PhD Dissertation Powerpoint

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Health & Medicine

Published on March 13, 2014

Author: mehtahemal

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Comparative effectiveness of ACEI and ARB for the risk of dementia in patients with diabetes and hypertension

Hemalkumar B. Mehta, MS PhD Candidate in Pharmaceutical Health Outcomes and Policy Comparative Effectiveness of ACEI and ARB for the Risk of Dementia in Elderly Patients with Diabetes and Hypertension 1

Outline 2 Introduction Objectives Methods Results Conclusions

Why elderly patients with type 2 diabetes and hypertension? Why dementia outcome? Why compare ACEI and ARB? How to properly account for confounding? Introduction 3

HypertensionType 2 Diabetes Two Major Public Health Problems 1 CDC, 2011; 2 Zhang, 2010; 3DIabetes Atlas, 2013; 4Wang, 2004; 5Yoon, 2012; 6Heidenreich, 2011 4 Prevalence • Adults: 60% • Elderly: 88% Cost • $131 billion (2010) • $389 billion (2030) Prevalence • All age: 8.3% • Elderly: 26.9% Cost • $198 billion (2010) • $264 billion (2030)

1 + 1 = 3 7Deedwania, 2005 5 HypertensionType 2 Diabetes Diabetes + Hypertension = “Deadly Duet”

Elderly Patients with “Deadly Duet” Conditions are At High Risk of Dementia 8Plassman, 2007; 9Hendrie, 2007; 10Fillit, 2012; 11Cukierman, 2005 6 96% of dementia patients ≥65 years of age Diabetes patients are twice as likely to develop dementia Hypertension is an independent risk factor for dementia

Burden of Dementia 12Alzheimer's disease facts and figures, 2013 7

Treatment of Patients with Type 2 Diabetes and Hypertension 13ADA, 2011 8 ADA Guideline “Should be with a regimen that includes either an ACEI or an ARB” ACEI: Captopril, enalapril, lisinopril, ramipril ARB: Losartan, valsartan, irbesartan, telmisartan

ACEI, ARB and Cognitive Function 14 9

 ONTARGET clinical trial  ARB (Telmisartan) vs. ACE (Ramipril) - Secondary endpoints  Cognitive impairment: OR = 0.90 (95%CI: 0.80-1.01)  Epidemiological Studies ACEI, ARB and the Risk of Dementia 15 Anderson, 2011; 16 Johnson, 2012; 17Li, 2010; 18 Davies, 2012; 19Yasar, 2013 10 Study Drug treatment HR, 95% CI Johnson et al., 2012 ARB versus non-users 0.78 (0.71–0.85) Li et al., 2010 ARB versus Lisinopril 0.81 (0.68-0.96) Davies et al., 2011 ARB versus other antihypertensive ACEI versus other antihypertensive 0.47 (0.37-0.58) 0.76 (0.69-0.84) Yasar et al., 2013 ARB versus none ACEI versus none ARB versus ACEI 0.31 (0.14-0.68) 0.50 (0.29-0.83) 0.62 (0.27-1.40)

 Baby boomers  By 2050, 88.5 million older Americans (20.2%) of total population  ↑ Incidence of type 2 diabetes and hypertension  Greater risk for dementia  Treatment that can delay dementia onset by few years  Major public health implication  Blood Pressure – time varying confounder affected by previous treatment history  Prior studies did not properly account for it Significance: CER of ACEI and ARB 11

CER of ACEI versus ARB for the Risk of Dementia 12 ACEI ARB

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Controlling Confounding in Observational Studies 14 ACEI ARB C

1. Categorical variables for comorbidities 2. Charlson comorbidity score (CCS) – 1987  Diagnosis based score – 17 diseases  Adaptation in administrative claims data – ICD-9-CM algorithms 3. Chronic disease score (CDS) – 1995  Rx based score – 29 disease categories  Drugs and drug classes - American Hospital Formulary system How to Control for Confounding? 20Charlson, 1987; 21Clark, 1995; 22Austin, 2013 15

