Patient-reported hope, quality of life, symptom burden, coping, and financial toxicity in early-phase clinical trial participants.
Bibliographic record
Abstract
275 Background: Early phase clinical trials (EP-CTs) investigate novel treatment options in oncology, with recent advances in personalized therapy leading to improved outcomes and offering hope to patients with cancer. However, little research has sought to understand associations of patient-reported hope with quality of life (QOL), symptom burden, coping, and financial toxicity in EP-CT participants. Methods: We prospectively enrolled consecutive adults with cancer participating in EP-CTs at Massachusetts General Hospital from 04/2021-05/2022. Participants completed baseline surveys prior to treatment initiation that assessed hope (Herth Hope Index [HHI], higher scores indicate greater hope), QOL (Functional Assessment of Cancer Therapy-General), symptom burden (physical: Edmonton Symptom Assessment System [ESAS]; psychological: Patient Health Questionaire-4 [PHQ4]), coping (Brief COPE: self-blame, acceptance, denial, emotional support, active, behavioral disengagement), and financial toxicity (COST tool, higher scores indicate greater financial wellbeing). We used regression models to determine associations of hope scores with patient-reported QOL, symptom burden, coping, and financial toxicity. Results: Of 157 eligible patients, we enrolled 129 (enrollment rate 82.2%, median age = 62.5 years [range 33.0-83.0], 53.9% female, and 96.0% metastatic cancer). Most common cancer types were gastrointestinal (37.5%), breast (20.3%), lung (8.6%), and head and neck (7.8%). Patients had an average HHI score of 27.5 (range 15.3 – 36.0), with 30.5% reporting high levels of hope. We found associations of higher hope scores with better QOL (B = 0.24, p < 0.001) and lower symptom burden (ESAS-physical: B = -0.14, p < 0.001; PHQ4-depression: B = -2.07, p < 0.001; PHQ4-anxiety: B = -0.93, p = 0.001). We also found that hope scores were associated with patients’ coping (self-blame [B = -1.44, p < 0.001]; acceptance [B = 1.40, p < 0.001], denial [B = -1.12, p = 0.004], emotional support [B = 0.99, p < 0.001], active [B = 1.02. p = 0.001], behavioral disengagement [B = -2.52, p < 0.001]). Lastly, we found that higher hope scores were associated with greater financial wellbeing (B = 0.11, p = 0.026). Conclusions: In this prospective cohort study, we demonstrated a substantial proportion of EP-CT participants had high baseline hope and identified associations of hope scores with other important patient-reported outcomes. Specifically, we found novel associations of higher hope scores with better QOL, lower symptom burden, more adaptive coping mechanisms, and greater financial wellbeing, underscoring the importance of targeting these patient-reported outcomes when seeking to enhance the care experience of EP-CT participants.
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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 | 0.025 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".