Outcomes of presumed malignant glioma treated without pathological confirmation: a retrospective, single-center analysis
Bibliographic record
Abstract
Abstract Background Tissue diagnosis is essential in the usual management of high-grade glioma. In rare circumstances, due to patient preference, performance status, comorbidities, or tumor location, biopsy is not feasible. Sometimes a biopsy is nondiagnostic. Many neuro-oncology clinics have patients like this, but these patients’ outcomes and responses to treatment are not known. Methods We retrospectively reviewed records from adult patients diagnosed with presumed high-grade glioma of the brain without definitive pathology, diagnosed between 2004 and 2016. We recorded several clinical variables including date of first diagnostic imaging and date of death. Results We identified 61 patients and subclassified them to brainstem glioma (n = 32), supratentorial presumed glioblastoma (n = 24), presumed thalamic diffuse midline glioma (n = 2), gliomatosis cerebri (n = 2), and cerebellar glioma (n = 1). Most brainstem glioma patients had no biopsy because of tumor location. Supratentorial presumed glioblastoma patients had no biopsy predominantly because of comorbidities. Median survival, from first diagnostic imaging, was 3.2 months (95% CI: 2.9 to 6.3 months) in the supratentorial glioblastoma group and 18.5 months (95% CI: 13.0 to 44.1 months) in the brainstem group. Treatment with radiation or chemotherapy did not alter the median survival of the supratentorial glioblastoma group (hazard ratio 1.41, uncorrected P = .5). Conclusions Patients with imaging diagnoses of high-grade glioma have similar, if not worse, survival than those with pathological confirmation. Based on these uncontrolled data, it is unclear how effective radiation or chemotherapy is in this population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".