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Data processing of qualitative results from an interlaboratory comparison for the detection of “ Flavescence dor é e ” phytoplasma: How the use of statistics can improve the reliability of the method validation process in plant pathology

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ABSTRACT

A working group established in the framework of the EUPHRESCO European collaborative project aimed to compare and validate diagnostic protocols for the detection of “Flavescence dorée” (FD) phytoplasma in grapevines. Seven molecular protocols were compared in an interlaboratory test performance study where each laboratory had to analyze the same panel of samples consisting of DNA extracts prepared by the organizing laboratory. The tested molecular methods consisted of universal and group-specific real-time and end-point nested PCR tests. Different statistical approaches were applied to this collaborative study. Firstly, there was the standard statistical approach consisting in analyzing samples which are known to be positive and samples which are known to be negative and reporting the proportion of false-positive and false-negative results to respectively calculate diagnostic specificity and sensitivity. This approach was supplemented by the calculation of repeatability and reproducibility for qualitative methods based on the notions of accordance and concordance. Other new approaches were also implemented, based, on the one hand, on the probability of detection model, and, on the other hand, on Bayes’ theorem. These various statistical approaches are complementary and give consistent results. Their combination, and in particular, the introduction of new statistical approaches give overall information on the performance and limitations of the different methods, and are particularly useful for selecting the most appropriate detection scheme with regards to the prevalence of the pathogen. Three real-time PCR protocols (methods M4, M5 and M6 respectively developed by Hren (2007), Pelletier (2009) and under patent oligonucleotides) achieved the highest levels of performance for FD phytoplasma detection. This paper also addresses the issue of indeterminate results and the identification of outlier results. The statistical tools presented in this paper and their combination can be applied to many other studies concerning plant pathogens and other disciplines that use qualitative detection methods.

No MeSH data available.


Related in: MedlinePlus

Relationship between pre- and post-test probabilities of “Flavescence dorée” phytoplasma infection, according to the results obtained during the interlaboratory test performance study for each evaluated method and for the combination of both methods M5 and M6.
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pone.0175247.g002: Relationship between pre- and post-test probabilities of “Flavescence dorée” phytoplasma infection, according to the results obtained during the interlaboratory test performance study for each evaluated method and for the combination of both methods M5 and M6.

Mentions: The likelihood ratio can be combined with the prevalence of infection to determine the post-test probability of infection. Fig 2 illustrates the post-test probabilities of FD phytoplasma (i.e. after a test result) as a function of the pre-test probabilities for each evaluated method and also for the combination of the two most reliable methods (methods M5 and M6). In this graph, the effect of the test result is described by two curves, one for a positive result and the other for a negative one (Lamb, 2007), making it possible to calculate the post-test probability of infection with a positive or negative result depending on the prevalence of the FD phytoplasma in the studied population. For example, in a population with a prevalence of 50%, the probability of a tested individual really being infected after a positive result is higher than 90% for methods Ma, M6 and M4; it is between 80% and 90% for methods M5, M1 and M2 and only 73.2% for M3. After a negative result, there is only 5.5% probability that the grapevine plant is infected by the FD phytoplasma when tested with method M5. This probability increases to 9.2% and 10.0% for methods M6 and M4 respectively, but remains low for these methods. Conversely, relatively high probabilities of infection are found for samples tested negative with Ma, M1, M3 and particularly M2 (35.4%).


Data processing of qualitative results from an interlaboratory comparison for the detection of “ Flavescence dor é e ” phytoplasma: How the use of statistics can improve the reliability of the method validation process in plant pathology
Relationship between pre- and post-test probabilities of “Flavescence dorée” phytoplasma infection, according to the results obtained during the interlaboratory test performance study for each evaluated method and for the combination of both methods M5 and M6.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383269&req=5

pone.0175247.g002: Relationship between pre- and post-test probabilities of “Flavescence dorée” phytoplasma infection, according to the results obtained during the interlaboratory test performance study for each evaluated method and for the combination of both methods M5 and M6.
Mentions: The likelihood ratio can be combined with the prevalence of infection to determine the post-test probability of infection. Fig 2 illustrates the post-test probabilities of FD phytoplasma (i.e. after a test result) as a function of the pre-test probabilities for each evaluated method and also for the combination of the two most reliable methods (methods M5 and M6). In this graph, the effect of the test result is described by two curves, one for a positive result and the other for a negative one (Lamb, 2007), making it possible to calculate the post-test probability of infection with a positive or negative result depending on the prevalence of the FD phytoplasma in the studied population. For example, in a population with a prevalence of 50%, the probability of a tested individual really being infected after a positive result is higher than 90% for methods Ma, M6 and M4; it is between 80% and 90% for methods M5, M1 and M2 and only 73.2% for M3. After a negative result, there is only 5.5% probability that the grapevine plant is infected by the FD phytoplasma when tested with method M5. This probability increases to 9.2% and 10.0% for methods M6 and M4 respectively, but remains low for these methods. Conversely, relatively high probabilities of infection are found for samples tested negative with Ma, M1, M3 and particularly M2 (35.4%).

View Article: PubMed Central - PubMed

ABSTRACT

A working group established in the framework of the EUPHRESCO European collaborative project aimed to compare and validate diagnostic protocols for the detection of “Flavescence dorée” (FD) phytoplasma in grapevines. Seven molecular protocols were compared in an interlaboratory test performance study where each laboratory had to analyze the same panel of samples consisting of DNA extracts prepared by the organizing laboratory. The tested molecular methods consisted of universal and group-specific real-time and end-point nested PCR tests. Different statistical approaches were applied to this collaborative study. Firstly, there was the standard statistical approach consisting in analyzing samples which are known to be positive and samples which are known to be negative and reporting the proportion of false-positive and false-negative results to respectively calculate diagnostic specificity and sensitivity. This approach was supplemented by the calculation of repeatability and reproducibility for qualitative methods based on the notions of accordance and concordance. Other new approaches were also implemented, based, on the one hand, on the probability of detection model, and, on the other hand, on Bayes’ theorem. These various statistical approaches are complementary and give consistent results. Their combination, and in particular, the introduction of new statistical approaches give overall information on the performance and limitations of the different methods, and are particularly useful for selecting the most appropriate detection scheme with regards to the prevalence of the pathogen. Three real-time PCR protocols (methods M4, M5 and M6 respectively developed by Hren (2007), Pelletier (2009) and under patent oligonucleotides) achieved the highest levels of performance for FD phytoplasma detection. This paper also addresses the issue of indeterminate results and the identification of outlier results. The statistical tools presented in this paper and their combination can be applied to many other studies concerning plant pathogens and other disciplines that use qualitative detection methods.

No MeSH data available.


Related in: MedlinePlus