Population-based retrospective analysis of response assessment criteria in patients with glioblastoma.
Bibliographic record
Abstract
2041 Background: Patients with glioblastoma are often treated with radiation and chemotherapy following surgery. Disease recurrence often occurs early in the disease course and during initial therapy, yet assessment of treatment response with MRI is highly variable in some situations. We sought to describe the clinical and imaging assessment and outcomes of an unselected cohort of patients with glioblastoma following the publication of the Response Assessment in Neuro-Oncology criteria. Methods: Patients diagnosed with glioblastoma in Manitoba, Canada, from 2012-2018 were identified from the Manitoba Cancer Registry. Chart review was performed to identify treatments given and decisions made by the treating team, and imaging analysis was performed to assess based on RANO and mRANO criteria. Determination of progression versus pseudoprogression according to these criteria was performed using clinical decision-making and review of follow-up imaging for confirmation. At time of the response assessment visit, patients were assessed by a primary oncologist (Radiation or Medical) and were also discussed at multidisciplinary Case Conference (comprised of Medical and Radiation Oncology, Neurosurgery, Neuropathology, and Neuroradiology). Treatment decisions were made with patient and primary oncologist, guided by input from the Case Conference. Tumour measurements were performed both in 2D using Product of Perpendicular Diameter analysis (PPD) and 3D volumetric measurements with/without necrotic region. Overall Survival (OS) and Progression Free Survival (PFS) were estimated to evaluate the effectiveness of response assessments and Kaplan-Meier method was used to compare the time to progression resulted from RANO, mRANO, and clinical impression. Results: A total of 285 patients were identified with a pathological diagnosis of glioblastoma. Of those, 199 (35% male, 65% female) were treated with concurrent temozolomide and radiation (75% 60Gy and 25% < 60Gy), and more than 90% went on to receive adjuvant temozolomide. Median Overall Survival of the 199 was 13.2 months. Of those treated with concurrent therapy, 122 (61%) had MRI studies with equivocal results within the first 6 months, with confirmatory MRI showing true progression in 73 (59.8%), pseudoprogression in 45 (36.9%), and 4 patients with undetermined outcome. Formal RANO and mRANO comparison is ongoing. Conclusions: Response assessment for patients with glioblastoma remains a frequent challenge despite the use of MRI and established response criteria, with more than half of patients having equivocal imaging changes and a high frequency of pseudoprogression.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".