1. Identification of individuals at high- risk of fracture Tuan V. Nguyen Garvan Institute of Medical Research Sydney, Australia

2. Contents Who should be treated: current guidelines Beyond bone mineral density Prognostic models of fracture Individualization of prognosis Applications of individualized prognosis

3. Consider two cases … Risk profileMrs. SmithMrs. Jones Age6070 BMD T-scores-1.5-2.0 Prior fractureOne at the forearm No FallOneNo Who should be treated?

4. 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)

5. 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)

6. Who should be treated? Risk profileMrs. SmithMrs. Jones Age6070 BMD T-scores-1.5-2.0 Prior fractureYesNo FallOneNo NOFYes IOFNo Australian recommendation YesNo

7. Risk factors of fracture Non-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 1 year) Low calcium intake Excessive alcohol intakes Impaired vision Multiple falls Low levels of physical activity Poor health/frailty

8. Association between risk factor and fracture Risk ratio associated with Risk factorAny fractureOsteoporotic fracture Hip fracture BMD (per SD) 1 1.451.552.07 Prior fracture 2 1.771.761.62 Family hx of fx 3 1.191.221.48 Corticosteroid use 4 1.571.662.25 Current smoking 5 1.13 1.60 Body mass index 6 0.98 a 1.01 b 1.02 a 0.96 b 1.42 a 1.00 b Milk intake 7 NA1.061.10 1Johnell 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

9. 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

10. 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

11. Bone mineral density (BMD) and fracture T < 2.5 osteoporosis

12. 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

13. “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 ?

14. 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)

15. Risk stratification as a prognostic model

16. Risk assessment in medicine Clinical judgment oInconsistency oProblem of accuracy oDifficulty in weighting the relative importance of risk factors Probabilistic model  Risk stratification approach  Individualized approach

17. Risk stratification Identification of risk factors Classify each risk factors into categories: low, medium, high Combine several risk factors to identify high risk individuals

18. Risk stratification approach

20. An example of risk stratification PatientAgePrior fxBMDRisk of hip fx Risk of non-vert fx 170No0.913.1 274No-2.00.913.1 375No-2.01.916.5 475No-2.13.919.8 Examples are calculated from the model presented in Black DM, et al. OI 2001. Different risk profiles  same risk Similar risk profiles  different risk

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

22. Individualization of fracture risk

23. Individualization of prognosis Disease is a personal, not a collective, event. In risk assessment oThe unit of interest is the individual (not the population) oThe unit of measurement is absolute risk (not relative risk) oThe unit of treatment is disease (not the statistics)

24. 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.

25. 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)

26. Categorization vs continuum Risk 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

27. Nomograms in osteoporosis

28. Nomogram for predicting hip fx in 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

29. 14 55 78 0.11 0.22 Risk profileMrs. SmithMrs. Jones Age6070 BMD T-scores-1.5-2.5 Prior fractureOne at forearm No FallOneNo 5-y risk0.110.10 10-y risk0.220.21 Nomogram for predicting fracture risk in a woman Risk profileMrs. SmithMrs. Jones Age6070 BMD T-scores-1.5-2.5 Prior fractureOne at forearm No FallOneNo 5-y and 10-y risk of fracture ?? Mrs. Smith Mrs. Jones 5 4 77 0.10 0.21 12 0 65 0

30. 10-year hip fracture probability at which intervention becomes cost-effective Borgstrom E, et al. Osteoporosis Int 2006; 17:1459-71

31. 0.20.51.21.82.7 0.30.61.52.33.4 0.40.81.92.94.4 0.51.1 2.5 3.75.6 0.61.43.24.87.2 60 65 70 75 80 0-2-2.53 No prior fracture 0.30.71.72.53.8 0.40.92.13.24.9 0.51.22.74.16.2 0.71.5 3.5 5.38.0 0.92.04.56.810.1 No fallFall 0.51.12.63.95.9 0.61.43.35.07.6 0.81.94.36.49.6 1.02.4 5.5 8.212.2 1.33.17.010.415.5 60 65 70 75 80 0.71.63.75.68.4 0.92.14.77.110.7 1.22.76.19.113.5 1.53.4 7.7 11.617.1 1.94.49.914.621.4 Prior fracture Individuals should be treated (based on 5-y risk of hip fx) Do not need to be treated Should be treated 0-2-2.53 Age T-score

32. 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

33. 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

34. 60 65 70 75 80 0-2-2.53 No prior fracture No fallFall 60 65 70 75 80 Prior fracture Five-year risk of fracture for women Under 10% 10-15%15-20%More than 20% 0-2-2.53 Age T-score

35. Website www.FractureRiskCalculator.com FRAX tm model

36. Variation in NNTs TrialAgentRisk profilePlaceboActiveNNT VERTEBRAL FRACTURE FIT-IALNPrev fx, T < -2.50.1500.08014 PROOFCTPrev fx, T < -2.50.1560.10821 MORE-2RLXPrev fx, T < -2.50.2120.14715 VERT-USRISPrev fx, T < -2.50.1630.11320 VERT-MNRISPrev fx, T < -2.50.2900.1819 Neer, 2001PTH 20 mgPrev fx, T < -2.50.1400.05011 Neer, 2001PTH 40 mgPrev fx, T < -2.50.1400.04010 FIT-2ALNNo prev fx0.0270.01583 ALNNo prev fx, T<-2.50.0420.02148 MORERLX 60No prev fx0.0450.02345 RLX 120No prev fx0.0450.02859 TROPOSStrontiumT<-2.50.1290.11259 Strontium Prev fx0.3280.2098 HORIZONZoledronatePrev fx0.1090.03313

37. NNT as a function of absolute risk