Common Pitfalls in Analysis of Tissue Scores

Area of Science:

• Biomedical Research
• Pathology
• Biostatistics

Background:

• Histopathology provides essential descriptive biological data.
• Reproducibility in scientific studies highlights the importance of tissue scoring.
• Accurate statistical analysis validates group comparisons and pathologist interpretation.

Purpose of the Study:

• To identify common statistical analysis pitfalls in histopathology tissue scoring.
• To guide pathologists in selecting appropriate statistical tests for tissue-scoring data.
• To enhance the validity and reproducibility of biomedical research findings.

Main Methods:

• Review of common statistical tests and their underlying assumptions.
• Identification of frequent errors in the analysis of semiquantitative and quantitative tissue scores.
• Emphasis on understanding experimental design and data characteristics (e.g., paired vs. unpaired, normality, group number).

Main Results:

• Three common pitfalls in tissue score analysis are identified: "shopping for significance," overuse of paired t-tests, and misguided analysis of multiple groups.
• Mismatched statistical test assumptions with data can lead to erroneous interpretations.
• Appropriate statistical test selection is influenced by study design and data properties.

Conclusions:

• Pathologists should be aware of common statistical pitfalls in tissue scoring.
• Utilizing resources like statistical software, key publications, and statisticians is recommended.
• Choosing the correct statistical test ensures the most valid interpretation of tissue-scoring data for enhanced research reproducibility.