Longitudinal Prevalence of Financial Worry in a Cohort of Patients with Advanced Colorectal Cancer: A Secondary Observational Cohort Study
Bibliographic record
Abstract
Introduction Financial hardship during cancer treatment is common in privatised healthcare systems and has been extensively studied in cancer survivorship groups. The experience of financial concerns by people living with advanced, incurable cancer has been less frequently explored. This paper sought to describe the proportion of patients experiencing financial worry longitudinally, in a cohort with advanced colorectal cancer, in a publicly funded healthcare system. Methods This secondary analysis of a prospective, observational cohort study ‘Palliative Care Early and Systematic (PaCES)’ project, analysed data from 131 patients with advanced colorectal cancer, from Alberta’s two tertiary cancer centres, treated between January 2018 - December 2020. Rates of self-reported financial concerns were obtained from the Canadian Problem Checklist, completed monthly for 10 months and 3 monthly thereafter. Results Fifty-seven patients (43%) affirmed at least once that they had worried about their finances in the preceding month. Of those who reported they had “noˮ financial concerns at enrolment, 41 (35%) subsequently answered “yesˮ. The proportion of patients experiencing financial worry at any given time point fluctuated but the mean proportion was 18%. Multivariable analysis confirmed younger age (<65) was associated with more financial worry ( P -value <0.01). Conclusion Financial worry is a common and often recurrent concern for patients with advanced colorectal cancer, particularly for younger patients. Serial screening is important to detect persisting or de novo worry.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".