title: Unbiased estimates of long-term net survival of hematological malignancy patients detailed by major subtypes in France.
abstract: Long-term population-based survival data detailed by cancer subtype are important to measure the overall outcomes of malignancy managements. We provide net survival estimates at 1, 3, 5 and 10-year postdiagnosis on 37,549 hematological malignancy (HM) patients whose ages were >15 years, diagnosed between 1989 and 2004 and actively followed until 2008 by French population-based cancer registries. These are, to our knowledge, the first unbiased estimates of 10-year net survival in HMs detailed by subtypes. HMs were classified according to the International Classification of Diseases-Oncology 3. Net survival was estimated with the unbiased Pohar-Perme method. The results are reported by sex and age classes. The changes of these indicators by periods of diagnosis were tabulated and the trends of the net mortality rates over time since diagnosis graphed. In all, 5- and 10-year age-standardized net survivals after HMs varied widely from 81 and 76% for classical Hodgkin lymphoma (CHL) to 18 and 14% for acute myeloid leukemia (AML). Even in HMs with the most favorable prognoses, the net survival decreased between 5- and 10-year postdiagnosis. Women had better prognoses than men and age at diagnosis was an unfavorable prognostic factor for most HMs. In patients <55 years old, the net mortality rate decreased to null values 5-year postdiagnosis in AML and 10-year postdiagnosis in CHL, precursor non-HL, chronic myelogenous leukemia, diffuse large B-cell lymphoma and follicular lymphoma. The prognoses improved for various HMs over the study period. The obtained unbiased indicators are important to evaluate national cancer plans.
authors.affiliation: Registre des Hémopathies Malignes de la Gironde, Institut Bergonié, Bordeaux, France. A.Monnereau@bordeaux.unicancer.fr
authors.forename: Alain
authors.initials: A
authors.lastname: Monnereau
authors.forename: Xavier
authors.initials: X
authors.lastname: Troussard
authors.forename: Aurélien
authors.initials: A
authors.lastname: Belot
authors.forename: Anne-Valérie
authors.initials: AV
authors.lastname: Guizard
authors.forename: Anne-Sophie
authors.initials: AS
authors.lastname: Woronoff
authors.forename: Simona
authors.initials: S
authors.lastname: Bara
authors.forename: Bénédicte
authors.initials: B
authors.lastname: Lapôtre-Ledoux
authors.forename: Jean
authors.initials: J
authors.lastname: Iwaz
authors.forename: Brigitte
authors.initials: B
authors.lastname: Tretarre
authors.forename: Marc
authors.initials: M
authors.lastname: Maynadié
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D015982:Bias; D005260:Female; D005602:France / Q000453:epidemiology; D019337:Hematologic Neoplasms / Q000401:mortality*; D006689:Hodgkin Disease / Q000401:mortality; D006801:Humans; D007938:Leukemia / Q000401:mortality; D008228:Lymphoma, Non-Hodgkin / Q000401:mortality; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009190:Myelodysplastic Syndromes / Q000401:mortality; D011379:Prognosis; D012042:Registries; D017678:Sex Distribution