Benchmarking Phase II industry-sponsored pancreatic cancer trials

GlobalData Healthcare 1st November 2019 (Last Updated November 6th, 2019 12:21)

About 56,770 people in the US will be diagnosed with pancreatic cancer in 2019, according to the American Cancer Society.

Benchmarking Phase II industry-sponsored pancreatic cancer trials

Pancreatic cancer is rarely detected in its early stages, as it develops in the pancreas and spreads rapidly to other organs. According to the American Cancer Society, about 56,770 people in the US will be diagnosed with pancreatic cancer in 2019, accounting for about 3% of all cancers. For all stages combined, the five-year relative survival rate is only 9%, and about half of patients are diagnosed at a distant stage where five-year survival is 3%. 

A drug developer for this indication in Phase II should currently expect an 80.97% likelihood of completion and a 0.32% chance of suspension for these trials. Projected median timelines include 20.77 months for enrolment period and 32.43 months for total trial duration. Enrolment goals suggest a median enrolment rate of 0.31 subjects per site per month, seven sites, and 54 subjects, based on previously completed trials in this indication. 

It is also important to examine why trials have failed and to learn from these mistakes. The biggest reasons for trial termination are lack of efficacy (29%), followed by low accrual rate (23%) and business/ strategic decisions (19%), as shown in Figure 1. 

Such a low accrual rate highlights the importance of selecting a suitable country or countries where developers can expect to find an available patient population to run a pancreatic cancer Phase II trial, as well as a study region that is not saturated from other planned or ongoing trials in this indication. 

The selection of sites and investigators with experience and availability to run these trials will also help developers avoid a low accrual rate and subsequent higher cost of development. GlobalData’s Feasibility Planner uses different algorithms to recommend the best geographies, investigators, and sites to help developers make informed decisions when planning these studies.

Figure 1: Reason for study termination