ARTIFICIAL INSEMINATION IN FARM ANIMALS - Phenix-Vet

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132Artificial Insemination in Farm AnimalsPerform method agreementConstruct Bland-Altman plotsExplain limits of agreement between two methodsChose an appropriate regression analysis used in the interpretation of comparing dataDefine the diagnostic parameters: specificity, sensitivity, accuracy, predictive values ofa testRecognize the validity and usefulness of the testEvaluate the performance of a diagnostic test using ROC (receiver operatingcharacteristic) analysisConstruct and compare ROC curvesDetermine optimal cut-off point for a testExplain the developing of a new method in semen evaluation2. Method agreement for determining sperm concentrationSemen samples, which often contain a variety of cells (immature germ cells, blood cells,epithelial cells, and cellular debris) in addition to spermatozoa, differ markedly from bloodsamples because of their heterogeneity. There is also no specific standard available forsperm cells of each species. It is therefore important to compare a new, more appropriate oradditional method to a conventional one. The counting chamber technique for estimatingsperm count appears to be adequate because of its simplicity, low cost and reproducibility.However, photometers are widely used routinely for determining sperm concentration bymany AI organisations, for bulls and boars as well as other species (Woelders, 1991). Theyneed to be evaluated before use, because accurate concentration measurement is the firstand crucial step of the semen preparation process for production of semen doses (Camus etal., 2011). Correct assessment of sperm concentration is essential to ensure that the numberof sperm per insemination dose meets requirements and that the maximal number of dosescan be produced per ejaculate.The increasing use of AI in swine emphasizes the need for the distribution of good qualitysperm by the AI centres (Vyt et al., 2004). Boar sperm quality is routinely assessed bymeasuring concentration, morphology and motility of spermatozoa (Johnson et al., 2000).Determination of sperm concentration is essential in evaluating fertility, whether in vivo orin vitro. However, there is no agreed method for use as a standard. Knuth et al. (1989)showed that introduction of an unevaluated laboratory method, without appropriate qualitycontrol, can cause a bias in semen analysis. However, the methodology of semen evaluationis complex, and standardization is difficult (Brazil et al., 2004). For example, the first largescale, nation-wide proficiency testing program for clinical andrology laboratories in theUnited States reported that the inter-laboratory coefficient of variation for manual spermconcentration determination was 80%, with a range for a single semen specimen of 3 – 492 x10 6 /ml (Keel et al., 2000). The accuracy, reliability and repeatability of different instrumentsthat evaluate sperm concentration of raw semen have already been compared in severalprevious studies (Christensen et al., 2004; Hansen et al., 2006; Prathalingam et al., 2006;Anzar et al., 2009; Camus et al., 2011). Variation in the results from different laboratoriescould be due to the lack of standardisation of methods between laboratories (Maatson,1995).The reason for comparing methods is often that a quicker, more convenient and moreeconomical adaptation has been made to an existing method. Studies comparing a new
Evaluation of a New Method and Diagnostic Test in Semen Analysis 133method with an established method are performed to assess whether the newmeasurements are comparable with existing ones (Jensen & Kjelgaard-Hansen, 2006).2.1 Precision of the evaluated methodsIt is necessary to establish that a method is repeatable before comparing two measurementsfor reproducibility (Petrie & Watson, 1999). Repeatability of boar semen concentrationassessment depends on instruments and procedures, for example CV for instruments FACS,HEMO, Photo C254, SpermVision, UltiMate and SP-100 were 2.7, 7.1, 10.4, 8.1, 5.4 and 3.1%,respectively (Hansen et al., 2006). Imade et al. (1993) reported similar overall precision(5.9%) for the Makler chamber, whereas CV for sperm counts in sperm suspensions can behigher, for example 18.6% (Christensen et al., 2005) or even 26.3% (Mahmoud et al, 1997). Itis generally admitted that intra-observer CVs are often greater than 10%. Althoughguidelines for standardizing the procedure have been proposed, relatively importantdegrees of intra- and inter- technician or inter-laboratory variability have been reported. Inthe external quality assessment (EQA) reported by Neuwinger and coworkers (1990), whichinvolved 10 experienced German laboratories in the evaluation of 8 sperm samples, themean CV was 37.5%. From the data of the external quality control obtained under the BritishFertility Society and reported by Matson (1995), the calculated inter-individual CV forsperm concentration was 64.7% for 24 semen samples collected by technicians from 20laboratories.2.2 Method agreementAccording to the literature, a very common way of investigating method agreement is toperform a paired t-test or to calculate a correlation coefficient to provide a measure ofagreement. However, in this instance, neither method is appropriate for the followingreasons (Petrie & Watson, 1999). The paired t-test tests the null hypothesis that thedifference is zero. If the differences between pairs are large – indicating that the methods donot agree – but are evenly scattered around zero, then the result is non-significant. We canonly conclude that there is no bias, not that the methods agree. Correlation is a statisticalmethod used to quantify any association between two continuous variables (Ma & Smith,2003). The correlation coefficient provides a measure of the linear association between themeasurements obtained by the two methods. It provides an indication of how close theobservations in the scatter diagram are to a straight line. R measures the strength of arelation between two variables, not the agreement between them (Bland and Altman, 1999).For example, the Pearson correlation coefficient gives no information of value in methodcomparison studies, because R can be highly significant even when there is an obvious biasbetween the two methods. It measures the strength of association, rather than agreement,although in the literature it has been used in many studies, such as comparison betweendifferent methods to determine sperm concentration (Prathalingam et al., 2006). R was alsoused to evaluate agreement between assessments within lab technician in sperm analysis(Christensen et al., 2005). In order to assess agreement, it is necessary to know how close thepoints are to the line of equality, i.e. the 45 line (Petrie & Watson, 1999). Therefore, in thestudy of Sokol et al. (2000), comparison of two methods for measuring sperm concentrationusing only Wilcoxon signed rank test and F-test, appears to be insufficient.Scatter plots and absolute and relative bias plots give the best overview of comparisons ofdata (Twormey, 2004; Twormey, 2005). Absolute bias plots are also called Bland and Altman
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ARTIFICIAL INSEMINATION IN FARM ANIMALS - Phenix-Vet

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