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Clinical Scores in Veterinary Medicine: What Are the Pitfalls of Score Construction, Reliability, and Validation? A General Methodological Approach Applied in Cattle.

ABSTRACT: Clinical scores are commonly used for cattle. They generally contain a mix of categorical and numerical variables that need to be assessed by scorers, such as farmers, animal caretakers, scientists, and veterinarians. This article examines the key concepts that need to be accounted for when developing the test for optimal outcomes. First, the target condition or construct that the scale is supposed to measure should be defined, and if possible, an adequate proxy used for classification should be determined. Then, items (e.g., clinical signs) of interest that are either caused by the target condition (reflective items) or that caused the target condition (formative items) are listed, and reliable items (inter and intra-rater reliability) are kept for the next step. A model is then developed to determine the relative weight of the items associated with the target condition. A scale is then built after validating the model and determining the optimal threshold in terms of sensitivity (ability to detect the target condition) and specificity (ability to detect the absence of the target condition). Its robustness to various scenarios of the target condition prevalence and the impact of the relative cost of false negatives to false positives can also be assessed to tailor the scale used based on specific application conditions.

SUBMITTER: Buczinski S

PROVIDER: S-EPMC8614512 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPneumonitis is one of the most common adverse events induced by the use of immune checkpoint inhibitors (ICI), accounting for a 20% of all ICI-associated deaths. Despite numerous efforts to identify risk factors and develop predictive models, there is no clinically deployed risk prediction model for patient risk stratification or for guiding subsequent monitoring. We believe this is due to systemic suboptimal approaches in study designs and methodologies in the literature. The nature and prevalence of different methodological approaches has not been thoroughly examined in prior systematic reviews.MethodsThe PubMed, medRxiv and bioRxiv databases were used to identify studies that aimed at risk factor discovery and/or risk prediction model development for ICI-induced pneumonitis (ICI pneumonitis). Studies were then analysed to identify common methodological pitfalls and their contribution to the risk of bias, assessed using the QUIPS and PROBAST tools.ResultsThere were 51 manuscripts eligible for the review, with Japan-based studies over-represented, being nearly half (24/51) of all papers considered. Only 2/51 studies had a low risk of bias overall. Common bias-inducing practices included unclear diagnostic method or potential misdiagnosis, lack of multiple testing correction, the use of univariate analysis for selecting features for multivariable analysis, discretization of continuous variables, and inappropriate handling of missing values. Results from the risk model development studies were also likely to have been overoptimistic due to lack of holdout sets.ConclusionsStudies with low risk of bias in their methodology are lacking in the existing literature. High-quality risk factor identification and risk model development studies are urgently required by the community to give the best chance of them progressing into a clinically deployable risk prediction model. Recommendations and alternative approaches for reducing the risk of bias were also discussed to guide future studies.

Dataset Information

Clinical Scores in Veterinary Medicine: What Are the Pitfalls of Score Construction, Reliability, and Validation? A General Methodological Approach Applied in Cattle.

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