title: High rate of uncaptured myelodysplastic syndrome cases and an improved method of case ascertainment.
abstract: The myelodysplastic syndromes (MDS) are often diagnosed in outpatient clinics and may be under-reported to state cancer registries, which predominantly rely on hospital records and laboratory reports. We used a new method of cancer case capture to determine the rate of missed cases and estimate a more accurate incidence of MDS. Using a unique keyword algorithm, we queried all electronic pathology (E-path) reports sent to the state of Florida cancer registry in 2006 to identify potential MDS cases. A stratified, random sample of E-path reports was then reviewed to confirm diagnosis and assign MDS subtype. Characteristics were compared between captured and uncaptured MDS cases. 7111 E-path reports with MDS keyword hits were identified, of which only 18% linked to a registered MDS case, 47% linked to a different cancer, and 34% did not link with any record. Case review of a stratified, random sampling of 285 individuals led to the discovery that uncaptured cases made up 37.7% of the total true MDS cases in 2006. It is estimated that the true incidence of MDS is 5.3 individuals out of 100,000, compared to previous reports of 3.3 out of 100,000. Uncaptured MDS cases were younger and more likely to have information in the pathology report facilitating MDS subtype assignment. Only two-thirds of true MDS cases are captured in Florida using current case-finding mechanisms. Application of a keyword search strategy to identify cases among E-path reports is a feasible technique to improve MDS case ascertainment.
authors.affiliation: Division of Hematology and Oncology, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL, United States. Electronic address: c@ufl.edu.
authors.forename: Christopher R
authors.initials: CR
authors.lastname: Cogle
authors.affiliation: Cancer Epidemiology Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States.
authors.forename: Michelle R
authors.initials: MR
authors.lastname: Iannacone
authors.affiliation: Department of Biostatistics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States; Temple University School of Medicine, Philadelphia, PA, United States.
authors.forename: Daohai
authors.initials: D
authors.lastname: Yu
authors.affiliation: Cancer Epidemiology Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States.
authors.forename: Ashley L
authors.initials: AL
authors.lastname: Cole
authors.affiliation: Division of Hematology and Oncology, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
authors.forename: Iman
authors.initials: I
authors.lastname: Imanirad
authors.affiliation: Department of Biostatistics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States.
authors.forename: Lulu
authors.initials: L
authors.lastname: Yan
authors.affiliation: Florida Cancer Data System, University of Miami School of Medicine, Miami, FL, United States.
authors.forename: Jill A
authors.initials: JA
authors.lastname: Mackinnon
authors.affiliation: Division of Hematologic Malignancies, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States.
authors.forename: Alan F
authors.initials: AF
authors.lastname: List
authors.affiliation: Cancer Epidemiology Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States.
authors.forename: Dana E
authors.initials: DE
authors.lastname: Rollison
mesh_terms: D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D009190:Myelodysplastic Syndromes / Q000175:diagnosis* / Q000453:epidemiology; D011159:Population Surveillance / Q000379:methods*; D012042:Registries / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D018426:SEER Program / Q000706:statistics & numerical data*; D014481:United States / Q000453:epidemiology
keywords: Epidemiology; Myelodysplastic syndromes