Implementing Frailty into Clinical Practice
A Cautionary Tale
Howard Bergman MD, FCFP, FRCPC
Chair, Department of Family Medicine
Professor of Family Medicine, Geriatric Medicine and
Oncology
Nadia Sourial MSc, PhD (cand)
Department of Family Medicine
McGill University
Alma 12.9.15
Department of
Family Medicine
Département de
médecine de famille
Mrs. R.
Mrs. R. is an 82 year old widow(x15 years), 3 adult
children and an active social life. Her PMH includes mild
MI (3 years ago), osteoporosis and osteoarthritis. Her
cognition is normal and she is compliant with
medications. She walks with a cane in her home but
needs a walker outside. She is independent in all ADL
and in IADL but needs help for transportation which she
organises
Department of
Family Medicine
Département de
médecine de famille
Mrs. P.
Mrs. P. is a 78 year old lady living with her 83
year old husband. PMH includes diabetes,
hypertension, osteoarthritis, falls and dementia.
She walks with a walker with supervision. She is
dependent in most IADL’s and needs help in
washing and dressing.
Department of
Family Medicine
Département de
médecine de famille
Professor. B.
Professor B. is a 70 year old university professor
and physician who lives with his wife. He has 2
children and 4 grandchildren. He is Chair of a
major university department and leads a major
research program. No PMH aside from mildly
elevated cholesterol.
Department of
Family Medicine
Département de
médecine de famille
Are Mrs. B and Pr. B. frail
What is frailty
What are the components of frailty
So What????
Should we screen all older people for frailty
Can her vulnerability be identified in the
clinical setting
Can the potential adverse outcomes, in
particular disability, be prevented or delayed
Is frailty a useful in these 3 patients
The Challenge of Defining Frailty
Frailty is like pornography: Clinicians can’t define it but
they recognize it when they see it.
an anonymous clinician
Clinicians and researchers
don’t know how to define it
are not sure if it is different from disability
cannot position frailty in the spectrum of heath status
don’t know whether it is a reversible condition or not
don’t know how much it is physiological aging and how
much is the result of diseases
don’t know where social factors fit in
6
Don’t know what to do with the information
Department of
Family Medicine
Département de
médecine de famille
Frailty General Agreement
Core feature of frailty is increased vulnerability to
stressors due to impairments in multiple, inter-related
systems that lead to decline in homeostatic “reserve”
and resiliency
The main consequence is an increased risk for
multiple adverse health-related outcomes
– disability, morbidity, falls, hospitalisation,
institutionalisation, death
a syndrome encountered in older persons with
diverse predisposing, precipitating, enabling and
reinforcing factors
Frailty and disability: while related and with overlap,
are distinct concepts
Bergman, Ferucci, Guralnick, et al Frailty, an Emerging Research and Clinical Paradigm: Issues
and Controversies. J of Gerontol: Med Sci. 2007
Department of
Family Medicine
Département de
médecine de famille
Survival According to Frailty Status
Cardiovascular Health Study
Percent Alive
100
80
60
No Frailty
Intermediate
Frail
40
20
0
0
24
48
72
96
Months After Study Entry
Fried et al, J. GerontologyDepartment
MedofSci,Département
2001 de
Family Medicine
médecine de famille
Relevance of the Frailty Syndrome
Improves our understanding of the aging process and
ability to characterise the heterogeneity of older persons
At population and clinical level: characterises health and
functional status beyond disability and co morbidity
Identifies a subset of vulnerable older adults at high risk
of adverse outcomes
– older persons who are functionally independent with
apparently normal cognitive function may be overlooked even
if they have identifiable frailty markers and are highly
vulnerable for adverse health outcomes and increased
utilisation of health services
Bergman, Hogan, Karunananthan. Frailty: A clinically relevant concept?
Canadian Journal of
Geriatrics 2007
Department of
Family Medicine
Département de
médecine de famille
Health and functional status of cancer patients, aged 70 years
and older referred for chemotherapy- preliminary findings
100
80
%
42%
(n=21)
60
40
20
12%
(n=6)
30%
(n=15)
16%
(n=8)
0
Without frailty
With frailty
markers or IADL /
markers but
ADL disability without IADL /
ADL disability
IADL disabled
without ADL
disability
ADL disabled
Retornaz F, Monette J, Monette M, Sourial N, Wan-Chow-Wah D, Puts M, Small D, Caplan S, Batist G, Bergman H.
Usefulness of frailty markers in the assessment of the health and functional status in older cancer patient referred for chemotherapy .
