Background Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA) using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity. Methods We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv, and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites. Results Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from − 6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 and 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset. Conclusions RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond 10 days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias, so the positivity rates are probably overestimated.
ObjectiveTo systematically review methods developed and employed to evaluate the diagnostic accuracy of medical test when there is a missing or no gold standard.Study design and settingsArticles that proposed or applied any methods to evaluate the diagnostic accuracy of medical test(s) in the absence of gold standard were reviewed. The protocol for this review was registered in PROSPERO (CRD42018089349).ResultsIdentified methods were classified into four main groups: methods employed when there is a missing gold standard; correction methods (which make adjustment for an imperfect reference standard with known diagnostic accuracy measures); methods employed to evaluate a medical test using multiple imperfect reference standards; and other methods, like agreement studies, and a mixed group of alternative study designs. Fifty-one statistical methods were identified from the review that were developed to evaluate medical test(s) when the true disease status of some participants is unverified with the gold standard. Seven correction methods were identified and four methods were identified to evaluate medical test(s) using multiple imperfect reference standards. Flow-diagrams were developed to guide the selection of appropriate methods.ConclusionVarious methods have been proposed to evaluate medical test(s) in the absence of a gold standard for some or all participants in a diagnostic accuracy study. These methods depend on the availability of the gold standard, its’ application to the participants in the study and the availability of alternative reference standard(s). The clinical application of some of these methods, especially methods developed when there is missing gold standard is however limited. This may be due to the complexity of these methods and/or a disconnection between the fields of expertise of those who develop (e.g. mathematicians) and those who employ the methods (e.g. clinical researchers). This review aims to help close this gap with our classification and guidance tools.
Background Ventilator-associated pneumonia is the most common intensive care unit (ICU)-acquired infection, yet accurate diagnosis remains difficult, leading to overuse of antibiotics. Low concentrations of IL-1β and IL-8 in bronchoalveolar lavage fluid have been validated as effective markers for exclusion of ventilator-associated pneumonia. The VAPrapid2 trial aimed to determine whether measurement of bronchoalveolar lavage fluid IL-1β and IL-8 could effectively and safely improve antibiotic stewardship in patients with clinically suspected ventilator-associated pneumonia. Methods VAPrapid2 was a multicentre, randomised controlled trial in patients admitted to 24 ICUs from 17 National Health Service hospital trusts across England, Scotland, and Northern Ireland. Patients were screened for eligibility and included if they were 18 years or older, intubated and mechanically ventilated for at least 48 h, and had suspected ventilator-associated pneumonia. Patients were randomly assigned (1:1) to biomarker-guided recommendation on antibiotics (intervention group) or routine use of antibiotics (control group) using a web-based randomisation service hosted by Newcastle Clinical Trials Unit. Patients were randomised using randomly permuted blocks of size four and six and stratified by site, with allocation concealment. Clinicians were masked to patient assignment for an initial period until biomarker results were reported. Bronchoalveolar lavage was done in all patients, with concentrations of IL-1β and IL-8 rapidly determined in bronchoalveolar lavage fluid from patients randomised to the biomarker-based antibiotic recommendation group. If concentrations were below a previously validated cutoff, clinicians were advised that ventilator-associated pneumonia was unlikely and to consider discontinuing antibiotics. Patients in the routine use of antibiotics group received antibiotics according to usual practice at sites. Microbiology was done on bronchoalveolar lavage fluid from all patients and ventilator-associated pneumonia was confirmed by at least 10⁴ colony forming units per mL of bronchoalveolar lavage fluid. The primary outcome was the distribution of antibiotic-free days in the 7 days following bronchoalveolar lavage. Data were analysed on an intention-to-treat basis, with an additional per-protocol analysis that excluded patients randomly assigned to the intervention group who defaulted to routine use of antibiotics because of failure to return an adequate biomarker result. An embedded process evaluation assessed factors influencing trial adoption, recruitment, and decision making. This study is registered with ISRCTN, ISRCTN65937227, and ClinicalTrials.gov, NCT01972425. Findings Between Nov 6, 2013, and Sept 13, 2016, 360 patients were screened for inclusion in the study. 146 patients were ineligible, leaving 214 who were recruited to the study. Four patients were excluded before randomisation, meaning that 210 patients were randomly assigned to biomarker-guided recommendation on antibiotics (n=104) or routine us...
Background Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA), using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity. Methods We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites. Findings Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from -6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 to 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset. Interpretation RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond ten days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias so the positivity rates are probably overestimated.
