Unknown

Dataset Information

0

A phase II study of liposomal irinotecan with 5-fluorouracil, leucovorin and oxaliplatin in patients with resectable pancreatic cancer: the nITRO trial.


ABSTRACT:

Background

Up-front surgery followed by postoperative chemotherapy remains the standard paradigm for the treatment of patients with resectable pancreatic cancer. However, the risk for positive surgical margins, the poor recovery after surgery that often impairs postoperative treatment, and the common metastatic relapse limit the overall clinical outcomes achieved with this strategy. Polychemotherapeutic combinations are valid options for postoperative treatment in patients with good performance status. liposomal irinotecan (Nal-IRI) is a novel nanoliposome formulation of irinotecan that accumulates in tumor-associated macrophages improving the therapeutic index of irinotecan and has been approved for the treatment of patients with metastatic pancreatic cancer after progression under gemcitabine-based therapy. Thus, it remains of the outmost urgency to investigate introduction of the most novel agents, such as nal-IRI, in perioperative approaches aimed at increasing the long-term effectiveness of surgery.

Methods

The nITRO trial is a phase II, single-arm, open-label study to assess the safety and the activity of nal-IRI with fluorouracil/leucovorin (5-FU/LV) and oxaliplatin in the perioperative treatment of patients with resectable pancreatic cancer. The primary tumor must be resectable with no involvement of the major arteries and no involvement or <180° interface between tumor and vessel wall of the major veins. A total of 72 patients will be enrolled to receive a perioperative treatment of three cycles before and three cycles after surgical resection with nal-IRI 50?mg/m2, oxaliplatin 60?mg/m2, leucovorin 200?mg/m2, and 5-fluorouracil 2400?mg/m2, days 1 and 15 of a 28-day cycle. The primary objective is to improve from 40% to 55% the proportion of patients achieving R0 resection after preoperative treatment.

Discussion

The nITRO trial will contribute to strengthen the clinical evidence supporting perioperative strategies in resectable pancreatic cancer patients. Moreover, this study represents a unique opportunity for translational analyses aimed to identify novel immune-related prognostic and predictive factors in this setting.

Trial registration

Clinicaltrial.gov: NCT03528785. Trial registration data: 1 January 2018Protocol number: CRC 2017_01EudraCT Number: 2017-000345-46.

SUBMITTER: Simionato F 

PROVIDER: S-EPMC7745557 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

altmetric image

Publications

A phase II study of liposomal irinotecan with 5-fluorouracil, leucovorin and oxaliplatin in patients with resectable pancreatic cancer: the nITRO trial.

Simionato Francesca F   Zecchetto Camilla C   Merz Valeria V   Cavaliere Alessandro A   Casalino Simona S   Gaule Marina M   D'Onofrio Mirko M   Malleo Giuseppe G   Landoni Luca L   Esposito Alessandro A   Marchegiani Giovanni G   Casetti Luca L   Tuveri Massimiliano M   Paiella Salvatore S   Scopelliti Filippo F   Giardino Alessandro A   Frigerio Isabella I   Regi Paolo P   Capelli Paola P   Gobbo Stefano S   Gabbrielli Armando A   Bernardoni Laura L   Fedele Vita V   Rossi Irene I   Piazzola Cristiana C   Giacomazzi Serena S   Pasquato Martina M   Gianfortone Morena M   Milleri Stefano S   Milella Michele M   Butturini Giovanni G   Salvia Roberto R   Bassi Claudio C   Melisi Davide D  

Therapeutic advances in medical oncology 20200904


<h4>Background</h4>Up-front surgery followed by postoperative chemotherapy remains the standard paradigm for the treatment of patients with resectable pancreatic cancer. However, the risk for positive surgical margins, the poor recovery after surgery that often impairs postoperative treatment, and the common metastatic relapse limit the overall clinical outcomes achieved with this strategy. Polychemotherapeutic combinations are valid options for postoperative treatment in patients with good perf  ...[more]

Similar Datasets