Multiple patient samples of an analyte improve detection of changes in clinical status

* Context.--When comparing results over time, biologic variation must be statistically incorporated into the evaluation of laboratory results to identify a physiologic change. Traditional methods compare the difference in 2 values with the standard deviation (SD) of the biologic variation to indicate whether a 'true' physiologic change has occurred. Objective.--To develop methodology to reduce the effect of biologic variation on the difference necessary to detect changes in clinical status in the presence of biologic variation. Design.--The standard test for change compares the difference between 2 points with the 95% confidence limit, given as [+ or -]1.96 x [square root of 2 x SD]. We examined the effect of multiple data pairs on the confidence limit. Results.--Increasing the number of data pairs using the formula 1.96 x [square root of 2/n x Sd], where n = number of data pairs, significantly reduces the difference between values necessary to achieve a 95% confidence limit. Conclusions.--Evaluating multiple paired sets of patient data rather than a single pair results in a substantial decrease in the difference between values necessary to achieve a given confidence interval, thereby improving the sensitivity of the evaluation. A practice of using multiple patient samples results in enhanced power to detect true changes in patient physiology. Such a testing protocol is warranted when small changes in the analyte precede serious clinical events or when the SD of the biologic variation is large. (Arch Pathol Lab Med. 2010;134:81-89)
Clinicians rely on laboratory tests to monitor the progression or remission of disease, or to identify pathologic alterations in physiology that may precede clinical events. Monitoring quantitative laboratory results represents [...]