1. Statistical Challenges Related to Population Screening for AF Christine M. Albert, MD, MPH Director, Center for Arrhythmia Prevention, Brigham and Women’s Hospital Professor of Medicine, Harvard Medical School

2. Screening: AF Prevalence
Effectiveness of Screening
Sensitivity and Specificity of the Test
Prevalence of AF in the Population. .
Relationship between Disease Prevalence and Positive and Negative Predictive Value
False Positives
Expense of monitoring
Exposure to risks of AOC without benefit
Sensitivity 95% and Specificity 85%

3. Focused on “Men over 85” 4.2% AF
SAFE Trial: Cluster Randomized Trial of Office -Based ECG Screening for Atrial Fibrillation
Overall Yield: 0.6 % new AF
Focused on “Men over 85” 4.2% AF
Fitzmaurice et al. BMJ 2007l

4. Mass Screening for Atrial Fibrillation in 75 Year Olds The STROKESTOP Study
Screened twice daily with a handheld device for 2 weeks
AF Defined as: Irregular rhythm lasting 30 secs, or 2 episodes of at least 10 seconds
1% of Unknown AF Diagnosed on Baseline ECG
12%
Add > 1 stroke risk factor to 75+: 7.4% have undetected AF.
Svennberg E et al. Circulation 2015;131:
Engdahl J et al. Circulation 2013: 127:930-93

5. CHA2DS2-VASc was not associated with AF detection
Characteristics of Patients with SCAF Detected
Female sex, lower weight, and absence of vascular disease were significantly associated with no detection of AF.
CHA2DS2-VASc was not associated with AF detection
Svennberg E et al. Circulation 2015;131:

6. Twice weekly iECGs over 12 months
Remote Heart Rhythm Sampling Using the AliveCor Heart Monitor to Screen for Atrial Fibrillation
The REHEARSE-AF Study
Twice weekly iECGs over 12 months
1001 Patients
Age>65
CHADS-VASc >2.0
19 versus 5 diagnosed with AF
Log-rank P=0.004 (Mantel-Cox).
1.2%
Cost per AF diagnosis of $10,780
Please also see the Figure Legend section.
Kaplan-Meier plot showing the estimated detection probabilities for atrial fibrillation (AF) in each study arm over the 52 weeks of the trial.
Shaded areas represent 95% confidence regions.
Halcox JPJ et al. Circulation 2017; 136:

7. The mHealth Screening to Prevent Strokes (mSToPS)Trial
Impact of Immediate Monitoring with a 2 week ECG-Patch
Intention to Treat Results:
Incidence of new AF cases:
AF Incidence 3.9% (53/1366) in the immediate monitoring group vs 0.9% (12/1293) in the delayed monitoring group
Absolute difference, 3.0% [95% CI,1.8%-4.1%]).
Population: 2659 individuals Randomized:
Age 75 years or older
Male > 55 years or Female > 65 years with 1 or more comorbidities
Intervention:
Randomized to Immediate (within 2 weeks) versus delayed monitoring (within 4 months)
3476 Matched Control Group with no monitoring
34.5% did not wear the patch
Please also see the Figure Legend section.
Endpoint:
>30 seconds of AF or new AF diagnosis in Claims Data
Steinhubl SR et al. JAMA 2018; 320:

8. US Taskforce: Analytic Framework: Screening for Atrial Fibrillation With Electrocardiography
Please also see the Figure Legend section.
Jonas DE et al. JAMA 2018; 320:

9. Inadequate Evidence to Support ECG Screening for AF
Screening for Atrial Fibrillation with Electrocardiography
Systematic Review for the US Preventive Services Task Force
Please also see the Figure Legend section.
Inadequate Evidence to Support ECG Screening for AF
Jonas DE et al. JAMA 2018; 320:

10. ECG Screening for AF
Sample Calculation of NNS for AF With ECG to Prevent 1 Stroke
New AF found on initial ECG in 0.5% of screened population
NNS to diagnose 1 new case of AF, 1/0.005 = 200 people
Estimated absolute risk reduction from anticoagulation, 2%
Number needed to treat to prevent 1 stroke, 1/0.02 = 50 people
NNS to prevent 1 stroke, 200 x 50 = 10,000 people
Please also see the Figure Legend section.
Mandrola J et al. JAMA Internal Medicine 2018; 178:
Kinsinger LS et al. JAMA Internal Medicine 2017; 177:

11. Sample Calculation: Stroke Stop: Two Week Monitor Screening for AF
NNS to Prevent 1 Stroke in Patients over Age 75
Sample Calculation:
New AF found in 3.0% of screened population
NNS to diagnose 1 new case of AF, 1/0.03 = 33 people
Estimated absolute risk reduction from anticoagulation, 2%
Number needed to treat to prevent 1 stroke, 1/0.02 = 50 people
NNS to prevent 1 stroke, 33 x 50 = 1650 people
Please also see the Figure Legend section.
Svennberg E et al. Circulation 2015;131:

