Phase II Trial of Symptom Screening With Targeted Early Palliative Care for Patients With Advanced Cancer
Bibliographic record
Abstract
BACKGROUND: Routine early palliative care (EPC) improves quality of life (QoL) for patients with advanced cancer, but it may not be necessary for all patients. We assessed the feasibility of Symptom screening with Targeted Early Palliative care (STEP) in a phase II trial. METHODS: Patients with advanced cancer were recruited from medical oncology clinics. Symptoms were screened at each visit using the Edmonton Symptom Assessment System-revised (ESAS-r); moderate to severe scores (screen-positive) triggered an email to a palliative care nurse, who called the patient and offered EPC. Patient-reported outcomes of QoL, depression, symptom control, and satisfaction with care were measured at baseline and at 2, 4, and 6 months. The primary aim was to determine feasibility, according to predefined criteria. Secondary aims were to assess whether STEP identified patients with worse patient-reported outcomes and whether screen-positive patients who accepted and received EPC had better outcomes over time than those who did not receive EPC. RESULTS: In total, 116 patients were enrolled, of which 89 (77%) completed screening for ≥70% of visits. Of the 70 screen-positive patients, 39 (56%) received EPC during the 6-month study and 4 (6%) received EPC after the study end. Measure completion was 76% at 2 months, 68% at 4 months, and 63% at 6 months. Among screen-negative patients, QoL, depression, and symptom control were substantially better than for screen-positive patients at baseline (all P<.0001) and remained stable over time. Among screen-positive patients, mood and symptom control improved over time for those who accepted and received EPC and worsened for those who did not receive EPC (P<.01 for trend over time), with no difference in QoL or satisfaction with care. CONCLUSIONS: STEP is feasible in ambulatory patients with advanced cancer and distinguishes between patients who remain stable without EPC and those who benefit from targeted EPC. Acceptance of the triggered EPC visit should be encouraged. CLINICALTRIALS: gov identifier: NCT04044040.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".