In Reply: Radiosurgery With Prior Embolization Versus Radiosurgery Alone for Intracranial Arteriovenous Malformations: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
To the Editor: We appreciate Dr Chen’s insightful comments on our article,1 “Radiosurgery with Prior Embolization Versus Radiosurgery Alone for Intracranial Arteriovenous Malformations: A Systematic Review and Meta-Analysis.”2 We agree with the author regarding the limitations of the Newcastle-Ottawa Scale (NOS) for quality assessment. However, studies comparing NOS with other tools demonstrate its comparative validity. For example, one study found high interrater agreement for both NOS and Risk Of Bias In Non-randomised Studies–of Interventions (ROBINS-I), with mean kappa statistics of 0.67 (95% CI: 0.50-0.83) and 0.73 (95% CI: 0.65-0.81), respectively. Importantly, NOS was significantly less time-consuming (30 minutes per study) compared with ROBINS-I (3-7 hours per study).3 Similarly, NOS showed strong agreement with the Downs and Black tool in criterion validity, while requiring less effort from evaluators.4 Consequently, the Cochrane Collaboration recommends NOS for assessing nonrandomized studies.5 On the other hand, the Methodological Index for Non-Randomized Studies emphasizes prospective data collection and sample size calculation, and because most studies are retrospective, this can lead to biased lower scores with Methodological Index for Non-Randomized Studies.6 Considering these points, we opted for the NOS scale for quality assessment in our study. To address the potential influence of studies with small sample sizes, we used 2 strategies. First, we conducted a leave-one-out analysis, which assesses the impact of each individual study on the overall results. Second, we performed subgroup analyses on studies with similar characteristics to identify potential variations in the effect. Our search strategy ensured comprehensive coverage of the relevant literature. We searched the following 3 established databases: PubMed (MEDLINE), Embase, and Cochrane. These databases have been shown to outperform Google Scholar in both coverage (Embase and MEDLINE: 97.5% vs Google Scholar: 97.2%) and recall (ability to identify relevant studies).7 In addition, these databases have rigorous quality control measures, ensuring the inclusion of reliable publications. For further comprehensiveness, we also conducted manual reference checking of the included articles. A limitation of our study, as previously mentioned, is the heterogeneity in outcome measures, particularly the grading scales used. There are several arteriovenous malformation (AVM) grading scales, categorized as integer-based (eg, Spetzler-Martin, Heidelberg score, and Virginia Radiosurgery AVM Scale) and continuous scores (eg, radiosurgery-based AVM score and proton radiosurgery AVM scale).8,9 Owing to these variations in assessed parameters and potential subjectivity in scoring some factors (such as AVM morphology and eloquence), pooling the data from these different scales was not feasible. Future well-designed randomized controlled trials and longitudinal registry studies can address some of the limitations. Such studies would provide stronger evidence to guide clinical decision-making for the treatment of patients with AVM.
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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 | 0.023 | 0.164 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".