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Determination of cut-off cycle threshold values in routine RT-PCR assays to assist differential diagnosis of norovirus in children hospitalized for acute gastroenteritis.

Trang NV, Choisy M, Nakagomi T, Chinh NT, Doan YH, Yamashiro T, Bryant JE, Nakagomi O, Anh DD - Epidemiol. Infect. (2015)

Bottom Line: A bimodal distribution of cycle threshold (Ct) values was observed in which the lower peak was assumed to represent cases for which NV was the causal agent of diarrhoea, whereas the higher peak was assumed to represent cases involving an alternative pathogen other than NV.Under these assumptions, we applied finite-mixture modelling to estimate a threshold of Ct <21·36 (95% confidence interval 20·29-22·46) to distinguish NV-positive patients for which NV was the likely cause of diarrhoea.We conclude that the use of an appropriate cut-off value in the interpretation of NV real-time RT-PCR results may improve differential diagnosis of enteric infections, and could contribute to improved estimates of the burden of NV disease.

View Article: PubMed Central - PubMed

Affiliation: The National Institute of Hygiene and Epidemiology,Hanoi,Vietnam.

ABSTRACT
Norovirus (NV) is an important cause of acute gastroenteritis in children, but is also frequently detected in asymptomatic children, which complicates the interpretation of NV detection results in both the clinical setting and population prevalence studies. A total of 807 faecal samples from children aged <5 years hospitalized for acute gastroenteritis were collected in Thai Binh, Vietnam, from January 2011 to September 2012. Real-time RT-PCR was used to detect and quantify NV-RNA in clinical samples. A bimodal distribution of cycle threshold (Ct) values was observed in which the lower peak was assumed to represent cases for which NV was the causal agent of diarrhoea, whereas the higher peak was assumed to represent cases involving an alternative pathogen other than NV. Under these assumptions, we applied finite-mixture modelling to estimate a threshold of Ct <21·36 (95% confidence interval 20·29-22·46) to distinguish NV-positive patients for which NV was the likely cause of diarrhoea. We evaluated the validity of the threshold through comparisons with NV antigen ELISA results, and comparisons of Ct values in patients co-infected with rotavirus. We conclude that the use of an appropriate cut-off value in the interpretation of NV real-time RT-PCR results may improve differential diagnosis of enteric infections, and could contribute to improved estimates of the burden of NV disease.

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Finite-mixture modelling of the Ct value distribution and identification of the cut-off values. The number of samples with Ct <40 was 346 and is represented by the grey histograms. The best finite-mixture model was D1 with a log-normal distribution (left blue curve), and D2 with a Weibull distribution (right blue curve). This model is shown in red. From these latter two, the probability P of belonging to the left-most peak of Ct values is computed as D1/(D1 + D2) and this is shown by the green curve (see the right vertical scale). The widths of the curves indicate the 95% confidence intervals.
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fig01: Finite-mixture modelling of the Ct value distribution and identification of the cut-off values. The number of samples with Ct <40 was 346 and is represented by the grey histograms. The best finite-mixture model was D1 with a log-normal distribution (left blue curve), and D2 with a Weibull distribution (right blue curve). This model is shown in red. From these latter two, the probability P of belonging to the left-most peak of Ct values is computed as D1/(D1 + D2) and this is shown by the green curve (see the right vertical scale). The widths of the curves indicate the 95% confidence intervals.

Mentions: The typical bimodal distribution of NV Ct values (Figs 1 and 2) was modelled by a finite-mixture model using continuous unimodal distributions from the exponential family [28]. In the absence of prior information on expected distribution for each peak, we evaluated the normal, log-normal, gamma, Weibull distributions, and all possible combinations (4 × 4 = 16). The normal distribution is defined on all the real numbers, whereas the three other distributions (log-normal, Weibull, gamma) are defined on positive reals. These distributions are all characterized by two parameters: a location parameter μ and a scale parameter σ. The first parameter accounts for most of the data and corresponds to the mean of the normal distribution, the mean on a log-scale for the log-normal distribution, and the shape parameter for the gamma and Weibull distributions. The second parameter accounts for the spread of the data around the location parameter and corresponds to the standard deviation in the case of the normal distribution, the standard deviation on a log-scale for the log-normal distribution, the rate parameter (1/scale) for the gamma distribution and the scale parameter for the Weibull distribution. We refer to μ1 and σ1 for the location and scale parameters of the first peak (i.e. lowest Ct values) and μ2 and σ2 for the location and scale parameters of the second peak (i.e. highest Ct values). The density of the bimodal distribution of Ct values thus readswhere D1 and D2 are the distributions accounting for the first (i.e. lowest Ct values) and second (i.e. the highest Ct values) peaks, respectively, and λ and (1 – λ) are the weights for the D1 and D2 distributions, respectively.Fig. 1.


