The prediction of lymph node metastases from oral squamous carcinoma

Cancer. 1976 Apr;37(4):1901-7. doi: 10.1002/1097-0142(197604)37:4<1901::aid-cncr2820370440>3.0.co;2-u.

Abstract

In an attempt to predict which cases of oral and oropharyngeal squamous carcinoma are likely to metastasize to regional lymph nodes a series of 898 cases was grouped according to site, size, grade of histological differentiation, and presence or absence of histologically confirmed regional lymph node metastases. The results were analysed by a logistic multiple regression analysis. They showed that the sites may be divided into three clusters, Cluster 1 consists of tumors of lip, floor of mouth, cheek mucosa, hard palate, and gingiva. These are not significantly different as regards metastasis rate. Cluster 2 consists of tumors of the anterior two-thirds of tongue and has a higher tendency to metastasis than those in Cluster 1. Lesions of the posterior third of tongue and oropharynx form Cluster 3 which exhibits the greatest tendency to metastasis. Sizes of primary lesions are clustered in groups of lesions less than 3 cm, those 3 to less than 4 cm, and those 4 cm or larger, in ascending tendency to metastasis. Well-differentiated and moderately differentiated tumors are not significantly different in their tendency to metastasize and may be reduced to a single cluster, whereas poorly differentiated tumors have a markedly higher metastasis rate. Using these clusters it has been possible to predict the logistically transformed probability of metastasis to a high degree of accuracy (R=0.9398). From this we conclude that if for a given tumor we know to which site, size or differentiation cluster it belongs, we can then estimate its probability of metastasising.

MeSH terms

  • Carcinoma, Squamous Cell / pathology*
  • Gingival Neoplasms / pathology
  • Humans
  • Lip Neoplasms / pathology
  • Lymphatic Metastasis*
  • Mouth Neoplasms / pathology*
  • Palatal Neoplasms / pathology
  • Prognosis
  • Regression Analysis
  • Tongue Neoplasms / pathology