Including CCS and CDS Improves Confounding Control 16 ACEI ARB CCS CDS

Including CCS and CDS improves Confounding Control 23Schneeweiss, 2001; 24Mehta, 2013; 25Mehta, 2013; 26Mcgregor, 2006 17

Including CCS and CDS improves Confounding Control 18

Including CCS and CDS improves Confounding Control 19

Including CCS and CDS improves Confounding Control 20

Including CCS and CDS improves Confounding Control 21

Issues with Existing Dementia Specific Risk Indices 27Exalto, 2013; 28Barnes, 2009; 29Barnes, 2010; 30Reitz, 2010; 31Kivipelto, 2006; 32Mehta, 2012; 33Exalto, 2013 22 Issues Use of genetic, MRI or MMSE information Use of lab values – How to deal with missing values No index included Rx medications as risk factors Why two separate indices based on Diagnosis and Prescription drug use Dementia Risk Index Mid-life dementia risk Late-life dementia risk index Brief dementia risk index Summary risk score for Alzheimer’s disease Late-life dementia risk index – GE data Diabetes-specific dementia risk score (DSDRS)

 Why to include two separate variables in the model?  Charlson comorbidity score  Chronic disease score  Why not combine two informations in a single summary score? RxDx risk index  Conditions will be identified from Bright !dea 23 Rx Dx

 First study to combine diagnosis and prescription drug information in one risk index  Easily applicable to claims and EMR data  Diagnosis  Prescription  New tool for confounding control  Useful for identifying patients at risk  Steps can be taken to target modifiable risk factors for dementia Significance: RxDx Risk Index 24

Summary 25 ACEI ARB RxDx Risk Index

Objectives 26 Aim 1 • Develop RxDx risk index to predict dementia in patients with type 2 diabetes mellitus and hypertension Aim 2 • Compare RxDx risk index with Charlson comorbidity index and Chronic disease score to predict dementia Aim 3 • To compare ACE versus ARB for the risk of dementia in patients with type 2 diabetes mellitus and hypertension

Data Source Study Cohort Variables Statistical Analysis Methods 27

 Electronic medical record data, United Kingdom (UK)  Information entered by general practitioner (GPs)  12 million patients - 593 general practices  Anonymized longitudinal clinical and prescribing information  Clinical diagnoses are recorded using medcodes  High validity (Median = 89%)  Prescription information is well documented  Computerized system generates each prescription  Clinically Rich  >450 lab measures Clinical Practice Research Data 34 Williams, 2012; 35Lewis, 2002 28

 Elderly (age ≥ 60 years)  Diagnosed with type 2 diabetes  Diagnosis or (abnormal lab value + oral hypoglycemic agent)  Diagnosed with hypertension  Diagnosis or (abnormal lab value + antihypertensive agent)  Prevalent dementia cases were excluded Study Cohort 29

 Covariates  Age  Gender  Risk indices  Lab measures  Blood pressure  HbA1c  Body mass index (BMI)  Smoking status  Alcohol consumption  Albumin  Serum creatinine  Platelets count  Pottasium  Total white blood cell count  Cholesterol, HDL and LDL  Exposure  ACEI / ARB Variables 30  Outcome  Time to dementia

 29 disease categories based on Rx drug use  Developed algorithm to map CDS to multiples Rx coding system  Two sets of weights Chronic disease score  17 disease categories  The CCS has been adapted to CPRD data medcodes system  Three sets of weights Charlson comorbidity index Risk Indices 20Charlson, 1987; 36Schneeweiss, 2003; 37Quan, 201; 21Clark, 1995; 38Johnson, 2006 31

 29 disease categories based on Rx drug use  Developed algorithm to map CDS to multiples Rx coding system  Two sets of weights Chronic disease score  17 disease categories  The CCS has been adapted to CPRD data medcodes system  Three sets of weights Charlson comorbidity index Risk Indices 32

 29 disease categories based on Rx drug use  Developed algorithm to map CDS to multiples Rx coding system  Two sets of weights Chronic disease score  17 disease categories  The CCS has been adapted to CPRD data medcodes system  Three sets of weights Charlson comorbidity index Risk Indices 33

