Current Landscape of Nutrition Within Prehabilitation Oncology Research: A Scoping Review
Bibliographic record
Abstract
Background: Prehabilitation aims to improve functional capacity prior to cancer treatment to achieve better psychosocial and clinical outcomes. Prehabilitation interventions vary considerably in design and delivery. In order to identify gaps in knowledge and facilitate the design of future studies, we undertook a scoping review of prehabilitation studies to map the range of work on prehabilitation being carried out in any cancer type and with a particular focus on diet or nutrition interventions. Objectives: Firstly, to describe the type of prehabilitation programs currently being conducted. Secondly, to describe the extent to which prehabilitation studies involved aspects of nutrition, including assessment, interventions, implementation, and outcomes. Eligibility Criteria: Any study of quantitative or qualitative design that employed a formal prehabilitation program before cancer treatment (“prehabilitation” listed in keywords, title, or abstract). Sources of Evidence: Search was conducted in July 2020 using MEDLINE, PubMed, EMBASE, EMCARE, CINAHL, and AMED. Charting Methods: Quantitative data were reported as frequencies. Qualitative nutrition data were charted using a framework analysis that reflects the Nutrition Care Process Model: assessment, intervention, and monitoring/evaluation of the nutrition intervention. Results: Five hundred fifty unique articles were identified: 110 studies met inclusion criteria of a formal prehabilitation study in oncology. prehabilitation studies were mostly cohort studies (41%) or randomized-controlled trials (38%) of multimodal (49%), or exercise-only (44%) interventions that were applied before surgery (94%). Nutrition assessment was inconsistently applied across these studies, and often conducted without validated tools (46%). Of the 110 studies, 37 (34%) included a nutrition treatment component. Half of these studies provided the goal for the nutrition component of their prehabilitation program; of these goals, less than half referenced accepted nutrition guidelines in surgery or oncology. Nutrition interventions largely consisted of counseling with dietary supplementation. The nutrition intervention was indiscernible in 24% of studies. Two-thirds of studies did not monitor the nutrition intervention nor evaluate nutrition outcomes. Conclusion: Prehabilitation literature lacks standardized and validated nutritional assessment, is frequently conducted without evidence-based nutrition interventions, and is typically implemented without monitoring the nutrition intervention or evaluating the intervention's contribution to outcomes. We suggest that the development of a core outcome set could improve the quality of the studies, enable pooling of evidence, and address some of the research gaps identified.
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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 | 0.040 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.036 | 0.040 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".