In Vitro Diagnostic Research Articles

Precisely designed growth of dual-color quantum dots bilayer nanobeads for ratiometric fluorescent immunoassay

Colloidal quantum dots (QDs) have been widely used as fluorescent labeling materials in the field of in vitro diagnostics (IVD). In spite of the significant development of direct single-signal response fluorescent immunosensors, it is still a challenge to obtain the high accuracy and sensitivity of quantitative results of these sensors due to the influence of several factors unrelated to the analysis. Herein, we present a delicate design and synthesis of dual-color QDs bilayer nanobeads (red and green QDs nanobeads, R&G-QD nanobeads), achieving the precisely control of growth of the silicon layer with different proportions of ammonia, and inhibiting fluorescence resonance energy transfer (FRET) successfully. The dual-color QDs bilayer nanobeads have realized dual-channel detection (the acquisition of two emission wavelengths) of the target, and avoided the problems of low analytical accuracy and imprecise sensitivity of single-signal response. A proof-of-concept demonstration of a fluorescence-linked immunosorbent assay (FLISA) platform is conducted for the quantitative detection of prostate-specific antigen (PSA) with a sensitivity of 49 pg/mL and a linear range of 0.2–800 ng/mL. The dual-color QDs bilayer nanobeads FLISA platform with high sensitivity and accuracy holds great potential for early diagnosis of cancer or other diseases and provides a new approach for IVD.

Image-based real-time feedback control of magnetic digital microfluidics by artificial intelligence-empowered rapid object detector for automated in vitro diagnostics.

In vitro diagnostics (IVD) plays a critical role in healthcare and public health management. Magnetic digital microfluidics (MDM) perform IVD assays by manipulating droplets on an open substrate with magnetic particles. Automated IVD based on MDM could reduce the risk of accidental exposure to contagious pathogens among healthcare workers. However, it remains challenging to create a fully automated IVD platform based on the MDM technology because of a lack of effective feedback control system to ensure the successful execution of various droplet operations required for IVD. In this work, an artificial intelligence (AI)-empowered MDM platform with image-based real-time feedback control is presented. The AI is trained to recognize droplets and magnetic particles, measure their size, and determine their location and relationship in real time; it shows the ability to rectify failed droplet operations based on the feedback information, a function that is unattainable by conventional MDM platforms, thereby ensuring that the entire IVD process is not interrupted due to the failure of liquid handling. We demonstrate fundamental droplet operations, which include droplet transport, particle extraction, droplet merging and droplet mixing, on the MDM platform and show how the AI rectify failed droplet operations by acting upon the feedback information. Protein quantification and antibiotic resistance detection are performed on this AI-empowered MDM platform, and the results obtained agree well with the benchmarks. We envision that this AI-based feedback approach will be widely adopted not only by MDM but also by other types of digital microfluidic platforms to offer precise and error-free droplet operations for a wide range of automated IVD applications.

Diagnostic Accuracy of Human Immunodeficiency Virus In Vitro Assays Evaluated by the World Health Organization Prequalification Evaluation Laboratories: Systematic Review and Meta-Analysis.

To maintain the performance quality, human immunodeficiency virus (HIV) in vitro diagnostic (IVD) kits are required to be evaluated by unbiased health regulatory organizations following predefined guidelines. The World Health Organization (WHO) prequalification is one such program for the evaluation of IVD assays. In the present systematic review and meta-analysis, we analyzed and compared the 17 WHO prequalified public reports of HIV IVDs to yield summarized information for performance parameters. Pooled sensitivity, pooled specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were used as overall performance evaluation parameters. High (≥98%) and comparable levels of sensitivity and specificity were observed for most of the assays. In addition, the overall diagnostic efficiency was observed to attain high precision, as evident by the value of the area under the curve (AUC) for the hierarchical summary receiver operating characteristic curve (AUC ≥ 0.98).

