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Statistical analyses of chicken intestinal lesion scores in battery cage studies of anti-coccidial drugs

机译:抗椰子药物电池笼中鸡肉肠病变评分的统计分析

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Establishing the efficacy of an anti-coccidial drug in poultry begins with conducting multiple battery cage studies, where the target animals are challenged with single and mixed Eimeria species inoculum under controlled laboratory conditions. One of the primary outcomes in a battery cage study is the intestinal lesion score defined on a discrete ordinal scale of 0 to 4. So far, the statistical analysis of lesion scores has routinely employed the linear mixed model (LMM). This present work proposes to apply the generalized linear mixed model (GLMM) with the cumulative logit link to statistically analyze coccidial lesion scores collected from battery cage studies. Upon applying this new approach on 9 datasets generated by challenging battery-cage-housed broilers with various mixtures of Eimeria species, it is observed that the GLMM fitted adequately to the data, produced variance component estimates that agreed with the experimental setup, and, at the 0.05 significance level, generated statistical results in complete concordance with the LMM approach. Advantages of the proposed GLMM over the LMM are discussed from several standpoints. Parallel to the regulatory requirement of a >= 1-unit reduction in the mean lesion score for clinical relevant efficacy under the LMM, the clinical relevancy criterion under the GLMM could be set as a >= 10-fold increase in the odds of having low lesion scores. That is, the effect of an anti-coccidial drug product would be deemed clinically relevant in battery-cage studies when the odds of having low lesion scores with the medication is 10 times or more than the odds without the medication.
机译:建立抗椰子药物在家禽中的疗效开始于进行多次电池笼,其中靶动物在受控实验室条件下用单一和混合的eimeria物种造成的单一和混合的eimeria物种攻击。电池笼中的主要结果之一是在离散的序号0至4上定义的肠道病变评分。到目前为止,病变评分的统计分析已经常规使用线性混合模型(LMM)。本工作提出将广义的线性混合模型(GLMM)用累积的Logit链路应用于统计学分析从电池笼研究中收集的可嗜病变评分。在将这种新方法应用于通过挑战电池笼式的肉鸡具有各种eimeria物种的各种混合物产生的9个数据集时,观察到GLMM适用于数据,产生了与实验设置同意的方差分量估计,以及0.05的显着性水平,统计结果与LMM方法完全一致。从几个角度讨论了所提出的GLMM在LMM上的优点。与LMM下的临床相关疗效的平均病变评分的调节要求平行,GLMM下的临床相关性标准可以设定为> = 10倍的增加的几率病变分数。也就是说,当患有药物的低病灶分数的几率比没有药物的可能性的低病灶分数的几率或更多的可能性,抗椰子药物产品的影响将被视为临床上。

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