Determination of cut-off cycle threshold values in routine RT-PCR assays to assist differential diagnosis of norovirus in children hospitalized for acute gastroenteritis.

Trang NV, Choisy M, Nakagomi T, Chinh NT, Doan YH, Yamashiro T, Bryant JE, Nakagomi O, Anh DD - Epidemiol. Infect. (2015)

Finite-mixture modelling of the Ct value distribution and identification of the cut-off values. The number of samples with Ct <40 was 346 and is represented by the grey histograms. The best finite-mixture model was D1 with a log-normal distribution (left blue curve), and D2 with a Weibull distribution (right blue curve). This model is shown in red. From these latter two, the probability P of belonging to the left-most peak of Ct values is computed as D1/(D1 + D2) and this is shown by the green curve (see the right vertical scale). The widths of the curves indicate the 95% confidence intervals.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4594052&req=5

fig01: Finite-mixture modelling of the Ct value distribution and identification of the cut-off values. The number of samples with Ct <40 was 346 and is represented by the grey histograms. The best finite-mixture model was D1 with a log-normal distribution (left blue curve), and D2 with a Weibull distribution (right blue curve). This model is shown in red. From these latter two, the probability P of belonging to the left-most peak of Ct values is computed as D1/(D1 + D2) and this is shown by the green curve (see the right vertical scale). The widths of the curves indicate the 95% confidence intervals.
Mentions: The typical bimodal distribution of NV Ct values (Figs 1 and 2) was modelled by a finite-mixture model using continuous unimodal distributions from the exponential family [28]. In the absence of prior information on expected distribution for each peak, we evaluated the normal, log-normal, gamma, Weibull distributions, and all possible combinations (4 × 4 = 16). The normal distribution is defined on all the real numbers, whereas the three other distributions (log-normal, Weibull, gamma) are defined on positive reals. These distributions are all characterized by two parameters: a location parameter μ and a scale parameter σ. The first parameter accounts for most of the data and corresponds to the mean of the normal distribution, the mean on a log-scale for the log-normal distribution, and the shape parameter for the gamma and Weibull distributions. The second parameter accounts for the spread of the data around the location parameter and corresponds to the standard deviation in the case of the normal distribution, the standard deviation on a log-scale for the log-normal distribution, the rate parameter (1/scale) for the gamma distribution and the scale parameter for the Weibull distribution. We refer to μ1 and σ1 for the location and scale parameters of the first peak (i.e. lowest Ct values) and μ2 and σ2 for the location and scale parameters of the second peak (i.e. highest Ct values). The density of the bimodal distribution of Ct values thus readswhere D1 and D2 are the distributions accounting for the first (i.e. lowest Ct values) and second (i.e. the highest Ct values) peaks, respectively, and λ and (1 – λ) are the weights for the D1 and D2 distributions, respectively.Fig. 1.

Bottom Line: A bimodal distribution of cycle threshold (Ct) values was observed in which the lower peak was assumed to represent cases for which NV was the causal agent of diarrhoea, whereas the higher peak was assumed to represent cases involving an alternative pathogen other than NV.Under these assumptions, we applied finite-mixture modelling to estimate a threshold of Ct <21·36 (95% confidence interval 20·29-22·46) to distinguish NV-positive patients for which NV was the likely cause of diarrhoea.We conclude that the use of an appropriate cut-off value in the interpretation of NV real-time RT-PCR results may improve differential diagnosis of enteric infections, and could contribute to improved estimates of the burden of NV disease.

View Article: PubMed Central - PubMed

Affiliation: The National Institute of Hygiene and Epidemiology,Hanoi,Vietnam.

ABSTRACT
Norovirus (NV) is an important cause of acute gastroenteritis in children, but is also frequently detected in asymptomatic children, which complicates the interpretation of NV detection results in both the clinical setting and population prevalence studies. A total of 807 faecal samples from children aged <5 years hospitalized for acute gastroenteritis were collected in Thai Binh, Vietnam, from January 2011 to September 2012. Real-time RT-PCR was used to detect and quantify NV-RNA in clinical samples. A bimodal distribution of cycle threshold (Ct) values was observed in which the lower peak was assumed to represent cases for which NV was the causal agent of diarrhoea, whereas the higher peak was assumed to represent cases involving an alternative pathogen other than NV. Under these assumptions, we applied finite-mixture modelling to estimate a threshold of Ct <21·36 (95% confidence interval 20·29-22·46) to distinguish NV-positive patients for which NV was the likely cause of diarrhoea. We evaluated the validity of the threshold through comparisons with NV antigen ELISA results, and comparisons of Ct values in patients co-infected with rotavirus. We conclude that the use of an appropriate cut-off value in the interpretation of NV real-time RT-PCR results may improve differential diagnosis of enteric infections, and could contribute to improved estimates of the burden of NV disease.

Show MeSH
Related in: MedlinePlus