Methods comparison biases due to differing uncertainties and data censoring

2019 ◽  
Vol 56 (5) ◽  
pp. 608-612 ◽  
Author(s):  
William A Sadler
Keyword(s):  
Censored Data ◽  
Limit Of Detection ◽  
Complete Removal ◽  
Clinical Results ◽  
Data Sets ◽  
Zero Bias ◽  
Methods Comparison ◽  
Negative Results ◽  
Deming Regression ◽  
Data Censoring

Background Measurements on clinical specimens that contain no analyte, or very low amounts of analyte, unavoidably generate assay response (signal) measurements that fall on the ‘negative’ side of the fitted zero response. It is virtually universal practice to left-censor such measurements to zero and this is frequently extended by left-censoring to the assay limit of detection (LoD) value for reporting purposes. This study considers the effect of censoring on methods comparison analysis. Methods Paired results were randomly generated from two hypothetical assays with zero bias, firstly assuming equal uncertainty near zero and secondly with uncertainties that differed by a moderate 50% near zero. In both cases results were left-censored to zero and to LoD and further subsets were extracted representing partial and complete removal of censored results. All data sets were subjected to overall bias evaluation and Bland–Altman and Deming regression analyses. Results The combination of differing uncertainties and data censoring produced spurious biases by both Bland–Altman and regression analysis, regardless of whether censored results were retained or discarded. Biases were small for data left-censored to zero but were non-trivial with LoD-censoring. Imposing a lower limit aimed at eliminating the influence of censored results did not resolve the problem. Conclusions When high proportion of clinical results are located near zero, caution is required when using censored data (and especially LoD-censored data) in methods comparison studies. Optional access to negative results would rectify the problem, but requires the cooperation of manufacturers.

scholarly journals Methods for Handling Left-Censored Data in Quantitative Microbial Risk Assessment

2018 ◽  
Vol 84 (20) ◽  
Author(s):  
Robert A. Canales ◽  
Amanda M. Wilson ◽  
Jennifer I. Pearce-Walker ◽  
Marc P. Verhougstraete ◽  
Kelly A. Reynolds
Keyword(s):  
Risk Assessment ◽  
Censored Data ◽  
Limit Of Detection ◽  
Environmental Microbiology ◽  
Infection Risk ◽  
Data Sets ◽  
Quantitative Microbial Risk Assessment ◽  
Data Set ◽  
Microbial Risk Assessment ◽  
Microbial Risk

ABSTRACTData below detection limits, left-censored data, are common in environmental microbiology, and decisions in handling censored data may have implications for quantitative microbial risk assessment (QMRA). In this paper, we utilize simulated data sets informed by real-world enterovirus water data to evaluate methods for handling left-censored data. Data sets were simulated with four censoring degrees (low [10%], medium [35%], high [65%], and severe [90%]) and one real-life censoring example (97%) and were informed by enterovirus data assuming a lognormal distribution with a limit of detection (LOD) of 2.3 genome copies/liter. For each data set, five methods for handling left-censored data were applied: (i) substitution with LOD/√2, (ii) lognormal maximum likelihood estimation (MLE) to estimate mean and standard deviation, (iii) Kaplan-Meier estimation (KM), (iv) imputation method using MLE to estimate distribution parameters (MI method 1), and (v) imputation from a uniform distribution (MI method 2). Each data set mean was used to estimate enterovirus dose and infection risk. Root mean square error (RMSE) and bias were used to compare estimated and known doses and infection risks. MI method 1 resulted in the lowest dose and infection risk RMSE and bias ranges for most censoring degrees, predicting infection risks at most 1.17 × 10−2from known values under 97% censoring. MI method 2 was the next overall best method. For medium to severe censoring, MI method 1 may result in the least error. If unsure of the distribution, MI method 2 may be a preferred method to avoid distribution misspecification.IMPORTANCEThis study evaluates methods for handling data with low (10%) to severe (90%) left-censoring within an environmental microbiology context and demonstrates that some of these methods may be appropriate when using data containing concentrations below a limit of detection to estimate infection risks. Additionally, this study uses a skewed data set, which is an issue typically faced by environmental microbiologists.

