scholarly journals Variation in the Accuracy of Endpoint Selection in Clinical Studies for Rare Diseases in Respect of Increasing Knowledge on Disease-Severity Measurement

2021 ◽  
Author(s):  
Ravi Jandhyala
Keyword(s):  
Disease Severity ◽  
Rare Diseases ◽  
Clinical Studies ◽  
False Positive ◽  
False Negative ◽  
Neutral Theory ◽  
Disease Prevalence ◽  
Type I ◽  
Prevalence Rates ◽  
Over Time

Abstract Background: Previous research assessed the accuracy of disease-severity measurement in clinical studies as a mathematical relationship between the set of endpoints selected and the disease-severity scale (DSS), a surrogate for the theoretical Neutral list of indicators representing the disease phenotype. New DSSs are continually developed, so clinical studies’ operationalisation of the Neutral list and resulting relative neutrality may vary over time. We assessed variation in the neutrality of clinical studies over time and the probability of false positive and false negative classifications at different disease prevalence rates.Methods: We used search strings extracted from the Orphanet Register of Rare Diseases using a proprietary algorithm to conduct a systematic review of studies published until January 2021 per Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Overall, 483 studies and 12 rare diseases met inclusion criteria. We extracted all indicators from clinical studies and calculated neutrality and its components, sensitivity and specificity, as well as the probability of misclassifications at 20%, 50% and 80% disease prevalence rates at two time points, the times of publication of the first and last DSS. Surrogate Neutral lists were the first DSS and a composite of all later DSSs.Results: Over time, the neutrality of clinical studies increased for six diseases and decreased for five diseases, driven by sensitivity for all but Friedreich ataxia. The neutrality of clinical studies in encephalitis decreased, but sensitivity remained constant at zero. At both timepoints, the likely false negative rate increased and the likely false positive rate decreased with increasing disease prevalence. The probability that the least neutral clinical study for most diseases would yield a false positive result was equal to one at all disease prevalence rates. Conclusions: The potential for accurate clinical trial disease-severity measurement increases over time. Neutral theory showed that endpoint selection and DSSs may need improvement in Charcot Marie Tooth disease, Gaucher disease Type I, Huntington’s disease, Sjogren’s syndrome and Tourette syndrome. Using Neutral theory to benchmark disease-severity measurement in rare disease clinical trials may reduce the risk of misclassification, ensuring that recruitment and treatment effect assessment optimise medicine adoption and benefit patients.

scholarly journals CD169/SIGLEC1 is expressed on circulating monocytes in COVID-19 and expression levels are associated with disease severity

Infection ◽  
2021 ◽  
Author(s):  
Jan-Moritz Doehn ◽  
Christoph Tabeling ◽  
Robert Biesen ◽  
Jacopo Saccomanno ◽  
Elena Madlung ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Disease Severity ◽  
Clinical Studies ◽  
Viral Infections ◽  
Severe Disease ◽  
Type I Interferons ◽  
Type I ◽  
Interferon Signaling ◽  
Expression Levels

AbstractCoronavirus disease 2019 (COVID-19) is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Type I interferons are important in the defense of viral infections. Recently, neutralizing IgG auto-antibodies against type I interferons were found in patients with severe COVID-19 infection. Here, we analyzed expression of CD169/SIGLEC1, a well described downstream molecule in interferon signaling, and found increased monocytic CD169/SIGLEC1 expression levels in patients with mild, acute COVID-19, compared to patients with severe disease. We recommend further clinical studies to evaluate the value of CD169/SIGLEC1 expression in patients with COVID-19 with or without auto-antibodies against type I interferons.

scholarly journals Incorporation of Second-Tier Biomarker Testing Improves the Specificity of Newborn Screening for Mucopolysaccharidosis Type I

2020 ◽  
Vol 6 (1) ◽  
pp. 10 ◽  
Author(s):  
Dawn S. Peck ◽  
Jean M. Lacey ◽  
Amy L. White ◽  
Gisele Pino ◽  
April L. Studinski ◽  
...  
Keyword(s):  
Newborn Screening ◽  
False Positive ◽  
Dermatan Sulfate ◽  
False Positive Rate ◽  
False Negative ◽  
Type I ◽  
Mucopolysaccharidosis Type ◽  
Mucopolysaccharidosis Type I ◽  
Second Tier ◽  
Mps I

