Prognostic variables and scores identifying the end of life in COPD: a systematic review

Abstract

Introduction

COPD is a major cause of mortality, and the unpredictable trajectory of the disease can bring challenges to end-of-life care. We aimed to investigate known prognostic variables and scores that predict prognosis in COPD in a systematic literature review, specifically including variables that contribute to risk assessment of patients for death within 12 months.

Methods

We conducted a systematic review on prognostic variables, multivariate score or models for COPD. Ovid MEDLINE, EMBASE, the Cochrane database, Cochrane CENTRAL, DARE and CINAHL were searched up to May 1, 2016.

Results

A total of 5,276 abstracts were screened, leading to 516 full-text reviews, and 10 met the inclusion criteria. No multivariable indices were developed with the specific aim of predicting all-cause mortality in stable COPD within 12 months. Only nine indices were identified from four studies, which had been validated for this time period. Tools developed using expert knowledge were also identified, including the Gold Standards Framework Prognostic Indicator Guidance, the RADboud Indicators of Palliative Care Needs, the Supportive and Palliative Care Indicators Tool and the Necesidades Paliativas program tool.

Conclusion

A number of variables contributing to the prediction of all-cause mortality in COPD were identified. However, there are very few studies that are designed to assess, or report, the prediction of mortality at or less than 12 months. The quality of evidence remains low, such that no single variable or multivariable score can currently be recommended.

Keywords:

• COPD
• palliative care
• end of life

Supplementary materials

Tools for the identification of patients in the last year of life in COPD which were identified as part of the review, but which have not been tested for accuracy

1. Gold Standards Framework Prognostic Indicator Guidance (GSF-PIG): The Gold Standards Framework is “a systematic, evidence based approach to optimising care for all patients approaching the end of life, delivered by generalist frontline care providers.” One part of the program is the provision of prognostic indicator guidance (GSF-PIG) which aims to identify those in the last year of life, to include them on the palliative care register, as when this is achieved “there is good evidence that they are more likely to receive well-coordinated, high quality care.”¹ It is emphasized in the guidance that prognostication is inherently difficult, and that the focus should be on identification of needs, and “rainy-day thinking” to plan ahead for those at risk of decline and death. Any tool must be placed within a clinical context, used alongside clinical judgment rather than in place of it. However, any tools claiming to aid the identification of those in the last year of life should be assessed for accuracy and impact. Studies which include patients with COPD have been conducted in hospitalized patients assessing the predictive value of the GSF-PIG, suggesting that screening with GSF-PIG may be useful in this population, although based on very small numbers in a single center. No similar studies were identified in patients with COPD in the community.

2. RADboud Indicators of Palliative Care Needs (RAD-PAC): The RADPAC study² proposed guidance on the identification of patients with COPD, heart failure and cancer nearing the end of life, developed through a literature review, focus group interviews and a modified Rand Delphi method. The literature review mainly identified prognostic indicators, while the focus groups included triggers to consider palliative care not necessarily related to prognosis. At the end of this process, six indicators were identified for COPD, to help general practitioners (GPs) identify patients in need of palliative care. RADPAC is under study in a randomized controlled trial including 158 GPs in the Netherlands, comparing the intervention to usual care. Outcomes will include quality of life, hospitalizations and other planned care, place of death and time before death that identification of palliative needs occurred.³

3. Supportive and Palliative Care Indicators Tool (SPICT): The SPICT was initially developed in 2010 by expert consensus as a guide to identify those at risk of deteriorating and dying who may benefit from supportive and palliative care. It was refined using a mixed-method approach, including peer review of multiple iterations of the tool via a web-based system, and a prospective case-finding study of patients with advanced renal, liver, cardiac or respiratory disease following an unplanned admission to an acute hospital followed up for 12 months. Although identified at hospital admission for this arm of the study, the prognostic indicators were designed to be used in both primary and secondary care. The indicators are not specific to COPD, but are for respiratory disease in general. Limited data are presented, but 17 patients with COPD were identified by the tool, 50% of whom had died by 12 months of follow-up.¹ Interestingly in the earlier version of the tool, parameters were more specifically defined, and the tool included the surprise question, while in the later version parameters are broader and the surprise question has been removed.

4. Necesidades Paliativas (NECPAL) program: The NEC-PAL program is part of the World Health Organization (WHO) Demonstration Project on Palliative Care in Catalonia (Spain), aiming to improve palliative care in the region. It focuses on early identification and improved care of patients with advanced chronic conditions in the community. The NECPAL CCOMS-ICO tool⁴ has been developed as part of the program, aiming to predict 12-month risk of death for patients with chronic advanced diseases. It was based on the GSF-PIG and SPICT tools with additional indicators felt to be relevant to a Spanish health care setting added. The tool was evaluated by a multidisciplinary expert panel, and after five iterations a final tool was proposed. The tool has been used in a cross-sectional, population-based study to investigate the prevalence and characteristics of patients with advanced chronic conditions (including COPD) in need of palliative care, estimating that this was 1.5% of the population. An analysis of the tool’s predictive capacity for 12-month risk of death (Part III of study) has not yet been published.

Table S1 GSF-PIG⁵

Table S2 RADPAC

Table S3 SPICT

Table S4 NECPAL tool

References

• Scottish GovernmentSPICT: Supportive and Palliative Indicators Tool2016 Available from: http://www.gov.scot/resource/doc/924/0111396.pdfAccessed June 28, 2017
   Google Scholar
• ThoonsenBEngelsYvan RijswijkEEarly identification of palliative care patients in general practice: development of RADboud indicators for PAlliative Care Needs (RADPAC)Br J Gen Pract201262602e625e63122947583
   PubMed Web of Science ®Google Scholar
• MeyerPAManninoDMReddSCOlsonDRCharacteristics of adults dying with COPDChest200212262003200812475839
   PubMed Web of Science ®Google Scholar
• Gómez-BatisteXMartínez-MuñozMBlayCIdentifying patients with chronic conditions in need of palliative care in the general population: development of the NECPAL tool and preliminary prevalence rates in CataloniaBMJ Support Palliat Care201333300308
   Google Scholar
• Gold Standards Framework [homepage on the Internet]National Gold Standards Framework for End of Life Care2017 Available from: http://www.goldstandardsframework.org.uk/Accessed June 28, 2017
   Google Scholar

Acknowledgments

This work was supported by the Wellcome Trust (grant number WT107183). The funder provided feedback on the overall research fellowship plan, but had no direct role in the content of the systematic review. PS receives core funding from Marie Curie, but the funder had no direct role in the content of the systematic review.

Author contributions

All authors made substantial contributions to the conception of the study. LJES and IA undertook screening, data extraction and risk of bias assessment. JKQ resolved any differences of opinion. LJES drafted the original manuscript which was reviewed and amended by EM, LS, JKQ and PS leading to revision for important intellectual content. All authors contributed toward data analysis, drafting and critically revising the paper and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.