“You Can Observe a Lot By Just Watching”

Wayne J. Morgan, MD, CM

Disclosures

• Genentech

– Epidemiological Study of Cystic Fibrosis, Scientific Advisory Group

• CF Foundation

– Data Safety Monitoring Board

– Registry/Comparative Effectiveness Research Committee

What is the CF Foundation

Patient Registry?

How has the CFF Patient Registry grown?

Knapp et al. Ann Am Thorac Soc 13:1173-1179, 2016.

The CFF Patient Registry Today

Inclusion criteria• Seen at CF care center• Consent to participate

Data collected at• Diagnosis• Clinic Visits• Hospitalizations / Home

IV treatments• Annually

Download a copy at CFF.org/InsightCF.

Where are CF Foundation-accredited care programs?

~34,500100%

~31,00090%

28,98384%

Who is followed in the Registry?Based on birth rates and CFTR allele prevalence, it is estimated

that there are about 34,500 persons with CF in the United States

6% do not consent toparticipate in Registry

Followed at US CF Care Centers

Followed in theCF Foundation Patient Registry

in 2015

How complete are Registry data?

95+%

90-<95%

80-<90%

FTR mutation (94%)

(90%)

Date of Birth

Sex

Race

Hispanic origin

FEV1

Weight

Height

Respiratory Cultures

Knapp et al. Ann Am Thorac Soc 13:1173-1179, 2016.

How accurate are Registry data?

95+%

90-<95%

80-<90%

Knapp et al. Ann Am Thorac Soc 13:1173-1179, 2016.

Demographic variables

Hospitalizations

Anthropometric measures

Respiratory cultures

Medications

Medical data accuracy

95+%

90-<95%

80-<90%

Knapp et al. Ann Am Thorac Soc 13:1173-1179, 2016.

Pancreatic enzymes (99%)Dornase alfa (94%)

Azithromycin (90%)Hypertonic saline

Inhaled tobramycin

Inhaled aztreonam

(89%)

(83%)

(83%)

Modified from Cystic Fibrosis Data Network http://www.cysticfibrosisdata.org/

Where are we now?

Survival for people with CF

12-year

improvement

8-year

improvement

Annual Data Report 2015, CF Foundation Patient Registry

Life expectancy by age

Annual Data Report 2015, CF Foundation Patient Registry

-3% 0% 3% 6%

B. cepacia complex

A. xylosoxidans

S. maltophilia

MRSA

P. aeruginosa

H. influenzae

S. aureus

Infection prevalence by age and over time

Salsgiver et al. Chest 149(2): 390-400, 2016.

Cross-sectional Prevalence, 2015

People

with

CF

Prevalence Change, 2006-2012

Patients

Annual Data Report 2015, CF Foundation Patient Registry

What is the CF Treatment Burden?

Annual Data Report 2015, CF Foundation Patient Registry

of people with CF take all three

inhaled medications

Chest Physiotherapy

Changing demographics: Adults with CF

CDC. Behavioral Risk Factor Surveillance System Survey Data, 2015Annual Data Report 2014, CF Foundation Patient Registry

ADULTS

CHILDREN

4,392 Adults 14,955 Adults >100 Adult CF Programs

What have we learned about CF and its care?

0

5

10

15

20

CFF Patient Registry data use

Publications

Year

What factors impact survival?

Liou et al. Am J Epidemiol. 2001 Feb 15;153(4): 345-52.

-50 -40 -30 -20 -10 0 10 20

Pulmonary Exacerbation

B. cepacia

S. aureus

CF-Related Diabetes

Weight-for-Age z-Score

Pancreatic Sufficiency

Age (5 years)

Female vs. Male

FEV1 % Predicted Equivalence

S. aureus

B. cepacia

How do CFTR genotypes affect phenotypes?

