A population-based study evaluating metastatic renal cell cancer (mRCC) patients treated with interferon (IFN) alone, first-line IFN then second-line sunitinib, or sunitinib alone
Bibliographic record
Abstract
15572 Background: Previously, immunotherapy agents such as IFN were the only treatments available for mRCC. Sunitinib has demonstrated prolonged progression free survival in a phase III trial but overall survival benefit has yet to be determined and few patients (pts) with poor MSKCC prognostic profiles were included. Methods: The province-wide BC Cancer Agency Registry was cross-referenced to the central pharmacy database to identify all pts with the diagnosis of mRCC who were treated with IFN and/or sunitinib. Sunitinib became available after October 2005 under an expanded access program or as standard treatment. Three groups of pts were identified: Group A consisted of pts who received IFN alone between January 2003 to October 2005, Group B was all pts who progressed on first-line IFN after October 2005 and subsequently were treated with second-line sunitinib and Group C was all pts treated with first-line sunitinib. Baseline characteristics and overall survival were collected on all patients. Results: A total of 75 patients were identified with 36 patients in Group A, 23 patients in Group B, and 16 patients in Group C. Data are reported from the initiation of IFN in Group A and the initiation of sunitinib in Groups B and C. Median follow-up was 6.0 months in group A, 7.6 months in group B, and 6.2 months in group C. Median age of treatment initiation (62y vs. 60y vs. 62y), number of metastatic sites (>1 site in 63% vs. 61% vs. 56%), and Karnofsky performance status (79 vs. 86 vs. 81) were similar between groups A, B and C, respectively. The MSKCC prognostic profiles were favorable, intermediate and poor in 26%, 51% and 23% in group A, 17%, 65% and 17% in group B and 31%, 38% and 31% in group C, respectively. The estimated 6-month overall survival in groups A, B and C was 56%, 72% and 100%, respectively (log rank A vs C p=0.009; log rank B vs C p=0.042). Conclusion: With the limitations of retrospective analysis and preliminary follow-up, the introduction of sunitinib as standard treatment into the general population of patients with mRCC appears to be associated with a longer overall survival compared to patients treated with IFN alone. Population-based analysis on the impact of the introduction of sunitinib therapy is ongoing. No significant financial relationships to disclose.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".