Relationships between financial toxicity and symptom burden among cancer patients: a longitudinal study
Bibliographic record
Abstract
Financial toxicity from cancer treatment significantly impacts the quality of life among patients. Understanding how financial toxicity interacts with symptom burden is crucial for developing effective interventions. This study aimed to assess the longitudinal associations between financial toxicity and symptom burden in cancer patients in China. Conducted from November 2022 to March 2024, this prospective cohort study recruited participants from four Grade-A public hospitals across China using a convenient sampling method. Eligibility criteria included age ≥18 years, cancer diagnosis with surgery, scheduled anti-tumor treatments, and Mandarin proficiency. Financial toxicity was measured using the Comprehensive Score for Financial Toxicity (range, 0-44; higher scores indicate better financial well-being), while symptom burden was assessed with the BCPT Eight Symptom Scale (range, 0-120; higher scores reflect greater symptom annoyance) and the Memorial Symptom Assessment Scale – Short Form Psychological Subscales (range, 4-16; higher scores indicate greater burden). Assessments occurred at baseline (T1), 3 months (T2), 6 months (T3), and 12 months (T4) post-surgery. Among 378 participants (median age, 48.9 years), moderate negative associations were found between physical symptom burden and financial toxicity (r = -0.498 to -0.411) and between psychological symptom burden and financial toxicity (r = -0.493 to -0.392). A Random Intercept Cross-lagged Panel Model demonstrated that financial toxicity negatively predicted subsequent physical symptom burden (r = -0.122 to -0.166, p<0.05), while physical symptom burden at T1 and T3 negatively predicted financial toxicity at subsequent time points (r = -0.186 to -0.294, p<0.05). Additionally, psychological symptom burden negatively predicted financial toxicity at the following time points (r = -0.069 to -0.116, p<0.05). Bidirectional associations between financial toxicity and symptom burden were found in this study. Future research should simultaneously take measures to alleviate symptom burden and improve financial toxicity in order to break the vicious cycle between symptom burden and financial toxicity.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".