Standardized approach to extract candidate outcomes from literature for a standard outcome set: a case- and simulation study.

AIMS: Standard outcome sets enable the value-based evaluation of health care delivery. Whereas the attainment of expert opinion has been structured using methods such as the modified-Delphi process, standardized guidelines for extraction of candidate outcomes from literature are lacking. As such, we aimed to describe an approach to obtain a comprehensive list of candidate outcomes for potential inclusion in standard outcome sets. METHODS: This study describes an iterative saturation approach, using randomly selected batches from a systematic literature search to develop a long list of candidate outcomes to evaluate healthcare. This approach can be preceded with an optional benchmark review of relevant registries and Clinical Practice Guidelines and data visualization techniques (e.g. as a WordCloud) to potentially decrease the number of iterations. The development of the International Consortium of Health Outcome Measures Heart valve disease set is used to illustrate the approach. Batch cutoff choices of the iterative saturation approach were validated using data of 1000 simulated cases. RESULTS: Simulation showed that on average 98% (range 92-100%) saturation is reached using a 100-article batch initially, with 25 articles in the subsequent batches. On average 4.7 repeating rounds (range 1-9) of 25 new articles were necessary to achieve saturation if no outcomes are first identified from a benchmark review or a data visualization. CONCLUSION: In this paper a standardized approach is proposed to identify relevant candidate outcomes for a standard outcome set. This approach creates a balance between comprehensiveness and feasibility in conducting literature reviews for the identification of candidate outcomes.

European Society of Cardiology quality indicators for the prevention and management of cancer therapy-related cardiovascular toxicity in cancer treatment.

AIMS: To develop quality indicators (QIs) for the evaluation of the prevention and management of cancer therapy-related cardiovascular toxicity. METHODS AND RESULTS: We followed the European Society of Cardiology (ESC) methodology for QI development which comprises (i) identifying the key domains of care for the prevention and management of cancer therapy-related cardiovascular toxicity in patients on cancer treatment, (ii) performing a systematic review of the literature to develop candidate QIs, and (iii) selecting of the final set of QIs using a modified Delphi process. Work was undertaken in parallel with the writing of the 2022 ESC Guidelines on Cardio-Oncology and in collaboration with the European Haematology Association, the European Society for Therapeutic Radiology and Oncology and the International Cardio-Oncology Society. In total, 5 main and 9 secondary QIs were selected across five domains of care: (i) Structural framework, (ii) Baseline cardiovascular risk assessment, (iii) Cancer therapy related cardiovascular toxicity, (iv) Predictors of outcomes, and (v) Monitoring of cardiovascular complications during cancer therapy. CONCLUSION: We present the ESC Cardio-Oncology QIs with their development process and provide an overview of the scientific rationale for their selection. These indicators are aimed at quantifying and improving the adherence to guideline-recommended clinical practice and improving patient outcomes.

Association of multimorbidity and changes in health-related quality of life following myocardial infarction: a UK multicentre longitudinal patient-reported outcomes study.

BACKGROUND: Multimorbidity is prevalent for people with myocardial infarction (MI), yet previous studies investigated single-health conditions in isolation. We identified patterns of multimorbidity in MI survivors and their associations with changes in HRQoL. METHODS: In this national longitudinal cohort study, we analysed data from 9566 admissions with MI from 77 National Health Service hospitals in England between 2011 and 2015. HRQoL was measured using EuroQol 5 dimension (EQ5D) instrument and visual analogue scale (EQVAS) at hospitalisation, 6, and 12 months following MI. Latent class analysis (LCA) of pre-existing long-term health conditions at baseline was used to identify clusters of multimorbidity and associations with changes in HRQoL quantified using mixed effects regression analysis. RESULTS: Of 9566 admissions with MI (mean age of 64.1 years [SD 11.9], 7154 [75%] men), over half (5119 [53.5%] had multimorbidities. LCA identified 3 multimorbidity clusters which were severe multimorbidity (591; 6.5%) with low HRQoL at baseline (EQVAS 59.39 and EQ5D 0.62) which did not improve significantly at 6 months (EQVAS 59.92, EQ5D 0.60); moderate multimorbidity (4301; 47.6%) with medium HRQoL at baseline (EQVAS 63.08, EQ5D 0.71) and who improved at 6 months (EQVAS 71.38, EQ5D 0.76); and mild multimorbidity (4147, 45.9%) at baseline (EQVAS 64.57, EQ5D 0.75) and improved at 6 months (EQVAS 76.39, EQ5D 0.82). Patients in the severe and moderate groups were more likely to be older, women, and presented with NSTEMI. Compared with the mild group, increased multimorbidity was associated with lower EQ-VAS scores (adjusted coefficient: -5.12 [95% CI -7.04 to -3.19] and -0.98 [-1.93 to -0.04] for severe and moderate multimorbidity, respectively. The severe class was more likely than the mild class to report problems in mobility, OR 9.62 (95% confidence interval: 6.44 to 14.36), self-care 7.87 (4.78 to 12.97), activities 2.41 (1.79 to 3.26), pain 2.04 (1.50 to 2.77), and anxiety/depression 1.97 (1.42 to 2.74). CONCLUSIONS: Among MI survivors, multimorbidity clustered into three distinct patterns and was inversely associated with HRQoL. The identified multimorbidity patterns and HRQoL domains that are mostly affected may help to identify patients at risk of poor HRQoL for which clinical interventions could be beneficial to improve the HRQoL of MI survivors. TRIAL REGISTRATION: ClinicalTrials.gov NCT01808027 and NCT01819103.