Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,00306932607174,alsfakia@gmail.com,
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Development of a risk prediction model for lung cancer: the Japan Public Health Center-based Prospective Study
by Hadrien Charvat, Shizuka Sasazuki, Taichi Shimazu, Sanjeev Budhathoki, Manami Inoue, Motoki Iwasaki, Norie Sawada, Taiki Yamaji, Shoichiro Tsugane, via Cancer Science
Abstract
While the impact of tobacco consumption on the occurrence of lung cancer is well-established, risk estimation could be improved by risk prediction models that consider various smoking habits, such as quantity, duration, and time since quitting. We constructed a risk prediction model using a population of 59,161 individuals from JPHC Study Cohort II. A parametric survival model was used to assess the impact of age, gender and smoking-related factors (cumulative smoking intensity measured in pack-years, age at initiation, and time since cessation). Ten-year cumulative probability of lung cancer occurrence estimates were calculated with consideration of the competing risk of death from other causes. Finally, the model was externally validated using 47,501 individuals from JPHC Study Cohort I. A total of 1210 cases of lung cancer occurred during 986,408 person-years of follow-up. We found a dose-dependent effect of tobacco consumption with hazard ratios for current smokers ranging from 3.78 (2.00-7.16) for cumulative consumption 15 pack-years to 15.80 (9.67-25.79) for 75 pack-years. Risk decreased with time since cessation. Ten-year cumulative probability of lung cancer occurrence estimates ranged from 0.04%-11.14% in men and 0.07%-6.55% in women. The model showed good predictive performance regarding discrimination (cross-validated c-index=0.793) and calibration (cross-validated χ2=6.60; p-value=0.58). The model still showed good discrimination in the external validation population (c-index=0.772). In conclusion, we developed a prediction model to estimate the probability of developing lung cancer based on age, gender, and tobacco consumption. This model appears useful in encouraging high-risk individuals to quit smoking and undergo increased surveillance.
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