J Gerontol A Biol Sci Med Sci. 2008
Explosion of frailty models
The single analysis and the single meeting models
Every year, new models of frailty are being proposed
in the literature
No agreement on conceptual model and underlying
biology
- Frailty as a syndrome or as a risk accumulation
Extensive literature that is difficult to interpret:
– Range of the reported crude prevalence of frailty based on a
systematic review: 1% to 98%
The leap from frailty as a risk to frailty as a
predictive clinical tool
12
Frailty: a Complex Syndrome of Increased Vulnerability
A possible working framework
Age
Prevent/Delay Frailty
Health Promotion and Prevention
Delay/Prevent
adverse outcomes, care
Delay Onset
FRAILTY
Life-course
Determinants:
Biological
(including genetic)
Psychological
Social, Societal
Environment
Candidate
domain
components
Disease
Decline in
physiologic
reserve
• Nutrition
• Mobility
• Activity
• Strength
• Endurance
• Cognition
• mood
Adverse outcomes
• Disability
• Morbidity
• Hospitalization
• Institutionalization
• Death
Biological, Psychological,
Social, societal
modifiers/assets and deficits
Canadian Initiative on Frailty and Aging / Initiative canadienne sur la fragilité et le vieillissement
www.frail-fragile.ca
FrData Objective 2: Testing the
predictive ability of the frailty markers
Test all possible combinations of the 7 frailty
markers + CHS phenotype model
– 129 models in all
Determine model with best prediction for incident
ADL disability
Determine how much frailty markers add to
predictive accuracy beyond age, sex and the number
of chronic diseases
Sourial, Bergman et al. Implementing Frailty into Clinical Practice: A Cautionary Tale.
J Gerontol A Biol Sci Med Sci. 2013 14
7-year survival by frailty phenotype group
in EPESE East Boston sample
1= Frail, 2=Pre-Frail, 3=Non-Frail
15
Predictive ability of frailty
1.0
Addition of frailty markers
Age, sex, disease
0.9
0.8
0.027
0.032
0.034
0.73
0.73
0.73
CHS model
Count model
Best model
0.7
C-Statistic
0.6
0.5
0.4
0.3
0.2
0.1
0.0
EPESE-Boston
Sourial, Bergman et al. Implementing Frailty into Clinical Practice: A Cautionary Tale.
J Gerontol A Biol Sci Med Sci. 2013
Predictive ability of frailty and chronic
disease: by age group
• Frailty contribution increased with age, from 4% to 9%
• Chronic disease contribution decreased with age, from 11% to 1%
Sourial, Bergman et al. Implementing Frailty into Clinical Practice: A Cautionary Tale.
J Gerontol A Biol Sci Med Sci. 2013
18
Prediction Is Very Hard
Especially about the future
Yogi Berra
19
Confusion in the literature between
explanatory and predictive ability
Most of the research in frailty has consisted of analyzing the
explanatory ability, i.e. testing frailty as a significant risk factor for
adverse outcomes within a given sample
Little is known on the true predictive ability of frailty to predict
accurate outcomes in new, out-of-sample subjects
Explanatory ability often used to infer predictive ability
Even highly significant risk factors can make poor predictors for a
prognostic tool
• Determinants of current market stock prices vs prediction future stock prices
• Application of a prediction model is sensible, if the model is able to provide
useful additional information for clinical decision making.
Grady, Berkowitz. Arch Intern Med. 2011
Siontis, Tzoulaki, Ioannidis. Arch Intern Med. 2011
Ware. N Engl J Med. 2006
Pepe et al. Am J Epidemiol. 2004
Studies on Prediction
Recent papers in predictive ability of frailty
–
–
–
–
- Afilalo et al. J Am Coll Cardiol. 2010
- Makary et al. J Am Coll Surg. 2010
- Studenski et al. JAMA. 2011
- Freiheit et al. J Am Geriatr Soc. 2011
Most have not tested different combinations of
frailty markers
Have not studied how much frailty adds to the
predictive capacity of basic demographic and
medical data (age, sex number of chronic
diseases
21
Summary of prediction results
Frailty markers were found to be significant risk factors at the
population level
However, as a prognostic clinical tool to predict disability in
new patients, frailty may add very little to the predictive
accuracy beyond age, sex and the number of chronic diseases
– - Moreover, very little difference in predictive ability across different
frailty models, especially the «best» ones
However, impact with age (up to 9%)
Age, number of chronic diseases and sex are not modifiable.
Frailty markers are.