Adapted from http://www.umd.be/CFTR/W_CFTR/gene.html

Cl -Cl -Cl -

Cl -

Cl - Cl -

Unaffected Class I

synthesis

Class II

maturation

XX

X

Class III

regulation

Class IV

conductance

X

Cl -Cl -

X

Cl -Cl -

Class V

quantity

‘severe’ mutations ‘mild’ mutations

How do CFTR genotypes affect phenotypes?

McKone et al. Lancet. 2003 May 17;361(9370):1671-6.

Cl -Cl -Cl -

Cl -

Cl - Cl -

Unaffected Class I

synthesis

Class II

maturation

XX

X

Class III

regulation

Class IV

conductance

X

Cl -Cl -

X

Cl -Cl -

Class V

quantity

Age at Diagnosis (yrs) 2.6 12.0

FEV1 % Predicted 78 93

Pancreatic Insufficient (%) 92 70

P. aeruginosa (%) 59 43

Mortality Rate (per 1000) 20.4 21.2 16.0 7.8 9.1

Contributors to phenotype

Cutting et al, Nat Rev Genet. 2015 January; 16(1): 45-56

90

94

98

102

106

FEV1 % Predictedat 6 Years

Age (years) when First Reached 50th WFA Percentile

What are the pulmonary impacts of early life nutrition?

80

85

90

95

100

105

FEV1 % Predictedat 6 Years

Weight-for-Age Percentile at 3 Years

Weight-for-Age (WFA) at 3 Years

and FEV1 at 6 Years

Age when First Reached 50th WFA Percentile

and FEV1 at age 6

Sanders et al. J Pediatr 2015;167:1081-8.Konstan MW et al. J Pediatr 2003;142(6):624-30.

What do we know about lung function decline?

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

Mean FEV1

Rate of Change (%pred/yr)

Age Group (Years)

Rate of FEV1 Decline by Age

Konstan et al. J Pediatr 2007;151:134-9 Dasenbrook et al. Poster 489. NACFC 2015

Predictors of Decline

Female Sex

Low BMI Percentile

Crackles

P. aeruginosa infection

S. aureus Infection

B. cepacia complex Infection

Prior Pulmonary Exacerbations

FEV1 ≥100% Predicted

FEV1 Variability

Konstan et al. J Pediatr 2007;151:134-9Cogen et al. Pediatr Pulmonol. 2015 Aug;50(8):763-70Waters et al. Eur Respir J. 2012 Jul;40(1):61-6.Morgan et al. J Pediatr. 2016 Feb;169:116-21

Pancreatic Sufficiency

Wheezing

F508del Heterozygote Genotype

Diagnosis by Newborn Screening

slower

faster

Sanders DB et al. Am J Respir Crit Care Med 2010; 182:627-632.

Exacerbation

BaselineBest in prior

6 months

What are the long-term implications ofpulmonary exacerbations for lung function decline?

75%

≥90% recovery

≥90% Recovery

81% 85%

≥90% Recovery

15% of patients failed to recover

90% of their Baseline FEV1

What predicts pulmonary exacerbations?

IV-Treated

Exacerbations in

the Prior Year

-1.1% predicted

per year

-1.8% predicted

per year

Median Days to Next Exacerbation (with 95% CI)

Past IV-Treated Exacerbations are the Strongest Predictor

of Future ExacerbationsMean Rate of

FEV1 Loss

Waters et al. Eur Respir J. 2012;40(1):61-6VanDevanter et al. J Cyst Fibros 2016;15;372-379

IV Treatment after ≥10% Acute FEV1 Decline

Morgan et al. J Peds. 2013;163(4):1152-7

Odds of IV Treatment Highest vs Lowest

FEV1 Deciles: 0.15 (95% CI 0.12, 0.20)

Patients Treated

FEV1 %

Predicted

Decile

>50%

<25%

It's like déjà vu all over again

Personal communication, J Ostrenga - CFFPR 2015

Can we evaluate the effectiveness of treatment?