scholarly journals Development and validation of a mass spectrometry-based assay for quantification of insulin-like factor 3 in human serum

2018 ◽  
Vol 56 (11) ◽  
pp. 1913-1920 ◽  
Author(s):  
Jakob Albrethsen ◽  
Hanne Frederiksen ◽  
Anna-Maria Andersson ◽  
Ravinder Anand-Ivell ◽  
Loa Nordkap ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cell Function ◽  
Limit Of Detection ◽  
Chemical Reduction ◽  
Pearson Correlation ◽  
Serum Samples ◽  
Clinical Role ◽  
Adult Men ◽  
Deming Regression ◽  
A Chain

Abstract Background: The circulating level of the peptide hormone insulin-like factor 3 (INSL3) is a promising diagnostic marker reflecting Leydig cell function in the male. Few commercial immunoassays of varying quality exist. Therefore, we decided to develop and validate a precise method for quantification of INSL3 by mass spectrometry. Methods: We developed an assay in which the INSL3 A-chain is released from the INSL3 A-B heterodimer by chemical reduction and alkylation. The alkylated INSL3 A-chain is quantitated by liquid chromatography-tandem mass spectrometry (LC-MS/MS), as substitute for serum INSL3. The method was compared to a validated and sensitive in-house serum INSL3 immunoassay using 97 serum samples from 12 healthy boys during pubertal transition. Adult levels were determined based on sera from 72 adult healthy males aged 18–40 years. Results: An LC-MS/MS assay with limit of detection and limit of quantification (LOQ) of 0.06 and 0.15 ng/mL, respectively, and intra-assay CVs <9% in the relevant ranges was obtained. The LC-MS/MS compared well with the in-house immunoassay (Deming regression slope: 1.28; Pearson correlation: R=0.86). INSL3 concentrations increased with pubertal maturation in healthy boys. INSL3 concentrations were above the LOQ in all samples from the adult men. The mean (±2 SD range)for serum INSL3 concentrations in the adult men was 2.2 (0.5–3.9) ng/mL. Conclusions: We have developed a robust and sensitive method suitable for quantitation of serum INSL3 in a clinical setting using LC-MS/MS instrumentation available in modern clinical laboratories. The method paves the way for future studies into the clinical role of serum INSL3 measurements.

scholarly journals Distribution of SARS-CoV-2 PCR Cycle Threshold Values Provide Practical Insight Into Overall and Target-Specific Sensitivity Among Symptomatic Patients

2020 ◽  
Vol 154 (4) ◽  
pp. 479-485 ◽  
Author(s):  
Blake W Buchan ◽  
Jessica S Hoff ◽  
Cameron G Gmehlin ◽  
Adriana Perez ◽  
Matthew L Faron ◽  
...  
Keyword(s):  
Viral Load ◽  
Limit Of Detection ◽  
False Negative ◽  
Age Group ◽  
Rt Pcr ◽  
Patient Age ◽  
Cycle Threshold ◽  
Negative Results ◽  
Patient Âgé ◽  
False Negative Results

Abstract Objectives We examined the distribution of reverse transcription polymerase chain reaction (RT-PCR) cycle threshold (CT) values obtained from symptomatic patients being evaluated for coronavirus disease 2019 (COVID-19) to determine the proportion of specimens containing a viral load near the assay limit of detection (LoD) to gain practical insight to the risk of false-negative results. We also examined the relationship between CT value and patient age to determine any age-dependent difference in viral load or test sensitivity. Methods We collected CT values obtained from the cobas severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) assay corresponding to 1,213 combined nasopharyngeal-oropharyngeal specimens obtained from symptomatic individuals that were reported as positive or presumptive positive for SARS-CoV-2. CT values were stratified by SARS-CoV target and patient age group. Results In total, 93.3% to 98.4% of specimens demonstrated CT values greater than 3× the assay LoD, at which point false-negative results would not be expected. The mean of CT values between age groups was statistically equivalent with the exception of patients in age group 80 to 89 years, which demonstrated slightly lower CTs. Conclusions Based on the distribution of observed CT values, including the small proportion of specimens with values near the assay LoD, there is a low risk of false-negative RT-PCR results in combined nasopharyngeal-oropharyngeal specimens obtained from symptomatic individuals.

