Predictors of objective response to first-line immuno-oncology combination therapies in metastatic renal cell carcinoma: Results from the international metastatic renal cell database consortium (IMDC).
Bibliographic record
Abstract
310 Background: Predictors of objective response to first-line (1L) immuno-oncology (IO) combination therapies remain elusive. We sought to characterise clinical variables and their association with investigator assessed best overall response. Methods: Using the IMDC, we retrospectively identified patients treated with 1L ipilimumab nivolumab (IPI-NIVO) or approved IO/vascular endothelial growth factor (VEGF) inhibitor combinations (IOVE). Patients were classified, per RECIST v1.1, as responders (complete or partial response (CR or PR)) or non-responders (stable or progressive disease (SD or PD)). Logistic regression was used to adjust for IMDC criteria. Results: Out of 1084 patients, 794 (73%) received IPI-NIVO and 290 (27%) received IOVE (axitinib+pembrolizumab, cabozantinib+nivolumab, axitinib+avelumab, lenvatinib+pembrolizumab). Favourable, intermediate and poor IMDC risk comprised 147 (16%), 517 (55%) and 272 (29%) respectively. Of the 898 patients with evaluable responses, 37 (4%) achieved a best response of CR, 343 (38%) PR, 315 (35%) SD and 203 (23%) PD. Corresponding median overall survival from time of 1L initiation was: not reached, 55.9, 48.1, and 13 months respectively (logrank p < 0.0001). In a multivariable model, lung metastases and cytoreductive nephrectomy (CN) (performed after diagnosis of metastatic disease and before 1L therapy) retained independent association with response, after adjustment for IMDC criteria. Factors not associated with response included (with univariable p values): gender (p = 0.58), age (p = 0.06), sarcomatoid histology (p = 0.99), smoking status (p = 0.39), liver (p = 0.63) and brain (p = 0.12) metastases. As in the VEGF monotherapy era, improved IMDC prognostic risk was associated with response. Results were similar when restricted to the IPI-NIVO cohort. Conclusions: Presence of lung metastases, CN and better IMDC risk group are associated with a higher probability of response to 1L immunotherapy combination regimens. Further work to identify reliable predictors of response to guide treatment selection and patient counselling is warranted.[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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".