Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials

Siontis, George C.M.; Mavridis, Dimitris; Greenwood, John P; Coles, Bernadette; Nikolakopoulou, Adriani; Jüni, Peter; Salanti, Georgia; Windecker, Stephan

doi:10.1136/bmj.k504

Cited by 95 publications

(82 citation statements)

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“…Siontis et al performed a network meta-analysis to of randomized trials to evaluate the 554 differences between the non-invasive diagnostic modalities used to detect coronary artery 555 disease in patients presenting with symptoms suggestive of acute coronary syndrome (11). 556…”

Section: Diagnostic Strategies For Patients With Low Risk Of Acute Comentioning

confidence: 99%

Assessing Confidence in the Results of Network Meta-Analysis (Cinema)

Nikolakopoulou

Higgins

Papakonstantinou

et al. 2019

Preprint

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Most network meta-analyses include only randomized controlled trials (RCTs), so we 62 will focus on this study design, and on relative treatment effects. A network meta-analysis 63 involves the integration of direct and indirect evidence in a network of relevant trials. We 64 assume that evaluation of the credibility of results takes place once all primary analyses and 65 sensitivity analyses have been undertaken. We assume that reviewers have implemented 66 their pre-specified study inclusion criteria, which may include risk of bias considerations, 67 and have obtained the best possible estimates of relative treatment effects using 68 appropriate statistical methods (e.g. those described in (7-10)). The question is then how to 69 make judgements about the credibility of relative treatment effects, given that trials with 70 variable risk of bias, precision, relevance and heterogeneity contribute information to the 71 estimate. 72This paper addresses how judgements should be formed about the six CINeMA 73 domains. We illustrate the methods using three examples: a network of trials that compare 74 outcomes of various diagnostic strategies in patients with suspected acute coronary 75 syndrome (11), a network of trials comparing the effectiveness of 18 antidepressants for 76 major depression (12), and a network comparing adverse events of statins (13). The three 77 examples are introduced in Error! Reference source not found.. All analyses were done in R 78 software using the netmeta package and the CINeMA web application (Box 2) (6,14). 79 WITHIN-STUDY BIAS 80 BACKGROUND AND DEFINITIONS 81Within-study bias refers to shortcomings in the design or conduct of a study that can 82 lead to an estimated relative treatment effect that systematically differs from the truth. In 83 5 our framework we assume that studies have been assessed for risk of bias. The majority of 84 published systematic reviews of RCTs currently use a tool developed by Cochrane to 85 evaluate risk of bias (15). This tool classifies studies as having low, unclear or high risk of 86 bias for various bias components (such as allocation concealment, attrition, blinding etc.), 87 and these judgements are then summarized across domains. A revision of the tool takes a 88 similar approach but labels the levels as low risk of bias, some concerns and high risk of bias 89 (16). 90 THE CINEMA APPROACH 91While it is straightforward to gauge the impact of within-study biases on the summary 92 relative treatment effect in a pairwise meta-analysis (17), in network meta-analysis studies 93 contribute data to the estimation of each summary effect in a complex manner. In the first 94 example discussed below we show the complexity underpinning the flow of information in 95 the network of diagnostic modalities used to detect coronary artery disease. A treatment 96 comparison directly evaluated in studies with low risk of bias might also be estimated 97 indirectly (via a common comparator) using studies at high risk of bias, and vice versa. While 98 studies at low risk of ...

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Section: Diagnostic Strategies For Patients With Low Risk Of Acute Comentioning

confidence: 99%

Assessing Confidence in the Results of Network Meta-Analysis (Cinema)

Nikolakopoulou

Higgins

Papakonstantinou

et al. 2019

Preprint

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“…Healthcare utilization is another aspect of great importance, especially for a cohort of patients with a generally low risk of adverse cardiovascular events . Many tests ordered in these patients have low diagnostic yield and contribute to the growing overall healthcare costs . Therefore, identification of patients at a higher risk of subsequent cardiac testing after an index negative test (exercise echocardiogram) becomes important.…”

Section: Discussionmentioning

confidence: 99%

Unsupervised clustering for phenotypic stratification of clinical, demographic, and stress attributes of cardiac risk in patients with nonischemic exercise stress echocardiography

et al. 2020

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Introduction and aim:Patients undergoing exercise echocardiography with no evidence of myocardial ischemia are considered a low-risk group; however, this group is likely heterogeneous in terms of short-term adverse events and subsequent cardiac testing. We hypothesized that unsupervised cluster modeling using clinical and stress characteristics can detect heterogeneity in cardiovascular risk and need for subsequent cardiac testing among these patients. Methods:We retrospectively studied 445 patients who had exercise echocardiography results negative for myocardial ischemia. All patients were followed for adverse cardiovascular events, subsequent cardiac testing, and nonacute coronary syndrome (ACS) revascularization. The heterogeneity of the study subjects was tested using computational clustering, an exploratory statistical method designed to uncover invisible natural groups within data. Clinical and stress predictors of adverse events were extracted and used to construct 3 unsupervised cluster models: clinical, stress, and combined. The study population was split into training (357 patients) and testing sets (88 patients). Results:In the training set, the clinical, stress, and combined cluster models yielded 5, 4, and 3 clusters, respectively. Each model had 1 high-risk and 1 low-risk cluster while other clusters were intermediate. The combined model showed a better predictive ability compared to the clinical or stress models alone. The need for future testing mirrored the pattern of adverse cardiovascular events. A risk score derived from the combined cluster model predicted end points with acceptable accuracy. The patterns of risk and the calculated risk scores were preserved in the testing set. Conclusions:Patients with no evidence of ischemia on exercise stress echocardiography represent a heterogeneous group. Cluster-based modeling using combined clinical and stress characteristics can expose this heterogeneity. The findings can help better risk-stratify this group of patients and aid cost-effective healthcare utilization toward better diagnostics and therapeutics.

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“…A Bayesian approach adopting probability values summarized as SUCRA was the most effective method . Another example of an NMA studied the outcomes of noninvasive diagnostic modalities for the detection of coronary artery disease . In that study, again, the authors performed a traditional pairwise meta‐analysis of studies that compared the different diagnostic modalities with associated network plots …”

Section: Discussionmentioning

confidence: 99%

“…48 Another example of an NMA studied the outcomes of noninvasive diagnostic modalities for the detection of coronary artery disease. 49 In that study, again, the authors performed a traditional pairwise meta-analysis of studies that compared the different diagnostic modalities with associated network plots. 49 Individual Patient/Participant Data (IPD) Meta-Analysis Meta-analyses of IPD have been performed for therapeutic studies, often using data from randomized controlled trials (RCTs).…”

Section: Discussionmentioning

confidence: 99%

“…49 In that study, again, the authors performed a traditional pairwise meta-analysis of studies that compared the different diagnostic modalities with associated network plots. 49 Individual Patient/Participant Data (IPD) Meta-Analysis Meta-analyses of IPD have been performed for therapeutic studies, often using data from randomized controlled trials (RCTs). It has been shown that some of these IPD metaanalyses have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials.…”

Section: Discussionmentioning

confidence: 99%

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