Summary Background The updated American Joint Committee on Cancer (AJCC) staging criteria for melanoma remain unable to identify high‐risk stage I tumour subsets. Objectives To determine the utility of epidermal autophagy and beclin 1 regulator 1 (AMBRA1)/loricrin (AMLo) expression as a prognostic biomarker for AJCC stage I cutaneous melanoma. Methods Peritumoral AMBRA1 expression was evaluated in a retrospective discovery cohort of 76 AJCC stage I melanomas. AMLo expression was correlated with clinical outcomes up to 12 years in two independent powered, retrospective validation and qualification cohorts comprising 379 AJCC stage I melanomas. Results Decreased AMBRA1 expression in the epidermis overlying primary melanomas in a discovery cohort of 76 AJCC stage I tumours was associated with a 7‐year disease‐free survival (DFS) rate of 81·5% vs. 100% survival with maintained AMBRA1 (P < 0·081). Following an immunohistochemistry protocol for semi‐quantitative analysis of AMLo, analysis was undertaken in validation (n = 218) and qualification cohorts (n = 161) of AJCC stage I melanomas. Combined cohort analysis revealed a DFS rate of 98·3% in the AMLo low‐risk group (n = 239) vs. 85·4% in the AMLo high‐risk cohort (n = 140; P < 0·001). Subcohort multivariate analysis revealed that an AMLo hazard ratio (HR) of 4·04 [95% confidence interval (CI) 1·69–9·66; P = 0·002] is a stronger predictor of DFS than Breslow depth (HR 2·97, 95% CI 0·93–9·56; P = 0·068) in stage IB patients. Conclusions Loss of AMLo expression in the epidermis overlying primary AJCC stage I melanomas identifies high‐risk tumour subsets independently of Breslow depth. What's already known about this topic? There is an unmet clinical need for biomarkers of early‐stage melanoma. Autophagy and beclin 1 regulator 1 (AMBRA1) is a proautophagy regulatory protein with known roles in cell proliferation and differentiation, and is a known tumour suppressor. Loricrin is a marker of epidermal terminal differentiation. What does this study add? AMBRA1 has a functional role in keratinocyte/epidermal proliferation and differentiation. The combined decrease/loss of peritumoral AMBRA1 and loricrin is associated with a significantly increased risk of metastatic spread in American Joint Committee on Cancer (AJCC) stage I tumours vs. melanomas, in which peritumoral AMBRA1 and loricrin are maintained, independently of Breslow depth. What is the translational message? The integration of peritumoral epidermal AMBRA1/loricrin biomarker expression into melanoma care guidelines will facilitate more accurate, personalized risk stratification for patients with AJCC stage I melanomas, thereby facilitating stratification for appropriate follow‐up and informing postdiagnostic investigations, including sentinel lymph node biopsy, ultimately resulting in improved disease outcomes and rationalization of healthcare costs.
Diagnostic tests are expensive and time-consuming to develop. Early economic evaluation using decision modeling can reduce commercial risk by providing early evidence on cost-effectiveness. The National Institute for Health Research Diagnostic Evidence Co-operatives (DECs) was established to catalyze evidence generation for diagnostic tests by collaborating with commercial developers; DEC researchers have consequently made extensive use of early modeling. The aim of this article is to summarize the experiences of the DECs using early modeling for diagnostics. We draw on 8 case studies to illustrate the methods, highlight methodological strengths and weaknesses particular to diagnostics, and provide advice. The case studies covered diagnosis, screening, and treatment stratification. Treatment effectiveness was a crucial determinant of cost-effectiveness in all cases, but robust evidence to inform this parameter was sparse. This risked limiting the usability of the results, although characterization of this uncertainty in turn highlighted the value of further evidence generation. Researchers evaluating early models must be aware of the importance of treatment effect evidence when reviewing the cost-effectiveness of diagnostics. Researchers planning to develop an early model of a test should also 1) consult widely with clinicians to ensure the model reflects real-world patient care; 2) develop comprehensive models that can be updated as the technology develops, rather than taking a “quick and dirty” approach that may risk producing misleading results; and 3) use flexible methods of reviewing evidence and evaluating model results, to fit the needs of multiple decision makers. Decision models can provide vital information for developers at an early stage, although limited evidence mean researchers should proceed with caution.
Bringing a diagnostic point of care test (POCT) to a healthcare market can be a painful experience as it requires the manufacturer to meet considerable technical, financial, managerial, and regulatory challenges. In this opinion article we propose a framework for developing the evidence needed to support product development, marketing, and adoption. We discuss each step in the evidence development pathway from the invention phase to the implementation of a new POCT in the healthcare system. We highlight the importance of articulating the value propositions and documenting the care pathway. We provide guidance on how to conduct care pathway analysis as little has been published on this. We summarize the clinical, economic and qualitative studies to be considered for developing evidence, and provide useful links to relevant software, on-line applications, websites, and give practical advice. We also provide advice on patient and public involvement and engagement (PPIE), and on product management. Our aim is to help device manufacturers to understand the concepts and terminology used in evaluation of in vitro diagnostics (IVDs) so that they can communicate effectively with evaluation methodologists, statisticians, and health economists. Manufacturers of medical tests and devices can use the proposed framework to plan their evidence development strategy in alignment with device development, applications for regulatory approval, and publication.
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