Enzyme-based newborn screening for Mucopolysaccharidosis type I (MPS I) has a high false-positive rate due to the prevalence of pseudodeficiency alleles, often resulting in unnecessary and costly follow up. The glycosaminoglycans (GAGs), dermatan sulfate (DS) and heparan sulfate (HS) are both substrates for α-l-iduronidase (IDUA). These GAGs are elevated in patients with MPS I and have been shown to be promising biomarkers for both primary and second-tier testing. Since February 2016, we have measured DS and HS in 1213 specimens submitted on infants at risk for MPS I based on newborn screening. Molecular correlation was available for 157 of the tested cases. Samples from infants with MPS I confirmed by IDUA molecular analysis all had significantly elevated levels of DS and HS compared to those with confirmed pseudodeficiency and/or heterozygosity. Analysis of our testing population and correlation with molecular results identified few discrepant outcomes and uncovered no evidence of false-negative cases. We have demonstrated that blood spot GAGs analysis accurately discriminates between patients with confirmed MPS I and false-positive cases due to pseudodeficiency or heterozygosity and increases the specificity of newborn screening for MPS I.

Trial Sequential Analysis in Meta-Analyses of Maintenance Therapies for Multiple Myeloma.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2975-2975
Author(s):  
Branko Miladinovic ◽  
Ambuj Kumar ◽  
Rahul Mhaskar ◽  
Helen Mahoney ◽  
Keith Wheatley ◽  
...  
Keyword(s):  
Randomized Controlled Trials ◽  
Risk Ratio ◽  
False Positive ◽  
False Negative ◽  
Trial Sequential Analysis ◽  
Controlled Trials ◽  
Type I ◽  
Randomized Controlled ◽  
Meta Analyses ◽  
Ratio Reduction

Abstract Abstract 2975 Background: Meta-analyses (MAs) with few participants (i.e. small number of primary studies) are at risk of producing random errors and consequently overestimating treatment effects. With insufficient information the risk of obtaining a false positive result (type I error) increases, which may lead to false conclusions. Trial sequential analysis (TSA) has been proposed as a method to ascertain whether results of MAs are conclusive (true vs. false positive, true vs. false negative). It adjusts for the risk of random error by constructing monitoring boundaries under the sample size necessary to conclude significant treatment effect. In TSA, the information size is calculated based on a pre-specified event rate in the control group, a minimum intervention effect (risk ratio reduction), and a desired maximum risk of type I error α and type II error β. Here we apply TSA on MAs of randomized controlled trials of maintenance therapies in the management of multiple myeloma. Methods: A comprehensive literature search of MEDLINE (PubMed), the Cochrane Central Register of Controlled Trials (CENTRAL), and meetings abstracts from American Society of Hematology, American Society of Clinical Oncology, European Society for Medical Oncology and European Hematology Association was undertaken to identify all phase III randomized controlled trials (RCTs) of maintenance therapy published until July 2012. We extracted data on overall survival and progression-free survival comparing treatments that could be pooled in random effects meta-analysis. We performed TSA for the apriori diversity-adjusted information size (APDIS) under risk ratio reduction of 20% and 25%. The information size was adjusted for between-study trial diversity, which is defined as the total relative variance expansion changing from a fixed effect into a random effects meta-analysis. We used two-sided α = 5% and 1 – β = 80% power. All analyses were done in Stata 11.2 using metacumbounds command. Results: Nine separate meta-analyses (18 randomized controlled trials) met the inclusion criteria (Table 1). The median number of patients was 1193 (range 351–2824) and median diversity 0% (range 0%-91%). Under both risk ratio reductions of 20% and 25%, 4/9 MAs were false negative and 1/9 false positive. The observed power based on the accrued sample size and observed risk ratio reduction was greater than 80% in 5/9 MAs. Conclusion: TSA detected one false positive MA of two trials comparing thalidomide with prednisone/dexamethosone for the outcome of overall survival. Future MAs need to consistently undertake TSA to avoid misleading conclusions. Disclosures: No relevant conflicts of interest to declare.

scholarly journals A statistical model of COVID-19 testing in populations: effects of sampling bias andtesting errors

