Format

Send to

Choose Destination
Radiother Oncol. 1986 Jul;6(3):167-84.

Klaas Breur Medal lecture 1985. The growth and progression of human tumors: implications for management strategy.

Abstract

The natural history of human cancers can be stimulated assuming an exponential growth pattern. This simple model shows that the duration of the tumor growth during the occult phase is always much shorter than the interval between the carcinogenic stimulus and the clinical emergence of the tumor; this is consistent with the existence of several stages of precancerous lesions which precede the development of the neoplastic clone. Metastatic spread can be simulated and a model of tumor growth can be used to predict the proportion of patients in whom metastatic dissemination can be avoided by an earlier diagnosis. The model predicts also that in the subsets of patients in whom metastatic spread occurs early the occult metastases will be large at the time of the treatment of the primary tumor and therefore adjuvant chemotherapy (CT) will be less effective; this is in keeping with clinical data. The model can also help to understand the relationship between the local control of a tumor and the cure of the patient, and to explain the discrepancy between the great reduction in the local incidence of local recurrence obtained with post-operative radiotherapy and its relatively small impact on survival. However, this simple model is insufficient to explain several features of the course of a human cancer, in particular the heterogeneity of the neoplastic cell population and the inexorable tendency for some cancers to progress towards a more malignant type and to become progressively more resistant to any treatment. Genetic instability appears to be an essential characteristic of human cancers and variations in its degree may be the cause of differences in the aggressiveness and in the severity of the various types of cancers. The recent advances in the molecular biology of cancers has already given to clinicians new and powerful prognostic indicators. These will probably, in the near future help, towards a better understanding of the biology of tumor growth and tumor progression.

PMID:
3529254
DOI:
10.1016/s0167-8140(86)80151-7
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center