Abstract
Background To improve our understanding of the natural course of head and neck paragangliomas
(HNPGL) and ultimately differentiate between cases that benefit from early treatment
and those that are best left untreated, we studied the growth dynamics of 77 HNPGL
managed with primary observation.
Methods Using digitally available magnetic resonance images, tumor volume was estimated at
three time points. Subsequently, nonlinear least squares regression was used to fit
seven mathematical models to the observed growth data. Goodness of fit was assessed
with the coefficient of determination (R
2) and root-mean-squared error. The models were compared with Kruskal–Wallis one-way
analysis of variance and subsequent post-hoc tests. In addition, the credibility of
predictions (age at onset of neoplastic growth and estimated volume at age 90) was
evaluated.
Results Equations generating sigmoidal-shaped growth curves (Gompertz, logistic, Spratt and
Bertalanffy) provided a good fit (median R
2: 0.996–1.00) and better described the observed data compared with the linear, exponential,
and Mendelsohn equations (p < 0.001). Although there was no statistically significant difference between the
sigmoidal-shaped growth curves regarding the goodness of fit, a realistic age at onset
and estimated volume at age 90 were most often predicted by the Bertalanffy model.
Conclusions Growth of HNPGL is best described by decelerating tumor growth laws, with a preference
for the Bertalanffy model. To the best of our knowledge, this is the first time that
this often-neglected model has been successfully fitted to clinically obtained growth
data.
Keywords
paragangliomas - growth - carotid body tumors - vagal body - mathematics - models
