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Showing content from https://pubmed.ncbi.nlm.nih.gov/33567163/ below:

An inverse stage-shift model to estimate the excess mortality and health economic impact of delayed access to cancer services due to the COVID-19 pandemic

Affiliations

• ¹ Centre for Cancer Research and Centre for Health Policy, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
• ² Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
• ³ Centre for Cancer Research and Department of General Practice, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
• ⁴ Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Australia.
• ⁵ Department of Cancer Research, Peter MacCallum Cancer Centre, Melbourne, Australia.
• ⁶ Division of Personalised Oncology, Walter and Eliza Hall Research Institute, Melbourne, Australia.
• ⁷ Department Medical Oncology, Western Health, Melbourne, Australia.
• ⁸ Department of Surgery, University of Melbourne, Melbourne, Australia.
• ⁹ Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia.
• ¹⁰ Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia.
• ¹¹ Health Technology and Services Research, Technical Medical Centre, Faculty of Behavioural, Management and Social Sciences, University of Twente, Enschede, the Netherlands.

• PMID: 33567163
• PMCID: PMC8014813
• DOI: 10.1111/ajco.13505

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Koen Degeling et al. Asia Pac J Clin Oncol. 2021 Aug.

• ¹ Centre for Cancer Research and Centre for Health Policy, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
• ² Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
• ³ Centre for Cancer Research and Department of General Practice, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
• ⁴ Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Australia.
• ⁵ Department of Cancer Research, Peter MacCallum Cancer Centre, Melbourne, Australia.
• ⁶ Division of Personalised Oncology, Walter and Eliza Hall Research Institute, Melbourne, Australia.
• ⁷ Department Medical Oncology, Western Health, Melbourne, Australia.
• ⁸ Department of Surgery, University of Melbourne, Melbourne, Australia.
• ⁹ Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia.
• ¹⁰ Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia.
• ¹¹ Health Technology and Services Research, Technical Medical Centre, Faculty of Behavioural, Management and Social Sciences, University of Twente, Enschede, the Netherlands.

• PMID: 33567163
• PMCID: PMC8014813
• DOI: 10.1111/ajco.13505

Item in Clipboard

Aim: Decreased cancer incidence and reported changes to clinical management indicate that the COVID-19 pandemic has delayed cancer diagnosis and treatment. This study aimed to develop and apply a flexible model to estimate the impact of delayed diagnosis and treatment on survival outcomes and healthcare costs based on a shift in the disease stage at treatment initiation.

Methods: A model was developed and made publicly available to estimate population-level health economic outcomes by extrapolating and weighing stage-specific outcomes by the distribution of stages at treatment initiation. It was applied to estimate the impact of 3- and 6-month delays based on Australian data for stage I breast cancer, colorectal cancer, and lung cancer patients, and for T1 melanoma. Two approaches were explored to estimate stage shifts following a delay: (a) based on the relation between time to treatment initiation and overall survival (breast, colorectal, and lung cancer), and (b) based on the tumor growth rate (melanoma).

Results: Using a conservative once-off 3-month delay and considering only shifts from stage I/T1 to stage II/T2, 88 excess deaths and $12 million excess healthcare costs were predicted in Australia over 5 years for all patients diagnosed in 2020. For a 6-month delay, excess mortality and healthcare costs were 349 deaths and $46 million over 5 years.

Conclusions: The health and economic impacts of delays in treatment initiation cause an imminent policy concern. More accurate individual patient data on shifts in stage of disease during and after the COVID-19 pandemic are critical for further analyses.

Keywords: COVID-19; diagnostic delays; economic outcomes; health outcomes; modeling; oncology; stage shift; time to treatment initiation; treatment delays.

© 2021 John Wiley & Sons Australia, Ltd.

PubMed Disclaimer

GMc has been a principal investigator for clinical trials with Array Biopharma and Roche/Genentech. All revenues were paid to his institution as reimbursement for trial costs. BJS has served on advisory boards for AstraZeneca, Roche/Genentech, Pfizer, Novartis, Merck, Bristol Myers Squibb, and Amgen. All other authors have declared no conflict of interest.

Graphical illustration of different types…

Graphical illustration of different types of delays within the care pathway that may…

Graphical illustration of different types of delays within the care pathway that may be induced by service disruptions due to the COVID‐19 pandemic [Color figure can be viewed at wileyonlinelibrary.com ]

Graphical illustration of how the…

Graphical illustration of how the combined overall survival for a patient population is…

Graphical illustration of how the combined overall survival for a patient population is obtained by weighting stage‐specific survival estimates by the stage distribution at treatment initiation [Color figure can be viewed at wileyonlinelibrary.com ]

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