NOVEMBER 2022
587
information is not available, a multiplication factor cannot be derived. I often encounter usage of erroneous multiplication factors and operators being unaware of how these should be properly derived. The formula for calculating the multiplication factor can be described as follows:
Volume of subsample analysed ½ml:
Total volume of suspension ½ml Mass of faeces processed ½g
As an example of this calculation, an often-used McMaster technique suspends 4 g of faeces in 56 ml of flotation medium, achieving a total suspension volume of 60 ml. If both grids are then counted on a classic two-chambered McMaster slide, the volume of the subsample analysed is 0.3 ml. Given this, the multiplication factor can be calculated as (60/4)/0.3 = 50 EPG. A multiplication factor is not an indication of
diagnostic performance. Despite this, it is often erroneously referred to as the sensitivity, which is incorrect and highly misleading. Diagnostic sensitivity is a performance parameter defined as the proportion of true positive samples that are tested positive with the technique, and it can only be determined in a properly performed validation study. As described above, a multiplication factor, on the other hand, is not determined in a study, but is a purely theoretically calculated number. It is important to recognise that the above-described calculation is based on assumptions that are inherently wrong. First of all, it assumes no egg loss in the process, which is never the case. Eggs can be
trapped and get lost in the faecal matter or during the filtration process, and eggs may have different floating capabilities (Norris et al., 2019). All of these factors contribute to a loss of eggs, which will, therefore, not be available for flotation. The proportion of lost eggs will, in turn, negatively affect the accuracy of the technique (see the section on accuracy and precision below for more information). Furthermore, the multiplication factor derivation assumes a perfect suspension and distribution of eggs within the flotation medium, which is also never thecase. In theliterature,
themultiplicationfactoris
sometimes referred to as the “analytical sensitivity”,which is not appropriate either. The analytical sensitivity of a technique is the lowest detectable concentration of the diagnostic target (Saah & Hoover, 1997), and it is determined by analysing a dilution series or a set of samples spiked with known quantities of eggs. Therefore, the multiplication factor cannot be regarded as indicative of analytical sensitivity. Some commercial diagnostic laboratories have promoted low multiplication factor techniques as being “more sensitive”,which is not appropriate unless proper documentation is provided. To illustrate this point, we recently estimated diagnostic sensitivity for three techniques with the following multiplication factors; 25 EPG, 4 EPG and 1 EPG. Despite these vastly different multiplication factors, the techniques performed with diagnostic sensitivities that were not statistically different from each other (Cain et al., 2020). Table 1 summarises quantitative performance parameters for three commonly used techniques, and it should be
Mini- FLOTAC 5
TABLE 1: Comparison of accuracy and precision levels estimated for determination of equine strongylid egg counts for commonly used manual faecal egg counting techniques
Technique
Multiplication factor
McMaster* 25, 50 Accuracy Precision References
Moderate- high
Moderate Noel et al., 2017; Cain et al., 2020
High High
Noel et al., 2017; Scare et al., 2017
Wisconsin 1 Low Low
Cain et al., 2020, 2021
McMaster and Mini-FLOTAC are both counting chamber-based techniques, while the Wisconsin technique is based on the test
tube and cover slip principle. * Multiple modifications exist but performance information is included for commonly used simple versions.
noted that the technique with the smallest multiplication factor (Wisconsin) generally has the poorest quantitative performance. Taken together, the multiplication factor of an egg counting technique simply cannot be regarded as indicative of test performance.
Sensitivity and specificity
Diagnostic sensitivity and specificity are regarded as classic diagnostic performance parameters. However, these are qualitative parameters and have limited implications for assessment of faecal egg count technique performance. Specificity is defined as the proportion of true negative
samples that are detected as negative with the technique being evaluated. Provided that pollen grains or other non- parasitic objects are not mistaken for parasite ova, diagnostic specificity is generally high for faecal parasite diagnostic techniques (Nielsen et al., 2010; Proudman & Edwards, 1992). Possible other sources of error leading to false-positive samples include coprophagy and laboratory contamination of utensils or counting chambers. For faecal egg counting techniques, diagnostic sensitivity
only has implications for samples with low egg counts. In our validation studies, we have consistently found that samples with counts above 50 EPG are generally always testing positive regardless of which technique was used (Noel et al., 2017; Scare et al., 2017). In samples with lower egg quantities, however, some techniques detected a higher proportion of positive samples than others. In other words, a technique with a higher diagnostic sensitivity will not offer any diagnostic advantages for samples with higher counts, but is more likely to detect a low faecal egg count. Thus, if the aim is to identify high strongyle egg shedders, there will no value to using a more sensitive technique. However, if it is important to reliably detect low faecal egg counts, a more sensitive technique should be used. I often encounter the misconception that a more sensitive test is expected to generate higher faecal egg counts.
© 2021 EVJ Ltd.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92
