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Treleaven L, Komesaroff P, La Brooy C, Olver I, Kerridge I, Philip J. A review of the utility of prognostic tools in predicting 6-month mortality in cancer patients, conducted in the context of voluntary assisted dying. Intern Med J 2023; 53:2180-2197. [PMID: 37029711 DOI: 10.1111/imj.16081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 03/07/2023] [Indexed: 04/09/2023]
Abstract
BACKGROUND Eligibility to access the Victorian voluntary assisted dying (VAD) legislation requires that people have a prognosis of 6 months or less (or 12 months or less in the setting of a neurodegenerative diagnosis). Yet prognostic determination is frequently inaccurate and prompts clinician discomfort. Based on functional capacity and clinical and biochemical markers, prognostic tools have been developed to increase the accuracy of life expectancy predictions. AIMS This review of prognostic tools explores their accuracy to determine 6-month mortality in adults when treated under palliative care with a primary diagnosis of cancer (the diagnosis of a large proportion of people who are requesting VAD). METHODS A systematic search of the literature was performed on electronic databases Medline, Embase and Cinahl. RESULTS Limitations of prognostication identified include the following: (i) prognostic tools still provide uncertain prognoses; (ii) prognostic tools have greater accuracy predicting shorter prognoses, such as weeks to months, rather than 6 months; and (iii) functionality was often weighted significantly when calculating prognoses. Challenges of prognostication identified include the following: (i) the area under the curve (a value that represents how well a model can distinguish between two outcomes) cannot be directly interpreted clinically and (ii) difficulties exist related to determining appropriate thresholds of accuracy in this context. CONCLUSIONS Prognostication is a significant aspect of VAD, and the utility of the currently available prognostic tools appears limited but may prompt discussions about prognosis and alternative means (other than prognostic estimates) to identify those eligible for VAD.
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Affiliation(s)
- Lydia Treleaven
- Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia
| | - Paul Komesaroff
- School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
- Department of Medicine, Alfred Hospital, Melbourne, Victoria, Australia
| | - Camille La Brooy
- School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Ian Olver
- School of Psychology, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Ian Kerridge
- Department of Medicine, Royal North Shore Hospital, St Leonards, New South Wales, Australia
- Sydney Health Ethics, The University of Sydney, Camperdown, New South Wales, Australia
| | - Jennifer Philip
- Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia
- Palliative Care Service, St Vincent's Hospital, Melbourne, Victoria, Australia
- Palliative Care Service, Peter MacCallum Cancer Centre, Royal Melbourne Hospital, Melbourne, Victoria, Australia
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Fletcher JA, Logan B, Reid N, Gordon EH, Ladwa R, Hubbard RE. How frail is frail in oncology studies? A scoping review. BMC Cancer 2023; 23:498. [PMID: 37268891 DOI: 10.1186/s12885-023-10933-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 05/08/2023] [Indexed: 06/04/2023] Open
Abstract
AIMS The frailty index (FI) is one way in which frailty can be quantified. While it is measured as a continuous variable, various cut-off points have been used to categorise older adults as frail or non-frail, and these have largely been validated in the acute care or community settings for older adults without cancer. This review aimed to explore which FI categories have been applied to older adults with cancer and to determine why these categories were selected by study authors. METHODS This scoping review searched Medline, EMBASE, Cochrane, CINAHL, and Web of Science databases for studies which measured and categorised an FI in adults with cancer. Of the 1994 screened, 41 were eligible for inclusion. Data including oncological setting, FI categories, and the references or rationale for categorisation were extracted and analysed. RESULTS The FI score used to categorise participants as frail ranged from 0.06 to 0.35, with 0.35 being the most frequently used, followed by 0.25 and 0.20. The rationale for FI categories was provided in most studies but was not always relevant. Three of the included studies using an FI > 0.35 to define frailty were frequently referenced as the rationale for subsequent studies, however, the original rationale for this categorisation was unclear. Few studies sought to determine or validate optimum FI categorises in this population. CONCLUSION There is significant variability in how studies have categorised the FI in older adults with cancer. An FI ≥ 0.35 to categorise frailty was used most frequently, however an FI in this range has often represented at least moderate to severe frailty in other highly-cited studies. These findings contrast with a scoping review of highly-cited studies categorising FI in older adults without cancer, where an FI ≥ 0.25 was most common. Maintaining the FI as a continuous variable is likely to be beneficial until further validation studies determine optimum FI categories in this population. Differences in how the FI has been categorised, and indeed how older adults have been labelled as 'frail', limits our ability to synthesise results and to understand the impact of frailty in cancer care.
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Affiliation(s)
- James A Fletcher
- Division of Cancer Services, Princess Alexandra Hospital, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia.
- Faculty of Medicine, The University of Queensland, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia.
- Faculty of Medicine, Centre for Health Services Research, The University of Queensland, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia.
| | - Benignus Logan
- Faculty of Medicine, Centre for Health Services Research, The University of Queensland, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia
| | - Natasha Reid
- Faculty of Medicine, Centre for Health Services Research, The University of Queensland, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia
| | - Emily H Gordon
- Faculty of Medicine, Centre for Health Services Research, The University of Queensland, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia
| | - Rahul Ladwa
- Division of Cancer Services, Princess Alexandra Hospital, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia
- Faculty of Medicine, The University of Queensland, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia
| | - Ruth E Hubbard
- Faculty of Medicine, Centre for Health Services Research, The University of Queensland, 199 Ipswich Road, Woolloongabba, QLD, 4102, Australia
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Extermann M, Hernández-Favela CG, Soto Perez de Celis E, Kanesvaran R. Global Aging and Cancer: Advancing Care Through Innovation. Am Soc Clin Oncol Educ Book 2022; 42:1-8. [PMID: 35452248 DOI: 10.1200/edbk_359154] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The oncology field, like many others, is digitalizing rapidly, a phenomenon that may have been accelerated by the COVID-19 pandemic. This movement is creating opportunities and challenges. Another rapidly developing change is the aging of the global population; because cancer is a disease of aging, there is a need for health systems to adapt to taking care of such patients. In this article, we address how these innovative technologies can be leveraged to improve the care of older patients with cancer beyond academic centers, such as in underserved areas and low- and middle-income countries. We review how digital technologies can be used to enhance the follow-up of patients in low- and middle-income countries. We also tackle the issue of training a global workforce to treat cancer in an aging population and how to leverage innovations in this matter. Finally, we review opportunities to expand the usefulness of big data and machine learning beyond academic centers to support private practices and underserved areas.
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Affiliation(s)
| | | | - Enrique Soto Perez de Celis
- Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
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