Development and External Validation of the Hidradenitis Suppurativa Cutaneous Abscess Prediction Score-2 (HSCAPS-2): A Clinical Decision Support Tool for Diagnosis of Hidradenitis Suppurativa over Cutaneous Abscess.
Amit Garg, Jonathan Koptyev, Melissa Butt, Joslyn Kirby, Andrew Strunk
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引用次数: 0
Abstract
Introduction: Patients with hidradenitis suppurativa (HS) experience a 10-year diagnosis delay, on average. Accordingly, time to diagnosis represents one of the greatest unmet needs in HS, which to date has not been adequately addressed. A general lack of awareness about HS in the medical community and a notable heterogeneity in clinical presentation, which is most often confused with cutaneous abscess (CA), forms the basis of poor disease recognition and diagnosis delay. Our objective was to develop and validate a prediction model for diagnosis of HS versus site-specific cutaneous abscess (CA).
Methods: We performed a cross-sectional study in which the model was developed using a large clinical database and externally validated using a sample of clinical records at Penn State Health. Prediction model discrimination and calibration were evaluated using the c-statistic, calibration intercept/slope, and a flexible calibration curve.
Results: Variable selection identified 15 predictors, 7 of which remained after model simplification. The following characteristics were predictive of HS relative to site-specific CA: female sex, increasing age up to 44 years, African American race, race other than White or African American, increasing body mass index, polycystic ovarian syndrome, and acne. The c-statistics of the 7-variable model in validation was 0.77 (95% CI 0.73-0.80). Calibration intercept and slope were 0.29 (95% CI 0.14, 0.43) and 1.09 (95% CI 0.90, 1.28).
Conclusion: Clinical characteristics can predict diagnosis of HS over CA in practice without reliance on a specialty-specific examination to identify disease and potentially reduce diagnosis delay.
化脓性汗腺炎(HS)患者平均诊断延迟10年。因此,诊断时间是卫生系统中最大的未满足需求之一,这一需求迄今尚未得到充分解决。医学界普遍缺乏对HS的认识,临床表现也存在明显的异质性,最常与皮肤脓肿(CA)混淆,这构成了疾病认识不佳和诊断延误的基础。我们的目的是建立和验证一个预测模型来诊断HS与部位特异性皮肤脓肿(CA)。方法:我们进行了一项横断面研究,其中使用大型临床数据库开发模型,并使用宾夕法尼亚州立大学健康中心的临床记录样本进行外部验证。采用c-统计量、校正截距/斜率和柔性校正曲线对预测模型判别和校正进行评价。结果:变量选择确定了15个预测因子,模型简化后保留了7个。与特定部位的CA相比,以下特征可预测HS:女性、年龄≥44岁、非裔美国人种族、非白人或非裔美国人种族、体重指数增加、多囊卵巢综合征和痤疮。7变量模型验证的c统计量为0.77 (95% CI 0.73 ~ 0.80)。校正截距和斜率分别为0.29 (95% CI 0.14, 0.43)和1.09 (95% CI 0.90, 1.28)。结论:临床特征可以在实践中预测HS而不是CA的诊断,而不依赖于专门的检查来识别疾病,并可能减少诊断延误。
期刊介绍:
Published since 1893, ''Dermatology'' provides a worldwide survey of clinical and investigative dermatology. Original papers report clinical and laboratory findings. In order to inform readers of the implications of recent research, editorials and reviews prepared by invited, internationally recognized scientists are regularly featured. In addition to original papers, the journal publishes rapid communications, short communications, and letters to ''Dermatology''. ''Dermatology'' answers the complete information needs of practitioners concerned with progress in research related to skin, clinical dermatology and therapy. The journal enjoys a high scientific reputation with a continually increasing impact factor and an equally high circulation.