Abstract CT124: Sitravatinib and nivolumab in oral cavity cancer window of opportunity study (SNOW)
Bibliographic record
Abstract
Abstract Background: Squamous cell carcinoma of the oral cavity (SCCOC) often presents at early stages but its prognosis remains guarded, with a 5-year survival rate of 60% despite curative-intent therapies. Preoperative window-of-opportunity (WOO) studies in resectable SCCOC enable pharmacodynamic evaluation of molecular endpoints without compromising curative-intent treatment. Preoperative nivolumab in SCCOC was safe and showed promising tumor responses in CheckMate-358 WOO study (Ferris et al. ESMO 2017, LBA46). Sitravatinib, a receptor tyrosine kinase inhibitor which potently inhibits Tyro, AXL, Mer, and VEGF family of receptors, has shown encouraging results when combined with nivolumab in non-small cell lung cancer patients who have progressed on anti-PD-1 agents (Leal et al. ESMO 2018, 1129O). We hypothesize that sitravatinib and nivolumab have synergistic antitumor and immunogenic effects by increasing tumor immune infiltration and by blocking oncogenic pathways implicated in disease progression and immune-checkpoint resistance. Methods: Trial design: SNOW is a single-center, non-randomized WOO study of preoperative sitravatinib and nivolumab in patients with resectable SCCOC. Sitravatinib 120 mg is given orally once daily from day 1 until 48h before surgery or for a maximum period of 28 days. Nivolumab 240mg is given intravenously on day 15 for one dose only. Surgery is planned between days 23-30 following study treatment initiation. Fresh tumor biopsies and serial blood samples for extensive immunophenotyping and evaluation of other pharmacodynamic biomarkers, as well as clinical photographs of the tumor, are collected at baseline, on day 15 prior to nivolumab and at the time of surgery. 18FAZA-PET scans are performed at baseline and before surgery. Key eligibility criteria: previously untreated and resectable SCCOC; T2-4a, N0-2 or T1 (greater than 1 cm)-N2; no history of tumor bleeding or invasion of major vessels; adequate organ function; no autoimmune disorders; no immunosuppressive therapy. Study objectives: primary objective is to evaluate the immune and pharmacodynamic effects of sitravatinib plus nivolumab. Secondary objectives are: safety and tolerability including toxicity, rate of surgery completion within the planned window and rate of postoperative complications; antitumor activity including rate of complete pathological response; pharmacokinetics of sitravatinib alone and in combination with nivolumab. Correlative studies: tumor and blood immunophenotyping, tumor genome and transcriptome analysis, changes in intratumoral hypoxia based on 18FAZA-PET testing. Sample size: SNOW is a proof-of-concept study with no specific statistical assumptions at trial onset. We plan to enroll 12-15 patients evaluable for correlative studies. Study activation: Aug 30th, 2018. Two patients enrolled as of Jan 10th2019. Clinical trial identification: NCT03575598. Citation Format: Marc Oliva Bernal, Douglas Chepeha, Amy Prawira, Douglass Vines, Anna Spreafico, Scott Bratman, John De Almeida, Aaron Hansen, David Goldstein, Ralph Gilbert, Patrick Gullane, Dale H. Brown, Ilan Weinreb, Bayardo Perez-Ordoñez, Pamela S. Ohashi, Tracy McGaha, Ben X. Wang, Jonathan Irish, Isan Chen, Lillian L. Siu. Sitravatinib and nivolumab in oral cavity cancer window of opportunity study (SNOW) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT124.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".