The costs of managing patients with stage 3 and 4 colorectal cancer and the influence of patient factors at presentation
Bibliographic record
Abstract
3656 Background: The costs of managing stage 3 and 4 colorectal cancer patients were determined and correlated with baseline patient characteristics. Methods: All patients presenting with stage 3 or 4 colorectal cancer at our institution between January 1986 and December 1993 were identified. Patients without pathologic confirmation or treated elsewhere for colorectal cancer were excluded. Ten patients were randomly selected from each of six categories based on disease site and stage, and resource utilization, clinical and demographic data were abstracted for each patient from hospital records. Unit costs obtained from a simultaneous fully allocated costing model and provincial billing data were attached to each resource. Average costs were determined, and univariate and multivariate regression analyses performed to estimate the influence on costs of baseline demographic and clinical variables. Results: Of 573 patients identified, 340 had colon cancer, 111 rectosigmoid cancer, and 122 rectal cancer. Of the 60 patients in the sample, 54% were men, and mean ages at presentation were 67.9 years for men and 69.9 years for women. Overall survival was 39 months for stage 3 and 11 months for stage 4 patients. Patient management in each category was described. Mean total costs per patient in each category varied from $13,075 (Canadian) to $21,853. Most costs were incurred during the first (71.3%) and second (21.1%) years following presentation. The ten most important cost categories were: number of admission days, surgical and operating room charges, clinic visits, medical imaging, inpatient physician charges, radiotherapy, laboratory tests, intensive care, medical specialist consultations, and surgical procedures. A multivariate regression model predicting total costs based on gender, disease site, stage at presentation, age, and comorbidity explained 33% of the variation in costs between patients. Conclusions: The cost components for stage 3 and 4 colorectal cancer were identified, and a multivariate regression model showed that baseline patient characteristics could explain one-third of the variation in health care costs. Author Disclosure Employment or Leadership Consultant or Advisory Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Pharmacia Hoffmann-La Roche
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".