| Literature DB >> 29878624 |
Akira Kawai1,2, Toshio Goto1,3, Tatsuhiro Shibata1,4, Kenzaburo Tani1,5, Shuki Mizutani1,6, Akiyoshi Nishikawa1,7, Taro Shibata1,8, Seiichi Matsumoto1,9, Kyosuke Nagata1,10, Mamoru Narukawa1,11, Shigeyuki Matsui1,12, Masashi Ando1,13, Junya Toguchida1,14, Morito Monden1,15, Toshio Heike1,16, Shinya Kimura1,17, Ryuzo Ueda1,18.
Abstract
This article discusses current obstacles to the rapid development of safe and effective treatments for rare cancers, and considers measures required to overcome these challenges. In order to develop novel clinical options for rare cancers, which tend to remain left out of novel therapeutic development because of their paucity, efficient recruitment of eligible patients, who tend to be widely dispersed across the country and treated at different centers, is necessary. For this purpose, it is important to establish rare cancer registries that are linked with clinical studies, to organize a central pathological diagnosis system and biobanks for rare cancers, and to consolidate patients with rare cancers to facilities that can conduct clinical studies meeting international standards. Establishing an all-Japan cooperative network is essential. Clinical studies of rare cancers have considerable limitations in study design and sample size as a result of paucity of eligible patients and, as a result, the level of confirmation of the efficacy and safety shown by the studies is relatively low. Therefore, measures to alleviate these weaknesses inherent to external conditions need to be explored. It is also important to reform the current research environment in order to develop world-leading treatment for rare cancers, including promotion of basic research, collaboration between industry and academia, and improvement of the infrastructure for clinical studies. Collaboration among a wide range of stakeholders is required to promote the clinical development of treatment for rare cancers under a nationwide consensus.Entities:
Keywords: cancer registry; evaluation method; rare cancer; rare subtype of cancer; therapeutic development
Mesh:
Year: 2018 PMID: 29878624 PMCID: PMC5980298 DOI: 10.1111/cas.13568
Source DB: PubMed Journal: Cancer Sci ISSN: 1347-9032 Impact factor: 6.716
Rare cancers and rare subtypes of cancer
| Rare cancers in the narrow sense | Rare subtypes of cancer | |
|---|---|---|
| Definition | A cancer that has been recognized as an entity anatomically and clinicopathologically, which occurs rarely (approximate morbidity of <6 per 100 000 population). | A rare disease group extracted through identification of a common molecular abnormality from among a cancer type that is anatomically and clinicopathologically recognized as an entity. |
| Disease examples | Soft tissue sarcoma, osteosarcoma, ocular malignancy, small intestinal cancer, neuroendocrine tumor, central nervous system glioma etc. | Rare fractions of lung adenocarcinoma: ALK gene translocation (5%), RET fusion gene (1%), ROS1 gene translocation (1%), and BRAF mutations (1%) etc. |
| Characteristics |
In many cases, the molecular abnormality characterizing each rare cancer type is absent or remains unknown It is difficult to expect that a drug targeting a single molecule would show marked therapeutic efficacy The physician or the department in charge may not always be specialized in cancer treatment In order to improve the quality of clinical practice and promote clinical research, measures including consolidation and networking are considered to be effective |
As each rare subtype has a common molecular abnormality, dramatic therapeutic efficacy can be expected by targeting a single molecule Proof of concept for drug vs efficacy is clear Many of the physicians and departments in charge of the treatment of the underlying cancers are specialized in cancer treatment In order to improve the quality of clinical practice, measures including development of guidelines are considered to be effective |
Study designs applicable for rare cancer clinical trials
| Study design | Outline of the design |
|---|---|
| Umbrella study | A method in which a clinical study platform (umbrella) with genomic analysis for patient selection is constructed, and the patients are assigned to multiple arms (rare fractions) according to actionable driver mutations and receive a matched molecular targeting drug in order to assess them simultaneously. Examples include NCI‐MATCH by the NCI in USA |
| Basket study | A method in which patients with common actionable driver mutations across organs (rare fractions of each organ cancer) are collected to promote the development of a drug corresponding to the relevant genomic abnormality. The aim is to obtain a therapeutic indication across organs based on a specific genomic abnormality. Examples include a clinical study of BRAF inhibitor in cancers with BRAF mutations and a clinical study of an immune checkpoint inhibitor for cancers with abnormalities in DNA repair (microsatellite instability‐positive: MSI‐H or dMMR). |
| N‐of‐1 study | A study in which multiple treatments are applied to 1 patient at different times to compare the effects of these treatments. Although an assessment can be made in a small number of subjects (rare cancers, rare fractions) by comparing the treatments in the same individual (under the same conditions), it has limitations similar to those of a cross‐over study |
| Adaptive design | A study design in which specific factors are changed based on the data obtained during the study, as planned in advance (selection of dose groups, change in the probability of assignment to a specific treatment group, change in the sample size etc.) |
| Bayesian design | An assessment can be carried out with a relatively small number of subjects by introducing a prior distribution that represents biological findings and/or data of previous research to a parameter such as therapeutic efficacy etc. Unlike conventional statistical inference (hypothesis testing and confidence interval by the frequentist approach), consistent inference procedures and criteria on therapeutic efficacy may be applied consecutively across analysis time points (without adjustment for the multiplicity of analysis), based on the posterior distribution combining the prior distribution and study data. It can also be applied to umbrella, basket, or N‐of‐1 studies, as well as those with adaptive designs |
Proposed action goals for promoting clinical development for rare cancers
| Objective | Action goals |
|---|---|
| Acquisition of accurate patient information and establishment of developmental bases |
Construction of an all‐Japan cooperative network Organization of a central pathological diagnosis system and biobank Promotion of rare cancer registries that are linked with clinical studies Consolidation of patients with rare cancers to facilities that can conduct clinical studies meeting international standards |
| Use of biomarkers |
Promotion of clinical studies that use biomarkers (genomic information etc.) Promotion of development of companion diagnostics |
| Environmental considerations for promotion of therapeutic development for rare cancers |
Promotion of basic research for rare cancers Promotion of industrial participation, and industry‐academia collaborative work Establishment of infrastructure for clinical studies of rare cancers including centralization of institutional review board Education and development of clinicians specializing in rare cancers Participation of patient advocates, and discussions involving the whole nation |
| Rearrangement of evaluation methods |
Listing of approaches for various measures to alleviate weakness as a result of external conditions on the study design Provision of ideas to improve the efficacy and efficiency of clinical trial consultation Provision of ideas for the method of collection of post‐marketing safety and efficacy information and systematic confirmation of the results |