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Identifying at-risk patients for adverse smoking outcomes: Models developed from cancer screening trial may help

Date:
October 26, 2012
Source:
Journal of the National Cancer Institute
Summary:
Risk prediction models developed from an ancillary study of the Prostate Lung Colorectal and Ovarian Cancer Screening Trial may be useful in the public health sector for identifying individuals who are at risk for adverse smoking outcomes, such as relapse among former smokers and continued smoking among current smokers, and those who may benefit from relapse prevention and smoking cessation interventions, according to a new study.
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Risk prediction models developed from an ancillary study of the Prostate Lung Colorectal and Ovarian Cancer Screening Trial (PLCO) may be useful in the public health sector for identifying individuals who are at risk for adverse smoking outcomes, such as relapse among former smokers and continued smoking among current smokers, and those who may benefit from relapse prevention and smoking cessation interventions, according to a study published October 26 in the Journal of the National Cancer Institute.

With a projected 226,160 new cases of lung cancer and 160,340 lung cancer deaths expected in the U.S. in 2012, researchers are looking at lung cancer screenings as a way to alter peoples' smoking behaviors. Although smoking abstinence is the most effective way to lower lung cancer mortality, both early detection and treatment of the disease may also lower mortality. Both the PLCO and the National Lung Screening Trial (NLST) have gathered data to determine whether screening can lower lung cancer mortality; however, the effects that screening has on smoking behavior is unknown.

To determine the effects of cancer screening on smoking behavior, Kathryn L. Taylor, Ph.D., of the Lombardi Comprehensive Cancer Center at Georgetown University, and colleagues, gathered data from participants who had completed a baseline questionnaire at PLCO trial enrollment and a supplemental questionnaire 4 years after enrollment, which assessed variables such as family history of cancer, comorbidity, and tobacco use. Multivariable logistic regression models were used to predict smoking status once the supplemental questionnaire was completed.

The researchers found that of the 31,694 former smokers on the baseline questionnaire, 1,042 had relapsed, and of the 6,807 current smokers, 4,439 had continued smoking on the supplemental questionnaire. Both relapse and continued smoking were statistically significantly linked with demographic, medical, and tobacco-related characteristics. "The relapse prediction model had excellent discrimination and calibration and suggested that relapse was more likely among longer-term smokers, recent quitters, smokers of light or ultra-light cigarettes, and pipe or cigar smokers," the researchers write, adding that the success of these models, "suggest important variables that should be considered in the development of effective intervention methods for long-term, heavily dependent smokers who are likely to be well represented in lung cancer-screening programs."


Story Source:

The above story is based on materials provided by Journal of the National Cancer Institute. Note: Materials may be edited for content and length.


Journal Reference:

  1. S. A. Barry, M. C. Tammemagi, S. Penek, E. C. Kassan, C. S. Dorfman, T. L. Riley, J. Commin, K. L. Taylor. Predictors of Adverse Smoking Outcomes in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. JNCI Journal of the National Cancer Institute, 2012; DOI: 10.1093/jnci/djs398

Cite This Page:

Journal of the National Cancer Institute. "Identifying at-risk patients for adverse smoking outcomes: Models developed from cancer screening trial may help." ScienceDaily. ScienceDaily, 26 October 2012. <www.sciencedaily.com/releases/2012/10/121026173009.htm>.
Journal of the National Cancer Institute. (2012, October 26). Identifying at-risk patients for adverse smoking outcomes: Models developed from cancer screening trial may help. ScienceDaily. Retrieved May 29, 2015 from www.sciencedaily.com/releases/2012/10/121026173009.htm
Journal of the National Cancer Institute. "Identifying at-risk patients for adverse smoking outcomes: Models developed from cancer screening trial may help." ScienceDaily. www.sciencedaily.com/releases/2012/10/121026173009.htm (accessed May 29, 2015).

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