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Lymphoma incidence, survival and prevalence 2004–2014: sub-type analyses from the UK's Haematological Malignancy Research Network

BACKGROUND: Population-based information about cancer occurrence and survival are required to inform clinical practice and research; but for most lymphomas data are lacking. METHODS: Set within a socio-demographically representative UK population of nearly 4 million, lymphoma data (N=5796) are from...

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Detalles Bibliográficos
Autores principales: Smith, A, Crouch, S, Lax, S, Li, J, Painter, D, Howell, D, Patmore, R, Jack, A, Roman, E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4453686/
https://www.ncbi.nlm.nih.gov/pubmed/25867256
http://dx.doi.org/10.1038/bjc.2015.94
Descripción
Sumario:BACKGROUND: Population-based information about cancer occurrence and survival are required to inform clinical practice and research; but for most lymphomas data are lacking. METHODS: Set within a socio-demographically representative UK population of nearly 4 million, lymphoma data (N=5796) are from an established patient cohort. RESULTS: Incidence, survival (overall and relative) and prevalence estimates for >20 subtypes are presented. With few exceptions, males tended to be diagnosed at younger ages and have significantly (P<0.05) higher incidence rates. Differences were greatest at younger ages: the <15 year male/female rate ratio for all subtypes combined being 2.2 (95% CI 1.3–3.4). These gender differences impacted on prevalence; most subtype estimates being significantly (P<0.05) higher in males than females. Outcome varied widely by subtype; survival of patients with nodular lymphocyte predominant Hodgkin lymphoma approached that of the general population, whereas less than a third of those with other B-cell (e.g., mantle cell) or T-cell (e.g., peripheral-T) lymphomas survived for ≥5 years. No males/female survival differences were detected. CONCLUSIONS: Major strengths of our study include completeness of ascertainment, world-class diagnostics and generalisability. The marked variations demonstrated confirm the requirement for ‘real-world' data to inform aetiological hypotheses, health-care planning and the future monitoring of therapeutic changes.