Prediction of the 10-year probability of gastric cancer occurrence in the Japanese population: The JPHC study cohort II

Abstract

Gastric cancer is a particularly important issue in Japan, where incidence rates are among the highest observed. In this work, we provide a risk prediction model allowing the estimation of the 10-year cumulative probability of gastric cancer occurrence. The study population consisted of 19,028 individuals from the Japanese Public Health Center cohort II who were followed-up from 1993 to 2009. A parametric survival model was used to assess the impact on the probability of gastric cancer of clinical and lifestyle-related risk factors in combination with serum anti-Helicobacter pylori antibody titres and pepsinogen I and pepsinogen II levels. Based on the resulting model, cumulative probability estimates were calculated and a simple risk scoring system was developed. A total of 412 cases of gastric cancer occurred during 270,854 person-years of follow-up. The final model included (besides the biological markers) age, gender, smoking status, family history of gastric cancer and consumption of highly salted food. The developed prediction model showed good predictive performance in terms of discrimination (optimism-corrected c-index: 0.768) and calibration (Nam and d'Agostino's χ2 test: 14.78; p values = 0.06). Estimates of the 10-year probability of gastric cancer occurrence ranged from 0.04% (0.02, 0.1) to 14.87% (8.96, 24.14) for men and from 0.03% (0.02, 0.07) to 4.91% (2.71, 8.81) for women. In conclusion, we developed a risk prediction model for gastric cancer that combines clinical and biological markers. It might prompt individuals to modify their lifestyle habits, attend regular check-up visits or participate in screening programmes. What's new? Gastric cancer is still one of the most common and deadly cancers, especially in Japan. In this study, the authors developed a model and a simple scoring system to estimate an individual's risk of developing gastric cancer, based on factors such as H. pylori antibodies, serum pepsinogen levels, and lifestyle habits. This predictive model may encourage people to modify their habits or participate in screening programmes, and may also enhance our understanding of H. pylori infection and atrophic gastritis as contributing factors in long-term gastric cancer risk.