Abstract P251: Assay Performance And System Compatibility For RAAS Triple-A Analysis In Hypertension Profiling

Recent studies revealed major concerns related to the accuracy of widely used clinical assays for aldosterone and renin, fueling the need for alternative and more robust bio-analytical solutions for assessment of the Renin-Angiotensin-Aldosterone-System (RAAS) in clinical samples. RAAS Triple-A profiling is a high-throughput mass-spectrometry based assay for quantification of Angiotensin I (Ang I), Angiotensin II (Ang II) and Aldosterone in serum samples. Quantified hormone levels are used to calculate markers for plasma-renin-activity (PRA-S), plasma angiotensin-converting-enzyme activity (ACE-S) and adrenal aldosterone secretion (AA2-Ratio), which can be used for clinical profiling in patients with uncontrolled hypertension. A RAAS Triple-A LC-MS/MS kit was recently launched as an In Vitro Diagnostic (IVD) device in Europe for hypertension profiling. In the current study, a comparative approach was used to assess analytical performance of the RAAS Triple-A assay on three different LC-MS/MS systems, Altis+ (Thermo Scientific), Xevo TQ-S (Waters), and Triple Quad 6500+ (Sciex) located in three different laboratories. RAAS Triple-A kits (96-well format) were used to analyze one set of n=50 triplicate human serum samples at each location. At each site, samples were sample preparation and LC-MS/MS analysis according to the RAAS Triple-A kit manual. Analytical validation of assay linearity, precision, and accuracy were evaluated at each site, and Bland-Altman-Analysis was used to test for quantification bias between sites. Results demonstrate the measured concentrations for each analyte, Ang I, Ang II, and aldosterone, were strongly correlated between sites (R 2 = Ang I: 0.996; Ang II: 0.991; Aldo: 0.983). Performance characteristics of all target analytes were in compliance with European Medical Agency (EMA) standards for bio-analytical assays on each instrument. Robust assay performance across laboratories and different LC-MS/MS systems allows for a broad clinical application of RAAS Triple-A profiling potentially improving treatment efficacy in hypertension by supporting treatment decisions with individual RAAS Triple-A profiles.

Smart Diagnostics: Combining Artificial Intelligence and In Vitro Diagnostics.

We are beginning a new era of Smart Diagnostics—integrated biosensors powered by recent innovations in embedded electronics, cloud computing, and artificial intelligence (AI). Universal and AI-based in vitro diagnostics (IVDs) have the potential to exponentially improve healthcare decision making in the coming years. This perspective covers current trends and challenges in translating Smart Diagnostics. We identify essential elements of Smart Diagnostics platforms through the lens of a clinically validated platform for digitizing biology and its ability to learn disease signatures. This platform for biochemical analyses uses a compact instrument to perform multiclass and multiplex measurements using fully integrated microfluidic cartridges compatible with the point of care. Image analysis digitizes biology by transforming fluorescence signals into inputs for learning disease/health signatures. The result is an intuitive Score reported to the patients and/or providers. This AI-linked universal diagnostic system has been validated through a series of large clinical studies and used to identify signatures for early disease detection and disease severity in several applications, including cardiovascular diseases, COVID-19, and oral cancer. The utility of this Smart Diagnostics platform may extend to multiple cell-based oncology tests via cross-reactive biomarkers spanning oral, colorectal, lung, bladder, esophageal, and cervical cancers, and is well-positioned to improve patient care, management, and outcomes through deployment of this resilient and scalable technology. Lastly, we provide a future perspective on the direction and trajectory of Smart Diagnostics and the transformative effects they will have on health care.

Asymmetric Mach-Zehnder Interferometric Biosensing for Quantitative and Sensitive Multiplex Detection of Anti-SARS-CoV-2 Antibodies in Human Plasma.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic has once more emphasized the urgent need for accurate and fast point-of-care (POC) diagnostics for outbreak control and prevention. The main challenge in the development of POC in vitro diagnostics (IVD) is to combine a short time to result with a high sensitivity, and to keep the testing cost-effective. In this respect, sensors based on photonic integrated circuits (PICs) may offer advantages as they have features such as a high analytical sensitivity, capability for multiplexing, ease of miniaturization, and the potential for high-volume manufacturing. One special type of PIC sensor is the asymmetric Mach–Zehnder Interferometer (aMZI), which is characterized by a high and tunable analytical sensitivity. The current work describes the application of an aMZI-based biosensor platform for sensitive and multiplex detection of anti-SARS-CoV-2 antibodies in human plasma samples using the spike protein (SP), the receptor-binding domain (RBD), and the nucleocapsid protein (NP) as target antigens. The results are in good agreement with several CE-IVD marked reference methods and demonstrate the potential of the aMZI biosensor technology for further development into a photonic IVD platform.

