MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1111/ajd.12595

Медицинская библиотека · The Australasian journal of dermatology · 2017

Lentigo maligna of the face: A quantitative simple method to identify individual patient risk probability on dermoscopy.

Carbone Anna, Ferrari Angela, Paolino Giovanni, Buccini Pierluigi, De Simone Paola, Eibenschutz Laura, Piemonte Paolo, Silipo Vitaliano, Sperduti Isabella, Catricalà Caterina, Frascione Pasquale

СтатьяПеревод пока не подготовлен

Аннотация

BACKGROUND/

OBJECTIVES

The clinical and dermoscopic differential diagnosis of flat pigmented facial lesions represents a great challenge for the clinicians. Our aim was to report a quantitative method based on dermoscopic features to better classify pigmented facial lesions.

METHODS

This is a retrospective case-series study that analysed the dermoscopic features of 582 pigmented facial lesions.

RESULTS

The individual patient probability of lentigo maligna (LM) was predicted by a multivariate model, with an accuracy of 0.72. According to the odds ratio at the multivariate analysis, an individual scoring index was assigned to each criterion, and a value of 4.56 was identified as optimal cut-off point. Up to a score of 2.5, the probability that a lesion is an LM is 0. The probability increases from 10 to 50% for a score ranging between 4.5 and 6. It is about 90% for a score of 7.

CONCLUSION

The optimal cut-off point obtained and the curve that identifies the probability of a patient having a LM could improve the classification and the management strategies of equivocal pigmented facial lesions.

Для цитирования: Carbone Anna, Ferrari Angela, Paolino Giovanni, Buccini Pierluigi, De Simone Paola, Eibenschutz Laura, Piemonte Paolo, Silipo Vitaliano, Sperduti Isabella, Catricalà Caterina, Frascione Pasquale. Lentigo maligna of the face: A quantitative simple method to identify individual patient risk probability on dermoscopy.. The Australasian journal of dermatology. 2017. DOI: 10.1111/ajd.12595.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.