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. 2016 Feb 20;34(6):566-71.
doi: 10.1200/JCO.2015.63.6266. Epub 2015 Dec 7.

Androgen Deprivation Therapy and Future Alzheimer's Disease Risk

Affiliations

Androgen Deprivation Therapy and Future Alzheimer's Disease Risk

Kevin T Nead et al. J Clin Oncol. .

Abstract

Purpose: To test the association of androgen deprivation therapy (ADT) in the treatment of prostate cancer with subsequent Alzheimer's disease risk.

Methods: We used a previously validated and implemented text-processing pipeline to analyze electronic medical record data in a retrospective cohort of patients at Stanford University and Mt. Sinai hospitals. Specifically, we extracted International Classification of Diseases-9th revision diagnosis and Current Procedural Terminology codes, medication lists, and positive-present mentions of drug and disease concepts from all clinical notes. We then tested the effect of ADT on risk of Alzheimer's disease using 1:5 propensity score-matched and traditional multivariable-adjusted Cox proportional hazards models. The duration of ADT use was also tested for association with Alzheimer's disease risk.

Results: There were 16,888 individuals with prostate cancer meeting all inclusion and exclusion criteria, with 2,397 (14.2%) receiving ADT during a median follow-up period of 2.7 years (interquartile range, 1.0-5.4 years). Propensity score-matched analysis (hazard ratio, 1.88; 95% CI, 1.10 to 3.20; P = .021) and traditional multivariable-adjusted Cox regression analysis (hazard ratio, 1.66; 95% CI, 1.05 to 2.64; P = .031) both supported a statistically significant association between ADT use and Alzheimer's disease risk. We also observed a statistically significant increased risk of Alzheimer's disease with increasing duration of ADT (P = .016).

Conclusion: Our results support an association between the use of ADT in the treatment of prostate cancer and an increased risk of Alzheimer's disease in a general population cohort. This study demonstrates the utility of novel methods to analyze electronic medical record data to generate practice-based evidence.

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Conflict of interest statement

Authors’ disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article.

Figures

Fig 1.
Fig 1.
Flow diagram of cohort selection. AD, Alzheimer’s disease; ADT, androgen deprivation therapy.
Fig 2.
Fig 2.
Kaplan-Meier curves according to androgen deprivation therapy (ADT) use for the cumulative probability of remaining Alzheimer’s disease–free (y-axis) from the initiation of ADT, for ADT users, or from the time of prostate cancer diagnosis plus the median time to ADT use, for non-ADT users (x-axis), in the full (A) and propensity score–matched (B) cohorts. AD, Alzheimer’s disease; ADT, androgen deprivation therapy.
Fig A1.
Fig A1.
Three steps of the text processing workflow: (1) A custom dictionary derived from BioPortal ontologies and supplemented with trigger terms from NegEx and ConText is used to index (recognize) disease and drug term mentions in narratives as well as recognize contextual cues such as negation or family history. Patient and temporal meta-data are also indexed in this step. The output of this step is indexed positive present mentions of drugs and conditions. (2) Specification of the definition for events (indications and outcomes) and drugs of interest along with normalization schemes for grouping and aggregating terms by synonymy or class. (3) Using the temporal information, the aggregated event and drug mentions, and contextual filters to create a patient-feature matrix and construct patient cohorts for further statistical analysis. Using the temporal information is crucial; for example, a case in which mentions of a drug temporally follows an outcome is used differently in the downstream analysis than a case where a drug precedes the outcome. NCBO, National Center for Biomedical Ontology.

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