Real-World Evidence Data on Metastatic Renal-Cell Carcinoma Treatment in Austria: The RELACS Study
Bibliographic record
Abstract
BACKGROUND: Treatment decisions in routine clinical practice are based on reports of clinical trials, which represent highly selected populations. Limited studies reported real-world evidences representing routine clinical practices in patients with renal-cell carcinoma (RCC) in Europe. The aim of this retrospective, noninterventional chart review was to collect data on the treatment landscape for patients with advanced/metastatic RCC in routine clinical practice in a broader patient population in Austria. PATIENTS AND METHODS: Patients with advanced/metastatic RCC receiving systemic treatment between June 2010 and June 2016 across 12 centers in Austria were included. Parameters were entered into an electronic case report form from the participating sites via the application Hermesoft electronic data capture system. Progression-free survival (PFS) and overall survival (OS) were the 2 primary end points. RESULTS: The median PFS and OS were 12 months and 44 months, respectively (first-line PFS was 14 months for pazopanib and 13 months for sunitinib; first-line OS was 44 months for pazopanib and 48 months for sunitinib). Factors influencing the OS were sex, with female patients at a significantly higher risk than male patients (hazard ratio = 1.719), Eastern Cooperative Oncology Group performance status > 0 increased the risk twice (hazard ratio = 2.048), and number of metastases > 3 before the first line doubled the risk compared to metastases (hazard ratio = 2.064). CONCLUSION: OS in this retrospective chart review was considerably longer than the previous reports in real-world patients, underlining the benefit of current RCC treatment options in routine clinical practice.
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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".