Patient-reported hope, quality of life (QOL), symptom burden, and coping mechanisms in early phase clinical trial participants.
Bibliographic record
Abstract
12114 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 QOL, symptom burden, and coping mechanisms in EP-CT participants. Methods: We prospectively enrolled consecutive adults with cancer participating in EP-CTs at Massachusetts General Hospital from 04/2021-01/2022. 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]), and coping mechanisms (Brief COPE). We used independent samples t-test to test for mean differences between groups and regression models to explore associations of hope with patient characteristics as well as patient-reported QOL, symptom burden, and coping mechanisms. Results: Of 92 eligible patients, we enrolled 85 (enrollment rate 92.4%, median age = 61.4 years [range 54.7-68.9]; 56.5% female, and 95.3% metastatic cancer). Most common cancer types were gastrointestinal (41.2%), breast (21.2%), lung (7.1%), and gynecologic (7.1%). Patients had an average HHI score of 28.2 (range 12.0-36.0), with 32.9% reporting high levels of hope. We found that married patients had higher mean hope score compared with non-married patients (28.9 versus 26.1, p = 0.024), those with children had higher mean hope scores than those without (28.9 versus 25.9, p = 0.013), and those who had received 3 or more lines of prior therapy compared with 1-2 (29.3 versus 27.2, p = 0.045) had higher hope scores. We also found associations of hope with patients’ QOL (B = 0.24, p < 0.001), symptom burden (ESAS-physical: B = -0.13, p = 0.001; PHQ4-depression: B = -2.26 p = < 0.001; PHQ4-anxiety: B = -0.94, p = 0.008), and coping (self-blame [B = -1.39, p = 0.003]; acceptance [B = 1.23, p = 0.002], denial [B = -1.09, p = 0.009], support [B = 1.06, p = 0.002], active [B = 0.73. p = 0.034], disengage [B = -3.24, p < 0.001]). Conclusions: In this prospective cohort study, we demonstrated that a substantial proportion of EP-CT participants had high baseline hope, and we identified several patient factors associated with their hope scores. We also found novel associations of higher hope scores with better QOL, lower symptom burden, and more adaptive coping mechanisms. Collectively, our findings highlight the potential for patient-reported hope to represent a key factor to consider when seeking to improve outcomes in 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 | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".