TL;DR
Stochastic simulation software is developed and used to calculate and visualize the detection power of complex QC rule combinations, including traditional Westgard rules as well as statistical tests of multiple QC repeats, with arbitrary degrees of multiplexing and levels of control.
Accessible molecular diagnostics is fundamental to effective healthcare. While most current point-of-care devices detect only the presence of a molecular biomarker(s), biomarker quantification can be equally important for decision-making on disease treatment and containment. Here, we present a diagnostic platform that enables the equipment-free quantification of molecular biomarkers with the simplicity of a binary (yes/no) readout. This capability is achieved by integrating a stoichiometric quantitative approach with widely available and easy-to-use lateral flow dipsticks. To implement the approach, we engineer negative cooperativity into target–probe binding interactions for oligonucleotide targets as a model system. The resulting threshold-based semi-quantitative assay with lateral flow dipsticks quantifies targets in the low-nanomolar range and operates reliably in complex biological backgrounds. A key advantage of this platform is its potential adaptability to new and emerging targets: repurposing will require only reagent redesign, without the need for additional fabrication.
Background Although clinical laboratories routinely implement internal quality control (IQC) to ensure the reliability of test results, emergency immunoassay testing introduces unique operational challenges. To mitigate financial burdens, some laboratories arbitrarily extend IQC batch lengths or reduce the number of quality control (QC) samples per analytical run. This study evaluated baseline IQC practices for emergency immunoassays across five laboratories in Suining, China, aiming to provide evidence-based guidance for regional quality improvement. Methods Average daily test volumes, external quality assessment (EQA) results, and historical IQC data were retrospectively collected from the five laboratories. Sigma metrics were calculated for each analyte. Concurrently, the “Westgard Sigma Rule with Run Length” nomogram was applied to design individualized, risk-based statistical quality control (RB-SQC) procedures. Results All emergency immunoassays, except for serum procalcitonin, were subjected to routine IQC across all five laboratories; notably, certain analytes followed an extended 72-h IQC batch interval. Within individual laboratories, QC rules, the number of QC results per batch, and batch lengths were consistent across analytes but varied between laboratories. Under the current QC scheme, the QC utilization rate (N/M-1) was 0.087 (0.047–0.143), which decreased significantly to 0.020 (0.004–0.133) after implementing RB-SQC procedures (N/M-2; Z = 3.154, P < 0.05), suggesting that RB-SQC may reduce QC material and reagent consumption while maintaining acceptable patient risk. However, arbitrary adjustments to batch lengths or the number of QC results may lead to elevated or reduced QC utilization rates. Conclusions Baseline IQC practices for emergency immunoassays in the surveyed laboratories were inconsistent and lacked a standardized risk-based foundation. We recommend that clinical laboratories implement individualized RB-SQC protocols designed using the Westgard Sigma Rule with Run Length nomogram, and periodically reassess their appropriateness based on updated sigma metrics.
Metrology facilitates the advancement of accurate, SI-traceable measurements. In many cases for molecular measurements, there is a lack of standardization of methods across laboratories and platforms which leads to variability in results. Standardizing methods may promote accuracy and reproducibility and facilitate data comparison across studies and platforms. Polymerase chain reaction (PCR) based techniques represent an ideal first diagnostic solution for infectious pathogens and are deployed to detect the genomes of infectious agents (DNA/RNA) as they can be quickly designed and demonstrate high sensitivity and specificity. The COVID-19 pandemic demonstrated how diagnostic testing was crucial in tracking and diagnosing patients infected with SARS-CoV-2, but initial testing was largely unstandardized and it is possible that patients were incorrectly diagnosed as a result. Digital PCR (dPCR) is a single molecule enumeration technique that can reproducibly quantify nucleic acid sequences without using calibration, offering a route to provide reference values to support PCR testing and diagnostics. dPCR has been used for quantitative detection of pathogens and has been established to serve as a potential reference measurement procedure (RMP) for the accurate quantification of nucleic acids from pathogens such as Mycobacterium tuberculosis, human cytomegalovirus, human immunodeficiency virus-1, some of which are already listed as reference methods in the JCTLM database. In the recent study, National Metrology Institutes/Designated Institutes (NMIs/DIs) developed a potential reverse transcription-dPCR (RT-dPCR)-based RMP for SARS-CoV-2 RNA. This approach was deployed to support external quality assurance (EQA) by assigning metrologically traceable values to whole viral SARS-CoV-2 EQA material. The value assignment standardized the SARS-CoV-2 RNA concentration and was used to determine the limit of detection. This collaboration has led to the support of international standardization of molecular testing using dPCR as an RMP, thereby ensuring accurate and reproducible nucleic acid reference values for the EQA materials. Current activities include participation in the CCQM Nucleic Acid Working Group (NAWG) for international interlaboratory comparison studies (pilot and key comparisons) to support the development of SI-traceable dPCR based RMPs. This poster will describe some of the recent work on dPCR-based RMPs and discuss how this can be applied to improve nucleic acid analysis measurements on a global scale in EQA schemes, clinical laboratories and harmonization studies for infectious disease diagnostics.
Accurate and comparable quantification of somatic mutations is essential for precision oncology, as clinical decision-making increasingly relies on the quantification of molecular biomarkers. Despite major technological advances, inter-laboratory variability and the lack of metrological traceability remain significant barriers to harmonization and confidence in mutation testing results. Reference Measurement Procedures (RMPs) represent a critical framework to address these challenges by anchoring molecular measurements to common quantitative standards. Here, we describe the development and validation of a candidate RMP for the detection and quantification of the clinically relevant NRAS p.Q61R mutation using digital PCR (dPCR). The assay was systematically optimized to maximize specificity and minimize cross-reactivity between wild-type and mutant alleles. Analytical characterization demonstrated excellent linearity across a broad range of variant allele frequencies (vAF), with a limit of detection of 0.1 %. Precision studies performed on commercially available circulating tumour DNA reference materials (RM) showed good repeatability and intermediate precision, while a full measurement uncertainty budget confirmed the robustness of the approach. Comparison with a commercial dPCR assay provided independent support for assay comparability and consistent vAF estimates across the investigated range. Preliminary inter-laboratory assessment supported transferability of the candidate RMP and comparability of the resulting measurements. Overall, this work establishes a metrologically characterized and transferable dPCR-based RMP for NRAS p.Q61R quantification. Its implementation can support the harmonization of molecular measurements, the value assignment of RM, and the alignment of routine and secondary methods, thereby strengthening the reliability of quantitative biomarker assessment in precision oncology.