Survival of Patients with Non-Small-Cell Lung Cancer after a Diagnosis of Brain Metastases
Bibliographic record
Abstract
BACKGROUND: The prognosis of patients with brain metastases from non-small-cell lung cancer (nsclc) is poor. However, some reports suggest that patients with brain metastases at the time of initial diagnosis have a more favourable survival than do patients with advanced nsclc without brain metastases. METHODS: In a retrospective cohort of all new lung cancer patients seen at a Canadian tertiary centre between July 2005 and June 2007, we examined survival after a diagnosis of brain metastases for patients with brain metastases at initial diagnosis and patients who developed brain metastases later in their illness. RESULTS: During the 2-year period, 91 of 878 patients (10.4%) developed brain metastases. Median age in this cohort was 64 years. In 45, brain metastases were present at initial diagnosis, and in 46, brain metastases developed later in the course of the illness. Median survival in the entire cohort was 7.8 months. Survival after the diagnosis of brain metastases was similar for patients with brain metastases at diagnosis and later in the illness (4.8 months vs. 3.7 months, p = 0.53). As a result, patients who developed brain metastases later in their illness had a longer overall survival than did patients with brain metastases at diagnosis (9.8 months vs. 4.8 months). Among patients who received chemotherapy, the survival of patients with brain metastases at diagnosis was still poor (6.2 months). CONCLUSIONS: Our data show limited survival in patients with brain metastases from nsclc. Careful patient selection for more aggressive treatment approaches is necessary.
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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 | 0.001 |
| 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".