Patient-Reported Outcomes after Surgical, Endoscopic, or Radiological Techniques for Nutritional Support in Esophageal Cancer Patients: A Systematic Review
Bibliographic record
Abstract
Several techniques exist to maintain oral and/or enteral feeding among esophageal cancer (EC) patients, but their impact on patient-reported outcomes (PROs) remains unclear. This systematic review aimed to assess the impact of nutritional support techniques on PROs in EC patients. We searched Medline, Web of Science, and CINAHL Complete from inception to 3 April 2024. Eligible studies included those evaluating EC patients, reporting PROs using standardized measures, and providing data on different nutritional support techniques or comparing them to no intervention. The reference lists of the included studies were also screened for additional eligible articles. The Mixed Methods Appraisal Tool was used to evaluate the quality of the included studies. Of the 694 articles identified from databases and 224 from backward citation, 11 studies met the inclusion criteria. Nine studies evaluated the overall quality of life (QoL), four assessed pain, and one evaluated depression. Among those submitted to esophagectomy, jejunostomy may be associated with higher QoL scores and less postoperative pain, compared to a nasojejunal tube, but no significant differences were found when compared to no intervention. For patients undergoing chemotherapy or receiving palliative/symptomatic treatment, expandable metal stents (SEMSs) were associated with higher levels of emotional functioning when compared with laparoscopic gastrostomy. Moreover, percutaneous endoscopic gastrostomy or SEMSs were associated with a higher QoL compared with nasogastric tubes. This review underscores the importance of considering PRO measures when evaluating nutritional support techniques in cancer patients, though further robust evidence is needed to fully understand these associations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".