OS14 - 208 The prognostic role of pre-operative complete blood count (CBC) in progression-free survival in patients with meningioma
Bibliographic record
Abstract
Factors which might influence outcome in patients with meningioma are not well-understood. Previous studies have examined associations of laboratory blood values including hemoglobin levels with patient outcomes in cancer. We hypothesized those changes in CBC before tumor resection can be used as one of the prognostic factors for tumor recurrence/progression in meningioma. To address this, we gathered the clinical and pre-operative CBC results for final analysis from 226 patients (64 males and 162 females) who underwent craniotomy for primary meningioma (grades: 157 WHO GI, 59 GII, 10 GIII) at our institution between 2001 and 2015.Individual parameters were analyzed for correlation with progression-free survival. The median recurrence free survival (RFS) was not reached and follow-up ranged 0.3-14 years. Fifty-six patients (25%) had anemia and 30% of the patients showed leukocytosis using standard cut-offs. On univariate analyses, low hemoglobin (Hb) level, as well as high leukocytes (Lkc), neutrophil (Neutro) and monocyte counts correlated with worse RFS. As expected, tumor grade was correlated with RFS. Low Hb level, high Lkc and Neutro counts were all significantly associated with RFS after adjusting for grade. Strikingly, 32% of patients with pre-operative anemia experienced a recurrence at 5 years, compared with only 11% of non-anemic patients. Conclusion: In this exploratory study, we find that pre-operative CBC data, which is readily available, may contain prognostic information relevant to subsequent risk of recurrence or progression in meningioma. While the biological mechanism for these associations is not clear, they represent hypotheses for further investigation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".