Abstract
Dementia and cancer are multifactorial, widely-feared, age-associated clinical syndromes that are increasing in prevalence. There have been major breakthroughs in clinical cancer research leading to some effective treatments, whereas the field of dementia has achieved comparatively limited success in clinical research. The lessons of cancer research may help those in the dementia research field in confronting some of the dilemmas faced when the clinical care regimen is not entirely safe or efficacious. Cancer clinical trials have assumed that untreated individuals with cancer are at high risk for morbidity and mortality after primary diagnoses. Thus, patients deserve a choice of clinical interventions, either standard of care or experimental, even if the benefits are not certain and the therapy’s side effects are potentially severe. The prognosis for many individuals at risk for dementia carries a correspondingly high level of risk for both mortality and severe morbidity, particularly if one focuses on “health-span” rather than lifespan. Caregivers and patients can be strongly impacted by dementia and the many troubling associated symptoms that often go well beyond amnesia. Polls, surveys, and a literature on “dementia worry” strongly underscore that the public fears dementia. While there are institutional and industry hurdles that complicate enrollment in randomized trials, the gravity of the future morbidity and mortality inherent in a dementia diagnosis may require reconsideration of the current protective stance that limits the freedom of at-risk individuals (either symptomatic or asymptomatic) to participate and potentially benefit from ongoing clinical research. There is also evidence from both cancer and dementia research that individuals enrolled in the placebo arms of clinical trials have unexpectedly good outcomes, indicating that participation in clinical trial can have medical benefits to enrollees. To highlight aspects of cancer clinical research that may inform present and future dementia clinical research, this review highlights three main themes: the risk of side effects should be weighed against the often dire consequences of non-treatment; the desirability of long-term incremental (rather than “magic bullet”) clinical advances; and, the eventual importance of combination therapies, reflecting that the dementia clinical syndrome has many underlying biological pathways.
Document Type
Article
Publication Date
2024
Digital Object Identifier (DOI)
https://doi.org/10.1186/s13195-024-01532-6
Funding Information
Funding for this project derived from NIA/NIH grants P30 AG072946, R01 AG061111, RF1 NS118584, R01 AG057187.
Repository Citation
Jicha, Gregory; Tucker, Thomas; Arnold, Susanne; and Nelson, Peter T., "Cancer research provides a model for advancing clinical trials in dementia in the era of disease-modifying Alzheimer’s-type dementia therapies" (2024). Neurology Faculty Publications. 94.
https://uknowledge.uky.edu/neurology_facpub/94
Notes/Citation Information
© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom- mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.