Diagnostic accuracy of the aortic dissection detection risk score alone or with D-dimer for acute aortic syndromes: Systematic review and meta-analysis.

OBJECTIVES: To evaluate the diagnostic accuracy of the aortic dissection detection risk score (ADD-RS) used alone or in combination with D-dimer for detecting acute aortic syndrome (AAS) in patients presenting with symptoms suggestive of AAS. METHODS: We searched MEDLINE, EMBASE, and the Cochrane Library from inception to February 2024. Additionally, the reference lists of included studies and other systematic reviews were thoroughly searched. All diagnostic accuracy studies that assessed the use of ADD-RS alone or with D-Dimer for diagnosing AAS compared with a reference standard test (e.g. computer tomographic angiography (CTA), ECG-gated CTA, echocardiography, magnetic resonance angiography, operation, or autopsy) were included. Two reviewers independently selected and extracted data. Risk of bias was appraised using QUADAS-2 tool. Data were synthesised using hierarchical meta-analysis models. RESULTS: We selected 13 studies from the 2017 citations identified, including six studies evaluating combinations of ADD-RS alongside D-dimer>500ng/L. Summary sensitivities and specificities (95% credible interval) were: ADD-RS>0 94.6% (90%, 97.5%) and 34.7% (20.7%, 51.2%), ADD-RS>1 43.4% (31.2%, 57.1%) and 89.3% (80.4%, 94.8%); ADD RS>0 or D-Dimer>500ng/L 99.8% (98.7%, 100%) and 21.8% (12.1%, 32.6%); ADD RS>1 or D-Dimer>500ng/L 98.3% (94.9%, 99.5%) and 51.4% (38.7%, 64.1%); ADD RS>1 or ADD RS = 1 with D-dimer>500ng/L 93.1% (87.1%, 96.3%) and 67.1% (54.4%, 77.7%). CONCLUSIONS: Combinations of ADD-RS and D-dimer can be used to select patients with suspected AAS for imaging with a range of trade-offs between sensitivity (93.1% to 99.8%) and specificity (21.8% to 67.1%).

Diagnostic Accuracy of D-Dimer for Acute Aortic Syndromes: Systematic Review and Meta-Analysis.

STUDY OBJECTIVE: Acute aortic syndrome is a life-threatening emergency condition. Previous systematic reviews of D-dimer diagnostic accuracy for acute aortic syndrome have been contradictory and based on limited data, but recently published studies offer potential for a more definitive overview. We aimed to perform a systematic review and meta-analysis to determine the diagnostic accuracy of D-dimer for diagnosing acute aortic syndrome. METHODS: We searched MEDLINE, EMBASE, and the Cochrane Library from inception to February 2024. Additionally, the reference lists of included studies and other systematic reviews were thoroughly searched. All diagnostic cohort studies (prospective or retrospective) that assessed the use of D-dimer for diagnosing acute aortic syndrome compared with a reference standard test (eg, computed tomographic angiography (CTA), ECG-gated CTA, echocardiography, magnetic resonance angiography, operation, or autopsy) were included. Two independent reviewers completed study selection, data extractions and quality assessment using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Data were synthesized using a bivariate meta-analysis model. RESULTS: Of 2017 potentially relevant citations, 25 cohort studies met the inclusion criteria, and 18 reporting the 500 ng/mL threshold were included in the primary meta-analysis. Risk of bias domains were mostly unclear due to limited study reporting. The summary sensitivity was 96.5% (95% credible interval [CrI] 94.8% to 98%) and summary specificity was 56.2% (95% CrI, 48.3% to 63.9%). Study specificity varied markedly from 33% to 86%, indicating substantial heterogeneity. Sensitivity analysis including the 7 studies reporting other thresholds showed summary sensitivity of 95.7% (95% CrI, 93.2% to 97.5%) and summary specificity of 57.5% (95% CrI, 50.1% to 64.6%). CONCLUSION: D-dimer concentration has high sensitivity (96.5%) and moderate specificity (56.2%) for acute aortic syndrome, with some uncertainty around estimates due to risk of bias and heterogeneity. Previous meta-analysis reporting higher specificity may be explained by inclusion of case-control studies that may overestimate accuracy.

Advancing unanchored simulated treatment comparisons: A novel implementation and simulation study.

Population-adjusted indirect comparisons, developed in the 2010s, enable comparisons between two treatments in different studies by balancing patient characteristics in the case where individual patient-level data (IPD) are available for only one study. Health technology assessment (HTA) bodies increasingly rely on these methods to inform funding decisions, typically using unanchored indirect comparisons (i.e., without a common comparator), due to the need to evaluate comparative efficacy and safety for single-arm trials. Unanchored matching-adjusted indirect comparison (MAIC) and unanchored simulated treatment comparison (STC) are currently the only two approaches available for population-adjusted indirect comparisons based on single-arm trials. However, there is a notable underutilisation of unanchored STC in HTA, largely due to a lack of understanding of its implementation. We therefore develop a novel way to implement unanchored STC by incorporating standardisation/marginalisation and the NORmal To Anything (NORTA) algorithm for sampling covariates. This methodology aims to derive a suitable marginal treatment effect without aggregation bias for HTA evaluations. We use a non-parametric bootstrap and propose separately calculating the standard error for the IPD study and the comparator study to ensure the appropriate quantification of the uncertainty associated with the estimated treatment effect. The performance of our proposed unanchored STC approach is evaluated through a comprehensive simulation study focused on binary outcomes. Our findings demonstrate that the proposed approach is asymptotically unbiased. We argue that unanchored STC should be considered when conducting unanchored indirect comparisons with single-arm studies, presenting a robust approach for HTA decision-making.