Economic burden of brain metastases among patients with metastatic melanoma in a USA managed care population
Why this work is in the frame
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Bibliographic record
Abstract
Malignant melanoma patients frequently relapse with metastases in the brain, making it the third most common cancer-causing brain metastases in the USA. Management of brain metastases remains challenging because of the rapid progression of disease and ineffectiveness of conventional therapies. This retrospective study, with a 'pre/post' design, quantifies the economic burden of brain metastases among melanoma patients in the USA. A large managed-care insurance claims database (2000 Q1-2011 Q3) was used to identify patients with melanoma and brain metastases. The preperiod was defined as the 6 months before the index date (diagnosis of first observed brain metastases) and postperiod as the period following the index date up to 12 months. All-cause and brain metastasis-related healthcare resource utilization and healthcare costs were compared on a per-patient-per-month (PPPM) basis between preperiods and postperiods. The study included 6076 patients (mean age 63.4 years); 57.6% were men. Significant differences (P<0.0001) were observed between the postperiods and preperiods in the mean all-cause and brain metastasis-related PPPM hospitalizations and emergency department and outpatient visits. Significant postperiod versus preperiod differences were also observed in the PPPM mean (standard error) all-cause healthcare costs [total: $14 489 ($231) vs. $7277 ($116); inpatient: $6330 ($195) vs. $1900 ($69); outpatient: $6609 ($102) vs. $4449 ($79); P<0.0001 for all] and brain metastasis-related costs [total: $6542 ($145) vs. $1933 ($62); inpatient: $2976 ($118) vs. $472 ($39); outpatient: $3451 ($76) vs. $1413 ($47); P<0.0001 for all]. Radiotherapy was the most common treatment. The economic burden associated with brain metastases in melanoma is significant and underscores the need for newer therapies to improve outcomes in these patients.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it