Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

Background Heart failure (HF) is a major public health problem with rising prevalence, especially in elderly. Survival rates for advanced HF patients are worse than those for breast or prostate cancer. Two decades of biomarker research highlighted the prognostic ability of certain markers, and informed the development of new or updated prognostic models. Despite numerous published models and NICE’s recognition of the need for prognosis information, no risk stratification models have been adequately established, nor has the quality of the models and the evidence they present being systematically brought together and tested. Objectives We hypothesise that HF–related biomarkers may offer an added value to the traditional prognostic factors for HF clinical outcomes, independent of other present co-morbidities. We aim to test this hypothesis through a systematic reviews series assessing the evidence of HF prognostic models using novel meta-analysis (MA) methodology and relevant critical appraisal tools. Methods We follow Cochrane methodology. Published search filters were combined for a sensitive literature search. Prognostic models including at least one HF-related biomarker were eligible. Independent pairs of co-authors carried out screening and data extraction. Based on the CHARMS and PROBAST checklists we considered model development studies with and without external validation in independent data, and model updating studies. MA will be carried out using recently published novel methodology. Results Searches yielded over 40,000 titles, highlighting the need for tighter, updated prognostic search filters. A pilot screening of 10% of these (ie 4000) returned only a 2% for full text screening, with an ultimate estimate of 150 included models for evaluation. Conclusions This is a complex time constrained project with potential to advise on future HF prognostic model design; contribute to improved HF clinical management; apply recently developed MA methodology for combining prognostic model data, and inform the project for developing Cochrane methodology standards of prognostic model reviews. Acknowledgements Project funded by the British Heart Foundation (grant no. PG/17/49/33099)

Type

Conference paper