- Title
- Prognostic models and factors identifying end-of-life in non-cancer chronic diseases: a systematic review
- Creator
- Gebresillassie, Begashaw Melaku; Attia, John Richard; Mersha, Amanual Getnet; Harris, Melissa L.
- Relation
- BMJ Supportive & Palliative Care Vol. 14, Issue e3, p. e2316-e2329
- Publisher Link
- http://dx.doi.org/10.1136/spcare-2023-004656
- Publisher
- BMJ Group
- Resource Type
- journal article
- Date
- 2024
- Description
- Backgroud: Precise prognostic information, if available, is very helpful for guiding treatment decisions and resource allocation in patients with non-cancer non-communicable chronic diseases (NCDs). This study aimed to systematically review the existing evidence, examining prognostic models and factors for identifying end-of-life non-cancer NCD patients. Methods: Electronic databases, including Medline, Embase, CINAHL, Cochrane Library, PsychINFO and other sources, were searched from the inception of these databases up until June 2023. Studies published in English with findings mentioning prognostic models or factors related to identifying end-of-life in non-cancer NCD patients were included. The quality of studies was assessed using the Quality in Prognosis Studies tool. Results: The analysis included data from 41 studies, with 16 focusing on chronic obstructive pulmonary diseases (COPD), 10 on dementia, 6 on heart failure and 9 on mixed NCDs. Traditional statistical modelling was predominantly used for the identified prognostic models. Common predictors in COPD models included dyspnoea, forced expiratory volume in 1 s, functional status, exacerbation history and body mass index. Models for dementia and heart failure frequently included comorbidity, age, gender, blood tests and nutritional status. Similarly, mixed NCD models commonly included functional status, age, dyspnoea, the presence of skin pressure ulcers, oral intake and level of consciousness. The identified prognostic models exhibited varying predictive accuracy, with the majority demonstrating weak to moderate discriminatory performance (area under the curve: 0.5-0.8). Additionally, most of these models lacked independent external validation, and only a few underwent internal validation. Conclusion: Our review summarised the most relevant predictors for identifying end-of-life in non-cancer NCDs. However, the predictive accuracy of identified models was generally inconsistent and low, and lacked external validation. Although efforts to improve these prognostic models should continue, clinicians should recognise the possibility that disease heterogeneity may limit the utility of these models for individual prognostication; they may be more useful for population level health planning.
- Subject
- advance care planning; chronic conditions; chronic obstructive pulmonary disease; heart failure; neurological conditions; prognosis; SDG 3; Sustainable Development Goal
- Identifier
- http://hdl.handle.net/1959.13/1518253
- Identifier
- uon:57263
- Identifier
- ISSN:2045-435X
- Rights
- © Author(s) (or their employer(s)) 2024. Published by BMJ Group. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
- Language
- eng
- Full Text
- Reviewed
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