title: Development and Validation of a Prediction Model to Estimate Individual Risk of Pancreatic Cancer.
abstract: BACKGROUND
  There is no reliable screening tool to identify people with high risk of developing pancreatic cancer even though pancreatic cancer represents the fifth-leading cause of cancer-related death in Korea. The goal of this study was to develop an individualized risk prediction model that can be used to screen for asymptomatic pancreatic cancer in Korean men and women.
  
  
  METHODS
  Gender-specific risk prediction models for pancreatic cancer were developed using the Cox proportional hazards model based on an 8-year follow-up of a cohort study of 1,289,933 men and 557,701 women in Korea who had biennial examinations in 1996-1997. The performance of the models was evaluated with respect to their discrimination and calibration ability based on the C-statistic and Hosmer-Lemeshow type χ2 statistic.
  
  
  RESULTS
  A total of 1,634 (0.13%) men and 561 (0.10%) women were newly diagnosed with pancreatic cancer. Age, height, BMI, fasting glucose, urine glucose, smoking, and age at smoking initiation were included in the risk prediction model for men. Height, BMI, fasting glucose, urine glucose, smoking, and drinking habit were included in the risk prediction model for women. Smoking was the most significant risk factor for developing pancreatic cancer in both men and women. The risk prediction model exhibited good discrimination and calibration ability, and in external validation it had excellent prediction ability.
  
  
  CONCLUSIONS
  Gender-specific risk prediction models for pancreatic cancer were developed and validated for the first time. The prediction models will be a useful tool for detecting high-risk individuals who may benefit from increased surveillance for pancreatic cancer.
authors.affiliation: Biometric Research Branch, Division of Cancer Epidemiology and Prevention, Research Institute & Hospital, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
authors.forename: Ami
authors.initials: A
authors.lastname: Yu
authors.affiliation: Center for Liver Cancer, Research Institute & Hospital, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
authors.forename: Sang Myung
authors.initials: SM
authors.lastname: Woo
authors.affiliation: Biometric Research Branch, Division of Cancer Epidemiology and Prevention, Research Institute & Hospital, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
authors.forename: Jungnam
authors.initials: J
authors.lastname: Joo
authors.affiliation: Biometric Research Branch, Division of Cancer Epidemiology and Prevention, Research Institute & Hospital, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
authors.forename: Hye-Ryung
authors.initials: HR
authors.lastname: Yang
authors.affiliation: Center for Liver Cancer, Research Institute & Hospital, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
authors.forename: Woo Jin
authors.initials: WJ
authors.lastname: Lee
authors.affiliation: Center for Liver Cancer, Research Institute & Hospital, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
authors.forename: Sang-Jae
authors.initials: SJ
authors.lastname: Park
authors.affiliation: Biometric Research Branch, Division of Cancer Epidemiology and Prevention, Research Institute & Hospital, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
authors.forename: Byung-Ho
authors.initials: BH
authors.lastname: Nam
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010190:Pancreatic Neoplasms / Q000453:epidemiology*; D016016:Proportional Hazards Models; D011446:Prospective Studies; D056910:Republic of Korea; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects