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Depoorter V, Vanschoenbeek K, Decoster L, Silversmit G, Debruyne PR, De Groof I, Bron D, Cornélis F, Luce S, Focan C, Verschaeve V, Debugne G, Langenaeken C, Van Den Bulck H, Goeminne JC, Teurfs W, Jerusalem G, Schrijvers D, Petit B, Rasschaert M, Praet JP, Vandenborre K, Milisen K, Flamaing J, Kenis C, Verdoodt F, Wildiers H. Long-term health-care utilisation in older patients with cancer and the association with the Geriatric 8 screening tool: a retrospective analysis using linked clinical and population-based data in Belgium. Lancet Healthy Longev 2023; 4:e326-e336. [PMID: 37327806 DOI: 10.1016/s2666-7568(23)00081-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Little evidence is available on the long-term health-care utilisation of older patients with cancer and whether this is associated with geriatric screening results. We aimed to evaluate long-term health-care utilisation among older patients after cancer diagnosis and the association with baseline Geriatric 8 (G8) screening results. METHODS For this retrospective analysis, we included data from three cohort studies for patients (aged ≥70 years) with a new cancer diagnosis who underwent G8 screening between Oct 19, 2009 and Feb 27, 2015, and who survived more than 3 months after G8 screening. The clinical data were linked to cancer registry and health-care reimbursement data for long-term follow-up. The occurrence of outcomes (inpatient hospital admissions, emergency department visits, use of intensive care, contacts with general practitioner [GP], contacts with a specialist, use of home care, and nursing home admissions) was assessed in the 3 years after G8 screening. We assessed the association between outcomes and baseline G8 score (normal score [>14] or abnormal [≤14]) using adjusted rate ratios (aRRs) calculated from Poisson regression and using cumulative incidence calculated as a time-to-event analysis with the Kaplan-Meier method. FINDINGS 7556 patients had a new cancer diagnosis, of whom 6391 patients (median age 77 years [IQR 74-82]) met inclusion criteria and were included. 4110 (64·3%) of 6391 patients had an abnormal baseline G8 score (≤14 of 17 points). In the first 3 months after G8 screening, health-care utilisation peaked and then decreased over time, with the exception of GP contacts and home care days, which remained high throughout the 3-year follow-up period. Compared with patients with a normal baseline G8 score, patients with an abnormal baseline G8 score had more hospital admissions (aRR 1·20 [95% CI 1·15-1·25]; p<0·0001), hospital days (1·66 [1·64-1·68]; p<0·0001), emergency department visits (1·42 [1·34-1·52]; p<0·0001), intensive care days (1·49 [1·39-1·60]; p<0·0001), general practitioner contacts (1·19 [1·17-1·20]; p<0·0001), home care days (1·59 [1·58-1·60]; p<0·0001), and nursing home admissions (16·7% vs 3·1%; p<0·0001) in the 3-year follow-up period. At 3 years, of the 2281 patients with a normal baseline G8 score, 1421 (62·3%) continued to live at home independently and 503 (22·0%) had died. Of the 4110 patients with an abnormal baseline G8 score, 1057 (25·7%) continued to live at home independently and 2191 (53·3%) had died. INTERPRETATION An abnormal G8 score at cancer diagnosis was associated with increased health-care utilisation in the subsequent 3 years among patients who survived longer than 3 months. FUNDING Stand up to Cancer, the Flemish Cancer Society.