Next generation biosensors employing molecularly imprinted polymers as sensing elements for in vitro diagnostics

Biosensors for in vitro diagnostics (IVD) have huge potential and are likely to play a significant role in advanced as well as in the low resource healthcare setups. With time, these devices are gaining traction in cardiac diagnosis, cancer, autoimmune diseases and pathogenic microbial infections. Periodical advancements in nanomaterials employed in biosensors have led to miniaturization and improved characteristics of both plasmonic and electrical sensors. Mostly antibodies are employed in the development of IVD however, there are challenges due to the fragile nature of these biological molecules that adversely affects the storage and shelf life of biosensors. Ongoing developments in the synthesis of artificial antibodies or MIPs that offer improved stability, selectivity and multiplexing ability facilitates their application in biosensors for IVD. In addition, versatility and facile synthesis protocols of MIPs enable their rapid integration into mass manufacturing systems. Here, we discuss the changing dynamics of IVD enabled by MIP based biosensors. We will mainly focus on microbes and clinically relevant biomarkers that have been targeted for infectious disease detection and different imprinting strategies relevant to them. The biosensor platforms employing MIPs for their POC and IVD potential for biological samples have been discussed. The commercial potential of MIPs which has translated into 8 commercial platforms so far including IVD have been delineated. To improve the performance of MIPs in general, the computationally aided MIP design that is actively focused to address some of the challenges associated with the translation of MIPs for various applications including IVD have been discussed.

Experience with a Continuous Education Program for Clinical, Regulatory and Quality Affairs in Northwestern Switzerland.

The European Medical Device and In-Vitro Diagnostic Medical Device industry is currently facing a highly challenging situation, as applied regulations have changed significantly over the last year. To cope with this, a novel continuing education program for employees from these sectors provides knowledge and hands-on experience in clinical, regulatory and quality affairs. Since 2020 two classes have been successfully completed at the University of Applied Sciences and Arts Northwestern Switzerland: this paper describes the concept and content, the students, and the benefits both for participants and their employers.

A digital assay for programmed death-ligand 1 (22C3) quantification combined with immune cell recognition algorithms in non-small cell lung cancer

PD-L1 (22C3) checkpoint inhibitor therapy represents a mainstay of modern cancer immunotherapy for non-small cell lung cancer (NSCLC). In vitro diagnostic (IVD) PD-L1 antibody staining is widely used to predict clinical intervention efficacy. However, pathologist interpretation of this assay is cumbersome and variable, resulting in poor positive predictive value concerning patient therapy response. To address this, we developed a digital assay (DA) termed Tissue Insight (TI) 22C3 NSCLC, for the quantification of PD-L1 in NSCLC tissues, including digital recognition of macrophages and lymphocytes. We completed clinical validation of this digital image analysis solution in 66 NSCLC patient samples, followed by concordance studies (comparison of PD-L1 manual and digital scores) in an additional 99 patient samples. We then combined this DA with three distinct immune cell recognition algorithms for detecting tissue macrophages, alveolar macrophages, and lymphocytes to aid in sample interpretation. Our PD-L1 (22C3) DA was successfully validated and had a scoring agreement (digital to manual) higher than the inter-pathologist scoring. Furthermore, the number of algorithm-identified immune cells showed significant correlation when compared with those identified by immunohistochemistry in serial sections stained by double immunofluorescence. Here, we demonstrated that TI 22C3 NSCLC DA yields comparable results to pathologist interpretation while eliminating the intra- and inter-pathologist variability associated with manual scoring while providing characterization of the immune microenvironment, which can aid in clinical treatment decisions.

Critical Implications of IVDR for Innovation in Diagnostics: Input From the BioMed Alliance Diagnostics Task Force.

