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Record W4407631367 · doi:10.1016/j.lanwpc.2024.101367

Relationships between financial toxicity and symptom burden among cancer patients: a longitudinal study

2025· article· en· W4407631367 on OpenAlexaff
Yi Kuang, Qi Xiang, Jiajia Qiu, Ye Liu, Sijin Guo, Ting Chen, Lichen Tang, Winnie K.W. So, Weijie Xing

Bibliographic record

VenueThe Lancet Regional Health - Western Pacific · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsDiscovery Centre
Fundersnot available
KeywordsToxicityCancerMedicineLongitudinal studyOncologyEnvironmental healthPsychologyInternal medicinePathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.114
GPT teacher head0.322
Teacher spread0.207 · 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 teacher head, 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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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