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Affiliation(s)
| | | | - Lore Decoster
- Department of Medical Oncology, Vrije Universiteit Brussel, University Hospitals Brussels, Brussels, Belgium
| | | | - Philip R Debruyne
- Division of Medical Oncology, Kortrijk Cancer Centre, AZ Groeninge, Kortrijk, Belgium; Medical Technology Research Centre, School of Life Sciences, Anglia Ruskin University, Cambridge, UK; School of Nursing and Midwifery, University of Plymouth, Plymouth, UK
| | - Inge De Groof
- Department of Geriatric Medicine, Iridium Network Antwerp, Sint-Augustinus Cancer Center, Wilrijk, Belgium
| | - Dominique Bron
- Department of Hematology, Institute Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - Frank Cornélis
- Department of Medical Oncology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Sylvie Luce
- Department of Medical Oncology, University Hospital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Christian Focan
- Department of Oncology, Clinique CHC MontLégia, Liège, Belgium
| | - Vincent Verschaeve
- Department of Medical Oncology, Grand Hôpital de Charleroi, Charleroi, Belgium
| | - Gwenaëlle Debugne
- Department of Geriatric Medicine, Centre Hospitalier de Mouscron, Mouscron, Belgium
| | | | | | - Jean-Charles Goeminne
- Department of Medical Oncology, Centre Hospitalier Universitaire UCL-Namur, Namur, Belgium
| | - Wesley Teurfs
- Department of Medical Oncology, ZNA Stuivenberg, Antwerp, Belgium
| | - Guy Jerusalem
- Department of Medical Oncology, Centre Hospitalier Universitaire Sart Tilman, Liège University, Liège, Belgium
| | - Dirk Schrijvers
- Department of Medical Oncology, ZNA Middelheim, Antwerp, Belgium
| | - Bénédicte Petit
- Department of Medical Oncology, Centre Hospitalier Jolimont, La Louvière, Belgium
| | - Marika Rasschaert
- Department of Medical Oncology, University Hospital Antwerp, Edegem, Belgium
| | - Jean-Philippe Praet
- Department of Geriatric Medicine, Centre Hospitalier Universitaire St-Pierre, Free Universities Brussels, Brussels, Belgium
| | | | - Koen Milisen
- Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium; Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Johan Flamaing
- Department of Public Health and Primary Care, Gerontology and Geriatrics, KU Leuven, Leuven, Belgium; Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Cindy Kenis
- Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium; Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium; Department of General Medical Oncology, University Hospitals Leuven, Leuven, Belgium
| | - Freija Verdoodt
- Research Department, Belgian Cancer Registry, Brussels, Belgium
| | - Hans Wildiers
- Department of Oncology, KU Leuven, Leuven, Belgium; Department of General Medical Oncology, University Hospitals Leuven, Leuven, Belgium.
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Depoorter V, Vanschoenbeek K, Decoster L, Silversmit G, Debruyne PR, De Groof I, Bron D, Cornélis F, Luce S, Focan C, Verschaeve V, Debugne G, Langenaeken C, Van Den Bulck H, Goeminne JC, Teurfs W, Jerusalem G, Schrijvers D, Petit B, Rasschaert M, Praet JP, Vandenborre K, De Schutter H, Milisen K, Flamaing J, Kenis C, Verdoodt F, Wildiers H. End-of-Life Care in the Last Three Months before Death in Older Patients with Cancer in Belgium: A Large Retrospective Cohort Study Using Data Linkage. Cancers (Basel) 2023; 15:3349. [PMID: 37444458 DOI: 10.3390/cancers15133349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 06/16/2023] [Accepted: 06/18/2023] [Indexed: 07/15/2023] Open
Abstract
This study aims to describe end-of-life (EOL) care in older patients with cancer and investigate the association between geriatric assessment (GA) results and specialized palliative care (SPC) use. Older patients with a new cancer diagnosis (2009-2015) originally included in a previous multicentric study were selected if they died before the end of follow-up (2019). At the time of cancer diagnosis, patients underwent geriatric screening with Geriatric 8 (G8) followed by GA in case of a G8 score ≤14/17. These data were linked to the cancer registry and healthcare reimbursement data for follow-up. EOL care was assessed in the last three months before death, and associations were analyzed using logistic regression. A total of 3546 deceased older patients with cancer with a median age of 79 years at diagnosis were included. Breast, colon, and lung cancer were the most common diagnoses. In the last three months of life, 76.3% were hospitalized, 49.1% had an emergency department visit, and 43.5% received SPC. In total, 55.0% died in the hospital (38.5% in a non-palliative care unit and 16.4% in a palliative care unit). In multivariable analyses, functional and cognitive impairment at cancer diagnosis was associated with less SPC. Further research on optimizing EOL healthcare utilization and broadening access to SPC is needed.
