Efficacy of Second-line Targeted Therapy for Renal Cell Carcinoma According to Change from Baseline in International Metastatic Renal Cell Carcinoma Database Consortium Prognostic Category
Bibliographic record
Abstract
BACKGROUND: We hypothesized that changes in International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) prognostic category at start of second-line therapy (2L) for metastatic renal cell carcinoma (mRCC) might predict response. OBJECTIVE: To assess outcomes of 2L according to type of therapy and change in IMDC prognostic category. DESIGN, SETTING, AND PARTICIPANTS: We performed a retrospective review of the IMDC database for mRCC patients who received first-line (1L) VEGF inhibitors (VEGFi) and then 2L with VEGFi or mTOR inhibitors (mTORi). IMDC prognostic categories were defined before each line of therapy (favorable, F; intermediate, I; poor, P). Data were analyzed for 1516 patients, of whom 89% had clear cell histology. INTERVENTION: All included patients received targeted therapy for mRCC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Overall survival (OS), time to treatment failure, and response to 2L were analyzed using Cox or logistic regression. RESULTS AND LIMITATIONS: At start of 2L, 60% of patients remained in the same prognostic category; 9.0% improved (3% I → F; 6% P → I); 31% deteriorated (15% F → I or P; 16% I → P). Patients with the same or better IMDC prognostic category had a longer time to treatment failure if they remained on VEGFi compared to those who switched to mTORi (adjusted hazard ratio [AHR] ranging from 0.33 to 0.78, adjusted p<0.05). Patients who deteriorated from F to I appeared more likely to benefit from switching to mTORi (median OS 16.5 mo, 95% confidence interval [CI] 12.0-19.0 for VEGFi; 20.2 mo, 95% CI 14.3-26.1 for mTORi; AHR 1.53, 95% CI 1.04-2.24; adjusted p=0.03). CONCLUSIONS: Changes in IMDC prognostic category predict the subsequent clinical course for patients with mRCC and provide a rational basis for selection of subsequent therapy. PATIENT SUMMARY: The pattern of treatment failure might help to predict what the next treatment should be for patients with metastatic renal cell carcinoma.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".