 RxDx risk index – 31 disease conditions  Few disease conditions were merged  CDS: Pain/Inflammation and Pain are separate conditions  Not possible to identify separately using diagnosis  CCS: Renal disease and ESRD  Not possible to identify using Rx drugs RxDx-Dementia Risk Index 34 Rx Dx

Statistical Analysis – Aim 1 35 Jan 1, 2003 Index date One year prior Jan 1, 2002 Dec 31, 2012 Baseline year to construct risk index Index date: Date when patient was diagnosed with type 2 diabetes mellitus and hypertension

 Cox proportional hazards regression  Dependent variable – Time to dementia  Independent variables  Age and gender  RxDx disease conditions  Censoring – discontinue, died, combination, end of study  Weights were assigned based on beta coefficient  Rule: Beta * 10  round it to the nearest integer  Discrimination: c-statistics  Validation: 10 cross-fold validation  Calibration: Hosmer-Lemeshow calibration Statistical Analysis – Aim 1 39Harrell, 2001 36

 Discrimination  C-statistics (0.7-0.8 = acceptable; 0.8-0.9 = excellent)  Net reclassification index (NRI)  Assesses risk reclassification and is the sum of improvement in cases and in controls  Positive NRI indicates “new” model is better compared to “old”  Integrated discrimination index (IDI)  Difference in discrimination slopes between two models  Positive IDI indicates “new” model is better compared to “old” Statistical Analysis – Aim 2 39Harrell, 2001; 40Cook, 2009 37

Statistical Analysis – Aim 3 38 Jan 1, 2003 Index date One year prior Jan 1, 2002 Dec 31, 2012 Baseline year to construct covariates Index date: Date when patient started taking ACEI or ARB New users study design

 Descriptive Statistics  Multivariable time-dependent Cox model  Dependent variable – Time to dementia  Independent variables  Drug exposure (quarterly)  Demographics, comorbidities and clinical measures  Censoring – discontinue, died, combination, end of study Statistical Analysis – Aim 3 39

 Marginal Structural Model (MSM)  Blood Pressure (BP) - time dependent confounder affected by previous treatment history  Time dependent Cox model – biased estimate  MSM – unbiased estimate – IPTW estimator Statistical Analysis – Aim 3 41Robins, 2000; 42Hernan, 2000; 43Delaney, 2009; 44Gerhard, 2012 40 BPt0 BPt1 Et0 Et1 Fixed confounders

Results | Discussion 41

Objectives 42 Aim 1 • Develop RxDx risk index to predict dementia in patients with type 2 diabetes mellitus and hypertension Aim 2 • Compare RxDx score with Charlson comorbidity index and Chronic disease score to predict dementia Aim 3 • To compare ACE versus ARB for the risk of dementia in patients with type 2 diabetes mellitus and hypertension

 Cohort included 133,176 patients  Means age = 72.12 years (SD =8.04)  52% of patients were male  Incidence of dementia = 3.42% Aim 1: Descriptive Statistics 43 Disease categories identified using diagnosis n, (%) Disease categories identified using prescription drug use (n, %) Disease categories identified using diagnosis or prescription drug use (n, %) Chronic pulmonary disease 3,501 (2.63) 27,154 (20.39) 27,583 (20.71) Rheumatologic disease 1,443 (1.08) 13,154 (9.88) 13,426 (10.08) Peptic ulcer disease 332 (0.25) 42,474 (31.89) 42,521 (31.93)

Aim 1 - Deriving Points for RxDX Conditions 44 Beta Estimates (p-value) Hazard Ratio (95% CI) Points Myocardial infarction -0.16 (0.21) 0.85 (0.65-1.10) -2 Congestive heart failure -0.07 (0.02) 0.93 (0.87-0.99) -1 Coronary and peripheral vascular disease 0.15 (<0.001) 1.16 (1.07-1.26) 1 Cerebrovascular disease 0.36 (<0.001) 1.43 (1.23-1.67) 4 Epilepsy 0.33 (<0.001) 1.39 (1.22-1.58) 3 Hyperlipidemia 0.11 (<0.001) 1.11 (1.05-1.19) 1 Parkinson’s disease 0.78 (<0.001) 2.19 (1.81-2.64) 8 Depression 0.61 (<0.001) 1.84 (1.71-1.97) 6 Psychotic illness 0.63 (<0.001) 1.88 (1.71-2.06) 6

