With the shift towards personalised medicine in oncology, cancer patients may be better served by smaller, faster clinical trials that impose less stringent criteria for evidence of safety and effectiveness, a new analysis suggests.
As improved knowledge of tumour biology allows for targeting of new cancer therapies to narrower subsets of patients, the traditional large-scale clinical trial model is a disincentive to pursuing the full range of therapeutic options, especially with rarer diseases, argues a research team led by Dr Marie-Cécile Le Deley, associate professor of clinical epidemiology and biostatistics at France’s Institut Gustave-Roussy in Villejuif.
“Considering that many new targeted agents have fewer safety issues than the older cytotoxic treatments, we feel that the risk of accepting a few therapies that offer no benefit, but with a very low chance of a truly poorer outcome, for a greater long-term benefit at the end seems reasonable,” Le Deley commented.
“The classical, large sample-size clinical trials are designed to avoid wrong decisions, but take a very long time to reach a definitive result when the disease is rare,” she added.
Le Deley presented the results of research conducted with US colleagues at The Mayo Clinic in Rochester, Minnesota to the 2011 European Multidisciplinary Cancer Congress, held by the European CanCer Organisation (ECCO), the European Society for Medical Oncology (ESMO) and the European Society for Therapeutic Radiology and Oncology in Stockholm, Sweden.
The researchers applied different design parameters to simulations of two-treatment superiority trials (i.e., a new treatment versus existing standard therapy) conducted over a 15-year period.
Estimating the survival improvements that could be expected from these different models, they found there were “important” gains associated with running more trials using smaller sample sizes and with less rigorous evidential criteria than in conventional trial designs, Le Deley reported.
“The downside of this approach is that we also reduce the certainty of the findings,” she added. On the other hand, “the fact that we will conduct many more trials will allow such errors to be quickly remedied”.
Convincing statisticians and regulators of the need to adjust trial designs to a new era of cancer therapy may be problematic, though, the researchers suggest.
“The culture within these groups is very risk-averse,” Le Deley said. “Their conservative approach is reasonable … But in rare diseases, which could include many small subsets of cancers, this approach is counterproductive as soon as many new agents become available for clinical testing.”
Le Deley made clear that sample sizes should be reduced and decision criteria relaxed only where there is no way of increasing trial accrual rates.
There will still be a need for classical large-scale clinical studies in oncology, she stressed. Where appropriate, though, smaller, more targeted trials could increase the number of studies, generate quicker results and get new therapies to patients in need sooner.
“Our approach of viewing a succession of clinical trials as a whole, as opposed to looking at them trial by trial, may help us to move forward,” Le Deley suggested. “Our work has shown that the current risk-averse trial design strategy is not always appropriate as patient populations become more and more specific, and hence smaller.”
ECCO president Professor Michael Baumann agreed that advances in the science of oncology call for more flexible approaches all round.
“The arrival of personalised medicine means that we will have to change our thinking and ways of doing many things, and trials are just one example of this,” he commented.
“The problems arising from the drafting and implementation of the [EU] Clinical Trials Directive have shown clearly that oncologists need to be looking ahead and planning for impending changes at all times.”