title: Simulation modelling to validate the flow method for estimating completeness of case ascertainment by cancer registries.
abstract: BACKGROUND
  To validate estimates of completeness of cancer ascertainment obtained by the flow method.
  
  
  METHODS
  We generated a computer simulation of patient-level cancer registration processes, based loosely on the age distribution and survival of colorectal carcinoma patients, and utilizing a mixture of 'cured' and 'killed' subjects with an age-dependent fraction of 'cured' cases. The simulated data were then used in an analysis of completeness using the flow method. Validation of the simulation process was based on similarity of outputs to those obtained using real data, and validation of the flow method on its ability to correctly estimate the known proportion of cases in the simulated data which would never be registered.
  
  
  RESULTS
  We successfully generated realistic data and have shown that completeness estimated by the flow method is close to the true value, whereas another method of estimating completeness (Ajiki's) was shown to be strongly biased. We also modelled what happens to completeness estimates when a new registry is set up.
  
  
  CONCLUSIONS
  When its assumptions are met (steady state for incidence, survival and stable population structure), the flow method works well but is biased for cancers with good survival. Further research is required to assess the robustness of the method when these conditions are not met.
authors.affiliation: Trent Cancer Registry, Fulwood House, 5 Old Fulwood Road, Sheffield S10 3TG, UK.
authors.forename: Paul B S
authors.initials: PB
authors.lastname: Silcocks
authors.forename: David
authors.initials: D
authors.lastname: Robinson
mesh_terms: D015982:Bias; D015179:Colorectal Neoplasms / Q000453:epidemiology; D003198:Computer Simulation; D006801:Humans; D015233:Models, Statistical; D009369:Neoplasms / Q000453:epidemiology*; D012042:Registries / Q000592:standards*; D013222:State Medicine; D006113:United Kingdom / Q000453:epidemiology