Evaluating hematologic parameters in newly diagnosed and recurrent glioblastoma: Prognostic utility and clinical trial implications of myelosuppression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Glioblastoma (GBM) patients are treated with radiation therapy, chemotherapy, and corticosteroids, which can cause myelosuppression. To understand the relative prognostic utility of blood-based biomarkers in GBM and its implications for clinical trial design, we examined the incidence, predictors, and prognostic value of lymphopenia, neutrophil-to-lymphocyte ratio (NLR), and platelet count during chemoradiation (CRT) and recurrence. Methods: This cohort study included 764 newly diagnosed glioblastoma patients treated from 2005 to 2019 with blood counts prior to surgery, within 6 weeks of CRT, and at first recurrence available for automatic extraction from the medical record. Logistic regression was used to evaluate exposures and Kaplan-Meier was used to evaluate outcomes. Results: Among the cohort, median age was 60.3 years; 87% had Karnofsky performance status ≥ 70, 37.5% had gross total resection, and 90% received temozolomide (TMZ). During CRT, 37.8% (248/656) of patients developed grade 3 or higher lymphopenia. On multivariable analysis (MVA), high NLR during CRT remained an independent predictor for inferior survival (Adjusted Hazard Ratio [AHR] = 1.57, 95% CI = 1.14-2.15) and shorter progression-free survival (AHR = 1.42, 95% CI = 1.05-1.90). Steroid use was associated with lymphopenia (OR = 2.66,1.20-6.00) and high NLR (OR = 3.54,2.08-6.11). Female sex was associated with lymphopenia (OR = 2.33,1.03-5.33). At first recurrence, 28% of patients exhibited grade 3 or higher lymphopenia. High NLR at recurrence was associated with worse subsequent survival on MVA (AHR = 1.69, 95% CI = 1.25-2.27). Conclusions: High NLR is associated with worse outcomes in newly diagnosed and recurrent glioblastoma. Appropriate eligibility criteria and accounting and reporting of blood-based biomarkers are important in the design and interpretation of newly diagnosed and recurrent glioblastoma trials.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it