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Affiliation(s)
| | | | - Lore Decoster
- Department of Medical Oncology, Oncologisch Centrum, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, 1090 Brussels, Belgium
| | - Geert Silversmit
- Research Department, Belgian Cancer Registry, 1210 Brussels, Belgium
| | - Philip R Debruyne
- Division of Medical Oncology, Kortrijk Cancer Centre, AZ Groeninge, 8500 Kortrijk, Belgium
- School of Life Sciences, Medical Technology Research Centre (MTRC), Anglia Ruskin University, Cambridge CB1 1PT, UK
- School of Nursing & Midwifery, University of Plymouth, Plymouth PL4 8AA, UK
| | - Inge De Groof
- Department of Geriatric Medicine, Iridium Cancer Network Antwerp, Sint-Augustinus, 2610 Wilrijk, Belgium
| | - Dominique Bron
- Department of Hematology, ULB-Institute Jules Bordet, 1070 Brussels, Belgium
| | - Frank Cornélis
- Department of Medical Oncology, Cliniques Universitaires Saint-Luc-UCLouvain, 1200 Brussels, Belgium
| | - Sylvie Luce
- Department Medical Oncology, University Hospital Erasme, Université Libre de Bruxelles ULB, 1000 Brussels, Belgium
| | - Christian Focan
- Department of Oncology, Groupe Santé CHC-Liège, Clinique CHC-MontLégia, 4000 Liège, Belgium
| | - Vincent Verschaeve
- Department of Medical Oncology, GHDC Grand Hôpital de Charleroi, 6000 Charleroi, Belgium
| | - Gwenaëlle Debugne
- Department of Geriatric Medicine, Centre Hospitalier de Mouscron, 7700 Mouscron, Belgium
| | | | | | | | - Wesley Teurfs
- Department Medical Oncology, ZNA Stuivenberg, 2060 Antwerp, Belgium
| | - Guy Jerusalem
- Department of Medical Oncology, Centre Hospitalier Universitaire Sart Tilman, Liège University, 4000 Liège, Belgium
| | - Dirk Schrijvers
- Department of Medical Oncology, ZNA Middelheim, 2020 Antwerp, Belgium
| | - Bénédicte Petit
- Department of Medical Oncology, Centre Hospitalier Jolimont, 7100 La Louvière, Belgium
| | - Marika Rasschaert
- Department of Medical Oncology, University Hospital Antwerp, 2650 Edegem, Belgium
| | - Jean-Philippe Praet
- Department of Geriatric Medicine, CHU St-Pierre, Free Universities Brussels, 1000 Brussels, Belgium
| | | | | | - Koen Milisen
- Academic Centre for Nursing and Midwifery, Department of Public Health and Primary Care, KU Leuven, 3000 Leuven, Belgium
- Department of Geriatric Medicine, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Johan Flamaing
- Department of Geriatric Medicine, University Hospitals Leuven, 3000 Leuven, Belgium
- Gerontology and Geriatrics, Department of Public Health and Primary Care, KU Leuven, 3000 Leuven, Belgium
| | - Cindy Kenis
- Academic Centre for Nursing and Midwifery, Department of Public Health and Primary Care, KU Leuven, 3000 Leuven, Belgium
- Department of Geriatric Medicine, University Hospitals Leuven, 3000 Leuven, Belgium
- Department of General Medical Oncology, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Freija Verdoodt
- Research Department, Belgian Cancer Registry, 1210 Brussels, Belgium
| | - Hans Wildiers
- Department of Oncology, KU Leuven, 3000 Leuven, Belgium
- Department of General Medical Oncology, University Hospitals Leuven, 3000 Leuven, Belgium
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Depoorter V, Vanschoenbeek K, Decoster L, De Schutter H, Debruyne PR, De Groof I, Bron D, Cornélis F, Luce S, Focan C, Verschaeve V, Debugne G, Langenaeken C, Van Den Bulck H, Goeminne JC, Teurfs W, Jerusalem G, Schrijvers D, Petit B, Rasschaert M, Praet JP, Vandenborre K, Milisen K, Flamaing J, Kenis C, Verdoodt F, Wildiers H. Linking clinical and population-based data in older patients with cancer in Belgium: Feasibility and clinical outcomes. J Geriatr Oncol 2023; 14:101428. [PMID: 36804333 DOI: 10.1016/j.jgo.2023.101428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 11/04/2022] [Accepted: 01/11/2023] [Indexed: 02/17/2023]
Abstract