Monoclonal antibodies evaluated for use in a screening assay for conjugates of human serum albumin and pyridoxal 5'-phosphate.

1989 ◽  
Vol 35 (8) ◽  
pp. 1756-1760 ◽  
Author(s):  
B B Miller ◽  
W E Turner
Keyword(s):  
Monoclonal Antibody ◽  
Monoclonal Antibodies ◽  
Human Serum Albumin ◽  
Human Serum ◽  
Limit Of Detection ◽  
Screening Method ◽  
Serum Samples ◽  
Screening Assay ◽  
Antibody Avidity ◽  
Negative Results

Abstract This enzyme immunoassay (EIA) was developed to measure pyridoxal 5'-phosphate bound to albumin (PLP-HSA) in human serum. The monoclonal antibody titer was 1:2000 and a sequential saturation analysis curve, prepared with samples containing from 10 to 1000 nmol/L, showed a 50% inhibition of antibody at 50 nmol of the conjugate per liter. The lower limit of detection for PLP-HSA was 10 nmol/L, a sensitivity 1000-fold greater than that for any potential interferent. When serum samples gave negative results in the assay, we compared the antigenicity of the principal sites for PLP binding on HSA. It was apparent that the preferred physiological site was not antigenic; however, three additional sites for PLP binding on HSA elicited comparable antibody avidity. This EIA is potentially quite sensitive and specific for PLP-HSA, but considerable additional effort is required to convert serum PLP to an HSA-bound form detectable in the assay, which limits its application as a screening method.

scholarly journals Recurrent SARS-CoV-2 Infection: Case Reports and Review of the Literature

2021 ◽  
Vol 2 (2) ◽  
pp. 1-4
Author(s):  
Brian Conway ◽  
Keyword(s):  
Limit Of Detection ◽  
Case Reports ◽  
False Negative ◽  
Recurrent Infection ◽  
Family Unit ◽  
Her Family ◽  
Negative Results ◽  
False Negative Results ◽  
Clinical Syndromes ◽  
Relapsing Remitting

We describe a 37-year-old woman who became infected with SARS-CoV-2. Over time, 4 other members in her family unit became infected, with 3/5 developing 2-3 separate clinical syndromes over two months. It is possible that each person had a single prolonged infection, with the literature reporting RNA detection for as long as 83 days in some cases. Syndromes of relapsing/remitting infection have also been well described. Intermittent negative RNA readings may represent “false negative” results with intermittent levels of viremia that occasionally fall below the limit of detection of the assay. An alternative explanation may be multiple episodes of infection, clearance, and re-infection within the family unit. Preliminary reports in the literature suggest onward transmission after recurrent infection in 3 reported cases. An understanding of the prevalence of cases series such as ours and their pathophysiologic and immunologic significance will improve our knowledge about SARS-CoV-2 infection and strategies to control it.

scholarly journals A Modified Chi-square Type Test Statistic for the Double Burr X Model with Applications to Right Censored Medical and Reliability Data

2021 ◽  
pp. 615-623
Author(s):  
Khaoula Aidi ◽  
Nadeem Shafique Butt ◽  
Mir Masoom Ali ◽  
Mohamed Ibrahim ◽  
Haitham M. Yousof ◽  
...  
Keyword(s):  
Censored Data ◽  
Goodness Of Fit ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Data Sets ◽  
Test Statistic ◽  
Goodness Of Fit Test ◽  
Chi Square ◽  
Right Censored Data ◽  
The Right

A new modified version of the Bagdonavičius-Nikulin goodness-of-fit test statistic is presented for validity for the right censor case under the double Burr type X distribution. The maximum likelihood estimation method in censored data case is used and applied. Simulations via the algorithm of Barzilai-Borwein is performed for assessing the right censored estimation method. Another simulation study is presented for testing the null hypothesis under the modified version of the Bagdonavičius and Nikulin goodness-of-fit statistical test. Four right censored data sets are analyzed under the new modified test statistic for checking the distributional validation.

