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Patient-reported hope, quality of life (QOL), symptom burden, and coping mechanisms in early phase clinical trial participants.

2022· article· en· W4286295659 on OpenAlexaboutno aff
Debra Lundquist, Andrea Pelletier, Sienna Durbin, Viola Bame, Victoria Turbini, Megan Healy, Kaitlyn Lynch, Casandra McIntyre, Dejan Juric, Betty Ferrell, Rachel Jimenez, Ryan David Nipp

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoping (psychology)Quality of life (healthcare)Lung cancerPhysical therapyClinical trialBreast cancerInternal medicineCancerClinical psychology

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.345
GPT teacher head0.480
Teacher spread0.135 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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