NCTQ-10 INPATIENT CARE COSTS AND ASSOCIATED REIMBURSEMENTS FOR PATIENTS WITH LEPTOMENINGEAL METASTATIC DISEASE: A REAL-WORLD CLAIMS-BASED ANALYSIS
Bibliographic record
Abstract
Abstract INTRODUCTION Leptomeningeal metastatic disease (LMD) is an increasingly well-recognized cause of cancer-related morbidity and mortality. While healthcare costs associated with brain metastases (BMs) have been well-described, minimal economic literature exists for LMD. This study sought to evaluate inpatient care costs (IPCCs) and reimbursements for LMD patients using a contemporary US-based claims database. METHODS This retrospective study, reported following STROBE guidelines, included adult LMD patients (aged 18-65 years) receiving inpatient care during January 2016 to December 2021 in MarketScan Commercial Claims and Encounters Database, currently the largest US-based commercial insurance database. Patient selection using ICD-10 codes, data management, and statistical analyses were performed in Stata/SE18.0. Demographic, clinical, and financial attributes were summarized through descriptive statistics. IPCC measures were adjusted using 2023 Consumer Price Index Medical Care component. Primary study outcome was adjusted gross total payments (total IPCC). Given skewness in IPCC, log-transformation was carried out, followed by multivariable linear regression using socio-demographic, clinical and insurance-related characteristics to identify significant covariates. RESULTS Total 1047 inpatient admissions across 1010 LMD patients were included. 43.8% (N=442) had brain metastases (BM) concomitantly present while 56.2% (N=568) did not. 54.8% (N=554) did not have any bone metastases and 78.6% (N=794) did not have any liver metastases. Per inpatient admission, median adjusted values of gross total payments were $32603.6 (IQR $19967-64960) and gross payments to principal physician $1119.26 (IQR $532.41-2919.78), being 3.4% of total payments. Covariates associated with significantly higher total IPCC included age, male sex, length -of-stay, whole brain radiotherapy, and admission year, while cancer from lung and melanoma, medical and psychiatric admission (versus surgical), and drug claims capture were associated with significantly lower IPCC. CONCLUSIONS Contemporary IPCCs for LMD patients in US are substantial but driven minimally by payments to principal physician, which has implications for current efforts to reduce costs of care.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".