CalibrationCross - Validation Aim 1: Cross-Validation | Calibration 45 RxDx-Dementia Risk Index C-statistics 0.806 (0.798 – 0.814) Ten-fold cross-validation C-statistics 0.806 (0.800 – 0.813) 1 2 3 4 5 6 7 8 9 10PercentageofDementiacases RxDx risk index deciles Observed % Expectd % * Likelihood-ratio Chi-square (df = 9) = 217.65; P-value = <0.0001

 First study to combine diagnosis and prescription information in a single summary risk index  RxDx-Dementia Risk Index  Control confounding in observational studies  Prognostic tool  Identify patients who are at high risk  Interventions can be focused on modifiable risk factors for dementia  Can be used in EMR as well as claims data  Diagnosis and prescription data are available  No issue of missing values Discussion for RxDx-Dementia 46

Objectives 47 Aim 1 • Develop RxDx risk index to predict dementia in patients with type 2 diabetes mellitus and hypertension Aim 2 • Compare RxDx score with Charlson comorbidity index and Chronic disease score to predict dementia Aim 3 • To compare ACE versus ARB for the risk of dementia in patients with type 2 diabetes mellitus and hypertension

Aim 2: RxDX-Dementia Risk Index Performance Model Risk Index C-Statistics (95% CI) NRI, % (P-value) IDI, % (P-value) 1 Baseline model (Age + Gender) 0.779 (0.773-0.786) 5.63 (<0.001) 1.93 (0.52) RxDx-Dementia risk index 2 RxDx-Dementia risk index 0.806 (0.798-0.814) Reference (New Model) Reference (New Model) 3 RxDx risk index categorical* 0.807 (0.801-0.813) 0.21 (0.38) -0.06 (0.95) Charlson comorbidity score (CCS) 4 Charlson original 0.782 (0.775-0.788) 6.47 (<0.001) 1.91 (0.52) 5 Charlson/Schneeweiss 0.782 (0.776-0.788) 6.50 (<0.001) 1.92 (0.52) 6 Charlson/Quan 0.781 (0.775-0.788) 5.63 (<0.001) 1.93 (0.52) 7 Charlson categorical† 0.783 (0.777-0.789) 6.13 (<0.001) 1.84 (0.53) Chronic disease Score (CDS) 8 CDS original 0.789 (0.782-0.795) 5.90 (<0.001) 1.67 (0.56) 9 CDS/RxRisk – V 0.787 (0.779-0.794) 6.59 (<0.001) 1.80 (0.54) 10 CDS categorical‡ 0.805 (0.798-0.812) 0.86 (0.02) 0.09 (0.96)

Model Risk Index C-Statistics (95% CI) NRI, % (P-value) IDI, % (P-value) RxDx-Dementia risk index 2 RxDx-Dementia risk index 0.806 (0.798-0.814) Reference Reference 3 RxDx risk index categorical* 0.807 (0.801-0.813) 0.21 (0.38) -0.06 (0.95) Combined comorbidity score (CCS+CDS) 12 Charlson original + CDS original 0.789 (0.783-0.795) 5.88 (<0.001) 1.67 (0.56) 13 Charlson/Schneeweiss + CDS original 0.789 (0.783-0.795) 5.94 (<0.001) 1.67 (0.56) 14 Charlson/Quan + CDS original 0.789 (0.782-0.796) 5.98 (<0.001) 1.68 (0.56) 15 Charlson original + CDS/RxRisk – V 0.787 (0.781-0.793) 6.06 (<0.001) 1.79 (0.54) 16 Charlson/Schneeweiss + CDS/ RxRisk-V 0.787 (0.780-0.794) 6.11 (<0.001) 1.79 (0.54) 17 Charlson/Quan + CDS/RxRisk – V 0.787 (0.781-0.793) 6.44 (<0.001) 1.80 (0.54) Aim 2: RxDX-Dementia Risk Index Performance

