Long-Term Quality of Life of Retroperitoneal Sarcoma Patients Treated with Pre-Operative Radiotherapy and Surgery
Bibliographic record
Abstract
PURPOSE: Retroperitoneal sarcomas (RPS) are connective tissue cancers that are often large and anatomically in close proximity to critical and radiation-sensitive normal structures and organs within the abdomen and pelvis. The management of RPS may include preoperative radiotherapy (RT) and surgery. We aimed to examine how treatment-related toxicities affect patient quality of life (QOL). Methods and materials: Within two prospective cohort studies, 48 RPS patients who were treated with preoperative RT from 1998-2012 were recruited and assessed for QOL (EORTC-QLQ-C30) and to determine toxicities potentially related to RT and surgery (graded using CTCAE V.4). Baseline and prospective QOL was available for 11 patients. In the other 37 patients, prospective data were obtained at different time points during their follow-up. Unless stated otherwise, all scores refer to the global QOL subscale. RESULTS: The patients' median age was 57 (38-82) and RT was administered to a median dose of 45 Gy (41.4-50.4). The median maximum tumor dimension was 16.0 cm (5.7-28) and the majority (35/48) were liposarcomas. The mean pre-RT QOL was 48.5/100. At one month post-RT, the mean QOL improved to 54.2; however, the mean diarrhea symptom scale worsened from baseline (78.3 vs. 18.2, p<0.001). Correspondingly, 54% of patients had gastrointestinal toxicities (92% G1-2 and 8% G3) by the end of RT. At 36 months post-RT, 88% of patients had chronic toxicities (19% G3). RPS patients who survived and are free of recurrence ≥ 36 months had significantly (mean: 75.0; p=0.001) better QOL than at diagnosis. The number of toxicities was significantly (p=0.001) associated with QOL. RT dose, tumor size, patient age, and patient gender were not associated with 36-month QOL. Conclusions: Treatment toxicities seem to contribute to QOL recovery during the first 36 months. QOL at 36 months was better than at diagnosis.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".