2012
DOI: 10.1159/000341542
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The Adapted Classification of Male Pattern Hair Loss Improves Reliability

Abstract: Background: The Hamilton-Norwood classification (HNC) is used to assess the severity of pattern hair loss (PHL). Conflicting associations between PHL and cardiovascular disease (CVD) have been reported from studies that used different methods to assess alopecia severity. No classification including the HNC has been validated for population studies. We aimed to simplify the HNC, produce the adapted HNC and test its reliability for use in population studies. Methods: Identifying vertex alopecia as distinct allow… Show more

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Cited by 6 publications
(8 citation statements)
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“…The BASP classification can easily be applied to both sexes and so has been widely utilized since its proposal by Lee et al . in 2007 . The BASP classification has been used in follow‐up studies and has also proven useful .…”
Section: Discussionmentioning
confidence: 99%
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“…The BASP classification can easily be applied to both sexes and so has been widely utilized since its proposal by Lee et al . in 2007 . The BASP classification has been used in follow‐up studies and has also proven useful .…”
Section: Discussionmentioning
confidence: 99%
“…released a more comprehensive basic and specific (BASP) classification that overcame the shortcomings mentioned above and can be widely used regardless of race or gender. The BASP classification is widely used in both clinical and research settings …”
Section: Introductionmentioning
confidence: 99%
“…Currently, Norwood-Hamilton classification is the most widely used hair loss classification. [ 8 9 ]…”
Section: Male-pattern Hair Loss Classificationmentioning
confidence: 99%
“…The type IIA that was present in the original Norwood-Hamilton was removed for simplification. Types VI and VII also do not have additional classification designation as the hair loss on these types involves both anterior (A) and vertex (V) [ Figure 3 ][ 8 ].…”
Section: Male-pattern Hair Loss Classificationmentioning
confidence: 99%
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