Reducing risk, even by a few % may be important (eg cardio
vascular risk score)
– If there is an intervention that will change the outcome
22
Summary of prediction results
Risk and prediction will vary depending on
the
– Population studied: socio-economic status,
ethnic origin, age.etc
– Setting: clinical (eg oncology, surgery, primary
care), population
– Outcomes studied (onset of disability, falls,
admissions, death etc)
Grady et al. Arch Intern Med. 2011
Siontis et al. Arch Intern Med. 2011
Combining indicators for risk prediction
in elderly patients undergoing cardiac surgery
 Risk prediction in elderly cardiac surgery patients
can be optimized by considering a combination of



5-meter gait speed for frailty
Nagi items for higher-level disability
Parsonnet score for comorbidities and illness
severity.
Afilalo, Mottillo, Eisenberg, Alexander, Noiseux, Perrault, Morin, Langlois, Ohayon, Monette, Boivin, Shahian, Bergman H.
Circ Cardiovasc Qual Outcomes. 2012
25
“I had come to an entirely
erroneous conclusion, which
shows my dear Watson, how
dangerous it always is to
reason from insufficient data.”
Sherlock Holmes in “The speckled band”
Conclusion
Frailty research and debate has opened new
horizons in understanding
– the aging process and the heterogeneity of older persons and
– the potential to identify independent vulnerable older adults and
prevent/delay adverse consequences
Still working towards an understanding of
frailty
- The biological underpinnings; The conceptual model; Its utility
population health; Its utility as a clinical instrument
27
Conclusion
Use as a clinical tool must be evidence-based
Conditions to be met for frailty as a clinical tool
Valid in different populations and settings and
for different outcomes of interest;
A combination of predictors may be more
useful clinically in order to capture complexity
of older persons
Needs to have a greater predictive capacity than
the usual information available to the clinician
28
Conclusion
Use as a clinical tool must be evidence-based
Conditions to be met for frailty as a clinical tool
Needs to be user and time friendly for the
clinician
Need to have interventions that delay onset of
frailty; delay onset of adverse outcomes
Needs to be cost-effective for a healthcare
system
29
Mrs. B.
Mrs. B. is an 82 year old widow(x15 years), 3 adult
children and an active social life. Her PMH includes
mild MI (3 years ago), osteoporosis and osteoarthritis.
Her cognition is normal and she is compliant with
medications. She walks with a cane in her home but
needs a walker outside. She is independent in all ADL
and in IADL but needs help for transportation which she
organises
Mrs. B.
Mrs. B. is a 78 year old lady living with her 83
year old husband. PMH includes diabetes,
hypertension, osteoarthritis, falls and dementia.
She walks with a walker with supervision. She is
dependent in most IADL’s and needs help in
washing and dressing.
Professor. B.
Professor B. is a 70 year old university professor
and physician who lives with his wife. He has 2
children and 4 grandchildren. He is Chair of a
major university department and leads a major
research program. No PMH aside from mildly
elevated cholesterol.
Embracing the heterogeneity and
complexity
Healthy older persons
– Primary medical care, Health
assessment/promotion/prevention
Early frail/low risk/chronic disease
– Primary medical care, Chronic disease management,
detection of vulnerability, preventive home visits
Medium risk/mild-moderate disability
– Primary medical care and home care, chronic disease
management. Specialized Geriatric care,
↑ Disability and multiple chronic disease
– systems of integrated care
End of life care
Collaborative care model
partnership patient/caregiver and clinician team
 Approach based on the
chronic disease collaborative
care model implemented in
Family Medicine Groups
(GMFs)
Patient Caregiver
Case finding - diagnostic
Treatment - follow-up
Family Medicine Group
Family
Physician
Nurse/SW
Support/Complex cases Coordination - transition
Specialized
services –
Memory clinic
Home-based services,
community pharmacy,
hospital,
Alzheimer society
3
4
Graduate programs in Family Medicine
Research at McGill?
The MSc and the PhD (ad hoc) in Family Medicine are research-oriented thesisbased graduate programs in family medicine. As many relevant research questions
cross conventional boundaries of disciplines and research traditions, we incorporate an
interdisciplinary approach with an emphasis on participatory research and
community engagement.
These programs provide training in epidemiology and statistics as well as in
qualitative, quantitative and mixed methods. Students are also oriented for knowledge
synthesis and participatory research approaches.
http://www.mcgill.ca/familymed/research-grad/graduate-programs
Contact me
howard.bergman@mcgill.ca