Preliminary results of a randomized controlled trial of early integration of specialist palliative care within a tertiary cancer center in the Czech Republic.
Bibliographic record
Abstract
113 Background: Clinical trials in the U.S. and Canada have shown the benefit for patients and the health care system of early integration of palliative care into oncological practice. Nevertheless the practical realisation and the timing of this integration may be controversial. The optimal model of specialist palliative care (SPC) involvement may depend on the quality of standard cancer care in the given country. Methods: We present preliminary results of a randomised controlled trial of early integration of SPC conducted in the largest tertiary cancer center in Czech Republic. The trial compares standard oncology care with integrated SPC to standard oncology care alone in patients with advanced solid tumors treated with palliative antineoplastic therapy. The design of the study is inspired by the study of early PC for patients with advanced NSCLC byTemel et al. (2010). The SPC intervention consists of consultations with palliative care team every 6 weeks. Outcomes assessed at baseline and at 3 and 6 months after enrollment are quality of life (EORTC-QoL-Q30), anxiety and depression (HADS) and structure and cost of end of life care. Results: 100 patients have been randomisd between September 2015 and January 2017 (integrated PC 51 pts, conotrole 49pts). There were differences at 3 and 6 months in QoL (66% vs. 55%, p > 0,05; 63% vs. 49% p > 0,05), prevalence of anxiety (37% vs. 43%, p > 0,05; 32% vs. 54%, p > 0,05) and depression (19% vs. 29% p = 0,02; 20% vs. 27% p > 0,05) in intergated and control arm respectively. The mean time from the last chemotherapy to death was 66 days vs.52 days (p = 0,04) and the enrollment rate to hospice programme was 63% vs. 43% (p = 0,02) at the end of life in favour of integrated palliative care. Conclusions: There seem to be a trend for better results in patient reported outcomes and reasonable resource utilisation in favour of integrated care model in the context of advanced cancer care in Czech Republic. But differences between study arms did not reach statistical significance in patient reported outcomes, probably due to small number of patients. We hope to enrol enough patients within next 6 months to overcome this limitation.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".