Effectiveness of oral appliances: Cardiovascular outcomes

Transcription

1 Effectiveness of oral appliances: Cardiovascular outcomes Presented by Kate Sutherland PhD Charles Perkins Centre, Sydney Medical School, University of Sydney Department Respiratory & Sleep Medicine, Royal North Shore Hospital The University of Sydney Page 1

2 Outline OSA and cardiovascular disease Standard CPAP treatment and cardiovascular outcomes Treatment profiles of Oral Appliances vs. CPAP Overview of evidence of Oral Appliance effects on Cardiovascular measures Blood pressure Other markers of cardiovascular risk Personalised Medicine/Future directions The University of Sydney Page 2

3 OSA and Cardiovascular Disease (CVD) OSA is an independent risk factor for Hypertension Metabolic dysregulation Coronary Heart Disease Heart Failure Stroke Mortality Nieto et al., JAMA, 2001; Punjabi et al., Am J Epidemiol, 2004; Gottlieb et al., Circulation, 2010: Hla et al., SLEEP, 2015; Redline et al., Am J Respir Crit Care Med, 2010; Young et al., SLEEP, 2008; Marshall et al., SLEEP, The University of Sydney Page 3

4 Mechanisms linking OSA to CVD The University of Sydney Somers et al., Circulation, 2008 Page 4

5 Effects of Standard treatment CPAP on CVD Demonstrated effects on improving CVD surrogate markers and CV morbidity/mortality Observational data Mean 10.1 year follow-up of: N=264 healthy men N=377 snorers N=404 mild-moderate OSA (untreated) N=235 severe OSA (untreated) N=372 severe OSA (CPAP treated) Fatal cardiovascular events Non-fatal cardiovascular events Marin et al., Lancet, 2005 The University of Sydney Page 5

6 Sleep Apnea Cardiovascular Endpoints (SAVE) study RCT of CPAP vs. usual care for secondary prevention of CVD N = 2717, years with previous coronary/cerebrovascular disease + moderate-severe OSA 1 end point (CV death/hospitalisation) 3.7 years follow-up Average CPAP usage 3.3 hours/night McEvoy et al., N Eng J Med, 2016 The University of Sydney Page 6

7 AHI in partial users of CPAP SAVE study usage (assuming 7 hours sleep) Boyd et al., J Oral Maxillofac Surg, 2013 The University of Sydney Page 7

8 CPAP adherence rates Review of 20 years of CPAP adherence in clinical trials (N=82 studies) Weighted-average CPAP usage 4.46 hours / night Non-adherence rate = 36.3% (assuming 7 hours sleep) Doesn t include 10.7% that were unable to tolerate No meaningful change in adherence over last 20 years Behavioural interventions 1 hour/night Over-estimation self-report vs. machine ~35% Rotenberg et al., J Otolaryngology Head, Neck Surgery, 2016 The University of Sydney Page 8

9 Oral appliance (OA) efficacy Mean AHI reduction 50.3 ± 50.7% Response rates across OSA severity Response definitions AHI <5 Complete response AHI <10 with 50% AHI 50% AHI Partial response The University of Sydney Sutherland et al., J Clin Sleep Med, 2015 Page 9

10 Oral appliance treatment adherence Objectively monitoring capabilities relatively recent One year treatment data Nightly usage 6.1 ± 2.2 hours Non-adherence rate 12.9% (assuming 7 hours sleep) 83% using OA 4 hours/night on 70% of days Dieltjens et al., Chest, 2013 The University of Sydney Page 10

11 Comparative Effectiveness? High efficacy Modest compliance Modest efficacy High compliance Sutherland et al., Journal Dental Sleep Medicine, 2015 The University of Sydney Page 11

12 What do we know about OA effects on CV outcomes? Blood pressure Surrogate markers CV risk Clinical endpoints The University of Sydney Page 12

13 Blood pressure effects of OSA treatment Network meta-analysis of RCTs of >2: 1) CPAP, 2) OA, 3) control Measurement of systolic/diastolic blood pressure post-treatment N = 51 studies, N = 4888 subjects with OSA CPAP vs. inactive control 2.5 mmhg SBP (95%CI ), P< mmhg DBP (95%CI ), P<0.001 OA vs. inactive control 2.1 mmhg SBP (95%CI ), P= mmhg DBP (95%CI ), P=0.008 No significant difference between CPAP and OA in BP reduction Bratton et al., JAMA, 2015 The University of Sydney Page 13

14 Blood pressure effects of OSA treatment Influence of treatment usage time on BP reduction (CPAP only) 1 hour/night = additional 1.5 mmhg SBP & 0.9 mmhg DBP Length of follow-up CPAP vs. control - ~15 weeks OA studies 4-10 weeks Bratton et al., JAMA, 2015 The University of Sydney Page 14