2021 ◽  
Vol 380 (2214) ◽  
Author(s):  
Lucas Böttcher ◽  
Maria R. D'Orsogna ◽  
Tom Chou
Keyword(s):  
Statistical Model ◽  
Disease Surveillance ◽  
Data Science ◽  
Sample Selection ◽  
False Negative ◽  
Sampling Bias ◽  
Disease Prevalence ◽  
Type I ◽  
Actual Case ◽  
Multiple Test

We develop a statistical model for the testing of disease prevalence in a population. The model assumes a binary test result, positive or negative, but allows for biases in sample selection and both type I (false positive) and type II (false negative) testing errors. Our model also incorporates multiple test types and is able to distinguish between retesting and exclusion after testing. Our quantitative framework allows us to directly interpret testing results as a function of errors and biases. By applying our testing model to COVID-19 testing data and actual case data from specific jurisdictions, we are able to estimate and provide uncertainty quantification of indices that are crucial in a pandemic, such as disease prevalence and fatality ratios. This article is part of the theme issue ‘Data science approach to infectious disease surveillance’.

scholarly journals A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors

2021 ◽  
Author(s):  
Lucas Böttcher ◽  
Tom Chou ◽  
Maria R. D'Orsogna
Keyword(s):  
Statistical Model ◽  
Sample Selection ◽  
False Negative ◽  
Sampling Bias ◽  
Disease Prevalence ◽  
Type I ◽  
Actual Case ◽  
Multiple Test ◽  
Testing Data ◽  
Case Data

We develop a statistical model for the testing of disease prevalence in a population. The model assumes a binary test result, positive or negative, but allows for biases in sample selection and both type I (false positive) and type II (false negative) testing errors. Our model also incorporates multiple test types and is able to distinguish between retesting and exclusion after testing. Our quantitative framework allows us to directly interpret testing results as a function of errors and biases. By applying our testing model to COVID-19 testing data and actual case data from specific jurisdictions, we are able to estimate and provide uncertainty quantification of indices that are crucial in a pandemic, such as disease prevalence and fatality ratios.

scholarly journals Agreement between results of meta-analyses from case reports and clinical studies, regarding efficacy and safety of idursulfase therapy in patients with mucopolysaccharidosis type II (MPS-II). A new tool for evidence-based medicine in rare diseases

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Miguel Sampayo-Cordero ◽  
Bernat Miguel-Huguet ◽  
Almudena Pardo-Mateos ◽  
Andrea Malfettone ◽  
José Pérez-García ◽  
...  
Keyword(s):  
Rare Diseases ◽  
Clinical Studies ◽  
Case Reports ◽  
Meta Analysis ◽  
Type I ◽  
Mucopolysaccharidosis Type ◽  
Type Ii ◽  
Mucopolysaccharidosis Type Ii ◽  
Mps Ii ◽  
Meta Analyses

Abstract Background A preliminary exploratory study shows solid agreement between the results of case reports and clinical study meta-analyses in mucopolysaccharidosis Type I (MPS-I) adult patients. The aim of the present study is to confirm previous results in another patient population, suffering from mucopolysaccharidosis Type II (MPS-II). Methods A systematic review and meta-analysis of case reports published by April 2018 was conducted for MPS-II patients treated with enzyme replacement therapy (ERT). The study is reported in accordance with PRISMA and MOOSE guidelines (PROSPERO database code CRD42018093408). The assessed population and outcomes were the same as previously analyzed in a meta-analysis of MPS-II clinical studies. The primary endpoint was the percent of clinical cases showing improvement in efficacy outcome, or no harm in safety outcome after ERT initiation. A restrictive procedure to aggregate case reports, by selecting standardized and well-defined outcomes, was proposed. Different sensitivity analyses were able to evaluate the robustness of results. Results Every outcome classified as “acceptable evidence group” in our case report meta-analysis had been graded as “moderate strength of evidence” in the aforementioned meta-analysis of clinical studies. Sensitivity, specificity, and positive-negative predictive values for results of both meta-analyses reached 100%, and were deemed equivalent. Conclusions Aggregating case reports quantitatively, rather than analyzing them qualitatively, may improve conclusions in rare diseases and personalized medicine. Additionally, we propose some methods to evaluate publication bias and heterogeneity of the included studies in a meta-analysis of case reports.

