The role of 5‐aminolevulinic acid in enhancing surgery for high‐grade glioma, its current boundaries, and future perspectives: A systematic review
Bibliographic record
Abstract
5-Aminolevulinic acid (5-ALA) has been approved as an intraoperative adjunct in glioma surgery in Europe, but not North America. A systematic review was conducted to assess the evidence regarding 5-ALA as a surgical adjunct. The MEDLINE, EMBASE, and CENTRAL databases were searched, using terms relevant to "5-ALA" and "high-grade gliomas." Included studies were based on adults aged ≥18 years who underwent surgical resection/biopsy. No language or date limitations were used. Forty-three studies (1830 patients) were identified. Thirty-six were coordinated by European countries, 2 were in the United States, and none were in Canada. One was randomized, 28 were prospective, and 14 were retrospective. Twenty-six studies assessed the utility of 5-ALA as a diagnostic tool, 24 assessed its influence on the extent of resection (EOR), 9 assessed survival, and 22 reported adverse events. 5-ALA had high sensitivity and positive predictive value, whereas its specificity increased with additional adjuncts. The EOR increased with 5-ALA, but only progression-free survival was significantly influenced. Reporting of adverse events was not systematic. The use of 5-ALA improved tumor visualization and thus enabled a greater EOR and perhaps increased survival. However, additional adjuncts may be necessary for maximizing the specificity of resection and patient safety. Additional parameters, such as patient quality of life and health economic analyses, would be informative. Thus, additional systematic collection of prospective evidence may be necessary for the global incorporation of this potentially valuable surgical adjunct into routine practice. Cancer 2016;122:2469-78. © 2016 American Cancer Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".