PROSPER: A phase III randomized study comparing perioperative nivolumab (nivo) versus observation in patients with localized renal cell carcinoma (RCC) undergoing nephrectomy (ECOG-ACRIN 8143).
Bibliographic record
Abstract
TPS684 Background: The anti-PD-1 antibody nivo improves overall survival in metastatic RCC and is well tolerated. There is no standard adjuvant systemic therapy that increases overall survival (OS) over surgery alone for non-metastatic RCC. Priming the immune system prior to surgery with anti-PD-1 has shown an OS benefit compared to a pure adjuvant approach in mouse solid tumor models. The PROSPER RCC trial aims to improve clinical outcomes by priming the immune system prior to nephrectomy with neoadjuvant nivo and continued engagement with adjuvant blockade in patients with high risk M0 RCC compared to surgery alone. Methods: This global, unblinded, phase 3 National Clinical Trials Network study is currently accruing patients with clinical stage ≥T2 or node positive M0 RCC of any histology. Tumor biopsy prior to randomization is mandatory to ensure RCC and permits in depth correlative science. The investigational arm will receive two doses of nivo 240mg prior to surgery followed by adjuvant nivo for 9 months (q2 wks x 3 mo followed by 480mg q4 wks x 6 mo). The control arm will undergo standard nephrectomy followed by observation. Randomized patients are stratified by clinical T stage, node positivity, and histology. To enhance accrual and patient quality of life, key upcoming amendments are being instituted. These include biopsy only in the nivo arm, allowance of oligometastatic disease and bilateral renal masses that can be fully resected/ablated, and change of nivo dosing to q4 wks (1 neoadj; 9 adj). With accrual of 766 patients, there is 84.2% power to detect a 14.4% absolute benefit in recurrence-free survival (RFS) at 5 years assuming the ASSURE historical control of ~56% to 70% (HR = 0.70). The study is also powered to evaluate a significant increase in overall survival (HR 0.67). Safety, feasibility, and quality of life endpoints critical to adjuvant therapy considerations are incorporated. PROSPER RCC embeds a wealth of translational work aimed at investigating the impact of the baseline immune milieu, the changes induced by neoadjuvant anti-PD-1 priming, and how both correlate with clinical outcomes. Clinical trial information: NCT03055013.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".