International Journal of Trichology International Journal of Trichology
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Year : 2009  |  Volume : 1  |  Issue : 2  |  Page : 120-122

Reliability of hamilton-norwood classification

1 Department of Endocrinological and Medical Sciences, Section of Dermatology, Genoa, Italy
2 Department of Health Sciences, Section of Dermatology, University of Genoa, Genoa, Italy
3 CNR, Institute for Macromolecular Studies, Genoa, Italy

Correspondence Address:
M Guarrera
Clinica Dermatologica, V.le Benedetto XV, 7, 16132 Genova
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0974-7753.58554

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Background: Hamilton-Norwood scale (HNS) has been largely used to assess clinically the severity of androgenetic alopecia (AGA), especially for therapeutical trials and even to establish its association with important diseases such as ischemic heart disease and prostate cancer. Objective : To study HNS reproducibility in the hands of dermatologists and dermatology residents. Materials and Methods: Seven dermatologists and 16 residents in dermatology classified 43 photographs of male heads with different degrees of AGA. In a second study, 8 appraisers (3 dermatologists and 5 residents in dermatology) examined 56 pictures with the same procedure and repeated the observation 3 months later. In the first study, the inter-rater agreement was estimated by calculating an intra-class correlation coefficient (ICC). In the second study, for intra-rater repeatability, each rater's scores from session 1 were paired with his/her scores for the same subjects in session 2, and the ordinary least products linear regression was calculated. Results: In the first study, the concordance of appraisers was unsatisfactory (ICC = 0.63-0.68)]. In the second study, repeatability was poor, without any significant difference between dermatologists and dermatology residents. Comment: Reliability of HNS is unsatisfactory even in the hands of expert appraisers. To obtain better reliability, the number of classes should be reduced, but with such reduction HNS would be usable to classify patients only in a broad way.

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