INTRODUCTION Geriatric screening and geriatric assessment (GS/GA) have proven their benefits in the care for older patients with cancer. However, less is known about the predictive value of GS/GA for outcomes. To research this, clinical data on GS/GA can be enriched with population-based data. In this article we describe the methods and feasibility of data linkage, and first clinical outcomes (GS/GA results and overall survival). MATERIALS AND METHODS A large cohort study consisting of patients aged ≥70 years with a new cancer diagnosis was established using linked data from clinical and population-based databases. Clinical data were derived from a previous prospective study where older patients with cancer were screened with G8, followed by GA in case of an abnormal result (GS/GA study; 2009-2015). These data were linked to cancer registration data from the Belgian Cancer Registry (BCR), reimbursement data of the health insurance companies (InterMutualistic Agency, IMA), and hospital discharge data (Technical Cell, TCT). Cox regression analyses were conducted to evaluate the prognostic value of the G8 geriatric screening tool. RESULTS Of the 8067 eligible patients with a new cancer diagnosis, linkage of data from the GS/GA study and data from the BCR was successful for 93.7%, resulting in a cohort of 7556 patients available for the current analysis. Further linkage with the IMA and TCT database resulted in a cohort of 7314 patients (96.8%). Based on G8 geriatric screening, 67.9% of the patients had a geriatric risk profile. Malnutrition and functional dependence were the most common GA-identified risk factors. An abnormal baseline G8 score (≤14/17) was associated with lower overall survival (adjusted HR [aHR] = 1.62 [1.50-1.75], p < 0.001). DISCUSSION Linking clinical and population-based databases for older patients with cancer has shown to be feasible. The GS/GA results at cancer diagnosis demonstrate the vulnerability of this population and the G8 score showed prognostic value for overall survival. The established cohort of almost 8000 patients with long-term follow-up will serve as a basis in the future for detailed analyses on long-term outcomes beyond survival.
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Affiliation(s)
| | | | - Lore Decoster
- Universitair Ziekenhuis Brussel - Vrije Universiteit Brussel, Oncologisch Centrum - Department of Medical Oncology, Brussels, Belgium
| | | | - Philip R Debruyne
- General Hospital Groeninge, Kortrijk Cancer Centre, Kortrijk, Belgium; Anglia Ruskin University, Medical Technology Research Centre (MTRC), School of Life Sciences, Cambridge, UK; University of Plymouth, School of Nursing & Midwifery, Plymouth, UK
| | - Inge De Groof
- Iridium Cancer Network Antwerp - Sint-Augustinus, Department of Geriatric Medicine, Wilrijk, Belgium
| | - Dominique Bron
- ULB Institute Jules Bordet, Department of Hematology, Brussels, Belgium
| | - Frank Cornélis
- Cliniques Universitaires Saint-Luc - UCLouvain, Department of Medical Oncology, Brussels, Belgium
| | - Sylvie Luce
- University Hospital Erasme- Université Libre de Bruxelles ULB, Department Medical Oncology, Brussels, Belgium
| | - Christian Focan
- Clinique CHC-MontLégia, Groupe Santé CHC-Liège, Department of Oncology, Liège, Belgium
| | - Vincent Verschaeve
- GHDC Grand Hôpital de Charleroi, Department of Medical Oncology, Charleroi, Belgium
| | - Gwenaëlle Debugne
- Centre Hospitalier de Mouscron, Department of Geriatric Medicine, Mouscron, Belgium
| | | | | | | | - Wesley Teurfs
- ZNA Stuivenberg, Department Medical Oncology, Antwerp, Belgium
| | - Guy Jerusalem
- Centre Hospitalier Universitaire Sart Tilman - Liège University, Department of Medical Oncology, Liège, Belgium
| | - Dirk Schrijvers
- ZNA Middelheim, Department of Medical Oncology, Antwerp, Belgium
| | - Bénédicte Petit
- Centre Hospitalier Jolimont, Department of Medical Oncology, La Louvière, Belgium
| | - Marika Rasschaert
- University Hospital Antwerp, Department of Medical Oncology, Edegem, Belgium
| | - Jean-Philippe Praet
- CHU St-Pierre - Free Universities Brussels, Department of Geriatric Medicine, Brussels, Belgium
| | | | - Koen Milisen
- University Hospitals Leuven - KU Leuven, Department of Geriatric Medicine - Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, Leuven, Belgium
| | - Johan Flamaing
- University Hospitals Leuven - KU Leuven, Department of Geriatric Medicine - Department of Public Health and Primary Care, Gerontology and Geriatrics, Leuven, Belgium
| | - Cindy Kenis
- University Hospitals Leuven, Department of General Medical Oncology - Department of Geriatric Medicine, Leuven, Belgium
| | - Freija Verdoodt
- Belgian Cancer Registry, Research Department, Brussels, Belgium
| | - Hans Wildiers
- University Hospitals Leuven - KU Leuven, Department of General Medical Oncology - Department of Oncology, Leuven, Belgium.
