A Polypharmacy Model and the Association of Polypharmacy with All-Cause Mortality and Incident Cognitive Impairment in the REGARDS Cohort Pubblico
Cashion, Winn Trevett (2015)
Published
Abstract
Importance: Medications are a cornerstone of medicine. Americans frequently use many medications simultaneously. While medications are tested individually for safety and efficacy, such complex drug regimens may have many unintended effects, including direct drug toxicity, drug-drug interactions, and adverse drug reactions. The phenomenon of taking many drugs simultaneously is known as "polypharmacy." While polypharmacy can be appropriate and the standard of care, it often occurs unnecessarily and exposes the patient to pharmacologic risk.
Objective: This dissertation sought to fill some of the pharmacoepidemiologic knowledge gaps by exploring factors related to polypharmacy and assessing the associations between polypharmacy and 1) all-cause mortality and 2) cognitive impairment using data from the large REGARDS cohort.
Methods: We first transformed the very large REGARDS medication database by assigning generic names, drug classes, and prescription/OTC/supplement status to each manually recorded medication name. We documented the generic name assignments for over 99% of entries using internet queries of Drugs.com and Google. The REGARDS Cohort data (total n= 30,183, comprised of blacks and whites ages ≥45 in the continental U.S.) were used. During an in-home study visit, pill-bottle inspections were conducted of all the medications used in the last two weeks. The cohort member's polypharmacy status was subsequently determined by summing the total number of generic (prescription or OTC) ingredients.
Study 1: A logistic model assessed whether polypharmacy status was associated with demographics, socioeconomic status, lifestyle, comorbidities, and biomarkers.
Study 2: Polypharmacy status (major [≥8 ingredients], minor [6-7 ingredients], none [0-5 ingredients]) was determined by counting the total number of generic (prescription or over-the-counter) ingredients. Cox Proportional Hazards models (using both time-on-study and age-time-scale methods to model time to event) were used to assess the relation of polypharmacy to mortality. Several alternative models were constructed to assess confounding by indication and to consider effect modification by CKD.
Table of Contents
Chapter 1: Introduction and Aims and Hypotheses. 1
1.0: Introduction. 1
1.1: Dissertation Aims and Hypotheses. 1
1.1.1: Study 1. 1
1.1.2: Study 2. 1
1.1.3: Study 3. 2
Chapter 2: Literature Review. 3
2.1: Terminology. 3
2.2: Medication Economics. 5
2.3: Medication Use Culture. 7
2.4: Rationale for Exclusion of Supplements/CAMs from Polypharmacy Definition. 9
2.5: Physiology, Pharmacology, and Polypharmacy. 11
2.6: Geriatric Pharmacoepidemiology and Polypharmacy. 12
2.7: Polypharmacy Prevalence. 13
2.8: Trends in Medication Use. 14
2.9: Suboptimal Medication Use. 14
2.10: Risk factors for Polypharmacy, Drug Interactions, and Potentially Inappropriate Meds. 16
2.10.1: Risk Factors for Polypharmacy. 16
2.10.2: Risk Factors for ADR/ADE. 16
2.10.3: Risk Factors for Drug-Drug Interaction. 17
2.10.4: Risk Factors for Potentially Inappropriate Drug Use. 17
2.11: Risks of Medication Use. 18
2.11.1: Risks of Polypharmacy. 18
2.11.2: Risks of Drug Interactions and Potentially Inappropriate Drugs. 19
2.11.3: Risks of ADRs/ADEs. 19
2.12: Cognitive Impairment. 20
2.12.1: Neurological Risks of Medications. 23
2.13: Chronic Kidney Disease. 24
2.13.1: Chronic Kidney Disease Overview. 24
2.13.2: Chronic Kidney Disease and Medication Use. 26
2.14: Literature Gaps in Knowledge. 27
2.14.1: Study 1 Knowledge Gaps. 27
2.14.2: Study 2 Knowledge Gaps. 27
2.14.3: Study 3 Knowledge Gaps. 28
Chapter 3: Methods. 30
3.1: Description of REGARDS Study. 30
3.2: REGARDS Sample. 33
3.2.1: Sample Size and Medication-Use Assumption for 0.29% of Cohort. 34
3.3: Covariate Data. 34
3.4: Database Construction. 36
3.4.1: Comprehensiveness of Medication Inventory. 42
3.5: Analysis. 42
3.5.1: The Challenge of Confounding by Indication. 42
3.5.2: Use of Propensity Scores to Account for Confounding by Indication. 44
3.6: Statistical Methodologies. 45
3.6.1: Use of Sampling Weights to Estimate National/Regional Med. Use Patterns. 45
3.6.2: Age as the Time-Scale Models. 45
3.6.3: Proportional Hazards Assumption Testing for Study 2. 45
Chapter 4: Results. 47
4.0: Results Introduction. 47
4.0.1: Study Aims and Hypotheses. 47
4.1: Study 1: Geographic Region and Racial Variations in Polypharmacy in the United States. 48
4.1.1: Abstract. 48
4.1.2: Introduction. 50
4.1.3: Methods. 51
4.1.4: Results. 55
4.1.5: Discussion. 57
4.1.6: Conclusions. 61
4.1.7: References. 62
4.1.8: Tables and Figures. 70
4.2: Study 2: The Association between Polypharmacy and Mortality in REGARDS. 74
4.2.1: Abstract. 74
4.2.2: Introduction. 76
4.2.3: Methods. 77
4.2.4: Results. 81
4.2.5: Discussion. 82
4.2.6: Tables and Figures. 87
4.3: Study 3: The Association between Polypharmacy and Cognitive Impairment in REGARDS. 95
4.3.1: Abstract. 95
4.3.2: Introduction. 97
4.3.3: Methods. 98
4.3.4: Results. 103
4.3.5: Discussion. 104
4.3.6: Tables and Figures. 109
Chapter 5: Research Summary, Strengths, Limitations, Public Health Impact, Future Directions. 117
5.1: Research Summary. 117
5.2: Research Strengths. 118
5.3: Research Limitations. 119
5.4: Research Public Health Impact. 120
5.5: Research Conclusions. 123
5.6: Research Future Directions. 124
5.7: References. 127
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