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BMC oral health · 2025

Development and validation of nomograms for ameloblastoma recurrence prediction: a multinational, two-center study from Seoul, South Korea and Wuhan, China.

СтатьяМногоцентровое исследованиеВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
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Zou Derong, Lin Hao, Chen Junxu, Wu Tianfu, Kim Hyung Jun, Liu Bing

Аннотация

OBJECTIVE: This study aimed to construct and validate region-specific nomograms to predict ameloblastoma recurrence and to investigate potential geographic differences in recurrence-related risk factors between South Korea and China.

MATERIALS AND METHODS: A total of 816 patients with ameloblastoma treated between 2006 and 2023 were retrospectively analyzed from Yonsei University Dental Hospital (n = 372) and Hospital of Stomatology, Wuhan University (n = 444). Demographic, radiographic, and pathological variables were collected. Logistic regression analysis identified recurrence-associated predictors. Separate nomograms were developed and internally validated for each cohort. Model performance was evaluated using the area under the curve (AUC), calibration curves, and decision curve analysis.

RESULTS: The South Korean nomogram incorporated six variables, including pathological type, malignant transformation, surgical method, imaging type, tumor size, and cortical bone destruction (AUC = 0.757). The Chinese model incorporated eight predictors, including sex, root resorption, and number of involved teeth (AUC = 0.787). Calibration and decision curves indicated strong agreement between predicted and observed outcomes and favorable clinical applicability.

CONCLUSIONS: Both nomograms demonstrated good predictive accuracy and highlighted regional differences in risk factors. These findings support the integration of multicenter data to enhance recurrence prediction in ameloblastoma.

CLINICAL RELEVANCE: The developed tools can guide individualized treatment planning and long-term follow-up, aiding clinicians in early identification of high-risk patients and optimizing surgical strategies.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты