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The estimation of limits of detection (LOD) for solely qualitative methods in analytical chemistry may prove challenging because all the approaches with which chemists are familiar require some type of numeric data input. The best model to describe the binary response in these methods (detected/not detected) is a logistic model; however, these models are not easily handled by most of the laboratories and generally demand expensive statistical software packages. In this work, the advantages of applying this approach are discussed and its implementation using commercial spreadsheet software is demonstrated. A free online application based on the R environment using shinyapps was developed and its application was validated and discussed with a dataset of 57 different target compounds analyzed in urine according to the requirements of the World Anti‐Doping Agency (WADA). This tool allows free, extremely quick, and easy determinations of LOD in qualitative analyses as well as the determination of the probabilities of detection in any given concentration.

Cholesterol is one of the most frequently measured substances in human blood/serum to assist in assessing the health status of individuals. Because of its clinical significance, CCQM-K6 determination of cholesterol in serum was completed in 2000 as one of the first key comparison (KC) studies performed within the Organic Analysis Working Group (OAWG). The first subsequent KC for cholesterol, CCQM-K6.1, was completed in 2001. Measurements for this second subsequent, CCQM-K6.2, were completed in 2012. These subsequent comparisons were conducted to enable CCQM members that had not participated in earlier studies to demonstrate their capabilities to measure a nonpolar (pKow < −2), low molecular mass (100 g/mol to 500 g/mol) metabolite in human serum at relatively high concentrations (1 mg/g to 3 mg/g) found in normal populations. Successful participation in CCQM-K6.2 demonstrated capabilities in analysis of complex biological matrices including sample preparation (extraction, derivatization), LC or GC separation, and quantification using an isotope dilution mass spectrometry approach. Normally in a subsequent KC, no key comparison reference value (KCRV) would be established and assessment of performance would be via the deviation of participants' results to the anchor institute's results, adjusted to account for the anchor's performance in the original comparison versus its KCRV. Due to the very long-time period since the original key comparison, the OAWG decided that this did not represent the best approach to assess performance in what is a relatively complex measurement. Given the excellent agreement between the anchor institute's results and robust consensus summary of the participants' values, the reference value for this study was taken as the anchor institute's result and treated as a 'KCRV'. Seven of the nine participants demonstrated agreement with the reference value. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Glucose and creatinine are two of the most frequently measured substances in human blood/serum for assessing the health status of individuals. Because of their clinical significance, CCQM-K11 Glucose in Human Serum and CCQM-K12 Creatinine in Human Serum were the fourth and fifth Key Comparisons (KCs) performed by the Organic Analysis Working Group (OAWG). These KCs were conducted in parallel and were completed in 2001. The initial Subsequent KCs for glucose, CCQM-K11.1, and creatinine, CCQM-K12.1, were completed in 2005. Measurements for the next KCs for these two measurands, CCQM-K11.2 and CCQM-K12.2, were completed in 2013. While designed as Subsequent KCs, systematic discordances between the participants' and the anchor institution's results in both comparisons lead the OAWG to request reference results from two experienced laboratories that had participated in the 2001 comparisons. Based on the totality of the available information, the OAWG converted both CCQM-K11.2 and CCQM-K12.2 to "Track C" KCs where the Key Comparison Reference Value is estimated by consensus. These comparisons highlighted that carrying out comparisons for complex chemical measurements and expecting to be able to treat them under the approaches used for formal subsequent comparisons is not an appropriate strategy. The approach used here is a compromise to gain the best value from the comparison; it is not an approach that will be used in the future. Instead, the OAWG will focus on Track A and Track C comparisons that are treated as stand-alone entities. Participation in CCQM-K11.2 demonstrates a laboratory's capabilities to measure a polar (pKow > 2), low molecular mass (100 g/mol to 500 g/mol) metabolite in human serum at relatively high concentrations (0.1 mg/g to 10 mg/g). Participation in CCQM-K12.2 demonstrates capabilities to measure similar classes of metabolites at relatively low concentrations (1 µg/g to 30 µg/g). The capabilities required for the analysis of complex biological matrices include sample preparation (protein precipitation, extraction, derivatization), gas chromatographic (GC) or liquid chromatographic (LC) separation, and quantification using an isotope dilution mass spectrometry (IDMS) approach.