Assays with lower detection limits: implications for epidemiological investigations

Abstract

Epidemiological investigations of health effects related to chronic low-level exposures or other circumstances often face the difficult task of dealing with levels of biomarkers that are hard to detect and/or quantify. In these cases instrumentation may not adequately measure biomarker levels. Reasons include a failure of instruments to detect levels below a certain value or, alternatively, interference by error or 'noise'. Current laboratory practice determines a 'limit of detection (LOD)', or some other detection threshold, as a function of the distribution of instrument 'noise'. Although measurements are produced above and below this threshold in many circumstances, rather than numerical data, all points observed below this threshold may be reported as 'not detected'. The focus of this process of determination of the LOD is instrument noise and avoiding false positives. Moreover, uncertainty is assumed to apply only to the lowest values, which are treated differently from above-threshold values, thereby potentially creating a false dichotomy. In this paper we discuss the application of thresholds to measurement of biomarkers and illustrate how conventional approaches, though appropriate for certain settings, may fail epidemiological investigations. Rather than automated procedures that subject observed data to a standard threshold, the authors advocate investigators to seek information on the measurement process and request all observed data from laboratories (including the data below the threshold) to determine appropriate treatment of those data.

Figure 1

The data as observed and after imputation for below-threshold values – polychlorinated biphenyl congener number 105 in paired serum and adipose tissue samples as measured by gas chromatography-mass spectrometry, and after blank subtraction and recovery adjustment. ■, observations; ——, estimated regression line; •, observations after imputation; - -·- -, estimated regression line after imputation; ┋, limit of detection (LOD). Most data points are below the LOD at 0.02159 pg/mL serum. Utilising all observed data points regardless of the LOD results in an estimated regression line with intercept equal to 3.3 and slope equal to 139.3. The estimated regression line after imputation of 0.01080 (LOD/2) for below-threshold points has intercept equal to 2.6 and slope equal to 161.0.