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http://hdl.handle.net/11434/2042
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DC Field | Value | Language |
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dc.contributor.author | Prince, Miles | - |
dc.contributor.other | Doo, Nicole | - |
dc.contributor.other | White, Victoria | - |
dc.contributor.other | Martin, Kara | - |
dc.contributor.other | Bassett, Julie | - |
dc.contributor.other | Harrison, Simon | - |
dc.contributor.other | Jefford, Michael | - |
dc.contributor.other | Winship, Ingrid | - |
dc.contributor.other | Millar, Jeremy | - |
dc.contributor.other | Milne, Roger | - |
dc.contributor.other | Seymour, John | - |
dc.contributor.other | Giles, Graham | - |
dc.date | 2019-07 | - |
dc.date.accessioned | 2021-11-22T03:06:20Z | - |
dc.date.available | 2021-11-22T03:06:20Z | - |
dc.date.issued | 2019-07 | - |
dc.identifier.citation | Cancers, 11(7), 928. | en_US |
dc.identifier.issn | 2072-6694 | en_US |
dc.identifier.uri | http://hdl.handle.net/11434/2042 | - |
dc.description.abstract | Introduction: Diffuse large B cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin lymphoma for which a cure is usually the therapeutic goal of optimal treatment. Using a large population-based cohort we sought to examine the factors associated with optimal DLBCL treatment and survival. Methods: DLBCL cases were identified through the population-based Victorian Cancer Registry, capturing new diagnoses for two time periods: 2008-2009 and 2012-2013. Treatment was pre-emptively classified as 'optimal' or 'suboptimal', according to compliance with current treatment guidelines. Univariable and multivariable logistic regression models were fitted to determine factors associated with treatment and survival. Results: Altogether, 1442 DLBCL cases were included. Based on multivariable analysis, delivery of optimal treatment was less likely for those aged ≥80 years (p < 0.001), women (p = 0.012), those with medical comorbidity (p < 0.001), those treated in a non-metropolitan hospital (p = 0.02) and those who were ex-smokers (p = 0.02). Delivery of optimal treatment increased between 2008-2009 and the 2012-2013 (from 60% to 79%, p < 0.001). Delivery of optimal treatment was independently associated with a lower risk of death (hazard ratio (HR) = 0.60 (95% confidence interval (CI) 0.45-0.81), p = 0.001). Conclusion: Delivery of optimal treatment for DLBCL is associated with hospital location and category, highlighting possible demographic variation in treatment patterns. Together with an increase in the proportion of patients receiving optimal treatment in the more recent time period, this suggests that treatment decisions in DLBCL may be subject to non-clinical influences, which may have implications when evaluating equity of treatment access. The positive association with survival emphasizes the importance of delivering optimal treatment in DLBCL. | en_US |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | en_US |
dc.subject | Cancer Survival | en_US |
dc.subject | Chemotherapy | en_US |
dc.subject | Diffuse Large B Cell Lymphoma (DLBCL) | en_US |
dc.subject | Epidemiologic Studies | en_US |
dc.subject | Patterns of Care | en_US |
dc.subject | Non-Hodgkin Lymphoma | en_US |
dc.subject | Victorian Cancer Registry | en_US |
dc.subject | Suboptimal Treatment | en_US |
dc.subject | Optimal Treatment | en_US |
dc.subject | Multivariable Analysis | en_US |
dc.subject | Demographic Variation | en_US |
dc.subject | Univariable/multivariable Logistic Regression models | en_US |
dc.subject | Therapeutic Modalities | en_US |
dc.subject | R-CHOP | en_US |
dc.subject | Non-Clinical Factors | en_US |
dc.subject | Socioeconomic Status (SES) | en_US |
dc.subject | Area of Remoteness Index of Australia | en_US |
dc.subject | Epworth Centre for Immunotherapies and Snowdome Laboratories | en_US |
dc.subject | Molecular Oncology and Cancer Immunology | en_US |
dc.subject | Cancer Services Clinical Institute, Epworth HealthCare, Victoria, Australia | en_US |
dc.title | The use of optimal treatment for DLBCL is improving in all age groups and is a key factor in overall survival, but non-clinical factors influence treatment. | en_US |
dc.type | Journal Article | en_US |
dc.identifier.doi | 10.3390/cancers11070928 | en_US |
dc.identifier.journaltitle | Cancers (Basel) | en_US |
dc.description.pubmeduri | https://pubmed.ncbi.nlm.nih.gov/31269764 | en_US |
dc.description.affiliates | Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia | en_US |
dc.description.affiliates | Concord Repatriation General Hospital, Sydney Medical School, University of Sydney, Sydney, NSW 2139, Australia | en_US |
dc.description.affiliates | Concord Clinical School, University of Sydney, Concord, NSW 2139, Australia | en_US |
dc.description.affiliates | School of Psychology, Faculty of Health, Deakin University, Geelong, VIC 3220, Australia | en_US |
dc.description.affiliates | Centre for Behavioural Research in Cancer, Cancer Council Victoria, Melbourne, VIC 3004, Australia | en_US |
dc.description.affiliates | Department of Haematology, Peter MacCallum Cancer Centre & Royal Melbourne Hospital, Melbourne, VIC 3000, Australia | en_US |
dc.description.affiliates | Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, VIC 3010, Australia | en_US |
dc.description.affiliates | Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia | en_US |
dc.description.affiliates | Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, VIC 3050, Australia | en_US |
dc.description.affiliates | Department of Medicine, The University of Melbourne, Parkville, VIC 3010, Australia | en_US |
dc.description.affiliates | Alfred Health Radiation Oncology, Alfred and LaTrobe Regional Hospital, Melbourne, VIC 3004, Australia | en_US |
dc.description.affiliates | School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia | en_US |
dc.description.affiliates | Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia | en_US |
dc.description.affiliates | Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3800, Australia | en_US |
dc.type.studyortrial | Cohort Study | en_US |
dc.type.contenttype | Text | en_US |
Appears in Collections: | Cancer Services MOCI |
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