Conditional survival (CS) for patients with metastatic renal cell carcinoma (mRCC) treated with vascular endothelial growth factor (VEGF)-targeted therapy (TT): Results from the International mRCC Database Consortium.
Bibliographic record
Abstract
358 Background: Survival estimates for patients with mRCC are traditionally reported from the time of TT initiation. These survival projections, however, may not be applicable to patients who have already survived a period of time after initiating therapy. CS accounts for elapsed time since starting therapy, providing more relevant prognostic information. Methods: Data on 1673 patients treated with first-line VEGF TT between 4/7/2003 and 10/12/2010 was analyzed. Median follow up for patients still alive is 20.1 months. Conditioned survival was calculated on the set of patients alive or on TT at 3 months and using 3 months increments for up to 18 months. Results: The 2-year CS probability tends to slightly improve from 44 to 51% when conditioned on having already survived 0 to18 months since initiation of TT, respectively. The Heng et al (JCO 2009) risk criteria (defined at therapy initiation) retains prognostic ability over time independent of previous survival time or previous time on TT up to 18 months (p<0.0001 for all comparisons). In the subgroup analysis stratified by Heng risk groups, 2-year CS minimally changes over time in the favorable (FAV) and in the intermediate (INT) groups, but in the poor risk group, the 2-year CS improves from 11% initially to 33% after 18 months. When conditioned on time on TT, 2-year CS improves from 44% to 68% overall, from 74% to 90% in the FAV risk group, 49% to 57% in the INT risk group and 11% to 73% in the poor-risk group. Conclusions: Conditional survival may be a more relevant measure of prognosis for those who have already survived or have been on TT for a period of time. The largest improvement was seen in patients in the poor risk group. [Table: see text]
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".