Statistical evaluation of diagnostic tests: A primer for pediatric surgeons.

BACKGROUND/PURPOSE: Diagnostic tests are of paramount importance for informing decision making in the surgical setting. Certain statistical methods are necessary to properly analyze data for diagnostic or prognostic tests involving biomarkers and risk factor data. Our goal is to provide a useful primer for the surgical researcher when performing a diagnostic research study in order to best analyze their data.

METHODS

We present the key concepts and statistics for diagnostic tests and receiver operating characteristic (ROC) curve analysis, and we illustrate each with hypothetical surgery research examples. We use hypothetical data regarding CT imaging and WBC count in their diagnostic ability in predicting acute appendicitis, an extremely common surgical condition, while reviewing the statistical concepts of sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, relative risk, odds ratio, and ROC curves. Then we will consider a hypothetical a risk factor analysis on 30-day readmission to illustrate how multiple predictors can be combined.

CONCLUSIONS

The statistical concepts presented are useful to the pediatric surgeon researcher in assessing the ability of diagnostic tests, which will translate into decision making and patient management implications in the clinical setting.

TYPE OF STUDY

Review Article LEVEL OF EVIDENCE: N/A.