Assessing Statistical Techniques for Comparing Biomarkers with Values Below Detection

Music City Center 

Biomarkers are increasingly important in diagnosing and treating cancer. However, due to instruments' inability to measure biomarker signals below a certain threshold, such observations are left censored and classified as Below the Level of Detection (BLoD). Incorporating data from these biomarkers into analysis presents significant challenges. Most of the literature focuses on estimating the location parameter and evaluating their efficiency. However, interest often lies in comparing biomarkers between groups, such as cases and controls. Typically, one would apply an estimation method and then use appropriate techniques to compare the groups. The evaluation of the performance of these methods in the context of comparing two groups has not been performed. In our analysis, we perform a comparison study of common method used for data subject to a Level of Detection (DL) and assess their efficacy regarding a case-control study framework for the comparison of two groups. We also assess the robustness of the test procedures when the underlying distribution is not lognormal. We examine the usefulness of these test procedures by applying them to a dataset from St. Jude on IL-6.

Censored data

Below the Limit of Detection

Biomarkers

Lognormal

Robustness

Interleukin 6 

Biopharmaceutical Section