Optimal cutoff estimation and evaluation of direct and indirect diagnostic methods for assessing bovine colostrum
Eleftherios Meletis1, Juan Carlos Arango-Sabogal2, J Trenton McClure3
1Laboratory of Epidemiology, Biostatistics and applied Artificial Intelligence, Faculty of Public and One Health, University of Thessaly, Karditsa 43100, Greece.
Abstract:
Ensuring high-quality colostrum for newborn calves is essential for their health and future productivity. We applied Bayesian finite mixture models to estimate optimal cutoff values and evaluate the diagnostic accuracy of 3 methods-radial immunodiffusion (RID) assay, transmission infrared (TIR) spectroscopy, and digital Brix (dBrix) refractometry-measured on a continuous scale for assessing bovine colostrum quality, using 591 colostrum samples from 42 Holstein dairy herds in Atlantic Canada. The mean and standard deviation of IgG concentrations for high-quality colostrum were 61.07 ± 39.8 g/L, 51.28 ± 27.38 g/L, and 24.32 ± 4.13% Brix for RID assay, TIR spectroscopy, and dBrix refractometry, respectively, compared with 19.93 ± 15.54 g/L, 7.78 ± 37.4 g/L, and 15.87 ± 3.45% Brix for low-quality samples. The prevalence of high-quality colostrum was estimated at 83% (95% credible interval [CrI]: 0.79-0.88). The dBrix refractometer demonstrated the highest discriminatory power, with an area under the curve (AUC) of 0.94 (95% CrI: 0.91-0.97), followed by RID assay (AUC: 0.92; 95% CrI: 0.88-0.96) and TIR spectroscopy (AUC: 0.82; 95% CrI: 0.76-0.88). Optimal cutoff values were determined using Youden's index: 34.15 g/L for RID assay (sensitivity [Se] = 0.86, specificity [Sp] = 0.83), 22.74 g/L for TIR spectroscopy (Se = 0.88, Sp = 0.66), and 19.62% Brix for dBrix refractometry (Se = 0.90, Sp = 0.85). Correlation between RID assay and TIR spectroscopy was stronger for high-quality colostrum samples (0.80; 95% CrI: 0.77-0.84) than for low-quality samples (0.36; 95% CrI: 0.16-0.55), indicating that these methods are not perfectly correlated and justifying the need for multiple diagnostic approaches. Among individual methods, dBrix refractometry showed the highest positive predictive value (PPV = 1.00), and all methods demonstrated moderate negative predictive values (NPV = 0.46-0.57). Combining methods in series interpretation increased PPV up to 1.00 when all 3 methods were used together, though with reduced NPV. Conversely, parallel interpretation substantially improved NPV, reaching 0.98 when all 3 methods were combined. By modeling continuous measurements instead of dichotomized test results, our analysis produced refined cutoff values for assessing colostrum quality. The findings indicate that existing thresholds remain largely adequate, offering only minor performance improvements, and emphasize the need to balance diagnostic refinements with their potential effects on calf management and passive immunity. Furthermore, our findings suggest that, although individual assessment methods offer valuable diagnostic information, combining multiple methods can optimize either Se or Sp, depending on the interpretation approach, thereby further enhancing the accuracy of colostrum quality evaluation.
Related Concept Videos
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Measurement of Bioavailability: Pharmacodynamic Methods
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Expected Frequencies in Goodness-of-Fit Tests


