Fujiwara-Igarashi Aki, Nakazawa Yuta, Ohshima Takafumi, Goto Sho, Ino Masatoshi, Hamamoto Yuji, Takeuchi Yoshinori, Kanemoto Hideyuki
Laboratory of Veterinary Radiology, School of Veterinary Medicine, Nippon Veterinary and Life Science University, Musashino, Tokyo, Japan.
Division of Medical Statistics, Department of Social Medicine, Faculty of Medicine, Toho University, Ota-ku, Tokyo, Japan.
Vet Med Sci. 2025 Mar;11(2):e70296. doi: 10.1002/vms3.70296.
Although feline nasal and nasopharyngeal diseases (NNDs) often require advanced tests under general anaesthesia for definitive diagnosis, not all patients can undergo them.
This study aimed to construct diagnostic prediction models for feline NNDs in Japan using noninvasive examinations, signalment and history.
Seventy-nine cats diagnosed with NNDs, including representative diseases in Japan-nasal and nasopharyngeal tumours (NNT), rhinitis (RS) and nasopharyngeal stenosis (NPS)-were retrospectively investigated to construct prediction models (model group, GM). Thirty-nine cats diagnosed were prospectively investigated to validate their efficacy (validation group, GV). Three predictive models were developed: Models 1 and 2 were manually constructed, with Model 1 designed to predict NNT, RS and NPS individually and Model 2 distinguishing between these diseases. Model 3 was constructed using least absolute shrinkage and selection operator logistic regression. Sensitivity, indicating the ability to identify cases of each disease, and specificity, reflecting the ability to exclude other diseases, were used to assess performance.
In Model 1 of the GV, the sensitivity and specificity for NNT, RS and NPS were 1.00 and 0.73, 0.62 and 0.96 and 0.78 and 0.97, respectively. In Model 2 of the GV, the values were 0.94 and 0.86 for NNT, 0.77 and 0.92 for RS and 0.75 and 0.94 for NPS. In Model 3 of the GV, they were 0.94 and 0.05 for NNT, 0.25 and 1.00 for RS and 0.13 and 0.84 for NPS.
The diagnostic prediction models, particularly Models 1 and 2, could help estimate whether advanced tests are necessary.
尽管猫鼻和鼻咽疾病（NND）通常需要在全身麻醉下进行高级检查以明确诊断，但并非所有患者都能接受这些检查。
本研究旨在利用非侵入性检查、特征和病史构建日本猫NND的诊断预测模型。
回顾性调查了79只被诊断为NND的猫，包括日本的代表性疾病——鼻和鼻咽肿瘤（NNT）、鼻炎（RS）和鼻咽狭窄（NPS），以构建预测模型（模型组，GM）。对39只被诊断的猫进行前瞻性调查以验证其有效性（验证组，GV）。开发了三种预测模型：模型1和模型2是手动构建的，模型1旨在分别预测NNT、RS和NPS，模型2用于区分这些疾病。模型3使用最小绝对收缩和选择算子逻辑回归构建。敏感性（表明识别每种疾病病例的能力）和特异性（反映排除其他疾病的能力）用于评估性能。
在GV的模型1中，NNT、RS和NPS的敏感性和特异性分别为1.00和0.73、0.62和0.96以及0.78和0.97。在GV的模型2中，NNT的值为0.94和0.86，RS为0.77和0.92，NPS为0.75和0.94。在GV的模型3中，NNT为0.94和0.05，RS为0.25和1.00，NPS为0.13和0.84。
诊断预测模型，特别是模型1和模型2，有助于估计是否需要进行高级检查。
