Clinicopathologic Characteristics and Survival Outcomes of Patients with Advanced Esophageal, Gastroesophageal Junction, and Gastric Adenocarcinoma: A Single-Institution Experience
Bibliographic record
Abstract
UNLABELLED: Most patients with gastric or gastroesophageal junction (gej) cancer are diagnosed with inoperable advanced or metastatic disease. In these cases, chemotherapy is the only treatment demonstrating survival benefit. The present study compares clinicopathologic characteristics and survival outcomes for patients with advanced esophageal, gej, and gastric adenocarcinoma treated with first-line chemotherapy [epirubicin-cisplatin-5-fluorouracil (ecf), epirubicin-cisplatin-capecitabine (ecx), or etoposide-leucovorin-5-fluorouracil (elf)] or best supportive care (bsc) at our institution with those for historical controls. METHODS: We retrospectively reviewed medical information for 401 patients with newly diagnosed advanced esophageal, gej, or gastric adenocarcinoma treated with first-line chemotherapy (ecf, ecx, or elf) or bsc from January 1, 2004, through December 31, 2010. Descriptive statistics were used to compare the data collected with data for historical control patients. RESULTS: Of the study patients, 93% were diagnosed with metastatic disease (n = 374), and 63% received bsc only (n = 251). The main reasons that patients received bsc only included poor Eastern Cooperative Oncology Group performance status (55%), patient decision (31%), and comorbidities (14%). Of the remaining patients, 98 (24%) received ecf or ecx and 52 (13%) received elf as first-line treatment. Median overall survival was significantly longer in patients treated with ecf or ecx or with elf than in those receiving bsc (12.7 months vs. 12.7 months vs. 5.5 months respectively). Chemotherapy also significantly reduced the risk of death (64% reduction with ecf or ecx, 58% with elf). CONCLUSIONS: We confirmed the substantial overall survival benefit of combination chemotherapy compared with bsc, with better survival in our patient population than in historical controls. However, novel treatment options are still warranted to improve outcomes in this patient population.
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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 | 0.001 | 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".