There are a range of products aimed at helping smokers quit, but how can doctors predict with any accuracy which strategy will be the most helpful for an individual? A new study suggests that patients’ metabolisms may provide clues to how successful different cessation aids may be.

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The authors say that, based on the study results, slow metabolizers would benefit more from using the patch than from taking pills to help give up smoking.

Although smoking rates have fallen considerably in the US since the 1960s, when smoking was at its peak, there are currently 42 million Americans who smoke – including teenagers and young adults.

About 6 million people die every year from smoking-related diseases worldwide. Globally, $200 billion is spent annually on tobacco-related health care costs. What is more, nearly 70% of smokers who attempt to quit fail within their first week. As such, there is a great demand for scientists to provide suggestions for improved cessation treatments.

Some studies have previously investigated the relationship between metabolism and smoking cessation treatments. However, the metabolisms of participants were not tested before the participants were randomly assigned to treatments in these studies. Also, none of the previous studies investigated varenicline – a newer cessation medication.

The new study is a multi-center collaboration by researchers from the Perelman School of Medicine at the University of Pennsylvania in Philadelphia, the Centre for Addiction and Health at the University of Toronto, Canada, the State University of New York at Buffalo, NY, and The University of Texas MD Anderson Cancer Center in Houston.

The findings of the study – purported to be the first of its kind – are published in The Lancet Respiratory Medicine.

Across the four medical centers, researchers recruited a total of 1,246 treatment-seeking smokers. Testing the metabolisms of the participants, the researchers sorted the participants into two groups – 662 people were “slow metabolizers” and 584 people were considered to be “normal metabolizers.”

To distinguish between “slow” or “normal,” the researchers took blood samples from the participants and examined the ratio of two metabolites that are derived from nicotine during smoking. This ratio is reflective of the activity of the major nicotine and cotinine-metabolizing enzyme in the liver – CYP2A6 – which helps smokers to metabolize nicotine.

The participants were then randomized to 11 weeks of treatment with either the nicotine patch plus a placebo pill, varenicline plus placebo patch, or a placebo patch and pill. All of the participants also received behavioral counseling.

The smoking behaviors of the participants were assessed at the end of the 11-week treatment period and followed up again at 6 and 12 months.

The team found that, among the normal metabolizers, nearly 40% of varenicline users had not relapsed, compared with 22% of patch users. Among the slow metabolizers, the effectiveness of these two treatments was about the same.

However, the slow metabolizers reported more overall side effects from taking varenicline. The authors say this suggests that slow metabolizers would benefit more from using the patch than from taking pills to help give up smoking.

The authors report that quitting success had decreased by the time of the 6- and 12-month follow-ups – which was expected, given the previous success rates reported in other smoking cessation studies – but that the ratios for normal and slow metabolizers using the patch and varenicline remained.

“This is a much-needed, genetically-informed biomarker that could be translated into clinical practice,” says lead author Caryn Lerman, PhD, professor of psychiatry and director of Penn Medicine’s Center for Interdisciplinary Research on Nicotine Addiction.

Lerman adds:

Matching a treatment choice based on the rate at which smokers metabolize nicotine could be a viable strategy to help guide choices for smokers and ultimately improve quit rates.

These findings not only support the use of the nicotine metabolite ratio as a biomarker to guide treatment choices, but also underscore the notion that tobacco dependence is a heterogeneous condition and that smoking cessation treatments are not equally effective for all smokers.”