With genotyping costs declining and the cost of conducting conventional trials increasing, researchers from the National Institutes of Health and Duke University have modeled data suggesting it may save money to genetically stratify patients in clinical trials for smoking cessation.
In mid-sized Phase II trials enrolling around 200 patients, "there was the clearest benefit for genotyping under a wide range of assumptions, [such as] cost per subject for the trial and genotyping cost per subject," lead study author George Uhl of the National Institute on Drug Abuse, told Pharmacogenomics Reporter this week.
The findings of the study, published in The Pharmacogenomics Journal, shed light onto the circumstances in which genotyping may be cost-effective in smoking-cessation studies, and could help inform the design of studies for other addictions and disease indications, the study authors noted.
In their modeling, the researchers attempted to capture half the total genetic influence of genotyping using a technique called half-max stratification. They assumed the genotyping cost per participant will be $150, $300, or $500. With half-max stratification and 0.9 power, the researchers determined they would need to recruit around 200 patients — 100 for treatment and 100 for placebo — and genotype 1,019 individuals. A non-stratified study of the same power would require around 450 patients, researchers calculated.
Assuming that genotyping costs $150 per patient, and trial costs range from $4,000 per patient for academic trails to $25,000 per patient for industry-sponsored trials, the researchers calculated direct savings of between $4 million to $15 million for conducting stratified versus non-stratified trials.
At genotyping costs of $300 per subject with similar range for trial and recruitment costs, savings from half-max genetic stratification are projected to be between $70,000 and $5.7 million. If genotyping costs rise to $500 per subject, and similar trial/recruitment costs are assumed, then savings from half-max genetic stratification could reach between $274,000 and $5.5 million, respectively, the study found.
Given these results, the researchers conclude that the "results of the current simulation studies appear to justify careful consideration of use of genotypic stratification for medium-sized trials that are characteristic of Phase II drug testing."
In their modeling, the researchers used 2,311 previously published SNPs shown to distinguish individuals who were successful and from those who were unsuccessful from quitting smoking. According to Uhl, most of the variants seem to predict patient response to bupropion and nicotine replacement therapies "equally well," while some variants appear to only predict response to nicotine-replacement thereapies.
Uhl identified calsyntenin 2 as among the most promising gene linked to patients' ability to stop smoking. "Since memory or thinking complaints are some of the difficulties that are reported to block success in individuals who try to quit, CLSTN2 is a highly plausible gene in which allelic variants could provide relatively selective influences on nicotine replacement therapies' effects on cessation," Uhl added.
As more of these smoking-cessation SNPs are validated in further studies, the cost/benefit associated with genetic stratification in smoking-cessation trials should also become more apparent, according to the study authors.
"More study is required to precisely determine the variance in quitting success that can be accounted for by the SNPs that are currently identified, and to precisely classify individuals who may display varying degrees of genetic versus environmental effects into quitters or nonquitters," the study authors wrote in The Pharmacogenomics Journal. "However, the data at hand do allow us to model the effects of genotypic stratification in smoking-cessation trials."
According to Uhl, the researchers are working to write up data from further validating studies that include both retrospective and prospective work. "We hope that we will have these results analyzed later in this year," Uhl said, without elaborating.
Although Uhl and his team have identified common variants and clinical variables linked to peoples' ability stop smoking, he acknowledged that none of the identified SNPs has "large effects."
Still, the researchers "would be happy to work with [industry] partners to facilitate development of these genetic tests," he said.