UNISON: Nivolumab then ipilimumab + nivolumab in advanced nonclear cell renal cell carcinoma (ANZUP 1602).
Bibliographic record
Abstract
TPS768 Background: Renal cell carcinomas (RCC) are predominantly the clear cell (cc) subtype, with a unique biology, characterized by sensitivity to angiogenesis inhibition. However vascular endothelial growth factor-tyrosine kinase inhibitors elicit modest responses in people with rare variant non-clear cell (ncc) RCC. Immune checkpoint inhibitors (ICI) are active against many cancers, but people with rare variant nccRCC have been excluded from frontline trials despite experiencing a more aggressive disease course and poorer prognosis compared to those with ccRCC. UNISON (NCT03177239) aims to test 2 ideas; the activity of ICI in nccRCC, and the novel sequencing strategy of anti-programmed cell death protein (PD)1 immunotherapy, followed by the combination of anti-PD1 and anti-cytotoxic T-lymphocyte-associated protein (CTLA)4 blockade, in people failed by single agent treatment. Methods: This single-arm, two-part trial recruits people of good performance status suffering metastatic or locally advanced unresectable rare variant nccRCC, including but not limited to papillary (type 1/2), chromophobe, sarcomatoid, Xp11 translocation, collecting duct, and unclassified histological subtypes. Participants are offered fixed dose nivolumab at 240mg every two weeks in Part 1 of the trial. If they experience progressive disease, eligible participants may proceed to Part 2 consisting of nivolumab (3mg/kg) plus ipilimumab (1mg/kg) every 3 weeks for up to 4 doses. People experiencing disease control after single-agent or combined ICI are eligible to continue treatment for up to 1 year. UNISON is powered to distinguish a clinically non-relevant objective tumor response rate (OTRR) of 15% in people taking combination ICI whose cancers are refractory to single-agent PD1, versus a clinically-relevant OTRR of 30% at 5% level of significance with 80% power. 85 participants were recruited in Part 1, on the assumption that 55% of those entering Part 1 will be eligible for inclusion in Part 2. Enrolment commenced in November 2017 and was completed ahead of schedule in September 2019. Of the 48 participants projected to experience progression on anti-PD1 immunotherapy, 36 have so far commenced combination ICI in Part 2. Clinical trial information: NCT03177239.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".