Immune-Enhancing Formulas for Patients With Cancer Undergoing Esophagectomy: Systematic Review Protocol
Bibliographic record
Abstract
BACKGROUND: Adult patients with an esophageal cancer can potentially be compromised with postoperative leaks or fistulae if patients' nutritional status is in a vulnerable stage. Currently in Australia, there is a growing need for clinicians to know whether use of immune-enhancing formulas (IEFs) containing Arg, omega-3, and RNA are a cost-effective approach compared with isonitrogenous-isocaloric formulas to reduce postoperative infectious complications in esophagectomy patients. Since IEFs may carry higher costs, this has led to inconsistencies in practice among clinicians and hospitals. OBJECTIVE: Our aim is to compile and present the most up-to-date nutrition evidence available regarding the provision of IEFs containing Arg, omega-3, and RNA to help clinicians develop an evidence-based nutrition care plan; identify available evidence of whether an esophagectomy patient should receive IEF; determine the cost-effectiveness and safety of such nutrition; and determine appropriate administration quantity and timing (pre-, peri-, or postesophagectomy). METHODS: This review will include RCTs involving the use of IEFs enriched with Arg, omega-3 polyunsaturated fatty acids, and RNA in the pre-, peri-, or postoperative period (for at least 5-7 days) given orally or via enteral feeding tube, in adult cancer patients undergoing esophageal resection. Lower gastrointestinal, gastric, or head cancer surgery with parenteral nutrition or non-IEF or use of isolated immunonutrient (Arg vs omega-3 vs RNA) will be excluded. Primary outcome comprises postoperative infectious complications. Secondary outcomes (pre/postoperatively) consist of cost-effectiveness, length of stay, survival/mortality, quality of life, nutritional status, percentage of weight loss, and biochemical changes. The risk of bias will be independently assessed by the reviewers, using a domain-based evaluation tool. Blinding will be assessed for subjective and objective outcome measures. Publication bias will be visually assessed by funnel plots. A meta-analysis will be generated by the Review Manager 5.3 software and represented in forest plots. RESULTS: The first results are expected in 2018. Outlining the protocol will ensure transparency for the completed review. CONCLUSIONS: This protocol for a systematic review and meta-analysis will enable a comprehensive appraisal of the literature to help determine whether overall institutional savings are associated with this approach. Findings will form a knowledge base relevant to stakeholders across the health system and researchers who are involved in decision making on evidence-based nutrition care plan pathways for patients undergoing esophagectomy, as well as the use of IEF, timing, and administration quantity. TRIAL REGISTRATION: PROSPERO Registration Number: CRD42017056908; http://www.crd.york.ac.uk/PROSPERO/ display_record.asp? ID=CRD42017056908 (Archived by WebCite at http://www.webcitation.org/6rLyeqaD6).
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
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".