Assessing Functional Outcomes and Health-Related Quality of Life After Radiation Therapy in Extremity Soft Tissue Sarcoma
Bibliographic record
Abstract
AIMS: Extremity soft-tissue sarcomas (ESTS) are rare neoplasms treated with limb-sparing surgery and radiation therapy (RT). While RT improves local control, it can be associated with late functional impairments that may affect health-related quality of life (HR-QOL). As survivorship care gains importance, understanding the relationship between functional outcomes (FO) and HR-QOL is crucial. This study evaluates the relationship between FO, measured by the Toronto Extremity Salvage Score (TESS), and HR-QOL, assessed with the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). MATERIALS AND METHOD: A cohort study including ESTS patients treated with RT (January 2009 to October 2024) was conducted. Eligible patients completed the TESS and QLQ-C30 questionnaires. Correlation analyses, receiver operating characteristic (ROC) curve analysis, and statistical comparisons were performed to assess the association between FO and HR-QOL and to determine a clinically relevant TESS threshold for impairment. RESULTS: Of 255 identified patients, 123 were eligible, and 61 (response rate: 52%) completed the questionnaires. TESS lower-limb scores showed strong correlations with QLQ-C30 physical (r = 0.74), role (r = 0.63), and social functioning (r = 0.62). Notably, ROC analysis identified a clinically meaningful TESS threshold of ≥80, demonstrating high sensitivity (88%) and specificity (100%) for detecting significant functional impairments. Most patients reported good FO and HR-QOL, but a subset experienced severe impairments. CONCLUSION: ESTS survivors generally maintain good function and HR-QOL, but functional impairments significantly affect some patients. The identified TESS threshold of ≥80 may help clinicians monitor at-risk patients and guide early interventions. Future studies should validate this threshold and explore interventions for patients with severe impairments.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".