Unbiased estimates of long‐term net survival of hematological malignancy patients detailed by major subtypes in France |
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| Authors: | Alain Monnereau Xavier Troussard Aurlien Belot Anne‐Valrie Guizard Anne‐Sophie Woronoff Simona Bara Bndicte Laptre‐Ledoux Jean Iwaz Brigitte Tretarre Marc Maynadi |
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| Institution: | 1. Registre des Hémopathies Malignes de la Gironde, Institut Bergonié, Bordeaux, France;2. Centre INSERM U897, CIC‐EC7, Centre d'Investigation Clinique—Epidémiologie Clinique, Bordeaux, FranceTel.: +33(0)5‐56‐33‐33‐33 (office 3820), Fax: +33(0)5‐56‐33‐33‐73;3. Laboratoire d'Hématologie CHU de Caen, France;4. Registre Régional des Hémopathies Malignes de Basse Normandie, Caen, France;5. Hospices Civils de Lyon, Service de Biostatistique, Lyon, France;6. Université de Lyon, Lyon, France;7. Université Lyon 1, Villeurbanne, France;8. CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biotatistique‐Santé, Villeurbanne France;9. Département des maladies chroniques et traumatismes, Institut de Veille Sanitaire, Saint‐Maurice, France;10. Registre Général des tumeurs du Calvados, U1086 Inserm, Caen, France;11. Registre des cancers du Doubs, EA 3181, CHU de Besan?on, France;12. Registre des cancers de la Manche, Cherbourg, France;13. Registre des cancers de la Somme, Amiens, France;14. Registre des cancers de l'Hérault, Montpellier, France;15. Registre des Hémopathies Malignes de C?te d'Or, EA 4184, Université de Bourgogne et CHU de Dijon, Dijon, France |
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| 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. |
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| Keywords: | net survival population‐based study hematological malignancies cancer registry |
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