An international review and meta-analysis of prehabilitation compared to usual care for cancer patients
Bibliographic record
Abstract
PURPOSE: The purpose of the study is to systematically review and synthesise randomised controlled trials investigating the effectiveness of prehabilitation compared to usual care for newly diagnosed, adult-onset cancer patients. METHODS: MEDLINE, EMBASE, PsycINFO, CINAHL and SSCI were searched up to April 2017. Studies were included if disease-related, treatment-related, patient-reported and health service utilisation outcomes were assessed. Two reviewers independently reviewed and appraised the risk of bias of each study. RESULTS: Eighteen studies were included. Interventions comprised one or more of the following components: psychological support, education and exercise. Meta-analyses found that pelvic floor muscle training (PFMT) significantly increased odds of continence at 3 months (OR = 3.29, 95% CI = 1.57-6.91), but did not significantly reduce daily pad use at 6 months post-surgery Mean Difference (MD)= ( = - 0.96, 95% CI = - 2.04-0.12) for prostate cancer patients. Although quality of life improved due to PFMT, functional ability or distress did not. Further meta-analyses indicated that pre-surgical exercise significantly reduced length of hospital stay (MD = - 4.18, 95% CI = - 5.43-- 2.93) and significantly lowered odds of post-surgery complications (OR = 0.25, 95% CI = 0.10-0.66) for lung cancer patients. Psychology-based prehabilitation significantly improved mood, physical well-being and immune function for prostate cancer patients and improved fatigue and psychological outcomes and a trend for better quality of life among breast cancer patients. Risk of bias was high for most studies. CONCLUSIONS: Prehabilitation appears to benefit cancer patients. Rigorous trials are needed to investigate the effectiveness of prehabilitation among other cancer sites and other related effects. The cost-effectiveness of prehabilitation remains unanswered. IMPLICATIONS FOR CANCER SURVIVORS: Providing interventions earlier in the care pathway may lead to better outcomes for patients during survivorship.
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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 | 0.017 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".