Efficacy (clinical trials) ≠ Effectiveness (real world)

Clinical Trials

• Design optimized to demonstrate safety and efficacy may limit generalizability– Disease stage

– Co-morbidities

– Problematic respiratory infection

– Poor follow up

• Frequent visits with careful follow-up

• Standardization of management and outcome measures

• Attention to adherence

Real World

• All who may benefit often including those excluded from trial and/or off-label use

• Less frequent visits and follow-up

• Less standardization of management and outcome measures

• Longer duration of therapy

• Less attention to adherence

Confounding by indication:sicker patients receive more treatments

increased

mortality

reduced

mortality

Inhaled tobramycin (unadjusted)a

Inhaled tobramycin (adjusted)a

Inhaled tobramycin (adjusted)b

a- Rothman and Wentworth. Epidemiology. 2003;14(1): 55-9 b- Sawicki et al. Ped Pulm 2012; 47:44-52.

Effect of Inhaled Tobramycin on Survival2.8

1.2

0.79

Effectiveness of dornase alfa

70

75

80

85

90

Baseline 6 Months 12 Months

FEV1 % Predicted

After adjustment for cohort differences,

there was a mean 4.3% increase in FEV1 for patients treated with dornase alfa

Johnson et al. J Peds. 1999; 134(6); 734-9

Comparator Patients

Dornase alfa Patients

CFTR modulator effectivenessIndividuals from CFTR modulator clinical trials compared to

matched F508del homozygote Registry controls

Sawicki et al. Am J Respir Crit Care Med. 2015;192(7):836-842.

Konstan et al. NACFC 2016, Poster 180.Bessonova et al. NACFC 2016, Poster 494.

Was treatment with chronic macrolides increasing NTM risk?

Binder et al. Am J Respir Crit Care Med. 2013;188(7):807-12.

37% of CFFPR patients with new NTM in 2011

received chronic macrolides in 2010

51% of CFFPR patients without NTM in 2011

received chronic macrolides in 2010

Historical macrolide use was associated with a decreased risk of NTM isolation

Putting it all together…genetic

defect

survival

Modified from Liou, 2016

malnutrition

liver

disease

pancreatic

insufficiency

liver

transplant airway

infectionabnormal

secretions

height, weight

inflammation

sinusitis

transplantinfertility

lung

function

exacerbations

sex, age diabetes

How does the Registry support care teams?

CFFPR Center-Specific Report

Annual Center-specific reports

CFFPR Center-Specific Report

Annual Center-specific reports

VCU Quality

Improvement Program

How Registry data can drive quality:One program’s story….

75

80

85

90

95

100

105

2009 2010 2011 2012 2013 2014 2015

Median FEV1

% Predicted

Virginia Commonwealth University Pediatric Program

National Average

Ten Best Performing Centers

Schechter et al. Poster 546. NACFC 2016Year

How have we partnered to create change?

• Quality improvement and leadership development

• Care center peer-review accreditation process

• Evidence-based clinical practice guidelines

• Benchmarking to learn from best practice

• Engaging people with CF and their families

What comes next?

More to do…

• Continue using Registry to improve care and learn more about CF as a disease and its treatments

• Increase value of Registry at point of care

• Recognizing limitations

– Some important questions can only be answered by clinical trials

– Integrating other data sources to enhance Registry

• Abstract 482: Linking Transplant and CFFPR Registries

• Inviting CF community to participate in asking research questions

Acknowledgments

• Patients and their families

• CF data coordinators and CF Center care teams

• CF Foundation leadership

• Registry committee (Chairs C. Goss and E. Dasenbrook)

• Clinicians and researchers who use Registry and other data to

improve understanding of CF and patient care

• Registry team at CF Foundation• Bruce Marshall

• Alex Elbert, Kris Petren, Samar Rizvi, Shathiya Kesevan, Tom O’Neil

• Aliza Fink, Josh Ostrenga, Deena Loeffler, Victoria Danner

• Ase Sewall

www.CNN.com

To learn more and submit your research

questions, visit CFF.org/InsightCF.