scholarly journals Microbial-Maximum Likelihood Estimation Tool for Microbial Quantification in Food From Left-Censored Data Using Maximum Likelihood Estimation for Microbial Risk Assessment

2021 ◽  
Vol 12 ◽  
Author(s):  
Gyung Jin Bahk ◽  
Hyo Jung Lee
Keyword(s):  
Risk Assessment ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Censored Data ◽  
Limit Of Detection ◽  
Likelihood Estimation ◽  
Food Microbiology ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk

In food microbial measurements, when most or very often bacterial counts are below to the limit of quantification (LOQ) or the limit of detection (LOD) in collected food samples, they are either ignored or a specified value is substituted. The consequence of this approach is that it may lead to the over or underestimation of quantitative results. A maximum likelihood estimation (MLE) or Bayesian models can be applied to deal with this kind of censored data. Recently, in food microbiology, an MLE that deals with censored results by fitting a parametric distribution has been introduced. However, the MLE approach has limited practical application in food microbiology as practical tools for implementing MLE statistical methods are limited. We therefore developed a user-friendly MLE tool (called “Microbial-MLE Tool”), which can be easily used without requiring complex mathematical knowledge of MLE but the tool is designated to adjust log-normal distributions to observed counts, and illustrated how this method may be implemented for food microbial censored data using an Excel spreadsheet. In addition, we used two case studies based on food microbial laboratory measurements to illustrate the use of the tool. We believe that the Microbial-MLE tool provides an accessible and comprehensible means for performing MLE in food microbiology and it will also be of help to improve the outcome of quantitative microbial risk assessment (MRA).

scholarly journals Rapid Identification of New Delhi Metallo-β-Lactamase (NDM) Using Tryptic Peptides and LC-MS/MS

2019 ◽  
Vol 63 (9) ◽  
Author(s):  
Honghui Wang ◽  
Jeffrey R. Strich ◽  
Steven K. Drake ◽  
Yong Chen ◽  
Jung-Ho Youn ◽  
...  
Keyword(s):  
Protein Expression ◽  
Limit Of Detection ◽  
Direct Detection ◽  
Multiple Reaction Monitoring ◽  
Protein Detection ◽  
Turnaround Time ◽  
Rapid Identification ◽  
New Delhi ◽  
Negative Results ◽  
Resistance Protein

ABSTRACT There is significant interest in the development of mass spectrometry (MS) methods for antimicrobial resistance protein detection, given the ability of these methods to confirm protein expression. In this work, we studied the performance of a liquid chromatography, tandem MS multiple-reaction monitoring (LC-MS/MS MRM) method for the direct detection of the New Delhi metallo-β-lactamase (NDM) carbapenemase in clinical isolates. Using a genoproteomic approach, we selected three unique peptides (SLGNLGDADTEHYAASAR, AFGAAFPK, and ASMIVMSHSAPDSR) specific to NDM that were efficiently ionized and spectrally well-defined. These three peptides were used to build an assay with turnaround time of 90 min. In a blind set, the assay detected 21/24 blaNDM-containing isolates and 76/76 isolates with negative results, corresponding to a sensitivity value of 87.5% (95% confidence interval [CI], 67.6% to 97.3%) and a specificity value of 100% (95% CI, 95.3% to 100%). One of the missed identifications was determined by protein fractionation to be due to low (∼0.1 fm/μg) NDM protein expression (below the assay limit of detection). Parallel disk diffusion susceptibility testing demonstrated this isolate to be meropenem susceptible, consistent with low NDM expression. Total proteomic analysis of the other two missed identifications did not detect NDM peptides but detected other proteins expressed from the blaNDM-containing plasmids, confirming that the plasmids were not lost. The measurement of relative NDM concentrations over the entire isolate test set demonstrated variability spanning 4 orders of magnitude, further confirming the remarkable range that may be seen in levels of NDM expression. This report highlights the sensitivity of LC-MS/MS to variations in NDM protein expression, with implications for how this technology may be used.

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