UB researchers develop a new method to more accurately predict tumor growth rates

Researchers at the University of Buffalo have developed a new method to more accurately predict tumor growth rates, an essential statistic used to plan screenings and define dosing schedules in cancer treatment.

The mathematical method has successfully estimated the doubling time (the time required for a tumor to double in size) for 12 types of cancer, ranging from bad and prostate cancer to melanoma.

The research, published in February in the AAPS Journal, was led by Dhaval Shah, PhD, badociate professor at the UB School of Pharmacy and Pharmaceutical Sciences.

"This new method allows clinicians and drug development scientists to use routinely generated clinical data to infer the doubling time of solid tumors.This parameter can be used to design individualized dosage regimens and develop models. reliable cancer treatments, "said Shah.

The doubling time of the tumor can significantly affect the results of cancer treatment, but the rate is difficult to determine. Current methods calculate doubling time by measuring the size of a tumor at two different times and baduming that the cancer is growing at an exponential rate.

However, most doubling times calculated using this method are overestimated and minimal changes in tumor size can make it difficult to determine growth rates.

The error affects the ability of clinicians to plan optimal follow-up screenings, establish effective dosing regimens, and determine whether surgery, chemotherapy, or radiation therapy is the best form of treatment.

UB researchers base their method on data extracted from progression-free survival plots, ie the duration during and after treatment that a cancer does not develop or does not not spread.

Shah explains Shah, progression-free survival charts contain by nature information that could help identify growth rates of the tumor.

The researchers examined data from 47 clinical trials involving patches of any one of 12 types of cancer: melanoma; pancreatic, lung, prostate, gastric, colorectal and three forms of bad cancer; hepatocellular carcinoma (liver) and renal cell carcinoma (kidney); and glioblastoma multiforme (brain).

Cancer growth rates predicted by researchers using progression-free survival curves were within the range of reported tumor doubling times.