15 Short-term effects CPAP vs. OA 24hr BP RCT of one month optimised CPAP and OA treatment (N=108) 24 hr Blood Pressure All subjects No difference (but no change) Hypertensives N=45 No difference (equal reduction in both) Philips et al., Am J Respir Crit Care Med, 2013 The University of Sydney Page 15

16 (self-report) Short-term effects CPAP vs. OA 24hr BP RCT of one month optimised CPAP and OA treatment (N=108) Mean MAS AHI: 11.1 ±1.2 events/hour Mean CPAP AHI: 4.5 ±0.7 events/hour Mean MAS use hrs Mean CPAP use hrs The University of Sydney Page 16 Philips et al., Am J Respir Crit Care Med, 2013

17 What do we know about OA effects on CV outcomes? Blood pressure OA effects on lowering blood pressure appear to be equivalent to standard treatment (CPAP) Potential explanation inferior efficacy of OA therapy mitigated by greater compliance Surrogate markers CV risk Clinical endpoints The University of Sydney Page 17

18 What do we know about OA effects on CV outcomes? Blood pressure Surrogate markers CV risk Arterial stiffness Endothelial function Heart rate variability Oxidative stress Biomarkers Clinical endpoints de Vries et al., Sleep Med Rev, 2017 The University of Sydney Page 18

19 Surrogate CV risk measures First author (year), N patients Measurement Study Design Intervention time Result Arterial stiffness Philips (2013), N = 108 Galic (2015), N=18 augmentation index, pulse wave analysis Pulse wave velocity RCT, crossover OA and CPAP Observational, OA One month One year No difference between treatments, 1-2% improvement in both Significant decrease in velocity baseline to one year Limited data, Hint that CPAP and OA may have same effects short term The University of Sydney Page 19

20 Surrogate CV risk measures Endothelial function First author (year), N patients Lin (2015), N = 30 Trzepizur (2009), N = 15 Gagnadoux (2017), N = 150 Measurement Flow-mediated dilation, NO serum levels Laser doppler flowmetry Peripheral arterial tonometry (PAT) Study Design Observational, OA (comparison responders and failures) RCT, crossover CPAP and OA RCT, parallel group, OA and inactive-oa Hint of improvement in small studies, Largest study negative? Intervention time One year Two months Two months Result NO serum levels & FMD in OA responders (No OA failures) Vasodilation increased, no difference between treatments No change in Reactive Hyperemia Index The University of Sydney Page 20

21 RCT: Endothelial function Good compliance: 6.6 hrs/night (inactive control 5.6 hrs/night)? abnormal vascular phenotype The University of Sydney Gagnadoux et al., Am J Respir Crit Care Med, 2017 Page 21

22 Surrogate CV risk measures First author (year), N patients Measurement Study Design Intervention time Result Heart rate variability Dal-Fabbro (2014), N = 29 Coruzzi (2006), N=10 ECG from polysomnography night ECG 20min supine rest during wakefulness RCT, crossover CPAP, OA, inactive-oa Observational, OA One month Three months total power both CPAP and OA, sleep autonomic variation index, OA only low/high R-R interval power ratio (Improved autonomic function Glos (2015), N=40 ECG wakefulness RCT, crossover CPAP and OA Three months Minimal changes, no difference between treatments Small heterogenous studies, hint no difference to CPAP? The University of Sydney Page 22

23 Surrogate CV risk measures First author (year), N patients Measurement Study Design Intervention time Result Oxidative stress Dal-Fabbro (2014), N = 29 Blood samples post PSG (malondialdehyde, catalase, superoxide dismutase, vitamins C, E, B6, B12, folate, homocystein, uric acid) RCT, crossover CPAP, OA, inactive-oa One month catalase, OA only Itzhaki (2007), N = 16 Blood samples for lipid peroxidation assays Observational, OA One year oxidative stress markers (correlation with change in AHI) Limited studies, heterogeneity, possible improvement The University of Sydney Page 23

