Identification of individuals at high-risk of fracture

Tuan V. Nguyen

Garvan Institute of Medical Research

Sydney, Australia

Contents

• Who should be treated: current guidelines

• Beyond bone mineral density

• Prognostic models of fracture

• Individualization of prognosis

• Applications of individualized prognosis

Consider two cases …

Risk profile Mrs. Smith Mrs. Jones

Age 60 70

BMD T-scores -1.5 -2.0

Prior fracture One at the forearm

No

Fall One No

Who should be treated?

Who should be treated? • National Osteoporosis Foundation (NOF)

Women with T-scores < -2 and no risk factors Women with T-scores < -1.5 and one or more risk factors Women with a prior vertebral or hip fracture(NIH. Osteoporosis Prevention, Diagnosis and Therapy JAMA

2001;285:293-312)

• International Osteoporosis Foundation (IOF) BMD is offered to individuals with a risk factor (prolonged

estrogen deficiency, corticosteroid use, prior fracture, and other risk factors that increase fracture risk) Women with T-scores below -2.5

(Kanis et al, Osteoporosis Int 1997)

Who should be treated?

• Australian experts’ recommendation: Women with osteoporosis and fractures: TREAT Women with osteopenia and a fracture: TREAT Women with osteoporosis but no fractures: TREAT Women with osteopenia but no fractures: DEFER(Seeman and Eisman, MJA 2004; 180: 298-303)

Who should be treated?

Risk profile Mrs. Smith Mrs. Jones

Age 60 70

BMD T-scores -1.5 -2.0

Prior fracture Yes No

Fall One No

NOF Yes Yes

IOF No No

Australian recommendation

Yes No

Risk factors of fractureNon-modifiable factors• A history of fracture as an adult

• A family history of fracture (first-degree relative)

• Being caucasian

• Advanced age

• Being woman

• Dementia

Ref: Eddy DM, Johnston CC, Cummings SR, et al. Osteoporosis Int 1998;8:S1-S88

Modifiable factors• Cigarette smoking

• Low body weight (<65 kg)

• Estrogen deficiency (early menopause < age 45, bilateral ovariectomy, prolonged premenopausal amenorrhea > 1 year)

• Low calcium intake

• Excessive alcohol intakes

• Impaired vision

• Multiple falls

• Low levels of physical activity

• Poor health/frailty

Association between risk factor and fracture

Risk ratio associated with

Risk factor Any fracture Osteoporotic fracture

Hip fracture

BMD (per SD)1 1.45 1.55 2.07

Prior fracture2 1.77 1.76 1.62

Family hx of fx3 1.19 1.22 1.48

Corticosteroid use4 1.57 1.66 2.25

Current smoking5 1.13 1.13 1.60

Body mass index6 0.98 a

1.01 b

1.02 a

0.96 b

1.42 a

1.00 b

Milk intake7 NA 1.06 1.101Johnell et al, J Bone Miner 2005; 2Kanis et al, Bone 2004; 3Kanis et al, Bone 2004; 4Kanis et al, J Bone Miner Res 2004; 2Kanis et al, Osteoporosis Int 2005; 6De Laet et al, Osteoporosis Int 2005; 7Kanis et al, Osteoporosis Int 2004. a:These are risk ratios were calculated for individuals with BMI = 20 comparing to those with BMI = 25 (as the reference level); b:These are risk ratios were calculated for individuals with BMI = 30 comparing to the reference level. All risk ratios for prior fracture, family history (first degree relative), corticosteroid use, current smoking, BMI and milk intake were adjusted for BMD

Osteoporosis and 15-yr fracture risk – women (Dubbo Osteoporosis Epidemiology Study)

1287 women

Osteoporosis 345 (27%)

Not Osteoporosis

942 (73%)

Fx = 137 (40%)

No Fx = 208 (60%)

No Fx = 751 (80%)

Fx = 191 (20%)

Sensitivity: 42%Specificity = 78%Positive predictive value: 40%

Baseline (1989-1994)

Follow-up:2005

Osteoporosis and 15-yr fracture risk – men (Dubbo Osteoporosis Epidemiology Study)

821 men

Osteoporosis 90 (11%)

Not Osteoporosis

731 (89%)

Fx = 27 (30%)

No Fx = 63 (70%)

No Fx = 640 (88%)

Fx = 91 (12%)

Sensitivity: 30%Specificity = 88%Positive predictive value: 23%

Baseline (1989-1994)

Follow-up:2005

Bone mineral density (BMD) and fracture

0

2

4

6

8

10

12

14

16

18

<0.40

0.40-

0.45-

0.50-

0.55-

0.60-

0.65-

0.70-

0.75-

0.80-

0.85-

0.90-

0.95-

1.00-

1.05-

1.10-

Femoral neck BMD

Pre

vale

nce

(%

)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

10-y

ear

Ris

k o

f F

x

T < 2.5 osteopor

osis

Multifactorial risk

Hip fracture incidence (per 1000 person-years) stratified by femoral neck bone mineral density T-scores and number of risk factors. Nguyen ND, et al. J Bone Miner Res 2005;20:1921-28

Ten-year risk of any fracture by BMD and number of risk factors. Kung AWC, et al. J Bone Miner Res 2007;22:1080-1087

“Risk assessment must consider all relevant factors together, rather than confine to a single test, for nearly all diseases are multifactorials”

(G. Rose. The Strategy of Preventive Medicine. P 41)

HOW ?

