Association of persistent morbidity after radiotherapy with quality of life in locally advanced cervical cancer survivors
Bibliographic record
Abstract
PURPOSE: To quantify the association of persistent morbidity with different aspects of quality of life (QOL) in locally advanced cervical cancer (LACC) survivors. MATERIAL AND METHODS: Longitudinal outcome from the EMBRACE-I study was evaluated. Patient-reported symptoms and QOL were prospectively scored (EORTC-C30/CX24) at baseline and regular follow-ups. Physician-assessed symptoms were also reported (CTCAEv.3). Persistent symptoms were defined if present in at least half of the follow-ups. QOL items were linearly transformed into a continuous scale. Linear mixed-effects models (LMM) were applied to evaluate and quantify the association of persistent symptoms with QOL. Overall QOL deterioration was evaluated by calculating the integral difference in QOL over time obtained with LMM for patients without and with persistent symptoms. RESULTS: Out of 1416 patients enrolled, 741 with baseline and ≥ 3 late follow-ups were analyzed (median 59 months). Proportions of persistent EORTC symptoms ranged from 21.8 % to 64.9 % (bowel control and tiredness). For CTCAE the range was 11.3-28.6 % (limb edema and fatigue). Presence of any persistent symptom was associated with QOL, although with varying magnitude. Role functioning and Global health/QOL were the most impaired aspects. Fatigue and pain showed large differences, with reductions of around 20 % for most of the QOL aspects. Among organ-related symptoms, abdominal cramps showed the largest effect. CONCLUSION: Persistent symptoms are associated with QOL reductions in LACC survivors. Organ-related symptoms showed smaller differences than general symptoms such as fatigue and pain. In addition to optimizing treatment to minimize organ-related morbidity, effort should be directed towards a more comprehensive and targeted morbidity management.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".