Critical Implications of IVDR for Innovation in Diagnostics: Input From the BioMed Alliance Diagnostics Task Force.

This Issue's Featured Solutions

Inside Precision MedicineVol. 9, No. 3 MarketplaceFree AccessThis Issue's Featured SolutionsPublished Online:18 Jun 2022https://doi.org/10.1089/ipm.09.03.18AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Custom Reagents and Services For Molecular DiagnosticsAt Fortis Life Sciences, we know what it takes to succeed. We first work with you to understand your specific challenges and then our experts will design, develop, manufacture, and validate complete assay solutions for your molecular diagnostic assay.Decision SupportGenomOncology's precision oncology solutions enhance decision support by combining proprietary technologies, curation processes, data-delivery systems, and public and licensed annotation sets, with internal clinical dataOLINK® TARGETOlink® Target allows for more focused studies on a specific area of disease or key biological processes, targeting 96 or 48 biomarkers. The Target readout uses qPCR.Companion Diagnostic (CDx) ServicesQ2 Solutions® has a venerable track record of successfully supporting drug developers and in-vitro diagnostic (IVD) companies in many global CDx programs, from the early stages of biomarker validation through clinical trials testing and commercialization.FiguresReferencesRelatedDetails Volume 9Issue 3Jun 2022 InformationCopyright © GEN PublishingTo cite this article:This Issue's Featured Solutions.Inside Precision Medicine.Jun 2022.69-69.http://doi.org/10.1089/ipm.09.03.18Published in Volume: 9 Issue 3: June 18, 2022PDF download

Cost-Effectiveness of PD-L1 Testing in Non-Small Cell Lung Cancer (NSCLC) Using In Vitro Diagnostic (IVD) Versus Laboratory-Developed Test (LDT).

Accurate PD-L1 testing for non-small cell lung cancer (NSCLC) maximizes the benefits of immune checkpoint inhibitor (ICI) drugs like pembrolizumab. False negative test results deny ICI treatments to eligible patients, worsening clinical and economic outcomes, while false positives increase costs by using ICI treatments without their benefits. This study evaluates the cost-effectiveness of PD-L1 testing with an invitro diagnostic (IVD) compared to a laboratory-developed test (LDT) for allocating patients with NSCLC to treatment with either pembrolizumab or chemotherapy using the German healthcare system as a model. We developed a decision analytical model to evaluate the cost-effectiveness of PD-L1 testing with a regulatory body approved IVD compared to an LDT from the national German healthcare payer (statutory health insurance system) perspective. Accuracy of PD-L1 testing was based on data from two independent proficiency testing programs. The 1-year model was based on outcomes data from the KEYNOTE-024 clinical trial and treatment patterns reflecting current German practices. IVDs produced accurate PD-L1 testing results in 93% (752/811) of tested cases compared to 73% (492/672) with LDTs. Most misclassifications concerned false negatives, occurring in 21% of LDTs vs 7% of IVDs. Total costs of the IVD group (48,878€) were 196€ higher than the LDT group (48,682€). These costs incorporate testing, first- and second-line therapy, managing treatment-related grade3+ adverse events (AEs), and end-of-life costs for those who died within the year. Total effectiveness (percentage of patients successfully diagnosed and prescribed the correct therapy per German treatment guidelines) was 19 percentage points higher for the IVD group (88%) compared to the LDT group (69%). These differences in costs and effects lead to an incremental cost-effectiveness ratio (ICER) of 1057€. Compared to LDT technology, on-label IVD use for PD-L1 testing is only slightly more costly and substantially more effective for aligning patients with PD-L1-positive NSCLC with ICI therapy according to German practice guidelines. Given these findings, changes to testing and reimbursement policies may be considered to maximize patient outcomes in NSCLC.

The Pre-Analytical CEN/TS Standard for Microbiome Diagnostics-How Can Research and Development Benefit?

