Influence of nutritional status and body composition on postoperative events and outcome in patients treated for primary localized retroperitoneal sarcoma
Bibliographic record
Abstract
Abstract Background Retroperitoneal sarcomas (RPS) are rare tumours of mesenchymal origin, commonly presented as a large tumour mass at time of diagnosis. We investigated the impact of body composition on outcome in patients operated on for primary localized RPS. Patients and methods We retrospectively analysed data for all patients operated on for primary RPS at our institution between 1999 and 2020. Preoperative skeletal muscle area (SMA), visceral and subcutaneous adipose tissue area (VAT and SAT) and muscle radiation attenuation (MRA) were calculated using computed tomography scans at the level of third lumbar vertebra. European Working Group on Sarcopenia in Older People (EWGSOP2) criteria were applied to define myopenia. Using maximum log-rank statistic method we determined the optimal cut-off values of body composition parameters. Myosteatosis was defined based on determined MRA cut-offs. Results In total 58 patient were eligible for the study. With a median follow-up of 116 months, the estimated 5-year overall survival (OS) and local-recurrence free survival (LRFS) were 66.8% and 77.6%, respectively. Patients with myopenia had significantly lower 5-year OS compared to non-myopenic (p = 0.009). Skeletal muscle index and subcutaneous adipose tissue index predicted LRFS on univariate analysis (p = 0.052 and p = 0.039, respectively). In multivariate analysis high visceral-to-subcutaneous adipose tissue area ratio (VSR) independently predicted higher postoperative complication rate (89.2% vs . 10.8%, p = 0.008). Myosteatosis was associated with higher postoperative morbidity. Conclusions Myopenia affected survival, but not postoperative outcome in RPS. Visceral obesity, VSR (> 0.26) and myosteatosis were associated with higher postoperative morbidity. VSR was better prognostic factor than VAT in RPS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".