Leptomeningeal carcinomatosis and brain metastases in gastroesophageal carcinoma: A real-world analysis of outcomes, clinical and pathologic characteristics.
Bibliographic record
Abstract
2029 Background: Brain metastasis (BM) and Leptomeningeal Carcinomatosis (LC) are uncommon complications in gastroesophageal carcinoma (GEC) patients (pts). These patients have a poor prognosis and are challenging to study. We described the clinicopathologic features and outcomes in the largest real-world cohort of CNS metastasis in GEC pts. Methods: We conducted a single-center retrospective study of GEC pts treated at the Princess Margaret Cancer Centre from 2007 to 2021 who developed BM. Clinicopathologic characteristics and treatment modalities were reviewed. Survival was calculated from the date of BM or LC diagnosis until date of death/last follow-up using the Kaplan-Meier method. A multivariable Cox proportional hazards regression model was used to examine the association of baseline covariates and survival. Results: Of 3283 consecutive pts with GEC, 101 (3.08%) were diagnosed with BM and 20 with LC (0.61%). Most pts with BM were male (75.3%), non-Asian (93%), with a primary gastroesophageal junction tumor (47%) and adenocarcinoma histology (86%). Among pts with known HER2 status (N= 48), 60% were HER2 positive (defined as IHC 3+ or IHC 2+/FISH+). All patients with LC had adenocarcinoma histology; most were signet-ring subtype (85%), poorly differentiated (80%) histology and only 15% (2/13) were HER2 positive. Median survival was 0.8; 3.8; and 7.7 months (mo) in BM pts treated with palliative care only, radiation only and surgery followed by radiation, respectively (p< 0.001). In LC, median survival was 0.7 mo in pts who had palliative care only (7/20) and 2.7 mo for those (13/20) who had whole brain radiation therapy (WBRT) (p .008). Multivariate analysis showed a higher probability of death in patients with number of BM ≥4 (p 0.02) and predicted superior survival in patients who received radiation and surgery followed by radiation (p 0.02). Conclusions: This is the most comprehensive summary of clinicopathologic characteristics and survival in patients with GEC and BM and LC disease to date. Biomarker analysis reveals an enriched frequency of HER2 expression in BM, while this is uncommon in pts with LC. BM pts who were treated with surgery followed by radiation had a significantly improved OS. WBRT benefited patients with LC over palliative care alone. These findings add to our understanding for the management of this understudied population with poor survival. [Table: see text]
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".