Pregnancy diagnosis in dairy cows by whey progesterone analysis: an ROC approach

Concentration of progesterone in milk may be used to predict pregnancy status of dairy cattle by the 21st day after insemination. However, the accuracy of this method may be affected by fat-solubility of progesterone and sample storage conditions. After coagulation of a milk sample with rennet, an alternative method is to quantify progesterone concentration in whey with a novel, validated EIA. In this experiment, a receiver operating characteristic (ROC) analysis was performed to estimate the optimal discrimination point for whey progesterone concentration, using a sample of 991 Friesian cows evaluated between the 42nd and 44th day after insemination. Cows also were diagnosed for pregnancy by rectal palpation at this time. The overall conception rate at palpation was 57%. ROC analysis indicated that 259 pg/mL progesterone in whey was the most effective cutoff to discriminate correctly between pregnant and non-pregnant cows. Using this point for prediction, sensitivity was 98.2%, specificity was 70.9% and the area under ROC curve was 0.859, levels generally considered to denote moderate accuracy. The negative likelihood ratio at the cutoff of 259 pg/mL was 0.02, indicating satisfactory performance in detecting negative subjects, while the positive likelihood ratio (+LR=3.37) suggested average performance. In conclusion, EIA of progesterone concentration in whey is a viable method for predicting pregnancy status in cows. However, operators should take management objectives for the herd into account in determining the cutoff point and also considering important influencing variables such as conception rate in the herd. This method can provide diagnostic support for efforts to improve reproductive success, especially in low-fertility herds.