Malnutrition and patient-reported quality of life determine short-term prehabilitation outcomes and patients’ body composition – early results of the prospective EPPIC prehabilitation trial in oesophageal and pancreatic cancer
Bibliographic record
Abstract
Introduction: Prehabilitation improves outcomes in several malignancies, its role in oesophageal and pancreatic cancer is unclear. The EPPIC trial evaluates an out-patient prehabilitation program in oesophageal (EC) and pancreatic (PDAC) cancer prior to resection. Patients and Methods: The EPPIC trial is a prospective feasibility trial. Baseline parameters, frailty, nutrition status, physical fitness, and quality of life are evaluated. Prior to surgery, patients receive individualized out-patient nutrition therapy, and complete APP-based physical therapy and breathing exercises over a two-week period. Patients’ routine CT scans are automatically segmented with a validated AI-based body composition algorithm. Baseline parameters, nutrition and functional status as well as quality of life and CT-derived body composition measures were available for time of study enrolment and 3 months follow-up. Results: 53 patients were enrolled, mean age was 65 y (STD 9.92). Preoperatvely, mean BMI was 26.9 kg/m2 (STD 5.4), mean weight loss during the past 6 months was 7.4kg (STD 7.5). 20.7% of patients were diagnosed as frail (CRF>3), malnutrition (NRS>2) was present in 26.4% of patients, and 15.1% had sarcopenia (SARC-F>3) preoperatively. Sarcopenia in functional testing (p≤0.001) and frailty (p≤0.001) were associated with impaired quality of life (EORTC-QLQ-C30). In patients with malnutrition, there was a trend for higher rates of visceral (VAT) (0.76 vs. 0.55, p=0.089) and a decrease in subcutaneous fat tissue (SAT) (0.51 vs. 0.59, p=0.048). Patients with impaired quality of life had lower overall muscle to adipose tissue ratios (0.52 vs. 0.82, p=0.050), higher levels of intramuscular fat deposits (0.24 vs. 0.16, p=0.008) and a trend for visceral fat deposits (0.037 vs. 0.032, p=0.088). At three months follow-up, patients with malnutrition were more likely to lose total muscle volume (-1.22 vs. -0.19, p=0.026). Patients with impaired quality of life at diagnosis experienced a more pronounced reduction of total (-4.64 vs. -1.11, p=0.004) and SAT (-7.63 vs. -2.59, p=0.004). Conclusion: First results showed a close association of patients’ frailty, nutrition and functional status with patient-reported quality of life. Body composition analysis confirms unique detrimental body composition profiles for patients with malnutrition and impaired quality of life that were identified as major determinants of short-term outcomes after prehabilitation. Publication History Article published online: 04 September 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".