Timing of receipt of palliative care among participants in early-phase cancer clinical trials.
Bibliographic record
Abstract
260 Background: Early phase clinical trials (EP-CTs) investigate novel therapeutics for patients with cancer. EP-CT participants often have advanced stages of disease, have received multiple lines of prior therapies, and remain sufficiently functional to enroll on EP-CTs. Limited research exists to describe the use and timing of palliative care (PC) in EP-CTs. Methods: We conducted a prospective study of patients with cancer enrolled on EP-CTs at Massachusetts General Hospital from April 2021- January 2023. We extracted demographic and clinical characteristics from the electronic health record as well as timing of receipt of PC (before/during EP-CT vs after EP-CT/never) and reason for PC referral documented in the referral. We used patient-reported surveys at time of treatment initiation to assess symptom burden (Edmonton Symptom Assessment System [ESAS]), financial toxicity (Comprehensive Score for Financial Toxicity [COST], lower scores indicate greater toxicity), quality of life (QOL; Functional Assessment of Cancer Therapy-General [FACT-G]), and hope (Herth Hope Index [HHI], higher scores indicate greater hope). We used descriptive statistics to explore associations of timing of receipt of PC with patient characteristics, symptom burden, financial wellbeing, QOL, and hope. Results: Of 221 eligible patients, we enrolled 204 (enrollment rate 92.3%, median age=63.4 years [range 54.8-70.2]; 57.0% female, 94.1% metastatic cancer). Less than one third of patients received PC before/during EP-CT (31.8% before/during, 68.2% post/never). Reasons for referral include: symptom management (84.4%), coping (12.5%), advance care planning (7.8%), illness understanding (1.6%), and treatment decision-making (1.6%). Patients age <65 were more likely than those 65+ to receive PC before/during EP-CT (39.1% vs 22.1%, p=0.01). Patients with ECOG=1 were more likely than those with ECOG=0 to receive PC before/during EP-CT enrollment than post enrollment/never (37.9% vs 22.9%, p=0.01). Patients who received PC before/during EP-CT had a higher symptom burden (ESAS: 20.7 vs 15.5, p=0.01), lower QOL (70.9 vs 77.0, p=0.003), and worse financial toxicity (25.2 vs 29.4, p=0.003). We found no significant differences in hope scores based on timing of receipt of PC (27.6 vs 27.1, p=0.53). Conclusions: In this prospective cohort of EP-CT participants with cancer,less than one third received PC before/during EP-CT enrollment. Symptom management was the most common reason for referral to PC, which aligns with our patient-reported survey data. Characteristics associated with receiving PC before/during trial participation include age, decreased performance status, higher symptom burden, lower QOL, and increased financial toxicity. These findings suggest that earlier PC was appropriately delivered to those most in need yet highlight the importance of efforts to ensure earlier integration of PC in this population.
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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 | 0.022 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".