12. Sample Calculation: New AF found in 7.4% of screened population
Stroke Stop: Two Week Monitor Screening for AF
NNS to Prevent 1 Stroke in Patients over Age 75
with 1 Stroke Risk factor
Sample Calculation:
New AF found in 7.4% of screened population
NNS to diagnose 1 new case of AF, 1/0.074 = 13 people
Estimated absolute risk reduction from anticoagulation, 2%
Number needed to treat to prevent 1 stroke, 1/0.02 = 50 people
NNS to prevent 1 stroke, 13 x 50 = 650 people
Please also see the Figure Legend section.
Svennberg E et al. Circulation 2015;131:

13. Sensitivity and Specificity of Different Methods of Screening for Atrial Fibrillation
Please also see the Figure Legend section.
Paper #6: Table 4
Freedman B et al. Circulation 2017; 135:

14. Passive Detection of Atrial Fibrillation using Neural Network Analysis of a Commercially Available Smartwatch
51 patients in Health eHeart Study
ECG Diagnosis
1617 patients in Health eHeart Study
Self Report of Persistent AF
C-Statistic 0.97
C-Statistic 0.72
Sensitivity 98.0%
Specificity 90.2%
Sensitivity 67.7%
Specificity 67.6%
Please also see the Figure Legend section.
Tue MP et al. JAMA Cardiol 2018; 3:

15. Screening for Atrial Fibrillation:
False Positives: Importance of Prevalence
Sample Calculation of Misdiagnosis at ECG Specificity of 95%
Screening Specificity, 95%
Screened population, 1,000,000 people
AF prevalence, 3%
Number with AF, 0.03 x 1,000,000 = 30,000 people
Number without AF, 1,000,000 – 30,000 = 970,000 people
True negative, 0.95 x 970,000 = 884,450 people reassured they have no AF
False positive, 0.05 x 970,000 = 48,500 people falsely diagnosed with AF
Please also see the Figure Legend section.
Mandrola J et al. JAMA Internal Medicine 2018; 178:
Paper #2: Box 2

16. Screening for Atrial Fibrillation:
False Positives: Importance of Prevalence
Sample Calculation of Misdiagnosis at ECG Specificity of 98%
Screening Specificity, 98%
Screened population, 1,000,000 people
AF prevalence, 10%
Number with AF, 0.10 x 1,000,000 = 100,000 people
Number without AF, 1,000,000 – 100,000 = 900,000 people
True negative, 0.98 x 900,000 = 882,000 people reassured they have no AF
False positive, 0.02 x 900,000 = 18,000 people falsely diagnosed with AF
Please also see the Figure Legend section.
Modified from Mandrola J et al. JAMA Internal Medicine 2018; 178:
Paper #2: Box 2

17. Subclinical Atrial Fibrillation detected on Continuous Monitoring (PPM or ILR)
ASSERT-I
REVEAL-AF
ASSERT-II
Van Gelder IC et al. Eur Heart J 2017; 38:
Healey JS et al. Circulation 2017; 136:
Reiffel JA et al. JAMA Cardiol 2017; 2:

18. What are the implications of detecting short durations of AF?

19. ASSERT: Ischemic Stroke/Systemic Embolism According to Time-Dependent Durations of AF
Please also see the Figure Legend section.
Van Gelder IC et al. European Heart Journal 2017; 38:

20. Resultant Variability in NNS
Uncertainty of Absolute Stroke Rate in Population
(events per 100 person-years)
Resultant Variability in NNS
Please also see the Figure Legend section.
Quinn GR et al. Circulation 2017; 135:

21. Reported Stroke Rates Stratified by CHA2DS2-VASc Scores of 0, 1, and 2 According to Different Cohorts
Please also see the Figure Legend section.
*<1% annual stroke rate, low or no expected net clinical benefit from anticoagulation.
†1% to 2% annual stroke rate, indeterminate expected net clinical benefit from anticoagulation.
‡>2% annual stroke rate, high expected net clinical benefit from anticoagulation.
ACTIVE indicates Atrial fibrillation Clopidogrel Trial with Irbesartan for prevention of Vascular Events; AF, atrial fibrillation; ATRIA,
AnTicoagulation and Risk Factors In Atrial Fibrillation; AVERROES, Apixaban Versus Acetylsalicylic Acid [ASA] to Prevent Stroke
in Atrial Fibrillation Patients Who Have Failed or Are Unsuitable for Vitamin K Antagonist Treatment; J-Rhythm, Japanese Rhythm
Management Trial for Atrial Fibrillation; and NHIRD, National Health Insurance Research Database.
Quinn GR et al. Circulation 2017; 135:

22. Statistical Challenges for Population Screening for AF Summary
Positive Predictive Value (PPV) of AF Screening in the population is dependent on the prevalence of undetected AF in the population.
Screening higher risk individuals will improve the PPV and the number needed to screen (NNS) to prevent one stroke.
The NNS to prevent one stroke also depends on the absolute incidence of stroke in the population and the benefit of anticoagulants in that population.
Even in high risk populations using high specificity measures, the positive predictive value will still be limited resulting in potentially large numbers of false positives.
Continuous monitoring suggests the prevalence of brief episodes of AF may be as high as 30-40% in high risk populations, but the stroke risk and response to anticoagulation is unknown.
Randomized trials are required before adopting systematic AF screening.