Apparently, the duration and costs of clinical trials of new oncological drugs could be reduced if surrogate measures, such as tumour reduction or time to progression, were to be used instead of survival, but a meta-analysis of 146 clinical trials of colorectal cancer and 191 of lung cancer found that only 10-16% of survival was explained by these variables; obviously a poor correlation. On the other hand, there is the question of the methodology used. A review of 43 studies found that, in 81% of the cases, promising results from phase II (without a control group) failed to transfer to phase III (double-blind randomized trial). The latter is another finding unfavourable to the rush with which many oncological drugs are introduced in the market. Perhaps it’s for this reason that, in an observation of 94 articles on the subject, Abola and Prasad have discovered that in half of them, the editors had resorted to adjectives of the type: miraculous, revolutionary, innovative, wonderful, transformative, etc...
People affected by rare cancers claim the benefit of the surrogate measures and the validity of phase II for the approval of the new drugs, since it’s impossible for their doctors to get enough cases to deploy survival studies on phase III. The reason they defend this is of course quite dramatic: they dare running out of time! Under this pressure, the regulatory agencies are pushed to approve new products that are known to have achieved hopeful anatomy-pathological changes or revolutionary reductions of tumour markers, but with few clues about toxicity, impairment of quality of life, or most logically, survival.
Victor Montori describes this phenomenon as little science, in the sense that today in the majority of university centres the investigation that they are carried out is incapable of making valid proposals for these situations. As an example of the scope of the problem, an evaluation shows that most of the oncological medicines approved by the European Medicines Agency between 2009-2013 were approved without sufficient evidence, and in the few cases that were available, their effects were marginal if compared with existing treatments.
For some, big data should be a solution for therapeutic advances of rare diseases or rare cancers, given that it should enable analysis of huge amounts of data that would make the number of cases, which are insufficient at the local level, remarkable, from a global view. Despite having an attractive methodological approach, big data is having problems due to the poor quality of the clinical databases, which limits its uses, especially in therapeutic evaluations and causality analysis. As Montori says: too often the big data is simply not great data.
Vinay Prasad says that people with rare cancers, or rare diseases, also deserve quality research, i.e. clinical trials in phase III, and therefore it’s necessary for science to give a cooperative rather than competitive response. He himself gives an example that confirms that this is possible. Adrenocortical cancer has a very low incidence, poor response to treatments and poor prognosis. Despite this, FIRM-ACT managed to develop a clinical trial collecting 304 patients from 40 hospitals in 12 different countries. Thanks to this initiative, for the first time several cytotoxic therapies could be solidly tested, with survival as a measure of the results.
To favour big science over little science, Montori continues, institutions should reward generous and collaborative scientists who promote shared projects among different research and clinical practice communities. Take another example of the importance of this vision: the article that explains the discovery of the Higgs Boson involved 5,154 scientists. Does anyone think that the discovery would have been achieved without having gathered so much knowledge?
Patients with rare cancers should ask the researchers to collaborate as much as necessary to develop robust, well-designed clinical trials, rather than the hasty and enthusiastic studies they currently offer.