Clinical prediction survival of advanced cancer patients by palliative care: a multi-site study
Bibliographic record
Abstract
AIMS: This study examined (1) accuracy of clinician prediction of survival (CPS) by palliative practitioners on first assessment with the use of standardised palliative tools, (2) factors affecting accuracy, (3) potential impact on clinical care. METHODS: A multi-site prospective study (n=1530) was used. CPS was divided into four time periods (<=2wks, >2 to 6wks, >6 to 12wks and >12wks). Multivariate analysis was assessed on six predictor variables. RESULTS: Overall, median survival of the sample was only 5 weeks. CPS category was accurate only 38.6% of the time, with 44.6% patients dying before the predicted time period. Of six candidate variables, on multivariate analysis only (i) the clinical time periods themselves and (ii) Palliative Performance Scale <=50 predicted for prognostic accuracy. CONCLUSION: CPS, even by palliative practitioners, remains overly optimistic with the existence of the horizon effect. This raises the question in that these individuals may have been potentially overtreated.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".