Bonnie LaFleur1, Wooin Lee2, Dean Billhiemer3, Craig Lockhart4, Junmei Liu5, Nipun Merchant6
1Department of Epidemiology and Biostatistics, BIO5, University of Arizona, Tucson, AZ, USA
2Department of Pharmaceutical Sciences, University of Kentucky, Lexington KY, USA
3Department of Agricultural and Biosystems Engineering and Statistical Consulting Laboratory, BIO5, University of Arizona, Tucson, AZ, USA
4Department of Medicine, Washington University, St. Louis, MO, USA
5Statistical Consulting Laboratory, BIO5, University of Arizona, Tucson, AZ, USA
6Department of Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
DOI: 10.4103/1477-3163.79681
ABSTRACT
In analytic chemistry a detection limit (DL) is the lowest measurable amount of an analyte that can be distinguished from a blank; many biomedical measurement technologies exhibit this property. From a statistical perspective, these data present inferential challenges because instead of precise measures, one only has information that the value is somewhere between 0 and the DL (below detection limit, BDL). Substitution of BDL values, with 0 or the DL can lead to biased parameter estimates and a loss of statistical power. Statistical methods that make adjustments when dealing with these types of data, often called left-censored data, are available in many commercial statistical packages. Despite this availability, the use of these methods is still not widespread in biomedical literature. We have reviewed the statistical approaches of dealing with BDL values, and used simulations to examine the performance of the commonly used substitution methods and the most widely available statistical methods. We have illustrated these methods using a study undertaken at the Vanderbilt-Ingram Cancer Center, to examine the serum bile acid levels in patients with colorectal cancer and adenoma. We have found that the modern methods for BDL values identify disease-related differences that are often missed, with statistically naive approaches.
Keywords: Bile acids, colorectal cancer, detection limits, statistical methods.