title: Estimating liver cancer deaths in Thailand based on verbal autopsy study.
abstract: BACKGROUND
  Liver cancer mortality is high in Thailand but utility of related vital statistics is limited due to national vital registration (VR) data being under reported for specific causes of deaths. Accurate methodologies and reliable supplementary data are needed to provide worthy national vital statistics. This study aimed to model liver cancer deaths based on verbal autopsy (VA) study in 2005 to provide more accurate estimates of liver cancer deaths than those reported. The results were used to estimate number of liver cancer deaths during 2000-2009.
  
  
  METHODS
  A verbal autopsy (VA) was carried out in 2005 based on a sample of 9,644 deaths from nine provinces and it provided reliable information on causes of deaths by gender, age group, location of deaths in or outside hospital, and causes of deaths of the VR database. Logistic regression was used to model liver cancer deaths and other variables. The estimated probabilities from the model were applied to liver cancer deaths in the VR database, 2000-2009. Thus, the more accurately VA-estimated numbers of liver cancer deaths were obtained.
  
  
  RESULTS
  The model fits the data quite well with sensitivity 0.64. The confidence intervals from statistical model provide the estimates and their precisions. The VA-estimated numbers of liver cancer deaths were higher than the corresponding VR database with inflation factors 1.56 for males and 1.64 for females.
  
  
  CONCLUSIONS
  The statistical methods used in this study can be applied to available mortality data in developing countries where their national vital registration data are of low quality and supplementary reliable data are available.
authors.affiliation: Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Thailand.
authors.forename: Salwa
authors.initials: S
authors.lastname: Waeto
authors.affiliation: Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Thailand.
authors.forename: Nattakit
authors.initials: N
authors.lastname: Pipatjaturon
authors.affiliation: Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Thailand. tphattra@bunga.pn.psu.ac.th.
authors.forename: Phattrawan
authors.initials: P
authors.lastname: Tongkumchum
authors.affiliation: Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Thailand.
authors.forename: Chamnein
authors.initials: C
authors.lastname: Choonpradub
authors.affiliation: Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Thailand.
authors.forename: Rattikan
authors.initials: R
authors.lastname: Saelim
authors.affiliation: Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Thailand.
authors.forename: Nifatamah
authors.initials: N
authors.lastname: Makaje
mesh_terms: D017677:Age Distribution; D001344:Autopsy / Q000379:methods*; D002423:Cause of Death; D016208:Databases, Factual; D003906:Developing Countries / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008113:Liver Neoplasms / Q000401:mortality*; D008297:Male; D008962:Models, Theoretical; D015203:Reproducibility of Results; D017678:Sex Distribution; D013785:Thailand / Q000453:epidemiology
keywords: Confidence intervals; Logistic regression; Mortality; Sum contrasts