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Depoorter V, Vanschoenbeek K, Decoster L, De Schutter H, Debruyne P, De Groof I, Bron D, Cornelis F, Luce S, Focan C, Verschaeve V, Debugne G, Langenaeken C, van den Bulck H, Goeminne JC, Milisen K, Flamaing J, Kenis C, Verdoodt F, Wildiers H. 1265MO Cause and place of death in older patients with cancer: Results from a large cohort study using linked clinical and population-based data. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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Depoorter V, Vanschoenbeek K, Decoster L, De Schutter H, Debruyne PR, DeGroof I, Bron D, Cornélis F, Luce S, Focan CNJ, Verschaeve V, Debugne G, Langenaeken CMLH, Van Den Bulck H, Goeminne JC, Milisen K, Flamaing J, Kenis C, Verdoodt F, Wildiers H. General practitioner contacts, hospitalizations, and nursing home transfers in older patients up to three years after new cancer diagnosis: Results from a large data linkage cohort study. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.12041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
12041 Background: Long-term outcomes after cancer diagnosis in older persons are largely unexplored because of limited follow-up in clinical studies. By linking clinical data with population-based data, studying long-term outcomes in large cohorts becomes feasible. The current study aims to explore long-term outcomes in the care trajectory of older patients with cancer and to assess their association with baseline geriatric screening and assessment (GS/GA) results. Methods: A large cohort study of older patients with a new cancer diagnosis was set up by linking clinical, cancer registry and administrative health data based on a unique patient identifier. Clinical data were derived from a previously performed prospective multicentric Belgian study (2009-2015). Patients aged ≥ 70 years were screened with G8 followed by GA in case of an abnormal result (≤14/17). Tumor characteristics and vital status were derived from cancer registry data and long-term outcomes (general practitioner (GP) contacts, hospitalizations and nursing home transfers) from administrative health data. In patients that survived at least 3 months since inclusion, outcomes were assessed from the day after inclusion until 3 years after. Event rates were calculated using person-time at risk to allow for varying follow-up time. Patients were censored 3 months before death to exclude influence of end-of-life care. Results: After data linkage, 6,391 older patients with a new cancer diagnosis were available for this analysis. The median age was 77 (range: 70–100) and 59.8% was female. Diagnoses included solid (92.8%) and hematologic malignancies (7.2%). In the patients with a solid tumor, breast, colorectal and lung cancer were the most common and 20.1% of patients had stage IV. 64.3% of patients had an abnormal baseline G8 score. During the 3 year follow-up, 2,602 (40.7%) of the included patients died. In these 3 years, 5,985 (95.2%) patients had at least one contact with a GP and 4,634 (72.5%) had at least one new hospital admission (event rates in Table 1). Of the 3,724 patients living independently at inclusion and still alive after 3 years, 281 (7.5%) had been transferred to a nursing home and of those, 240 (85.4%) patients had an abnormal baseline G8 score. Conclusions: Older patients with an abnormal baseline G8 score have more GP contacts, hospital admissions and nursing home transfers in the 3 years following a new cancer diagnosis compared to patients with normal baseline G8 score. Baseline G8 could help identify patients at risk for higher long-term healthcare utilization.[Table: see text]