 Performed superior compared to CCS, CDS or CCS + CDS  Performance is superior or comparable to existing dementia-specific risk indices  Future studies  RxDxClin-Risk Index Risk Index C-Stat RxDx – Dementia 0.81 Mid-life dementia risk 0.75 Late-life dementia risk index 0.81 Brief dementia risk index 0.77 Summary risk score for Alzheimer’s disease 0.79 Late-life dementia risk index – GE data 0.72 Diabetes-specific dementia risk score (DSDRS) 0.75 Discussion for RxDX-Dementia Performance 27Exalto, 2013; 28Barnes, 2009; 29Barnes, 2010; 30Reitz, 2010; 31Kivipelto, 2006; 32Mehta, 2012; 33Exalto, 2013 50

Objectives 51 Aim 1 • Develop RxDx risk index to predict dementia in patients with type 2 diabetes mellitus and hypertension Aim 2 • Compare RxDx score with Charlson comorbidity index and Chronic disease score to predict dementia Aim 3 • To compare ACE versus ARB for the risk of dementia in patients with type 2 diabetes mellitus and hypertension

Aim 3: Descriptive Statistics 52 Characteristics Total* n = 32,856; n (%) ACE users n = 28,562; n (%) ARB Users n =3,943; n (%) P-value Age, mean (SD) 71.55 (7.86) 71.52 (7.88) 71.79 (7.77) 0.04 Age Categories 60-64 years 7,490 (22.80) 6,572 (23.01) 836 (21.20) 0.03 65-69 years 7,220 (21.97) 6,275 (21.97) 878 (22.27) 70-74 years 6,891 (20.97) 5,986 (20.96) 821 (20.82) 75-79 years 5,517 (16.79) 4,730 (16.56) 721 (18.29) 80-84 years 3,515 (10.70) 3,047 (10.67) 431 (10.93) >85 years 2,223 (6.77) 1,952 (6.83) 256 (6.49) Male, n (%) 17,600 (53.57) 15,642 (54.77) 1,810 (45.90) <0.0001 RxDx-Dementia risk index 0.71 (3.74) 0.72 (3.75) 0.66 (3.67) 0.31

Aim 3: CER of ACEI and ARB 53 Treatment Risk Ratio 95% Confidence Interval ARB vs. ACEI Unadjusted 0.86 0.73 – 1.01 Time-dependent Cox regression 0.88 0.75 – 1.04 Marginal structural Cox model 0.61 0.50 – 0.77

 Current study  ARB offers 39% reduction in the risk of dementia  Previous epidemiological studies  Estimates ranged from 19% to 69%  What is the true estimate?  Prior studies showed MSM estimates ~ true estimates  All prior studies  Standard regression methods  Shorter follow-up  Time varying effect of blood pressure not considered Discussion for CER of ARB versus ACEI 41Robins, 2000; 42Hernan, 2000; 43Delaney, 2009 54

Strengths | Limitations 55 - Created new RxDx-Dementia risk index - 10 years of longitudinal follow-up - Causal effect of ACEI and ARB on dementia (use of MSM) - Cannot ascertain that prescriptions are always filled or taken by patients - Missing data imputation

Conclusions 56

Conclusions 57 Aim 1 • Successfully developed and validated RxDx-Dementia Risk Index Aim 2 • RxDx-Dementia Risk Index outperformed all other risk indices Aim 3 • ARB may offer protective effect on the risk of dementia compared to ACEI

 RxDx-Dementia Risk Index  Prognosis of dementia  Control of confounding  Protective effect of ARB compared to ACEI  Proper adjustment of time dependent confounding is important in estimating causal effect  Use of ARB will increase due to generics  Losartan (2010); Irbesartan (2012)  Delay the onset of dementia  Reduce healthcare expenditure, improve patient quality of life and have public health implications Implications 58

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