Progression‐free survival as a predictor of overall survival in metastatic renal cell carcinoma treated with contemporary targeted therapy
Bibliographic record
Abstract
BACKGROUND: The majority of metastatic renal cell carcinoma (mRCC) clinical trials that examined targeted agents used progression-free survival (PFS) as the primary endpoint. Whether PFS can be used as a predictor of overall survival (OS) is unknown. METHODS: Patients from 12 cancer centers who received targeted therapy for mRCC were identified. Landmark analyses for progression at 3 months and 6 months after drug initiation were performed to minimize lead-time bias. A proportional hazards model was used to assess the utility of PFS for predicting OS. RESULTS: In total, 1158 patients were included. The median follow-up was 30.6 months, the median age was 60 years, and the median Karnofsky performance status was 80%. For the entire cohort, the median PFS was 7.6 months, and the median OS was 19.7 months. In the landmark analysis, the median OS for patients who progressed at 3 months was 7.8 months compared with 23.6 months for patients who did not progress (log-rank test; P < .0001). Similarly, for patients who progressed at 6 months, the median OS was 8.6 months compared with 26 months for patients who did not progress (P < .0001). Compared with those who did not progress, for the patients who progressed at 3 months and at 6 months, the hazard ratios for death adjusted for adverse prognostic factors were 3.05 (95% confidence interval, 2.42-3.84) and 2.96 (95% confidence interval, 2.39-3.67), respectively. Similar results were demonstrated with landmark analyses at 9 months and at 12 months and in the bootstrap validation. Kendall tau rank correlation and a Fleischer model demonstrated a statistically significant dependent correlation. CONCLUSIONS: PFS at 3 months and at 6 months predicted OS, and the current results indicated that PFS may be a meaningful intermediate endpoint for OS in patients with mRCC who receive treatment with novel agents.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 teacher head, 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".