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Affiliation(s)
| | | | | | | | | | | | | | - Frank Cornélis
- Cliniques Universitaires Saint-Luc - UCLouvain, Brussels, Belgium
| | - Sylvie Luce
- University Hospital Erasme, Brussels, Belgium
| | - C. N. J. Focan
- Clinique Saint-Joseph - CHC-Liège Hospital Group, Liège, Belgium
| | | | | | | | | | | | | | | | - Cindy Kenis
- University Hospitals Leuven, Leuven, Belgium
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Depoorter V, Vanschoenbeek K, Decoster L, De Schutter H, Debruyne P, De Groof I, Bron D, Cornélis F, Luce S, Focan C, Verschaeve V, Debugne G, Langenaeken C, Van Den Bulck H, Goeminne J, Teurfs W, Jerusalem G, Schrijvers D, Petit B, Geboers K, Forceville K, Praet J, Vandenborre K, Milisen K, Flamaing J, Kenis C, Verdoodt F, Wildiers H. Geriatric screening and assessment among older patients with cancer: evaluation of long-term outcomes in a multicentric cohort of > 7, 000 patients. J Geriatr Oncol 2021. [DOI: 10.1016/s1879-4068(21)00457-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Izci H, Tambuyzer T, Tuand K, Depoorter V, Laenen A, Wildiers H, Vergote I, Van Eycken L, De Schutter H, Verdoodt F, Neven P. A Systematic Review of Estimating Breast Cancer Recurrence at the Population Level With Administrative Data. J Natl Cancer Inst 2021; 112:979-988. [PMID: 32259259 DOI: 10.1093/jnci/djaa050] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 03/20/2020] [Accepted: 03/31/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Exact numbers of breast cancer recurrences are currently unknown at the population level, because they are challenging to actively collect. Previously, real-world data such as administrative claims have been used within expert- or data-driven (machine learning) algorithms for estimating cancer recurrence. We present the first systematic review and meta-analysis, to our knowledge, of publications estimating breast cancer recurrence at the population level using algorithms based on administrative data. METHODS The systematic literature search followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We evaluated and compared sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of algorithms. A random-effects meta-analysis was performed using a generalized linear mixed model to obtain a pooled estimate of accuracy. RESULTS Seventeen articles met the inclusion criteria. Most articles used information from medical files as the gold standard, defined as any recurrence. Two studies included bone metastases only in the definition of recurrence. Fewer studies used a model-based approach (decision trees or logistic regression) (41.2%) compared with studies using detection rules without specified model (58.8%). The generalized linear mixed model for all recurrence types reported an accuracy of 92.2% (95% confidence interval = 88.4% to 94.8%). CONCLUSIONS Publications reporting algorithms for detecting breast cancer recurrence are limited in number and heterogeneous. A thorough analysis of the existing algorithms demonstrated the need for more standardization and validation. The meta-analysis reported a high accuracy overall, which indicates algorithms as promising tools to identify breast cancer recurrence at the population level. The rule-based approach combined with emerging machine learning algorithms could be interesting to explore in the future.
