Real-world efficacy and toxicity of ipilimumab and nivolumab as first line treatment of metastatic renal cell carcinoma (mRCC) in a subpopulation of elderly and poor performance status patients.
Bibliographic record
Abstract
367 Background: Ipilimumab and nivolumab (ipi/nivo) improved overall survival (OS) and response rates compared to sunitinib in the pivotal Checkmate 214 trial of intermediate/poor risk mRCC. A subgroup analysis showed no significant difference in OS for ipi/nivo in pts 65 to 75 years old (yo), as well as pts >75 yo. In another subgroup analysis, Karnofsky performance status (KPS) <70 was associated with worse median OS compared with pts with KPS ≥ 70. We evaluated efficacy and toxicity of ipi/nivo in an older and frailer population in a real-world cohort. Methods: Analysis was conducted on a real-world cohort with mRCC (N=378) treated with ipi/nivo as first line treatment from the Canadian Kidney Cancer Information System (CKCis) database from January 2011 to March 2022. Median follow-up was 14.3 m (range 0 to 87.6). A comparison was made between outcomes and toxicity in pts ≥ versus (vs) <70 yo, ≥ vs <75 yo, KPS < vs ≥70, and ≥70 yo with KPS <70 vs <70 yo with KPS >70. Toxicity was graded as per CTCAE v4.03 or any toxicity that resulted in a dose/schedule change. OS, progression free survival (PFS) and time to treatment failure (TTF) were calculated by Kaplan-Meier analysis. Log rank tests were used for comparison between groups. Multivariate analysis was done including IMDC for all outcomes. Results: Median OS was worse in older patients at 30.0 m in pts ≥ 70 yo vs 45.4 m in pts < 70 yo (p=0.060), and 19.0 m in the pts ≥ 75 yo vs 45.5 m in pts < 75 yo (p=0.003) despite similar disease control rates and toxicity. Median PFS was similar in younger and older pts: < vs ≥ 70 yo (p=0.560) and < vs ≥ 75 yo (p=0.296). Median TTF was comparable in < 70 yo and ≥ 70 yo (p=0.106) and < 75 and ≥ 75 yo groups (p-value=0.733). Median OS, PFS and TTF were comparable in pts KPS < 70 vs pts KPS ≥ 70 and in pts ≥70 yo with KPS < 70 vs pts < 70 yo with KPS >70. Adjusted and unadjusted analysis showed no difference in OS and PFS between groups. Conclusions: Use of ipi/nivo in mRCC in older patients was associated with inferior OS, while decreased performance status had equivalent OS. Both groups had equivalent TTF and PD without higher toxicity. We believe that ipi/nivo is a reasonable treatment option for older and low performance status patients. [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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".