P.082 Preoperative corticosteroids reduce diagnostic accuracy for primary central nervous system lymphoma biopsies: a meta-analysis
Bibliographic record
Abstract
Background: Primary central nervous system lymphoma (PCNSL) is highly sensitive to corticosteroid induced cell arrest, apoptosis and shrinkage. However, the precise impact of preoperative corticosteroid on accuracy of PCNSL diagnosis using tissue obtained from open or stereotactic biopsies remains debated. Methods: We conducted a systematic review and meta-analysis to determine the effect of preoperative corticosteroids on non-diagnostic biopsy rates for PCNSL in immunocompetent adults. Subgroup analyses explored whether non-diagnostic rates varied based on biopsy type. Results: Nineteen studies, comprising 1226 patients (55% male; mean age: 60.3 years), of which 679 (55.4%) received corticosteroids prior to biopsy were included. Overall, patients pretreated with corticosteroids were two times more likely to have a non-diagnostic biopsy compared to patients that were corticosteroid-naïve prior to biopsy (RR = 2.1 [95% CI: 1.1-4.1]). In the subgroup analysis limited to stereotactic biopsies, patient pretreated with corticosteroids were three times more likely to have a non-diagnostic biopsy (RR = 3.0 [95% CI: 1.2-7.5]). Whereas, in the open biopsy subgroup, there was no significant difference in non-diagnostic rates. Conclusions: Corticosteroids should be withheld, if clinically safe, prior to stereotactic biopsies in cases of suspected PCNSL. If corticosteroids are administered preoperatively, an open biopsy should be considered instead of stereotactic biopsy.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.042 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".