Background
20–60% of patients with initially locally advanced Renal Cell Carcinoma (RCC) develop metastatic disease despite optimal surgical excision. Adjuvant strategies have been tested in RCC including cytokines, radiotherapy, hormones and oral tyrosine-kinase inhibitors (TKIs), with limited success. The predominant global standard-of-care after nephrectomy remains active monitoring. Immune checkpoint inhibitors (ICIs) are effective in the treatment of metastatic RCC; RAMPART will investigate these agents in the adjuvant setting.
Methods/design
RAMPART is an international, UK-led trial investigating the addition of ICIs after nephrectomy in patients with resected locally advanced RCC. RAMPART is a multi-arm multi-stage (MAMS) platform trial, upon which additional research questions may be addressed over time. The target population is patients with histologically proven resected locally advanced RCC (clear cell and non-clear cell histological subtypes), with no residual macroscopic disease, who are at high or intermediate risk of relapse (Leibovich score 3–11). Patients with fully resected synchronous ipsilateral adrenal metastases are included. Participants are randomly assigned (3,2:2) to Arm A - active monitoring (no placebo) for one year, Arm B - durvalumab (PD-L1 inhibitor) 4-weekly for one year; or Arm C - combination therapy with durvalumab 4-weekly for one year plus two doses of tremelimumab (CTLA-4 inhibitor) at day 1 of the first two 4-weekly cycles. The co-primary outcomes are disease-free-survival (DFS) and overall survival (OS). Secondary outcomes include safety, metastasis-free survival, RCC specific survival, quality of life, and patient and clinician preferences. Tumour tissue, plasma and urine are collected for molecular analysis (TransRAMPART).
Trial registration
ISRCTN #: ISRCTN53348826, NCT #:
NCT03288532
, EUDRACT #: 2017–002329-39, CTA #: 20363/0380/001–0001, MREC #: 17/LO/1875,
ClinicalTrials.gov
Identifier:
NCT03288532
, RAMPART grant number: MC_UU_12023/25, TransRAMPART grant number: A28690 Cancer Research UK, RAMPART Protocol version 5.0.
We present the design and evaluation of an architecture for collision avoidance and escape of mobile autonomous robots operating in unstructured environments. The approach mixes both reactive and deliberative components. This provides the vehicle's behaviour designers with an explicit means to design-in avoidance strategies that match system requirements in concepts of operations and for robot certification. The now traditional three layer architecture is extended to include a fourth Scenario layer, where scripts describing specific responses are selected and parameterised on the fly. A local map is maintained using available sensor data, and adjacent objects are combined as they are observed. This has been observed to create safer trajectories. Objects have persistence and fade if not re-observed over time. In common with behaviour based approaches, a reactive layer is maintained containing pre-defined knee jerk responses for extreme situations. The reactive layer can inhibit outputs from above. Path planning of updated goal point outputs from the Scenario layer is performed using a fast marching method made more efficient through lifelong planning techniques. The architecture is applied to applications with Autonomous Underwater Vehicles. Both simulated and open water tests are carried out to establish the performance and usefulness of the approach.
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