Statistical methods to develop and evaluate risk prediction models

• Project/Area Number: 15K15956
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Statistical science
• Research Institution: National Cancer Center Japan
• Principal Investigator: Kuchiba Aya 国立研究開発法人国立がん研究センター, 研究支援センター, 室長 (40510699)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Project Status: Completed (Fiscal Year 2017)
• Budget Amount: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000); Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000); Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000); Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
• Keywords: 予測モデル / がん罹患 / Calibration / Discrimination / 疫学研究 / がん発症 / 絶対リスク / calibration / discrimination / リスク因子の効果の推定 / リスクの推定

Outline of Final Research Achievements

Recent cancer epidemiology has provided much evidence for cancer risk factors, including environmental, lifestyle and genetic factors. Prediction model to provide the risk of cancer based on the established risk factors, would contribute to developing risk-based prevention or health management strategies.
In the research project, the methods to estimate prediction ability of the prediction models has been examined and applied to real epidemiology studies, in particular for data from often-used study designs with biomarker data. The statistical methods for assessing etiologic heterogeneity of a cancer have been developed and applied to the cohort study data as a relevant topic. In addition, new index to evaluate prediction ability for outcome with more than two categories has been proposed and the characteristics of this index have been examined by simulation studies.

Research Products

• [Int'l Joint Research] Harvard TH Chan School of Public Health(米国)
• [Journal Article] Decomposition of the population attributable fraction for two exposures (2018)
  • Author(s): Taguri M, Kuchiba A.
  • Journal Title: Annals of Epidemiology Volume: 28 Issue: 5 Pages: 331
  • DOI: 10.1016/j.annepidem.2018.02.012
  • Peer Reviewed
• [Journal Article] Plasma 25-hydroxyvitamin D concentration and subsequent risk of total and site specific cancers in Japanese population: Large case-cohort study within Japan Public Health Center-based Prospective Study cohort (2018)
  • Author(s): Budhathoki Sanjeev、Hidaka Akihisa、Yamaji Taiki、Sawada Norie、Tanaka-Mizuno Sachiko、Kuchiba Aya、Charvat Hadrien、Goto Atsushi、Kojima Satoshi、Sudo Natsuki、Shimazu Taichi、Sasazuki Shizuka、Inoue Manami、Tsugane Shoichiro、Iwasaki Motoki
  • Journal Title: BMJ Volume: 360 Pages: k671-k671
  • DOI: 10.1136/bmj.k671
  • Peer Reviewed / Open Access
• [Journal Article] Inclusion of a genetic risk score into a validated risk prediction model for colorectal cancer in Japanese men improves performance (2017)
  • Author(s): Iwasaki Motoki、Tanaka-Mizuno Sachiko、Kuchiba Aya、Yamaji Taiki、Sawada Norie、Goto Atsushi、Shimazu Taichi、Sasazuki Shizuka、Wang Hansong、Marchand Lo?c Le、Tsugane Shoichiro
  • Journal Title: Cancer Prevention Research Volume: 10 Issue: 9 Pages: 535
  • DOI: 10.1158/1940-6207.capr-17-0141
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] A Prospective Study of Smoking and Risk of Synchronous Colorectal Cancers (2017)
  • Author(s): Drew DA, Nishihara R, Lochhead P, Kuchiba A, Qian ZR, Mima K, Nosho K, Wu K, Wang M, Giovannucci E, Fuchs CS, Chan AT, Ogino S
  • Journal Title: American Journal of Gastroenterology Volume: 112 Issue: 3 Pages: 493
  • DOI: 10.1038/ajg.2016.589
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] Statistical methods for studying disease subtype heterogeneity (2016)
  • Author(s): Wang, M., Spiegelman, D., Kuchiba, A., Lochhead, P., Kim, S., Chan, A.T., Poole, E.M., Tamimi, R., Tworoger, S.S., Giovannucci, E., Rosner, B., Ogino, S
  • Journal Title: Statistics in medicine Volume: 35 Issue: 5 Pages: 782
  • DOI: 10.1002/sim.6793
  • URL: https://localhost/en/publications/6bbaec07-a63b-40ad-97d3-e25e5f5a635b
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] A meta-regression method for studying etiological heterogeneity across disease subtypes classified by multiple biomarkers (2015)
  • Author(s): Wang, M., Kuchiba, A., Ogino, S.
  • Journal Title: American journal of epidemiology Volume: 182 Issue: 3 Pages: 263
  • DOI: 10.1093/aje/kwv040
  • Peer Reviewed / Int'l Joint Research
• [Presentation] Discrimination Index for Multi-Category Outcome (2018)
  • Author(s): Kuchiba Aya、Sakamaki Kentaro
  • Organizer: ENAR 2018 Spring Meeting
  • Int'l Joint Research
• [Presentation] Efficiency Consideration of the Etiological Heterogeneity Evaluation in Case-Case and Case-Control Studies (2017)
  • Author(s): Wang M*, Kuchiba A*, Gao R
  • Organizer: ENAR Spring Meeting
  • Place of Presentation: Washington, D.C., USA
  • Year and Date: 2017-03-12
  • Int'l Joint Research
• [Presentation] Statistical Methods for Studying Disease Etiologic Heterogeneity (2016)
  • Author(s): Wang M, Spiegelman D, Kuchiba A, Rosner B, Ogino S
  • Organizer: 2016 Epidemiology Congress of the Americas
  • Place of Presentation: Miami, Florida, USA
  • Year and Date: 2016-06-21
  • Int'l Joint Research
• [Presentation] A prospective study of smoking habit and risk of synchronous colorectal cancers (2016)
  • Author(s): Drew DA, Nishihara R, Lochhead P, Kuchiba A, Qian ZR, Mima K, Nosho K, Wu K, Wang M, Spiegelman D, Giovannucci EL, Fuchs CS, Ogino S, Chan AT
  • Organizer: AACR Annual Meeting 2016
  • Place of Presentation: New Orleans, Louisiana, USA
  • Year and Date: 2016-04-16
  • Int'l Joint Research
• [Book] (Book Chapter) Evaluation of Cancer Risk in Epidemiologic Studies with Genetic and Molecular Data. In Matsui, S. and Crowley, J. (Eds.), Frontiers of Biostatistical Methods and Applications in Clinical Oncology (2017)
  • Author(s): Kuchiba Aya
  • Publisher: Springer Singapore
  • ISBN: 9789811001246