Recently, CEN/TS 17626:2021, the European pre-analytical standard for human specimens intended for microbiome DNA analysis, was published. Although this standard relates to diagnostic procedures for microbiome analysis and is relevant for in vitro diagnostic (IVD) manufacturers and diagnostic laboratories, it also has implications for research and development (R&D). We present here why standards are needed in biomedical research, what pre-analytical standards can accomplish, and which elements of the pre-analytical workflow they cover. The benefits of standardization for the generation of FAIR (findable, accessible, interoperable, reusable) data and to support innovation are briefly discussed.

Comparison of disk diffusion, MIC test strip and broth microdilution methods for cefiderocol susceptibility testing on carbapenem-resistant enterobacterales

ObjectivesCefiderocol is a catechol-substituted cephalosporin dedicated to the treatment of infections caused by multidrug resistant gram-negative rods. Cefiderocol susceptibility testing might be complex. We compared cefiderocol susceptibility testing methods on a relevant collection of carbapenem-resistant Enterobacterales. MethodsCE-IVD (European CE marking required for all in vitro diagnostic (IVD)) broth microdilution (BMD) plate (ThermoFisher, Waltham, MA, USA) using regular Mueller-Hinton broth, MIC test strip (Liofilchem, Teramo, Italy), and disk diffusion (Liofilchem) were compared to a frozen BMD plate prepared with iron depleted Mueller-Hinton broth. First, a collection of 100 entirely sequenced carbapenem-resistant Enterobacterales was used to compare these methods. Then, a prospective comparison of disk diffusion and CE-IVD BMD was performed on 827 consecutive carbapenem non-susceptible Enterobacterales including 634 carbapenemase-producers. ResultsCompared to reference method, CE-IVD BMD plate gave 95.0% (95% CI, 88.8–97.9) categorisation agreement (CA), 2.8% (95% CI, 0.4–14.2) very major errors (VME), and 1.6% (95% CI, 0.3–8.7) major errors (ME) with high reproducibility. MIC strip gave only 63% (95% CI, 53.2–71.8) of CA and 94.9% (95% CI, 83.1–98.6) of VME due to critical underestimation of the MICs. Disk diffusion gave 77% (95% CI, 67.9–84.2) CA with additional 8% of the isolates within the area of technical uncertainty of 18–22 mm.Prospectively, disk diffusion gave 81.7% (95% CI, 79.0–84.2) CA, 23.3% (95% CI, 15.1–34.2%)VME, and 4.9% (95% CI, 3.6–6.7) ME. Additionally, 21.3% (95% CI, 18.6–24.2) of CRE were within the area of technical uncertainty. DiscussionCommercial CE-IVD BMD (ThermoFisher) is accurate for cefiderocol MIC determination in difficult-to-treat Enterobacterales whereas MIC test strip (Liofilchem), that was formulated for Pseudomonas aeruginosa only, should be avoided. Disk diffusion might be useful for screening, but many of these CRE have to be re-tested using BMD to assess definitive categorization.

Artificial intelligence reinforced upconversion nanoparticle-based lateral flow assay via transfer learning

The combination of upconverting nanoparticles (UCNPs) and immunochromatography has become a widely used and promising new detection technique for point-of-care testing (POCT). However, their low luminescence efficiency, non-specific adsorption, and image noise have always limited their progress toward practical applications. Recently, artificial intelligence (AI) has demonstrated powerful representational learning and generalization capabilities in computer vision. We report for the first time a combination of AI and upconversion nanoparticle-based lateral flow assays (UCNP-LFAs) for the quantitative detection of commercial internet of things (IoT) devices. This universal UCNPs quantitative detection strategy combines high accuracy, sensitivity, and applicability in the field detection environment. By using transfer learning to train AI models in a small self-built database, we not only significantly improved the accuracy and robustness of quantitative detection, but also efficiently solved the actual problems of data scarcity and low computing power of POCT equipment. Then, the trained AI model was deployed in IoT devices, whereby the detection process does not require detailed data preprocessing to achieve real-time inference of quantitative results. We validated the quantitative detection of two detectors using eight transfer learning models on a small dataset. The AI quickly provided ultra-high accuracy prediction results (some models could reach 100% accuracy) even when strong noise was added. Simultaneously, the high flexibility of this strategy promises to be a general quantitative detection method for optical biosensors. We believe that this strategy and device have a scientific significance in revolutionizing the existing POCT technology landscape and providing excellent commercial value in the in vitro diagnostics (IVD) industry.

The Current Landscape and Emerging Applications for Real-World Data in Diagnostics and Clinical Decision Support and its Impact on Regulatory Decision Making.

Real-world data (RWD) and real-world evidence (RWE) are becoming essential tools for informing regulatory decision making in health care and offer an opportunity for all stakeholders in the healthcare ecosystem to evaluate medical products throughout their lifecycle. Although considerable interest has been given to regulatory decisions supported by RWE for treatment authorization, especially in rare diseases, less attention has been given to RWD/RWE related to in vitro diagnostic (IVD) products and clinical decision support systems (CDSS). This review examines current regulatory practices in relation to IVD product development and discusses the use of CDSS in assisting clinicians to retrieve, filter, and analyze patient data in support of complex decisions regarding diagnosis and treatment. The review then explores how utilizing RWD could augment regulatory body understanding of test performance, clinical outcomes, and benefit-risk profiles, and how RWD could be leveraged to augment CDSS and improve safety, quality, and efficiency of healthcare practices. Whereas we present examples of RWD assisting in the regulation of IVDs and CDSS, we also highlight key challenges within the current healthcare system which are impeding the potential of RWE to be fully realized. These challenges include issues such as data availability, reliability, accessibility, harmonization, and interoperability, often for reasons specific to diagnostics. Finally, we review ways that these challenges are actively being addressed and discuss how private-public collaborations and the implementation of standardized language and protocols are working toward producing more robust RWD and RWE to support regulatory decision making.

Performance of Idylla™RAS-BRAF mutation test for formalin-fixed paraffin-embedded tissues of colorectal cancer

BackgroundThe Biocartis Idylla™ platform is a fully automated, real-time PCR-based diagnostic system. The Idylla™KRAS and NRAS-BRAF Mutation Tests have been developed for the qualitative detection of mutations in KRAS, NRAS and BRAF genes, facilitating the genomic profiling of patients with colorectal cancer. The aim of the present study was to evaluate clinical performances of these tests in Japan.MethodsThe RAS and BRAF mutation statuses of 253 formalin-fixed paraffin-embedded (FFPE) colorectal cancer tissues were analyzed using the Investigational Use Only Idylla™KRAS Mutation Test and the Idylla™NRAS-BRAF Mutation Test and an in vitro diagnostics (IVD) kit (MEBGEN RASKET™-B kit).ResultsThe success rate for obtaining a valid mutational data without retest of the Idylla tests was 97.6% (247/253): 111 KRAS mutations (43.8%), 9 NRAS mutations (3.6%), and 36 BRAF V600E mutations (14.2%) were detected using the Idylla tests. Compared with the MEBGEN RASKET-B results, the positive concordance rate was 97.4%, the negative concordance rate was 95.7%, and the overall concordance rate was 95.3% (κ = 0.919, 95% CI 0.871–0.967). The average turnaround time to Idylla™KRAS and NRAS-BRAF Mutation Test was 5.6 working days (range: 3–11 days).ConclusionThis result demonstrates a high concordance between the Idylla™KRAS and NRAS-BRAF Mutation Tests and an existing IVD kit. In this manner, the Idylla™ mutation tests were validated for the detection of clinically significant KRAS, NRAS, and BRAF mutations in FFPE samples from colorectal cancer patients.

Examining the effect of evaluation sample size on the sensitivity and specificity of COVID-19 diagnostic tests in practice: a simulation study