A major priority in osteoporosis research is to develop models for identifying individuals with high risk of fracture for early intervention

(L. Raisz. Clinical practice. Screening for osteoporosis. N Engl J Med. 2005 14;353:164-71)

Risk stratification as a prognostic model

Risk assessment in medicine

• Clinical judgmento Inconsistencyo Problem of accuracyo Difficulty in weighting the relative importance of risk

factors

• Probabilistic model Risk stratification approach Individualized approach

Risk stratification

• Identification of risk factors

• Classify each risk factors into categories: low, medium, high

• Combine several risk factors to identify high risk individuals

Risk stratification approach

Risk stratification approach

An example of risk stratification

Patient Age Prior fx BMD Risk of hip fx

Risk of non-vert fx

1 70 No -1.0 0.9 13.1

2 74 No -2.0 0.9 13.1

3 75 No -2.0 1.9 16.5

4 75 No -2.1 3.9 19.8

Examples are calculated from the model presented in Black DM, et al. OI 2001.

Different risk profiles same risk

Similar risk profiles different risk

Risk stratification

Predicted risk from the risk stratification can only be applied to a group of individuals, not to an individual.

Individualization of fracture risk

Individualization of prognosis

• Disease is a personal, not a collective, event.

• In risk assessmento The unit of interest is the individual (not the

population)o The unit of measurement is absolute risk (not

relative risk) o The unit of treatment is disease (not the statistics)

Individualization vs stratification

Individualisation• Absolute risk

• Risk factors are treated in in their continuous scales

• Recognition of an inidvidual’s unique risk profile

• Prognosis applied to an individual

Risk stratification• Relative risk

• Categorisation or dichotomisation of risk factors

• Grouping individuals with similar characteristics

• Prognosis applied to a group of individuals

Individualized prognosis: two individuals with the same age and BMD can have different risks of fracture.

Absolute risk (AR) vs relative risk (RR)

• RR describes the change (increase or decrease) in the likelihood of fracture in a population in comparison to another (referent) population.– It imparts no information about risk for an individual.

• AR quantifies the probability or odds of fracture occurring in an individual.

• “Relative risk is only for researchers; decision call for absolute risk measures” (G Rose)

Categorization vs continuumRisk stratificiation

(categorisation)

• BMD: 3 groups• Age (60+): 3 groups• Fall: 2 groups• Prior fracture: 2 groups

• Total: 36 possible groups

Continuous measurements

• BMD: 400 values• Age (60+): 40 values• Fall: 4 values• Prior fracture: 3 values

• Total: 192,000 individuals

Nomograms in osteoporosis

Nomogram for predicting hip fx in women

Points 0 10 20 30 40 50 60 70 80 90 100

Age (y)55 60 65 70 75 80 85 90 95

BMD T-scores4 3 2 1 0 -1 -2 -3 -4 -5 -6

Prior fracture 0 2

1 >= 3

Fall in the last 12 months 0 2

1

Total Points 0 10 20 30 40 50 60 70 80 90 100 110 120 130

5-year risk0.01 0.05 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

10-year risk0.01 0.05 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.99

>= 3

WOMEN

Example: Mrs. A, 70 years old, has a BMD T-score of -2.5, had a prior fracture and a fall in the past 12 months; her point for age is 9, her BMD point is 65; prior fracture point is approximately 10 and fall point is 4. Her total points is therefore 9+65+10+4=88, and her probability of having a hip fracture is around 0.09 in the next 5 years and 0.17 in the next 10 years. In other words, in 100 women like the woman, one would expect 9 and 17 of them will have a hip fracture in the next 5 years and next 10 years, respectively

