domingo, 7 de enero de 2018

Lifestyle Risk Prediction Model for Prostate Cancer in a Korean Population. - PubMed - NCBI

Lifestyle Risk Prediction Model for Prostate Cancer in a Korean Population. - PubMed - NCBI

Lifestyle Risk Prediction Model for Prostate Cancer in a Korean Population.

Kim SH1,2Kim S3Joung JY1Kwon WA4Seo HK1,5Chung J1Nam BH6Lee KH1.

Abstract

PURPOSE:

The use of prostate-specific antigen as a biomarker for prostate cancer (PC) has been controversial and is, therefore, not used by many countries in their national health screening programs. The biological characteristics of PC in East Asians including Koreans and Japanese are different from those in the Western populations. Potential lifestyle risk factors for PC were evaluated with the aim of developing a risk prediction model.

MATERIALS AND METHODS:

A total of 1,179,172 Korean men who were cancer free from 1996 to 1997, had taken a physical examination, and completed a lifestyle questionnaire, were enrolled in our study to predict their risk for PC for the next eight years, using the Cox proportional hazards model. The model's performance was evaluated using the C-statistic and Hosmer-Lemeshow type chi-square-statistics.

RESULTS:

The risk prediction model studied age, height, body mass index, glucose levels, family history of cancer, the frequency of meat consumption, alcohol consumption, smoking status, and physical activity, which were all significant risk factors in a univariate analysis. The model performed very well (C statistic, 0.887; 95% confidence interval, 0.879 to 0.895) and estimated an elevated PC risk in patients who did not consume alcohol or smoke, compared to heavy alcohol consumers (hazard ratio [HR], 0.78) and current smokers (HR, 0.73) (p<0.001).

CONCLUSION:

This model can be used for identifying Korean and other East Asian men who are at a high risk for developing PC, as well as for cancer screening and developing preventive health strategies.

KEYWORDS:

Decision aids; Forecasting; Life style; Prostate neoplasms

PMID:
 
29268567
 
DOI:
 
10.4143/crt.2017.484
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