Management of supernumerary teeth

Most supernumerary teeth are located in the anterior maxillary region. They are classified according to their form and location. Their presence may give rise to a variety of clinical problems. Detection of supernumerary teeth is best achieved by thorough clinical and radiographic examination. Their management should form part of a comprehensive treatment plan. This article presents an overview of the clinical problems associated with supernumerary teeth and includes a discussion of the classification, diagnosis and management of this difficult clinical entity.

Genetic and environmental factors are implicated in the aetiology of supernumerary teeth, hypodontia, megadontia and microdontia ; these anomalies tend to be associated. 1115 school children aged 11-14 years examined clinically and radiographically provided prevalence data. A further 703 children with dental anomalies were studied. 153 of these became probands for a family study and 327 of their first-degree relatives were examined. There were much higher frequencies (p less than 0.001) of all anomalies among the relatives of probands than in the general population. Males more often had supernumerary teeth and megadontia and females more frequently had hypodontia (p less than 0.05) and microdontia . For hypodontia, the proportion of relatives affected varied with the severity of the condition in the proband (p less than 0.05). In the prevalence study, there was an association between hypodontia and microdontia (p less than 0.001). These findings may be explained by a multifactorial model having a continuous scale, related to tooth number and size, with thresholds. Position on the scale usually depends upon the combination of numerous genetic and environmental factors, each with a small effect, but occasionally a chromosomal anomaly, a major single gene or a major environmental insult may have a large effect. The finding that the estimated difference between the means of the sexes was the same for each anomaly, within the limits of experimental error, supports the validity of the model.