BackgroundIn response to the global COVID-19 pandemic, many in vitro diagnostic (IVD) tests for SARS-CoV-2 have been developed. Given the urgent clinical demand, researchers must balance the desire for precise estimates of sensitivity and specificity against the need for rapid implementation. To complement estimates of precision used for sample size calculations, we aimed to estimate the probability that an IVD will fail to perform to expected standards after implementation, following clinical studies with varying sample sizes.MethodsWe assumed that clinical validation study estimates met the ‘desirable’ performance (sensitivity 97%, specificity 99%) in the target product profile (TPP) published by the Medicines and Healthcare products Regulatory Agency (MHRA). To estimate the real-world impact of imprecision imposed by sample size we used Bayesian posterior calculations along with Monte Carlo simulations with 10,000 independent iterations of 5,000 participants. We varied the prevalence between 1 and 15% and the sample size between 30 and 2,000. For each sample size, we estimated the probability that diagnostic accuracy would fail to meet the TPP criteria after implementation.ResultsFor a validation study that demonstrates ‘desirable’ sensitivity within a sample of 30 participants who test positive for COVID-19 using the reference standard, the probability that real-world performance will fail to meet the ‘desirable’ criteria is 10.7–13.5%, depending on prevalence. Theoretically, demonstrating the 'desirable' performance in 90 positive participants would reduce that probability to below 5%. A marked reduction in the probability of failure to hit ‘desirable’ specificity occurred between samples of 100 (19.1–21.5%) and 160 (4.3–4.8%) negative participants. There was little further improvement above sample sizes of 160 negative participants.ConclusionBased on imprecision alone, small evaluation studies can lead to the acceptance of diagnostic tests which are likely to fail to meet performance targets when deployed. There is diminished return on uncertainty surrounding an accuracy estimate above a total sample size of 250 (90 positive and 160 negative).

Clinical Importance of Superior Sensitivity of the Aptima TMA-Based Assays for Mycoplasma genitalium Detection.

Mycoplasma genitalium (MG) is a common cause of nongonococcal cervicitis and urethritis. We investigated the demographic and clinical characteristics of patients tested in Denmark with the Conformité Européenne (CE)/in vitro diagnostics (IVD) Aptima Mycoplasma genitalium assay (CE/IVD AMG; Hologic) and examined the clinical significance of the higher sensitivity of the TMA-based MG assays. From March to June 2016, urogenital and extragenital specimens from consecutive attendees at a sexually transmitted infection clinic in Copenhagen, Denmark were tested with the CE/IVD AMG assay (TMA-based), the research-use-only MG Alt TMA-1 assay (Hologic), a laboratory-developed TaqMan mgpB quantitative real-time PCR (qPCR), and the Aptima Combo 2 (CT/NG; Hologic). Demographic characteristics and clinical symptoms were collected from the patient records. There were 1,245 patients included in the study. The MG prevalence among female subjects was 9.4%, and the MG prevalence among male subjects was 8.7%. Compared to the TMA-based assays, the sensitivity of the PCR-based MG assay was 64.52%, and 55 specimens from 48 individuals were missed in the mgpB qPCR. Of these, 26 individuals (54.2%) were symptomatic, whereas, among 64 individuals with concordant results, 30 individuals (46.9%) were symptomatic; no statistically significant difference was found between the groups (P = 0.567). The improved sensitivity of the TMA-based assays resulted in diagnoses of more patients with clinically relevant symptoms for which antibiotic treatment is indicated. However, approximately half of the MG-infected patients reported no symptoms, and future research is needed to investigate the pros and cons of diagnosing and treating MG in asymptomatic subjects.

Nanomaterials-assisted metabolic analysis toward in vitro diagnostics.

In vitro diagnostics (IVD) has played an indispensable role in healthcare system by providing necessary information to indicate disease condition and guide therapeutic decision. Metabolic analysis can be the primary choice to facilitate the IVD since it characterizes the downstream metabolites and offers real-time feedback of the human body. Nanomaterials with well-designed composition and nanostructure have been developed for the construction of high-performance detection platforms toward metabolic analysis. Herein, we summarize the recent progress of nanomaterials-assisted metabolic analysis and the related applications in IVD. We first introduce the important role that nanomaterials play in metabolic analysis when coupled with different detection platforms, including electrochemical sensors, optical spectrometry, and mass spectrometry. We further highlight the nanomaterials-assisted metabolic analysis toward IVD applications, from the perspectives of both the targeted biomarker quantitation and untargeted fingerprint extraction. This review provides fundamental insights into the function of nanomaterials in metabolic analysis, thus facilitating the design of next-generation diagnostic devices in clinical practice.