A Contemporary Report of Clinical Outcomes in Patients with Melanoma Brain Metastases
Bibliographic record
Abstract
Background: Brain metastases are observed in more than 40% of all patients with stage 4 melanoma. In recent years, more extensive use of stereotactic radiation (STRT) and the advent of immune checkpoint inhibitors have positively impacted outcomes in patients with metastatic melanoma.brain metastases. Here, we examined real world clinical outcomes of patients presenting with melanoma brain metastases (MBMs). Methods: This retrospective review evaluated MBMs patients treated at The Ottawa Hospital from April 2000 to July 2017. Clinical, radiologic, pathologic and treatment information were gathered from the electronic medical records. The primary outcome was overall survival. The proportional Cox regression model was employed for survival data, while the Fisher’s exact and Mann–Whitney U tests analyzed the relationship between categorical and continuous data, respectively. Results: This retrospective study included 276 patients. Brain metastases were detected symptomatically in 191 patients (69.2%); the rates of detection by routine screening were 4.6% in the pre-2012 era and 11.7% in the contemporary era (p = 0.029). Median survival was three months. Predictors of overall survival were age, higher lactate dehydrogenase (LDH) values, multiple brain lesions, more extensive extracranial disease, neurological symptoms, infratentorial lesions and treatment type. Multivariable analysis demonstrated that stereotactic radiotherapy (STRT) was associated with a hazard ratio of 0.401 (p < 0.001) for survival; likewise, immune checkpoint inhibitor therapy was associated with a hazard ratio of 0.375 (p < 0.001). Conclusion: The findings from this study as “real world” data are consistent with results of pivotal clinical trials in MBMs patients and support contemporary locoregional and immunotherapy practices.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".