title: A novel web informatics approach for automated surveillance of cancer mortality trends.
abstract: Cancer surveillance data are collected every year in the United States via the National Program of Cancer Registries (NPCR) and the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute (NCI). General trends are closely monitored to measure the nation's progress against cancer. The objective of this study was to apply a novel web informatics approach for enabling fully automated monitoring of cancer mortality trends. The approach involves automated collection and text mining of online obituaries to derive the age distribution, geospatial, and temporal trends of cancer deaths in the US. Using breast and lung cancer as examples, we mined 23,850 cancer-related and 413,024 general online obituaries spanning the timeframe 2008-2012. There was high correlation between the web-derived mortality trends and the official surveillance statistics reported by NCI with respect to the age distribution (ρ=0.981 for breast; ρ=0.994 for lung), the geospatial distribution (ρ=0.939 for breast; ρ=0.881 for lung), and the annual rates of cancer deaths (ρ=0.661 for breast; ρ=0.839 for lung). Additional experiments investigated the effect of sample size on the consistency of the web-based findings. Overall, our study findings support web informatics as a promising, cost-effective way to dynamically monitor spatiotemporal cancer mortality trends.
authors.affiliation: Health Data Sciences Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, United States. Electronic address: tourassig@ornl.gov.
authors.forename: Georgia
authors.initials: G
authors.lastname: Tourassi
authors.affiliation: Health Data Sciences Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, United States.
authors.forename: Hong-Jun
authors.initials: HJ
authors.lastname: Yoon
authors.affiliation: Information Systems Department, New Jersey Institute of Technology, Newark, NJ 07102, United States.
authors.forename: Songhua
authors.initials: S
authors.lastname: Xu
mesh_terms: D001943:Breast Neoplasms; D006801:Humans; D015994:Incidence; D020407:Internet; D008175:Lung Neoplasms; D008490:Medical Informatics; D009026:Mortality; D009369:Neoplasms / Q000401:mortality*; D011159:Population Surveillance; D018426:SEER Program; D014481:United States / Q000453:epidemiology
keywords: Breast cancer; Cancer mortality; Digital epidemiology; Lung cancer; Web informatics; Web mining