Trigeminal Neuralgia Recurrence Prediction Models from a Systematic Review

A 2026 systematic review and meta-analysis by Xinxin Tian, aggregating findings from 20 studies involving 4,291 patients. The document analyzes prediction models for postoperative recurrence of trigeminal neuralgia, reporting a pooled area under the curve of 0.86 for training sets and 0.83 for validation sets.

Use Cases

• Benchmarking new prediction models against the reported pooled AUC of 0.86 based on the meta-analysis results.
• Identifying key predictors like age over 65 or disease duration over 5 years for feature selection in clinical models.
• Assessing risk of bias and reporting quality in existing trigeminal neuralgia recurrence studies based on the review's methodology.

Strengths

• Includes data from 20 studies and 4,291 patients, providing a substantial evidence base.
• Follows structured methodology using the CHARMS checklist and Prediction Model Risk of Bias Assessment Tool.
• Reports specific performance metrics, including a pooled AUC of 0.86 for training sets.

Limitations

• The dataset is a 50.4 KB DOC file containing review text, not structured data; column-level documentation is absent.
• The review notes potential risks of bias, publication bias, and heterogeneity, suggesting the pooled AUC may be overestimated.
• Row count is unknown, which may limit suitability assessment for direct data analysis.

Provenance

Source

figshare

Collection Method

Systematic review and meta-analysis of eight databases up to September 23, 2025.

Time Range

Studies reviewed up to September 2025.

Freshness

Last updated 2026-05-07 04:45:14