Diagnostic Test Accuracy of Cardiac Biomarkers for Light Chain Amyloidosis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: In patients with systemic light-chain amyloidosis, cardiac involvement is common. Cardiac involvement (presence and severity) is the most important predictor of mortality in patients with AL amyloidosis. Endomyocardial biopsy remains the gold standard, but it is a costly and invasive test. Consequently, cardiac biomarkers are used for screening for cardiac involvement and have significant prognostic value.In this systematic review, we aim to estimate the diagnostic test accuracy (DTA) of Nt-proBNP, BNP, and high sensitivity troponin for cardiac amyloidosis. Methods: As part of the American Society of Hematology guidelines on the diagnosis of Amyloidosis, we searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials from inception till January 2024 for relevant studies. Two reviewers independently performed title and abstract screening and full-text article screening on LASER Al and extracted relevant data using piloted Excel sheets. The panel judged whether the reference test is acceptable or not. Acceptable reference test is EMB alone or a combination of extracardiac biopsy plus cardiac imaging (CMR or echocardiography) with or without positive cardiac biomarkers (troponin or BNP or NT-proBNP). For statistical analysis, we only included studies reporting on both the sensitivity and specificity of the cardiac biomarker. We used Stata 18.0 software for meta-analysis. We evaluated risk of bias using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of the evidence. We report diagnostic test accuracy as sensitivity (95% confidence interval) and specificity (95% confidence interval). Results: After screening 29,237 studies, a total of 10 studies addressed DTA of Nt-proBNP for cardiac amyloidosis. These studies used a wide variety of cutoffs for diagnosis of cardiac involvement, ranging from 150 to 5000 ng/L and a cutoff of 332 ng/L was the most studied and reported. The pooled estimates for sensitivity and specificity of Nt-proBNP using 332 as cutoffs are 0.99 ( 0.97, 1) and 0.53 (0.3, 0.75), respectively. The pooled estimates were based on 4 studies (n=645) with moderate certainty in the evidence. For BNP, DTA was assessed in 3 studies (n= 257). Each study used a different cutoff for BNP (73, 100, and 412 ng/L). The sensitivity and specificity of BNP in each study were comparable and not significantly affected by the cutoff variation. Pooled sensitivity and specificity across studies, were 0.87 (0.80, 0.92), and 0.79 (0.71, 0.85), respectively. The certainty in evidence for the DTA of BNP was low. Eight studies reported on DTA of high sensitivity troponin, with cutoffs ranging from 14 to 86 ng/L. Meta-analysis of studies reporting on cutoff 14 ng/L yielded sensitivity of 0.94 (0.87, 0.97) and specificity of 0.11 (0.08, 0.16) with moderate certainty evidence. Increasing the cutoff to 35 ng/l led to a decrease in sensitivity to 0.82 (0.66, 0.92) and an increase in specificity to 0.86 (0.74, 0.93) with low certainty evidence. Conclusion: Cardiac biomarkers are highly sensitive, valuable initial tests for increasing suspicion of cardiac involvement in patients with AL amyloidosis. However, they lack specificity and, on their own, are insufficient for a definitive diagnosis of cardiac involvement. These biomarkers may be used in conjunction with other diagnostic tests to accurately identify and assess the extent of cardiac involvement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.075 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.038 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".