Maria Cadenas de Llano-Pérula1, Eunice Kihara2, Patrick Thevissen3, Donna Nyamunga4, Steffen Fieuws5, Mary Kanini6, Guy Willems1. 1. Department of Oral Health Sciences - Orthodontics, KU Leuven and Dentistry, University Hospital Leuven, Leuven, Belgium. 2. Department of Oral and Maxillofacial Surgery, School of Dental Sciences, University of Nairobi, Nairobi, Kenya. 3. Department of Imaging and Pathology - Forensic Odontology, KU Leuven, Leuven, Belgium. 4. Forensic Odontologist, Ministry of Health - NPHLS, Nairobi, Kenya. 5. Interuniversity Institute for Biostatistics and Statistical Bioinformatics, KU Leuven and University Hasselt, Leuven, Belgium. 6. Kenyatta National Hospital, Nairobi, Kenya.
Abstract
PURPOSE: This study aimed to validate the Willems Belgian Caucasian (Willems BC) age estimation model in a Kenyan sample, to develop and validate a Kenyan-specific (Willems KB) age estimation model and to compare the age prediction performances of both models. METHODS: Panoramic radiographs of 1038 (523 female, 515 male) Kenyan children without missing permanent teeth and without all permanent teeth fully developed (except third molars) were retrospectively selected. Tooth development of the seven lower-left permanent teeth was staged according to Demirjian et al. The Willems BC model, performed on a Belgian Caucasian sample and a constructed Kenyan-specific model (Willems KB) were validated on the Kenyan sample. Their age prediction performances were quantified and compared using the mean error (ME), mean absolute error (MAE) and root-mean-square error (RMSE). RESULTS: The ME with Willems BC method equalled zero. Hence, there was no systematic under- or overestimation of the age. For males and females separately, the ME with Willems BC was significantly different from zero, but negligible in magnitude (-0.04 and 0.04, respectively). Willems KB was found not to outperform Willems BC, since the MAE and RMSE were comparable (0.98 vs 0.97 and 1.31 vs 1.29, respectively). Although Willems BC resulted in a higher percentage of subjects with predicted age within a one-year difference of the true age (63.3% vs 60.4%, p=0.018), this cannot be considered as clinically relevant. CONCLUSION: There is no reason to use a country-specific (Willems KB) model in children from Kenya instead of the original Willems (BC) model.
PURPOSE: This study aimed to validate the Willems Belgian Caucasian (Willems BC) age estimation model in a Kenyan sample, to develop and validate a Kenyan-specific (Willems KB) age estimation model and to compare the age prediction performances of both models. METHODS: Panoramic radiographs of 1038 (523 female, 515 male) Kenyan children without missing permanent teeth and without all permanent teeth fully developed (except third molars) were retrospectively selected. Tooth development of the seven lower-left permanent teeth was staged according to Demirjian et al. The Willems BC model, performed on a Belgian Caucasian sample and a constructed Kenyan-specific model (Willems KB) were validated on the Kenyan sample. Their age prediction performances were quantified and compared using the mean error (ME), mean absolute error (MAE) and root-mean-square error (RMSE). RESULTS: The ME with Willems BC method equalled zero. Hence, there was no systematic under- or overestimation of the age. For males and females separately, the ME with Willems BC was significantly different from zero, but negligible in magnitude (-0.04 and 0.04, respectively). Willems KB was found not to outperform Willems BC, since the MAE and RMSE were comparable (0.98 vs 0.97 and 1.31 vs 1.29, respectively). Although Willems BC resulted in a higher percentage of subjects with predicted age within a one-year difference of the true age (63.3% vs 60.4%, p=0.018), this cannot be considered as clinically relevant. CONCLUSION: There is no reason to use a country-specific (Willems KB) model in children from Kenya instead of the original Willems (BC) model.
Entities:
Keywords:
Caucasian sample; Forensic dentistry; Kenyan black sample; Willems method; dental age estimation; forensic odontology
Authors: Eunice Kihara; Ivan Galic; Donna Nyamunga; Fuad Mehdi; Luz Andrea Velandia Palacio; Roberto Cameriere Journal: Int J Legal Med Date: 2022-06-16 Impact factor: 2.791