Illness perceptions, financial toxicity, symptom burden, and survival in cancer clinical trial (CCT) participants.
Bibliographic record
Abstract
160 Background: Patients’ perceptions of their illness are important for treatment decision-making and quality of life. Limited data exist describing associations of illness perceptions with other patient-centered outcomes, particularly in CCT participants. We sought to examine associations among illness perceptions and CCT patients’ financial toxicity, physical and psychological symptoms, and survival. Methods: From 7/2015-7/2017, we prospectively enrolled CCT participants who expressed interest in financial assistance programs (n = 157) and a group of patients matched by age, sex, cancer type, specific trial, and trial phase (n = 103). We assessed baseline illness perceptions (Brief Illness Perceptions Questionnaire [BIPQ] with scores > 50 indicating negative perceptions), financial toxicity (degree costs of cancer care have been a burden, moderate to catastrophic indicating financial toxicity), physical (Edmonton Symptom Assessment Scale [ESAS]) and psychological (Patient Health Questionnaire-4 [PHQ-4]) symptoms. We used descriptive statistics to examine associations of BIPQ and sociodemographic/clinical factors, financial toxicity, ESAS, PHQ-4, and overall survival. We used the Kaplan-Meier method to estimate median survival times and Cox regression to assess the association of BIPQ and overall survival. Results: Among 260 patients, 189 (72.7%) completed BIPQ surveys (median age 69 [Range 26 to 83] years, 66.1% female). 68.8% had negative illness perceptions. We found no significant associations among negative illness perceptions and patients’ age, sex, race, education, marital status, performance status, insurance, cancer type, metastatic disease status, self-reported income, trial phase, trial year, or Charlson Comorbidity Index score. Patients with negative illness perceptions were more likely to report financial toxicity (69.8% vs 48.8%, p = 0.006), and had higher ESAS-total (Medians: 44 [Range 0-89] vs 21 [Range 0-78], p < 0.001), PHQ-4 depression (Medians: 2 [Range 0-6] vs 0 [Range 0-6], p < 0.001), and PHQ-4 anxiety (Medians: 3 [Range 0-6] vs 1 [Range 0-6], p < 0.001) scores. Patients with negative illness perceptions had shorter overall survival (Medians: 22 [Range 10-29] vs 42 [Range 28-Not Reached] months, log-rank p = 0.004). Adjusting for receipt of financial assistance, patients with negative illness perceptions experienced higher risk of death (HR 1.65, 95% CI 1.10-2.48). Conclusions: In this prospective study of CCT participants, we found that patients with negative illness perceptions experienced greater financial toxicity, more symptom burden, and worse survival than those with more positive perceptions, despite comparable sociodemographic/clinical factors. These findings highlight the need to assess and address patients’ illness perceptions and financial burden when seeking to enhance patient-centered outcomes in oncology.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".