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Affiliation(s)
- Hava Izci
- Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium
| | - Tim Tambuyzer
- Research Department, Belgian Cancer Registry, Brussels, Belgium
| | - Krizia Tuand
- KU Leuven Libraries - 2Bergen - Learning Centre Désiré Collen, Leuven, Belgium
| | - Victoria Depoorter
- Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium
| | - Annouschka Laenen
- Interuniversity Centre for Biostatistics and Statistical Bioinformatics, Leuven, Belgium
| | - Hans Wildiers
- Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium.,Department of General Medical Oncology, University Hospitals Leuven, Leuven, Belgium
| | - Ignace Vergote
- Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium.,Department of Gynaecological Oncology, University Hospitals Leuven, Leuven, Belgium
| | | | | | - Freija Verdoodt
- Research Department, Belgian Cancer Registry, Brussels, Belgium
| | - Patrick Neven
- Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium.,Department of Gynaecological Oncology, University Hospitals Leuven, Leuven, Belgium
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Jeurissen S, Vergauwen G, Van Deun J, Lapeire L, Depoorter V, Miinalainen I, Sormunen R, Van den Broecke R, Braems G, Cocquyt V, Denys H, Hendrix A. The isolation of morphologically intact and biologically active extracellular vesicles from the secretome of cancer-associated adipose tissue. Cell Adh Migr 2017; 11:196-204. [PMID: 28146372 DOI: 10.1080/19336918.2017.1279784] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Breast cancer cells closely interact with different cell types of the surrounding adipose tissue to favor invasive growth and metastasis. Extracellular vesicles (EVs) are nanometer-sized vesicles secreted by different cell types that shuttle proteins and nucleic acids to establish cell-cell communication. To study the role of EVs released by cancer-associated adipose tissue in breast cancer progression and metastasis a standardized EV isolation protocol that obtains pure EVs and maintains their functional characteristics is required. We implemented differential ultracentrifugation as a pre-enrichment step followed by OptiPrep density gradient centrifugation (dUC-ODG) to isolate EVs from the conditioned medium of cancer-associated adipose tissue. A combination of immune-electron microscopy, nanoparticle tracking analysis (NTA) and Western blot analysis identified EVs that are enriched in flotillin-1, CD9 and CD63, and sized between 20 and 200 nm with a density of 1.076-1.125 g/ml. The lack of protein aggregates and cell organelle proteins confirmed the purity of the EV preparations. Next, we evaluated whether dUC-ODG isolated EVs are functionally active. ZR75.1 breast cancer cells treated with cancer-associated adipose tissue-secreted EVs from breast cancer patients showed an increased phosphorylation of CREB. MCF-7 breast cancer cells treated with adipose tissue-derived EVs exhibited a stronger propensity to form cellular aggregates. In conclusion, dUC-ODG purifies EVs from conditioned medium of cancer-associated adipose tissue, and these EVs are morphologically intact and biologically active.
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Affiliation(s)
- Sarah Jeurissen
- a Laboratory of Experimental Cancer Research , Department of Radiation Oncology and Experimental Cancer Research, Ghent University , Ghent , Belgium.,b Department of Medical Oncology and Department of Gynaecology , Ghent University Hospital , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - Glenn Vergauwen
- a Laboratory of Experimental Cancer Research , Department of Radiation Oncology and Experimental Cancer Research, Ghent University , Ghent , Belgium.,c Department of Gynaecology , Ghent University Hospital , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - Jan Van Deun
- a Laboratory of Experimental Cancer Research , Department of Radiation Oncology and Experimental Cancer Research, Ghent University , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - Lore Lapeire
- b Department of Medical Oncology and Department of Gynaecology , Ghent University Hospital , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - Victoria Depoorter
- a Laboratory of Experimental Cancer Research , Department of Radiation Oncology and Experimental Cancer Research, Ghent University , Ghent , Belgium
| | - Ilkka Miinalainen
- e Biocenter Oulu and Departments of Pathology , University of Oulu and Oulu University Hospital , Oulu , Finland
| | - Raija Sormunen
- e Biocenter Oulu and Departments of Pathology , University of Oulu and Oulu University Hospital , Oulu , Finland
| | - Rudy Van den Broecke
- c Department of Gynaecology , Ghent University Hospital , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - Geert Braems
- c Department of Gynaecology , Ghent University Hospital , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - Véronique Cocquyt
- b Department of Medical Oncology and Department of Gynaecology , Ghent University Hospital , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - Hannelore Denys
- b Department of Medical Oncology and Department of Gynaecology , Ghent University Hospital , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
| | - An Hendrix
- a Laboratory of Experimental Cancer Research , Department of Radiation Oncology and Experimental Cancer Research, Ghent University , Ghent , Belgium.,d Cancer Research Institute Ghent (CRIG) , Ghent , Belgium
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