title: Frailty modeling of the bimodal age-incidence of Hodgkin lymphoma in the Nordic countries.
abstract: BACKGROUND
  The bimodality of the age-incidence curve of Hodgkin lymphoma (HL) has been ascribed to the existence of subgroups with distinct etiologies. Frailty models can be usefully applied to age-incidence curves of cancer to aid the understanding of biological phenomena in these instances. The models imply that for a given disease, a minority of individuals are at high risk, compared with the low-risk majority.
  
  
  METHODS
  Frailty modeling is applied to interpret HL incidence on the basis of population-based cancer registry data from the five Nordic countries for the period 1993 to 2007. There were a total of 8,045 incident cases and 362,843,875 person-years at risk in the study period.
  
  
  RESULTS
  A bimodal frailty analysis provides a reasonable fit to the age-incidence curves, employing 2 prototype models, which differ by having the sex covariate included in the frailty component (model 1) or in the baseline Weibull hazard (model 2). Model 2 seemed to fit better with our current understanding of HL than model 1 for the male-to-female ratio, number of rate-limiting steps in the carcinogenic process, and proportion of susceptibles; whereas model 1 performed better related to the heterogeneity in HL among elderly males.
  
  
  CONCLUSIONS
  The present analysis shows that HL age-incidence data are consistent with a bimodal frailty model, indicating that heterogeneity in cancer susceptibility may give rise to bimodality at the population level, although the individual risk remains simple and monotonically increasing by age.
  
  
  CONCLUSIONS
  Frailty modeling adds to the existing body of knowledge on the heterogeneity in risk of acquiring HL.
authors.affiliation: Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway. tom.grotmol@kreftregisteret.no
authors.forename: Tom
authors.initials: T
authors.lastname: Grotmol
authors.forename: Freddie
authors.initials: F
authors.lastname: Bray
authors.forename: Harald
authors.initials: H
authors.lastname: Holte
authors.forename: Marion
authors.initials: M
authors.lastname: Haugen
authors.forename: Lauren
authors.initials: L
authors.lastname: Kunz
authors.forename: Steinar
authors.initials: S
authors.lastname: Tretli
authors.forename: Odd O
authors.initials: OO
authors.lastname: Aalen
authors.forename: Tron A
authors.initials: TA
authors.lastname: Moger
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D003718:Denmark / Q000453:epidemiology; D005260:Female; D005387:Finland / Q000453:epidemiology; D006689:Hodgkin Disease / Q000453:epidemiology*; D006801:Humans; D007055:Iceland / Q000453:epidemiology; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D009664:Norway / Q000453:epidemiology; D016016:Proportional Hazards Models; D012042:Registries; D013548:Sweden / Q000453:epidemiology; D055815:Young Adult