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Selecting the right cardiac implantable electrical device for the right patient at the right time remains a critical public health problem. Consensus guidelines generally conform to the inclusion criteria for the pivotal clinical studies, but several important considerations remain distressingly murky for patients considering implantable cardioverter defibrillator (ICD) or cardiac resynchronisation therapy (CRT) with defibrillator (CRT-D) or pacemaker (CRT-P) function.1 How effective are these therapies in subgroups that are relatively uncommon in clinical studies, but common in practice, particularly older patients and those with substantial comorbidities?2 How effective are these therapies compared with one another in patients eligible for either based on current criteria? Can subgroups be identified that clearly do not benefit from or may even be harmed by these therapies? What are the best estimates of individual outcomes with or without therapy that might improve informed consent and shared decision-making?3
Into this fray step Woods and colleagues, whose network meta-analysis of nearly 13 000 patients with heart failure and reduced EF is published in Heart.4 Assembling data from 13 separate randomised trials, representing 95% of all such randomised patients, Woods et al compared the survival advantage of CRT-D, CRT-P and ICD versus medical therapy alone and each other with the goal of providing tailored survival benefits according to key covariate combinations such as age and sex. The network meta-analytical approach uses direct treatment comparisons (such as studies examining CRT vs medical therapy) to learn about comparative effectiveness and also indirect treatment comparisons (eg, CRT vs medical therapy in one study, ICD vs medical therapy in another) to supplement or even replace direct evidence. All three devices achieved substantial relative risk reductions for mortality compared …
Contributors All authors approve the final manuscript, and contributed meaningfully to conception, design, writing of the first draft and critical revisions thereof.
Funding National Institutes of Health (grants no. K23AG045963); US Food and Drug Administration (U01FD004493).
Competing interests DBK reports research funding from the NIH. LAH and S-LTN's efforts were supported by grant U01FD004493 from the US Food and Drug Administration.
Provenance and peer review Not commissioned; internally peer reviewed.
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