GCIG SB-001/NSGO-CTU-PEACE/ANZGOG 1923/2020: Palliation in gynae-oncology—Patients' expectations and assessment of care.
Bibliographic record
Abstract
TPS5635 Background: Patients with advanced gynaecological cancers who are approaching end of life (EOL) have a high symptom burden and following several prior lines of therapy, a low likelihood of response to further anti-cancer treatment. Despite this, 20-30% of women with gynecological cancer received chemotherapy in the last 30 days of life, with potentially detrimental effects on health and quality of life. Little is known about patients' and carers' perceptions and preferences in this phase of illness. Eliciting patient’s values and preferences for EOL care and shared decision-making are central elements of GCIG SB-001/NSGO-CTU-PEACE with the aim of improving patient-centered EOL care. The primary aim of PEACE is to assess the feasibility of collecting data on patient satisfaction towards EOL. Secondary aims include collecting data on patient and carer satisfaction with care, as well as prospective collection of details of their care. Methods: PEACE will prospectively enroll patients in Norway and Australia. Key eligibility criteria include: Patients with gynaecological cancer at an advanced stage with a predicted life expectancy of approximately 4 months. Patients may be on anti-cancer treatment or may be under observation/palliative care. In addition, the patient must be able (both physically and cognitively) to complete patient-reported outcome measures independently. The study will also include an appointed carer (not mandatory). Patient and carer satisfaction with care and the importance of domains of care will be assessed with the CANHELP-Lite individualized (Canadian Health Care Evaluation Project) instrument and FACIT (Functional Assessment of Chronic Illness Therapy). Carer’s perception of the bereavement period and the quality of the patient’s death will be assessed with the CANHELP lite bereavement and the Quality of Death and Dying questionnaire. The study will prospectively collect data on EOL treatment. Patient and carer satisfaction with care and quality of the dying process will be summarized by standard descriptive statistical measures. A sample size of 65 patients would have at least 80% power with 95% confidence to rule out a 60% completion rate in favour of the more interesting 75% rate. Assuming a 10% drop-out rate, PEACE will enrol 73 patients. Enrolment commenced in December 2022. ClinicalTrials.gov Identifier: NCT05142150 Clinical trial information: NCT05142150 .
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".