Research statistical method seemingly non-transferrable to clinical pathology practice: A case for d-dimer quantitative testing

Research statistical method seemingly non-transferrable to clinical pathology practice: A case for d-dimer quantitative testing

Background
Plasma D-dimer data are often not normally distributed. In the research setting, such data is non-parametric and statistical analysis is often based on log-transformed data. In the clinical pathology, results are not transformed, but interpreted as it is.

Objective
Plasma D-dimer data are often not normally distributed. In the research setting, such data is non-parametric and statistical analysis is often based on log-transformed data. In the clinical pathology, results are not transformed, but interpreted as it is.

Methods
This was a critical review of cross-sectional laboratory data. A total of ninety samples comprising N = 30 per group were equally selected from groups from a pool of plasma D-dimer tests. The three groups were control, diabetes mellitus (DM), and diabetes plus cardiovascular (DM + CVD) disease. A descriptive analysis and comparison were performed on log-transformed and untransformed data.

Results
ANOVA on untransformed data showed non-significant difference between groups, but the log normalized data achieved statistical significance (p < 0.03). Comparing the DM with DM + CVD groups, mean value is higher in DM group of untransformed data, but lower in the same data when it is log-transformed.

Conclusion
There is need to clarify the background statistics behind the reference values recommended in various quantitative kits- whether it is based on log-transformed or untransformed data. Either the researcher who transforms data or the clinician who does not transform result would need to review the correctness of employing the recommendations on the reagent kit to interpret results.