Clinical Inquiries

Does office spirometry improve quit rates in smokers?

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EVIDENCE-BASED ANSWER

IT DEPENDS. Simply performing spirometry and offering cessation advice doesn’t improve quit rates in patients who smoke (strength of recommendation [SOR]: A, systematic review of randomized controlled trials [RCTs]). However, when the spirometry results are communicated in terms of “lung age,” smokers are more likely to quit (SOR: B, large RCT). Patients with abnormal spirometry results may be more likely to quit than patients with normal results (SOR: B, cohort studies).

Evidence summary

A systematic review of 3 RCTs with a total of 649 participants evaluated office spirometry as a motivational tool to improve quit rates by comparing spirometry plus cessation advice with cessation advice alone. All participants were men and women 19 to 75 years of age recruited from outpatient clinics.1

In 1 trial, the intervention group received repeated counseling at 4 visits and underwent spirometry; the control group had 1 counseling session and was given a brochure. In the other 2 trials, the intervention group had both carbon monoxide measurements and spirometry, and all participants received more extensive counseling, including cessation skills training.

At 9 to 12 months’ follow-up, quit rates ranged from 6% to 24% in the intervention groups vs 5% to 14% in the control groups (not significantly different).1

A subsequent study randomized 221 smokers to receive either spirometry plus brief cessation advice or advice alone. Researchers recruited patients 15 to 80 years of age who were willing to quit smoking from 16 general practice clinics in Belgium. Fifty-one percent of patients in both groups used nicotine replacement therapy (a larger percentage than is typical in studies done in the United States). At 6, 12, and 24 months, 5%, 2%, and 5% more smokers, respectively, from the spirometry group quit smoking compared with the control group, but this difference was not significant.2

Reporting spirometry results in terms of lung age may spur quitting
One RCT found significantly improved quit rates when patients who smoked were given their office spirometry results in terms of “lung age” (the age of an average healthy person with similar spirometry results) rather than as forced expiratory volume in 1 second (FEV1). Investigators performed office spirometry and gave smoking cessation advice to 561 smokers older than 35 years who were recruited from 5 general practices. They randomized patients to receive their spirometry results as either lung age or FEV1 and recorded quit rates at 12 months (smoking cessation was verified by measuring blood levels of carbon monoxide).

Patients whose spirometry results were reported as lung age were significantly more likely to quit than smokers whose results were given as FEV1 (13.6% vs 6.4%; P=.005; number needed to treat [NNT]=14 smokers counseled using lung age to cause 1 more patient to quit). Smokers with normal lung ages were no more likely to quit than smokers with abnormal results.3

Abnormal results also may be a motivator
However, 3 prospective cohort studies demonstrated that patients with abnormal spirometry results were more likely to quit than patients with normal spirometry. In the first study, 4494 patients with at least 10 pack-years of smoking from 10 outpatient chest clinics in Poland underwent spirometry and were counseled to quit smoking; 1177 had abnormal spirometry results.

One year later, 16.3% of smokers with abnormal results had quit smoking, compared with 12% in the group with normal spirometry (P=.0003; NNT=23).4

The second study, also at outpatient chest clinics in Poland, evaluated spirometry plus cessation advice among 558 smokers, 297 of whom had abnormal spirometry results. At 1 year, 10.6% of patients with abnormal results had quit, compared with 8.4% of patients with normal lung function. A subgroup of 109 patients with moderate to severe airflow limitation showed significantly higher quit rates when compared with patients with mildly abnormal spirometry (16.5% vs 6.4%; P<.0001; NNT=10).5

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