Development and validation of a new standardised data collection tool to aid in the diagnosis of canine skin allergies.

Abstract

Canine atopic dermatitis (CAD) is a common hereditary clinical syndrome in domestic dogs with no definitive diagnostic tests, which causes marked morbidity and has a high economic impact internationally.

We created a novel questionnaire for labrador (LR) and golden retriever (GR) owners to evaluate canine skin health with respect to clinical signs of CAD. 4,111 dogs had fully completed questionnaires (2,803 LR; 1,308 GR). ‘Cases’ (793) had a reported veterinary diagnosis of CAD, and ‘controls’ (1652) had no current or past clinical signs of CAD and were aged >3 years. Remaining dogs (1666) were initially categorised as ‘Other’. Simulated annealing was used comparing ‘Cases’ and ‘Others’ to select a novel set of features able to classify a known case. Two feature sets are proposed, one for use on first evaluation and one for dogs with a history of skin problems. A sum for each list when applied to the whole population (including controls) was able to classify ‘Cases’ with a sensitivity of 89% to 94% and specificity of 71% to 69%, respectively, and identify potentially undiagnosed cases. Our findings demonstrate for the first time that owner questionnaire data can be reliably used to aid in the diagnostic process of CAD.

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