Finding studies
Finding studies
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Lead
United States Naval Medical Center, San Diego
With
The NCI Division of Cancer Prevention has recognized AIMSS as a priority area for future study. The symptoms are associated with a high rate of AI discontinuation and therefore compromise survival outcomes at great cost to both patients and society. Very little is known about AIMSS, or how to predict who is at risk for the condition, or for discontinuing therapy because of the symptoms. This study will provide a basis for comprehensive assessment of risk factors at the patient-reported outcomes, phenotypic, and laboratory levels. We will explore the natural history of AIMSS in different ethnic populations, and will validate previously reported genetic determinants of the development of AIMSS. A common problem with multicenter GWAS studies of very large sample size, especially in the absence of measurable diagnostic parameters, is inclusion of heterogeneous groups of patients. In addition to assessing pharmacogenomic predictors, this study involves specification of a pre-defined AIMSS phenotype and collection of patient-reported outcomes (PROs). As such, these data will have clinical utility by clarifying the factors associated with aromatase inhibitor discontinuation and thus guiding clinicians towards interventions to improve adherence. Coupled with other studies, the long-term goals are to develop a gene signature that will be used to better guide the selection of endocrine interventions for patients with breast cancer. The underlying physiology of AIMSS remains obscure. A small exploratory case control study did not find a role for commonly encountered cytokines in AIMSS. The role of estrogen and estrogen metabolites remains a possible explanatory variable, as well as new cytokines such as IL-17. This newly described cytokine has been implicated in disorders such as rheumatoid arthritis and other autoimmune diseases, and has been specifically linked to articular nociception in animal models of arthritis. AIMSS Phenotype: The large studies to date of AIs (ATAC, BIG I-98, E1Z03) have been limited by the absence of a clearly defined phenotype for AIMSS. Retrospective analyses have provided some information that clearly cannot replace (PROs). The lack of good prospective PROs represents a major gap as a well-defined phenotype is necessary in order to identify useful genomic associations. Methods evaluating possible predictors such as the use of MRI of the wrists for tenosynovitis are expensive and have not been definitive, and patient-reported symptoms are used and may represent the most useful clinical phenotype.
Age
18–60
Sex
FEMALE
Healthy volunteers
Not accepted
