A Predictive Model to Determine the Pattern of Nodal Metastasis in Oral Squamous Cell Carcinoma
Background. Developing histological prediction models that estimate the probability of developing metastatic deposit will help clinicians to identify individuals who need either radical or prophylactic neck dissection, which leads to better prognosis. Identification of accurate predictive models in...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2018-01-01
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| Series: | BioMed Research International |
| Online Access: | http://dx.doi.org/10.1155/2018/8925818 |
| Summary: | Background. Developing histological prediction models that estimate the probability of developing metastatic deposit will help clinicians to identify individuals who need either radical or prophylactic neck dissection, which leads to better prognosis. Identification of accurate predictive models in oral cancer is important to overcome extensive prophylactic surgical management for neck nodes. Therefore, accurate prediction of metastasis in oral cancer would have an immediate clinical impact, especially to avoid unnecessary radical treatment of patients who are at a low risk of metastasis. Methods. Histologically confirmed OSCC cases with neck dissection were used. Interrelation of demographic, clinical, and histological data was done using univariate and multivariate analysis. Results. 465 cases were used and presence of metastasis and extracapsular invasion were statistically well correlated with level of differentiation (p<0.001) and pattern of invasion (p<0.001). Multivariate analysis showed level of differentiation, pattern of invasion, and stage as predictors of metastasis. Conclusions. The proposed predictive model may provide some guidance for maxillofacial surgeons to decide the appropriate treatment plan for OSCC, especially in developing countries. This model appears to be reliable and simple and may guide surgeons in planning surgical management of neck nodes. |
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| ISSN: | 2314-6133 2314-6141 |