811 WHETHER 10 WATER SWALLOWS NECESSARY TO OBTAIN REPRODUCIBLE RESULTS OF HIGH-RESOLUTION OESOPHAGEAL MANOMETRY?

2021 ◽  
Vol 34 (Supplement_1) ◽  
Author(s):  
Sergey Morozov ◽  
Vasily Kropochev ◽  
Alexey Artemov
Keyword(s):  
High Resolution ◽  
Diagnostic Accuracy ◽  
False Positive ◽  
Roc Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Ratio Test ◽  
Type I ◽  
Primary Position ◽  
Oesophageal Manometry

Abstract   Not less than ten wet swallows assessment in the primary test position is recommended by Chicago classification 4.0 for high-resolution oesophageal manometry (HREM); however, the required number of measurements are not sufficiently supported. Aim to evaluate the number of wet swallows necessary for correct interpretation of the results of lower esophageal sphincter integrated relaxation pressure (IRP) with low probability of type I and II errors. Methods Patients referred to perform HREM were enrolled. Solid-state 10Fr catheter and Solar (Laborie) software were used. Minimum 10 swallows by 5 mL water were obtained. These were analysed for cumulative means of IRP after 1…9 measurements. Conclusion made at each moment was compared with one based on 10 measurements. The results were characterized as true/false positive/negative for calculation of diagnostic accuracy. To exclude sample influence, Monte-Carlo simulation of sequential decision-making was performed with the use of sequential probability ratio test. Association of the diagnostic accuracy from recall was studied with the use of receiver operating characteristic curve (ROC) analysis. Results One hundred subjects were enrolled (25 with disorders of EGJ outflow). During the simulation, the probability of matching the decisions based on the 10 measurements and lower number of them was high. ROC analysis showed that actual probability to obtain false-positive results was twice as lower then ‘allowed’ rate of 5%. The probability to make false-negative results did not exceed 10% in any number of measurements. The probability that the conclusions made after 2 and after 10 measurements match was 0.9584 in those with disorders of EGJ outflow and 0.9652 in those without (figure 1). Conclusion The standard number of measurements required to support the presence of disorders of EGJ outflow during evaluation of 5 mL wet swallows in the primary position is excessive. Values of the IRP after 2 swallows allows to make similar decision to that after 10 swallows with >95% probability. This allows to reduce the number of wet swallows to assess in the primary position and save time for assessments in alternative position or perform provocation tests.

A Clinical Analysis of Dupuytren’s Disease of the Thumb

2008 ◽  
Vol 33 (3) ◽  
pp. 272-279 ◽  
Author(s):  
A. FIGUS ◽  
J. A. BRITTO ◽  
R. H. RAGOOWANSI ◽  
D. ELLIOT
Keyword(s):  
Detailed Analysis ◽  
Disease Severity ◽  
Clinical Studies ◽  
Clinical Analysis ◽  
Dupuytren’S Disease ◽  
Dupuytren's Disease ◽  
Over Time

Although Dupuytren’s disease of the thumb was first described in 1833, the literature on this subject is limited to a few anatomical and clinical studies. This study examined the pattern of cords of Dupuytren’s disease in 260 thumbs in 181 consecutive patients with evidence of disease relating to the thumb attending an out-patient clinic over a period of 36 months. Discrepancies in the literature are discussed in the light of the findings of this more detailed analysis and a simple but practical pictorial system for recording disease severity and detailing progression over time is presented.

scholarly journals Correcting for population stratification reduces false positive and false negative results in joint analyses of host and pathogen genomes

2017 ◽  
Author(s):  
Olivier Naret ◽  
Nimisha Chaturvedi ◽  
Istvan Bartha ◽  
Christian Hammer ◽  
Jacques Fellay
Keyword(s):  
False Positive ◽  
False Negative ◽  
Error Rates ◽  
Type I ◽  
Association Analyses ◽  
Negative Results ◽  
Genome Wide ◽  
False Negative Results ◽  
Inflated Type ◽  
Pathogen Populations

Studies of host genetic determinants of pathogen sequence variation can identify sites of genomic conflicts, by highlighting variants that are implicated in immune response on the host side and adaptive escape on the pathogen side. However, systematic genetic differences in host and pathogen populations can lead to inflated type I (false positive) and type II (false negative) error rates in genome-wide association analyses. Here, we demonstrate through simulation that correcting for both host and pathogen stratification reduces spurious signals and increases power to detect real associations in a variety of tested scenarios. We confirm the validity of the simulations by showing comparable results in an analysis of paired human and HIV genomes.

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