Points 0 10 20 30 40 50 60 70 80 90 100

Age (years)55 60 65 70 75 80 85 90 95 100

FNBMD T-scores4 3 2 1 0 -1 -2 -3 -4 -5 -6

Prior fracture (at age >50 yrs)0 2

1 ≥3

Number of falls (past 12 mo)0 2

1 ≥3

Total Points 0 20 40 60 80 100 120 140 160 180

5-year risk0.01 0.05 0.1 0.2 0.3

0.40.5

0.60.7

0.80.9

10-year risk0.05 0.1 0.2 0.3

0.40.5

0.60.7

0.80.9 0.99

14 55

78

0.11

0.22

Risk profile Mrs. Smith Mrs. Jones

Age 60 70

BMD T-scores -1.5 -2.5

Prior fracture One at forearm

No

Fall One No

5-y risk 0.11 0.10

10-y risk 0.22 0.21

Nomogram for predicting fracture risk in a woman

Risk profile Mrs. Smith Mrs. Jones

Age 60 70

BMD T-scores -1.5 -2.5

Prior fracture One at forearm

No

Fall One No

5-y and 10-y risk of fracture

? ?

Mrs. SmithMrs. Jones54

77

0.10

0.21

120 650

10-year hip fracture probability at which intervention becomes cost-effective

1.63

4.47

7.17

11.7

10

1.2

2.9

5.4

9

7.5

1

2.6

4.7

7.26.8

1

3.2

5.7

8.4

6.5

1

2.4

5.8

8.6 8.5

0

5

10

15

50 60 70 80 90 Age

Hip

fx

pro

bab

ility

Australia Germany Japan UK USA

Borgstrom E, et al. Osteoporosis Int 2006; 17:1459-71

0.2 0.5 1.2 1.8 2.7

0.3 0.6 1.5 2.3 3.4

0.4 0.8 1.9 2.9 4.4

0.5 1.1 2.5 3.7 5.6

0.6 1.4 3.2 4.8 7.2

60

65

7075

80

0 -1 -2 -2.5 3

No prior

fracture

0.3 0.7 1.7 2.5 3.8

0.4 0.9 2.1 3.2 4.9

0.5 1.2 2.7 4.1 6.2

0.7 1.5 3.5 5.3 8.0

0.9 2.0 4.5 6.8 10.1

No fall Fall

0.5 1.1 2.6 3.9 5.9

0.6 1.4 3.3 5.0 7.6

0.8 1.9 4.3 6.4 9.6

1.0 2.4 5.5 8.2 12.2

1.3 3.1 7.0 10.4 15.5

60

65

7075

80

0.7 1.6 3.7 5.6 8.4

0.9 2.1 4.7 7.1 10.7

1.2 2.7 6.1 9.1 13.5

1.5 3.4 7.7 11.6 17.1

1.9 4.4 9.9 14.6 21.4

Prior

fracture

Individuals should be treated (based on 5-y risk of hip fx)

Do not need to be treated Should be treated

0 -1 -2 -2.5 3AgeT-score

Application of individualization

• Identifying individuals at high risk of fracture

• Improving clinical decision-making

• Planning intervention trials

• Assisting in creating benefit–risk indices

• Estimating the cost of the population burden of disease

• Designing population prevention strategies

Toward individualization of fracture prognosis

• Nomogram enabling technology for data converge in predictive

medicine. Updatable

• Individualization of risk Maximize predictive power Help select individuals for intervention or counseling

60

65

7075

80

0 -1 -2 -2.5 3

No prior

fracture

No fall Fall

60

65

7075

80

Prior

fracture

Five-year risk of fracture for women

Under 10% 10-15% 15-20% More than 20%

0 -1 -2 -2.5 3AgeT-score

Website

www.FractureRiskCalculator.com

FRAXtm model

Variation in NNTsTrial Agent Risk profile Placebo Active NNT

VERTEBRAL FRACTURE

FIT-I ALN Prev fx, T < -2.5 0.150 0.080 14

PROOF CT Prev fx, T < -2.5 0.156 0.108 21

MORE-2 RLX Prev fx, T < -2.5 0.212 0.147 15

VERT-US RIS Prev fx, T < -2.5 0.163 0.113 20

VERT-MN RIS Prev fx, T < -2.5 0.290 0.181 9

Neer, 2001 PTH 20 mg Prev fx, T < -2.5 0.140 0.050 11

Neer, 2001 PTH 40 mg Prev fx, T < -2.5 0.140 0.040 10

FIT-2 ALN No prev fx 0.027 0.015 83

ALN No prev fx, T<-2.5 0.042 0.021 48

MORE RLX 60 No prev fx 0.045 0.023 45

RLX 120 No prev fx 0.045 0.028 59

TROPOS Strontium T<-2.5 0.129 0.112 59

Strontium Strontium Prev fx 0.328 0.209 8

HORIZON Zoledronate Prev fx 0.109 0.033 13

NNT as a function of absolute risk

0.05 0.10 0.15 0.20 0.25 0.30

10

20

30

40

50

60

70

80

Incidence of vertebral fracture in placebo group

Nu

mb

er

ne

ed

ed

to tr

ea

t (N

NT

)