Use of relative survival to evaluate non-ST-elevation myocardial infarction quality of care and clinical outcomes

European Heart Journal. Quality of Care & Clinical Outcomes, Jan 1753

Survival after non-ST-elevation myocardial infarction (NSTEMI) is high and non-cardiovascular death has become more frequent. Observational studies typically quantify quality of care and clinical outcomes using all-cause mortality, which nowadays may not reflect the impact of index NSTEMI. We review and investigate relative survival for quantifying longer term outcomes after NSTEMI. National cohort study of hospitalized NSTEMI (Myocardial Ischaemia National Audit Project; patients: n = 346 546, hospitals: n = 243, countries: England and Wales). Mortality rates derived from two relative survival techniques were compared with all-cause mortality, and the impact of relative survival adjusted patient characteristics compared with those from Cox proportional estimates. Cox proportional hazards models provide lower survival estimates because they include deaths from all causes, overestimate the impact of increasing age on survival, and underestimate temporal improvements in care. The Royston–Parmar model allows more accurate estimation of relative survival because it is flexible to the high early hazard of death after hospitalized NSTEMI. All-cause mortality gives an overall assessment of survival for a cohort of patients. Relative survival provides a more accurate and informed estimation of the impact of an index cardiovascular event and, if necessary, patient characteristics on survival.

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Use of relative survival to evaluate non-ST-elevation myocardial infarction quality of care and clinical outcomes

European Heart Journal - Quality of Care and Clinical Outcomes Use of relative survival to evaluate non-ST-elevation myocardial infarction quality of care and clinical outcomes Marlous Hall 2 Oras A. Alabas 2 Tatendashe B. Dondo 2 Tomas Jernberg 0 1 Chris P. Gale 0 2 0 York Teaching Hospital NHS Foundation Trust , York , UK 1 Department of Medicine, Section of Cardiology, Huddinge, Karolinska Institutet, Karolinska University Hospital , Stockholm , Sweden 2 Division of Epidemiology and Biostatistics, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds , Leeds , UK Survival after non-ST-elevation myocardial infarction (NSTEMI) is high and non-cardiovascular death has become more frequent. Observational studies typically quantify quality of care and clinical outcomes using all-cause mortality, which nowadays may not reflect the impact of index NSTEMI. We review and investigate relative survival for quantifying longer term outcomes after NSTEMI. National cohort study of hospitalized NSTEMI (Myocardial Ischaemia National Audit Project; patients: n ¼ 346 546, hospitals: n ¼ 243, countries: England and Wales). Mortality rates derived from two relative survival techniques were compared with all-cause mortality, and the impact of relative survival adjusted patient characteristics compared with those from Cox proportional estimates. Cox proportional hazards models provide lower survival estimates because they include deaths from all causes, overestimate the impact of increasing age on survival, and underestimate temporal improvements in care. The Royston - Parmar model allows more accurate estimation of relative survival because it is flexible to the high early hazard of death after hospitalized NSTEMI. All-cause mortality gives an overall assessment of survival for a cohort of patients. Relative survival provides a more accurate and informed estimation of the impact of an index cardiovascular event and, if necessary, patient characteristics on survival. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Introduction The increasing global burden of cardiovascular survivorship, as a consequence of an aging, and more intensively treated population,1 – 4 has resulted in a need to prioritise survival studies as a means of evaluating quality of care and clinical outcomes.5,6 Over the last 30 years, there has been a shift from predominantly cardiovascular to non-cardiovascular deaths after percutaneous coronary intervention.7 To date, however, estimates of survival after a cardiovascular event are typically reported using all-cause mortality. Such data also include the risk of death from causes other than cardiovascular disease, and cause-specific risks of death cannot be determined explicitly from these analyses.8,9 Specifically, studies that use all-cause mortality to investigate the effect of age on survival may overestimate the effects of increasing mortality rates with age regardless of whether the patient has cardiovascular disease or not. Similarly, a study describing temporal improvements in all-cause survival may not be able to accurately determine whether this was associated with clinical factors (such as improvements in the application of evidence based treatments) or was a reflection of decreasing mortality rates over time in the general population. Moreover, all-cause survival rates limit international comparisons of care—due to potential differences in the underlying mortality rates between populations with different health profiles and provision. One solution is the use of cause-specific mortality data, which is the proportion of patients who died from the disease being studied; arguably more useful to patients, clinicians, and service providers than all-cause mortality rates.10 However, cause-specific mortality data are often unavailable and where it is available, it has been shown to be unreliable for cancer11 – 14 and cardiovascular-related15 – 17 causes of death. Inherent problems with cause-specific death data arise due to disagreements between clinicians or recording of mechanisms of death rather than underlying causes.15,17 In particular, there is evidence to show that death from coronary heart disease tends to be over-represented within death certificate data.16 In contrast, relative survival techniques provide an estimate of the likelihood that a patient will not die from causes associated with the disease under study, without the need for cause-specific death data provided the assumption that factors affecting disease-specific and other cause survival are controlled for by comparing with the mortality in the background population.18 Such methods are well established and are the gold standard in cancer survival (...truncated)


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Hall, Marlous, Alabas, Oras A., Dondo, Tatendashe B., Jernberg, Tomas, Gale, Chris P.. Use of relative survival to evaluate non-ST-elevation myocardial infarction quality of care and clinical outcomes, European Heart Journal. Quality of Care & Clinical Outcomes, 1753, pp. 85-91, Volume 1, Issue 2, DOI: 10.1093/ehjqcco/qcv011