title: Specific growth rate versus doubling time for quantitative characterization of tumor growth rate.
abstract: Doubling time (DT) is widely used for quantification of tumor growth rate. DT is usually determined from two volume estimations with measurement time intervals comparable with or shorter than DT. Clinical data show that the frequency distribution of DT in patients is positively skewed, with some very long DT values compared with the average DT. Growth rate can also be quantified using specific growth rate (SGR; %/d), equal to ln2/DT. The aim of this work was to compare DT and SGR as growth rate variables. Growth rate calculations were computer simulated for a tumor with DT of 100 days, measurement time interval of 1 to 200 days, and volume estimation uncertainty of 5% to 20%. Growth rate variables were determined and compared for previously published clinical data. The study showed that DT is not a suitable variable for tumor growth rate because (a) for short measurement time intervals, or high volume uncertainties, mean DT can either overestimate or underestimate the average growth rate; (b) DT is not defined if the consecutively estimated volumes are equal; and (c) the asymmetrical frequency distribution of DT makes it unsuitable for common statistical testing. In contrast, mean SGR and its equivalent DT give the correct values for average growth rate, SGR is defined for all tumor volume changes, and it has a symmetrical frequency distribution. SGR is also more accurate to use when discussing, for example, growth fraction, cell loss rate, and growth rate heterogeneities within the tumor. SGR should thus be used, instead of DT, to quantify tumor growth rate.
authors: Departments of Radiation Physics and Surgery, Göteborg University, Göteborg, Sweden. e.mehrara@radfys.gu.se
authors: Esmaeil
authors: E
authors: Mehrara
authors: Eva
authors: E
authors: Forssell-Aronsson
authors: Håkan
authors: H
authors: Ahlman
authors: Peter
authors: P
authors: Bernhardt
mesh_terms: D048708:Cell Growth Processes / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D009010:Monte Carlo Method; D009369:Neoplasms / Q000473:pathology*