a footnote to explain
- Consistent terminology (e.g., If presenting >5% common adverse events [AEs], use this cut-off throughout)
- Reference Quantitiative Satefy Analysis Plans (QSAPs) where applicable
- Discuss statistical issues with AEs; search the database for related AEs
- Always show gender specific denominators
- Mention denominator over time
- Graph representation is good
- Present clinically significant criteria for laboratory, ECGm vital signs and AEs; where applicable, referencing most current criteria
- Multiple labs - ensure reference ranges in same unit of measure (applying conversions, where necessary)
- Lab ranges and lab cut-offs often come up when reviewing
Efficacy Summaries
- Mention limitations of sample size
- Age, sex, race and geographic location; clinically relevant demographic factors
- Consider US versus non-US - Does this have an impact on efficacy? Describe regional differences
- Deal with the drop outs - planned versus actual
- Consider and discuss risk benefit
- Analyse postive and negative findings
- Focus on pre-specified endpoints
- Consider sub-populations
- Use graphical representations such as Forest Plots
- Data format is important (e.g., convert to the same unit of measure)
- Use tables to combine and present data. All cells should have something or it may be construed as missing; use consistent footnote symbol order for every table
- When pooling data, discuss and present selection process
- State and discuss problems; it provides a more credible analysis
- Include clinical information relevant to dose recommendations and individual dose responses
- Listings are not required anymore by FDA; SAS viewer is used

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Authors note: This blog was originally published on 05/04/2012 and has since been updated.