Favourable health-related quality of life reported in survivors of thymic malignancies†
Bibliographic record
Abstract
OBJECTIVES: The management of patients with locally advanced thymic malignancies remains controversial. Differing combinations of surgical resection, chemotherapy and radiation are used in the management of initial and relapsed disease. Treatment-related toxicities and quality of life could inform therapeutic options. This study describes health utility scores (HUS) in survivors with locally advanced thymic malignancies and investigates the impact of multimodality regimens on HUS. METHODS: In a cross-sectional study (2014-2017), patients with Masaoka Stage II-IVa thymic malignancies completed various self-reported questionnaires, including EuroQol-5-Dimensions with visual analogue scale (VAS), Eastern Cooperative Oncology Group (ECOG) and Edmonton Symptom Assessment Scale tools. Trimodality versus uni- or bimodality regimens and aggressive versus non-aggressive management of recurrent disease were compared using regression analyses. RESULTS: Of the 72 patients, 43 (60%) were male with a median age of 58 years, 65 (90%) had thymoma while 7 (10%) had thymic carcinomas; and median time since diagnosis was 50.5 months (range: 3-266). Median HUS and VAS did not differ between groups (trimodality n = 24 vs uni- or bimodality n = 48: HUS = 0.77 vs 0.80, P = 0.29; VAS = 80 vs 75, P = 0.79, respectively). The distributions of patient-reported ECOG were also similar (P = 0.86). Edmonton Symptom Assessment Scale scores for every assessed symptom were similar for different modalities of therapy. Median scores on these tools were also similar regardless of recurrence status or management of relapsed disease (aggressive versus non-aggressive). CONCLUSION: Survivors with Stage II-IVa thymic malignancies report favourable HUS, VAS and self-reported ECOG with minimal symptom burden. These outcomes may be independent of number and type of initial treatment modalities or management of recurrence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".