24 Surrogate CV risk measures Inflammatory, metabolic, cardiac function markers First author (year), N patients Galic (2015), N=18 Fernandez- Julian (2017) N = 30 Nizankowska- Jedrzejczyk (2014) N = 22 Hoekema (2008), N = 28 Measurement CRP, Fibrinogen, Triglycerides, cholesterol, HDL/LDL, cortisol, insulin, glucose, HbA1c CRP, IL-1, IL-6, TNF-, 6-keto-PGF1, glucose, fibrin clot lysis time (CLT) CRP, IL-1, IL-10, IL-6, P-selectin, fibrinogen, D- dimer Study Design Observational, OA Case-control, OA and Tx refusers Observational, OA + healthy control group Intervention time One year Six months Small studies, mostly observational, mixed bag of blood markers Echocardiography Brain natriuretic peptide (NT-pro- BNP) RCT, parallel CPAP and OA Six months The University of Sydney Page 24 Result Significant changes: Fibrinogen Fasting glucose Fasting insulin OA group, improved IL-1, TNF-. OA improved IL-1, D-dimer, TAF1a, CLT 2-3 months Left ventricular structure/function no change (no difference between treatments) NT-pro-BNP improved, OA only (but higher baseline levels)

25 What do we know about OA effects on CV outcomes? Blood pressure Surrogate markers CV risk Some studies show improvements in surrogate markers of CV health with OA therapy, but overall evidence limited and short-term Clinical endpoints The University of Sydney Page 25

26 What do we know about OA effects on CV outcomes? Blood pressure Surrogate markers CV risk Clinical endpoints Observational data (N=1 study) The University of Sydney Page 26

27 CV mortality observational data Outcome = fatal CV events (hospital/national records) Stroke, myocardial infarction, sudden cardiac arrest or cardiac arrhythmias Median follow-up 6.5 years Anandam et al., Respirology, 2013 The University of Sydney Page 27

28 CV mortality observational data Residual AHI OA > CPAP 16 ± 5.1 vs. 4.5 ± 2.3 events/hour Treatment usage OA > CPAP 6.5 ± 1.2 vs. 5.8 ± 1.6 hours/night Event rate untreated OSA No difference OA vs. CPAP Anandam et al., Respirology, 2013 The University of Sydney Page 28

29 What do we know about OA effects on CV outcomes? Blood pressure Surrogate markers CV risk Clinical endpoints Limited data: CPAP and OA appear to have equivalent benefit in N=1 observational study The University of Sydney Page 29

30 Summary OSA treatment There is a need to consider non-pap alternatives for potential to impact on long-term cardiovascular health CPAP acceptance and usage below what needed to impact cardiovascular health (e.g. the SAVE study) Evidence Oral appliances may be as effective as CPAP in the short-term (at least for blood pressure) Objective evidence is emerging of good oral appliance usage, out to one year equivalent outcomes explained by comparative effectiveness? Long-term? Other CVD markers? The University of Sydney Page 30

31 Personalised medicine heterogeneous disorder e.g. OSA Each circle represents one theoretical patient Patients grouped by similar clinical characteristics Adapted from Agusti A, Thorax 2014 Comprehensive understanding of clinically meaningful characteristics at the individual level - personalised medicine The University of Sydney Page 31

32 Better patient phenotyping towards identification of clinically meaningful subtypes Clinical symptom clusters Clinical subtypes CV risk subtypes Who is susceptible to OSA-related CVD? Who will respond to OSA treatment? Ye et al., Eur Respir J, 2014 Keenan et al., SLEEP 2018 Review on application of Personalised (P4) Medicine to OSA Lim, Sutherland, Cistulli, & Pack. Respirology, 2017 The University of Sydney Page 32

33 CV responses to OSA treatment more than just compliance Blood samples molecular signatures (cardiovascular-specific microrna) Good CPAP users >4 hrs/night able to discriminate blood pressure responders Derivation sample AUC 0.98 Validation sample AUC 0.92 No blood pressure response to CPAP Blood pressure response to CPAP Sanchez-de-la-Torre et al., J Am Coll Cardiol, 2015 The University of Sydney Page 33

34 Future directions Shift in focus from just the AHI Comparative effectiveness studies How do treatments compare long-term? What is the level of effectiveness needed? Long-term, quality studies, comprehensive assessment of early markers of CV risk, mortality data consideration of at risk vascular phenotypes Identification of biomarkers The University of Sydney Page 34

35 Research Centres Sydney, Australia Royal North Shore Hospital Peter Cistulli Joachim Ngiam Andrew Chan Melanie Madronio Nina Sarkissian Aimee Lowth Nicola Davies Sleep Investigation Unit staff Dr Kate Sutherland Clinical Research Research Students Prof Peter Cistulli Sleep Medicine The Sleep Group, Charles Perkins Centre, University of Sydney Research Leaders Dr Kristina Cook Cell biology Ahmad Bamagoos Clinical Research Prof Philip de Chazal Engineering Research Fellows Dr Yu Sun Bin Public Health Dr Madhuka Jayawardhana Engineering Anna Mohammadieh Clinical Research Dr Nadi Sadr Lahijany Engineering Dr Asghar Tabatabaei Balaei Engineering Ben Johnston Engineering The University of Sydney Page 35