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      Delayed diagnosis resulting in increased disease burden in multiple myeloma: the legacy of the COVID-19 pandemic

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          Abstract

          The COVID-19 pandemic has had global healthcare impacts, including high mortality from SARS-CoV-2 infection in cancer patients; individuals with multiple myeloma (MM) are especially susceptible to poor outcomes. However, even for MM patients who avoided severe infection, the ramifications of the pandemic have been considerable. The consequences of necessary socio-geographical behavior adaptation, including prolonged shielding and interruptions in delivery of non-pandemic medical services are yet to be fully understood. Using a real-world dataset of 323 consecutive newly diagnosed MM patients in England, we investigated the impact of the COVID-19 pandemic on routes to myeloma diagnosis, disease stage at presentation and relevant clinical outcomes. We demonstrate increasing MM presentations via emergency services and increased rates of bony and extra-medullary disease. Differences were seen in choice of induction therapy and the proportion of eligible patients undertaking autologous stem cell transplantation. Whilst survival was statistically inferior for emergency presentations, significant survival differences have yet to be demonstrated for the entire cohort diagnosed during the pandemic, making extended follow-up critical in this group. This dataset highlights wide-ranging issues facing MM patients consequent of the COVID-19 pandemic, with full impacts for clinicians and policy-makers yet to be elucidated.

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          International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma.

          This International Myeloma Working Group consensus updates the disease definition of multiple myeloma to include validated biomarkers in addition to existing requirements of attributable CRAB features (hypercalcaemia, renal failure, anaemia, and bone lesions). These changes are based on the identification of biomarkers associated with near inevitable development of CRAB features in patients who would otherwise be regarded as having smouldering multiple myeloma. A delay in application of the label of multiple myeloma and postponement of therapy could be detrimental to these patients. In addition to this change, we clarify and update the underlying laboratory and radiographic variables that fulfil the criteria for the presence of myeloma-defining CRAB features, and the histological and monoclonal protein requirements for the disease diagnosis. Finally, we provide specific metrics that new biomarkers should meet for inclusion in the disease definition. The International Myeloma Working Group recommends the implementation of these criteria in routine practice and in future clinical trials, and recommends that future studies analyse any differences in outcome that might occur as a result of the new disease definition.
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            The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study

            Summary Background Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types. Methods In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15–84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data. Findings We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9–9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266–295) and 344 (329–358) additional deaths. For colorectal cancer, we estimate 1445 (1392–1591) to 1563 (1534–1592) additional deaths, a 15·3–16·6% increase; for lung cancer, 1235 (1220–1254) to 1372 (1343–1401) additional deaths, a 4·8–5·3% increase; and for oesophageal cancer, 330 (324–335) to 342 (336–348) additional deaths, 5·8–6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291–3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204–63 229 years. Interpretation Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer. Funding UK Research and Innovation Economic and Social Research Council.
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              Routes to diagnosis for cancer – determining the patient journey using multiple routine data sets

              Background: Cancer survival in England is lower than the European average, which has been at least partly attributed to later stage at diagnosis in English patients. There are substantial regional and demographic variations in cancer survival across England. The majority of patients are diagnosed following symptomatic or incidental presentation. This study defines a methodology by which the route the patient follows to the point of diagnosis can be categorised to examine demographic, organisational, service and personal reasons for delayed diagnosis. Methods: Administrative Hospital Episode Statistics data are linked with Cancer Waiting Times data, data from the cancer screening programmes and cancer registration data. Using these data sets, every case of cancer registered in England, which was diagnosed in 2006–2008, is categorised into one of eight ‘Routes to Diagnosis'. Results: Different cancer types show substantial differences between the proportion of cases that present by each route, in reasonable agreement with previous clinical studies. Patients presenting via Emergency routes have substantially lower 1-year relative survival. Conclusion: Linked cancer registration and administrative data can be used to robustly categorise the route to a cancer diagnosis for all patients. These categories can be used to enhance understanding of and explore possible reasons for delayed diagnosis.
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                Author and article information

                Contributors
                g.cook@leeds.ac.uk
                Journal
                Blood Cancer J
                Blood Cancer J
                Blood Cancer Journal
                Nature Publishing Group UK (London )
                2044-5385
                15 March 2023
                15 March 2023
                December 2023
                : 13
                : 1
                : 38
                Affiliations
                [1 ]GRID grid.9909.9, ISNI 0000 0004 1936 8403, Leeds Institute of Clinical Trial research & Leeds Cancer Centre, , University of Leeds, ; Leeds, UK
                [2 ]NIHR Medtech & In Vitro Diagnostics Cooperative (Leeds), Leeds, UK
                [3 ]GRID grid.415967.8, ISNI 0000 0000 9965 1030, Dept of Haematology, Leeds Cancer Centre, , Leeds Teaching Hospitals Trust, ; Leeds, UK
                [4 ]GRID grid.412563.7, ISNI 0000 0004 0376 6589, University Hospitals Birmingham NHS Foundation Trust, ; Birmingham, UK
                [5 ]GRID grid.52996.31, ISNI 0000 0000 8937 2257, Dept of Haematology, , University College London Hospitals NHS Foundation Trust, ; London, UK
                [6 ]Dept of Haematology, Calderdale & Huddersfield Foundation Trust, Huddersfield, UK
                [7 ]GRID grid.415005.5, ISNI 0000 0004 0400 0710, Dept of Haematology, , Pinderfields Hospital, Mid Yorkshire NHS Trust, ; Wakefield, UK
                [8 ]GRID grid.1006.7, ISNI 0000 0001 0462 7212, Department of Haematology, , Newcastle University, ; Newcastle, UK
                [9 ]College of Myeloma (UK), London, UK
                Author information
                http://orcid.org/0000-0001-5946-0384
                http://orcid.org/0000-0002-0887-7195
                http://orcid.org/0000-0003-0756-969X
                Article
                795
                10.1038/s41408-023-00795-w
                10015143
                36922489
                d3a912e3-36ef-4760-9a41-04858b91c607
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 November 2022
                : 11 January 2023
                : 30 January 2023
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                © The Author(s) 2023

                Oncology & Radiotherapy
                diagnosis,signs and symptoms
                Oncology & Radiotherapy
                diagnosis, signs and symptoms

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