Real-World Retrospective Study of Clinical and Economic Outcomes Among Patients with Locally Advanced or Metastatic Urothelial Carcinoma Treated with First-Line Systemic Anti-Cancer Therapies in the United States: Results from the IMPACT UC-III Study
Bibliographic record
Abstract
This retrospective cohort study evaluated characteristics, treatment patterns, and clinical outcomes in adults with locally advanced/metastatic urothelial carcinoma (la/mUC) receiving first-line (1L) systemic treatment with or without avelumab 1L maintenance (1LM) between January 2020 and July 2023. The index date was the first date with a claim for 1L systemic therapy after a la/mUC diagnosis. Patients with continuous health plan enrollment for ≥6 months before and ≥1 month after the index date were identified from Carelon Research's Healthcare Integrated Research Database. Of 2820 patients receiving 1L treatment, 37.0% received platinum-based chemotherapy (PBC); 39.0%, immuno-oncology (IO) monotherapy; and 24.0%, other therapies. Renal disease and other comorbidities influenced 1L regimen choice. Healthcare resource utilization (HCRU) and costs were reported for patients receiving second-line (2L) treatment. HCRU was high in 32.8% of patients (926 of 2820) who received 2L treatment. Median all-cause direct medical costs per patient per month were USD 15,859, USD 19,781, USD 11,346, and USD 9516 for 1L PBC, 1L PBC + avelumab 1LM, 1L IO monotherapy, and 1L other therapies, respectively. Most direct healthcare costs were attributed to all-cause outpatient visits.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".