What Is the Optimal Management of Dysphagia in Metastatic Esophageal Cancer?
Bibliographic record
Abstract
BACKGROUND: The palliation of dysphagia in metastatic esophageal cancer remains a challenge, and the optimal approach for this difficult clinical scenario is not clear. We therefore sought to define and determine the efficacy of various treatment options used at our institution for this condition. METHODS: We reviewed a prospective database for all patients managed in an esophageal cancer referral centre over a 5-year period. All patients receiving palliation of malignant dysphagia were reviewed for demographics, palliative treatment modalities, complications, and dysphagia scores (0 = none to 4 = complete). The Wilcoxon signed rank test was used to determine significance (p < 0.05). RESULTS: During 2004-2009, 63 patients with inoperable esophageal cancer were treated for palliation of dysphagia. The primary treatment was radiotherapy in 79% (brachytherapy in 18 of 50; external-beam in 10 of 50; both types in 22 of 50), and stenting in 21%. Mean wait time from diagnosis to treatment was 22 days in the stent group and 54 days in the radiotherapy group (p = 0.003). Mean duration of treatment was 1 day in the stent group and 40 days in the radiotherapy group (p = 0.001). In patients treated initially by stenting, dysphagia improved within 2 weeks of treatment in 85% of patients (dysphagia score of 0 or 1). However, 20% of patients presented with recurrence of dysphagia at 10 weeks of treatment. In the radiotherapy group, the onset of palliation was slower, with only 50% of patients palliated at 2 weeks (dysphagia score of 0 or 1). However, long-term palliation was more satisfactory, with 90% of patients remaining palliated after 10 weeks of treatment. CONCLUSIONS: In inoperable esophageal cancer at our centre, radiation treatment provided durable long-term relief, but came at a high price of a long wait time for initiation of treatment and a long lag time between initiation of treatment and relief of symptoms. On the other hand, endoluminal stenting provided more rapid and effective early relief from symptoms, but was affected by recurrence of dysphagia in the long-term. It is now time for a prospective randomized trial to assess the safety and efficacy of combined-modality treatment with both endoluminal stenting and radiation therapy compared with either treatment alone.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".