Multi-modality Therapy Leads to Longer Survival in Primary Central Nervous System Lymphoma Patients
Bibliographic record
Abstract
BACKGROUND: Primary central nervous system lymphoma (PCL) is more frequently encountered by neurosurgeons given the increasing incidence among both nonimmunocompromised and immunocompromised patients. The most frequent surgery is stereotactic biopsy. Historically, radiation therapy has been the standard treatment modality for this disease and median survival was in the 15-month range. More recently, multi-modality therapy combining radiation therapy with chemotherapy (systemic, intrathecal, and/or intra-arterial) have resulted in longer survivals. We reviewed survival data for our series of patients treated for PCL over the last decade. METHODS: Thirty-four patients with histologically confirmed PCL were treated at our center. Multivariate Cox regression analysis was performed to determine which factor(s) (age, gender, HIV status, Karnofsky Performance Scale, chemotherapy, single modality therapy, histology, location, number of lesions, surgical resection) had a significant impact on survival. RESULTS: The overall median survival was 19 months. Patients receiving multi-modality therapy (n=17) (chemotherapy and radiation) had a median survival of 34 months compared to four months for patients receiving single modality therapy (n=17 including seven HIV positive patients). Multi-modality therapy was the only significant factor affecting survival in this multivariate analysis (p<0.0001). CONCLUSIONS: Chemotherapy plus radiotherapy significantly enhances survival over patients treated with single modality therapy alone. Quality of life issues should be addressed on a case by case basis as additional treatment modalities are initiated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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".