The Longest Title in the Meeting

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1 The Longest Title in the Meeting Steven R. Cummings, MD, FACP S.F. Coordinating Center Financial support from several companies that make treatments for osteopenia and osteoporosis

2 "What is critical for a meaningful indication/diagnosis, and how such definition could relate to drug development, including Phase 3 registration clinical trials and drug labeling"

3 Should a Biomarker Cut Point Serve All of These Purposes? Steven R. Cummings, MD, FACP S.F. Coordinating Center Financial support from several companies that make treatments for osteopenia and osteoporosis

4 Osteoporosis: Analogy for Sarcopenia Imperfect: People feel getting weaker People don t feel loss of bone density

5 Osteoporosis: Analogy for Sarcopenia Imperfect: People feel getting weaker People don t feel loss of bone density But development of Sarcopenia resembles development of Osteoporosis in 1990s We can learn from that history

6 Osteoporosis: a success story Osteoporosis is recognized as a disease BMD T-score <-2.5 is an indication for treatment BMD is widely available, strongly associated with fracture risk is a useful for drug development

7 Osteoporosis: a cautionary tale BMD definition of Osteoporosis increased awareness But created an epidemic of Osteopenia BMD Osteoporosis led to over and under treatment BMD is a poor surrogate marker

8 Should one definition of a marker to serve all of these needs? Diagnosis Indication for treatment Enrollment in Phase III trials? Drug labeling Target for drug development

9 No

10 Outline Potential uses of a the marker Diagnosis Indication for treatment Enrollment in Phase III trials? Drug labeling Target for drug development

11 Osteoporosis: the clinical diagnosis signs and symptoms Before BMD, osteoporosis meant painful vertebral fractures. A disease that warrants treatment Goal: 2 prevention of fracture

12 BMD Osteoporosis In 1980s-90s, densitometry became widely available A cut-point was needed to define osteoporosis

13 Decreased bone mineral density (BMD) increases the risk of fracture Continuous No apparent cut point

14 Defining osteoporosis A World Health Organization committee met in Geneva in 1992 Days of expert review of data

15 Mean hip BMD T-score It was decided to use T-scores T-score = SDs from young adult mean -1 SD, T = -1.0, (~10% below) Age

16 Mean hip BMD T-score It was decided to use T-scores The prevalence of Osteoporosis will dramatically increase with age Age

17 Defining osteoporosis Fracture is the outcome Hip BMD the strongest predictor of hip fracture No natural cut-point

18 Defining osteoporosis No natural cut-point At T<-2.0, the prevalence of osteoporosis (45%) seemed too high.

19 Defining osteoporosis No natural cut-point At T<-2.0, the prevalence of osteoporosis (45%) seemed too high. At T<-3.0, it seemed too low (<5%)

20 Goldilock s problem Too high, too low Smaller effect is important to health Larger effect is important for your budget

21 The Goldilocks Solution At T<-2.5, the prevalence (15%) seemed OK Smaller effect is important to health Larger effect is important for your budget -3.0 T -2.5 Just right At T<-2.5, the prevalence (15%) was OK -2.0

22 The Goldilocks Solution At T<-2.5, the prevalence (15%) seemed OK Smaller effect is important to health Larger effect is important for your budget -3.0 T -2.5 Just right At T<-2.5, the prevalence (15%) was OK -2.0 A white woman s lifetime risk of hip fracture = 15%

23 It worked! BMD-Osteoporosis became a common disease Became an entry criterion for trials and an indication for drug treatment Insurers paid for BMD measurements to make diagnoses Doctors got a billing code for osteoporosis Millions of patients have been screened Millions started drug therapy

24 Osteopenia T-score -1.0 to -2.5 Added to increase awareness No knows why -1.0 was chosen The mean value at age 55 By definition about 50% of postmenopausal women have osteopenia

25 Prevalence of BMD-Osteoporosis and Osteopenia % who have hip BMD T<-2.5 Age Osteoporosis Osteopenia Normal BMD Few elderly women are normal

26 Unintended consequences: labelling Millions get a diagnosis X You have severe Osteopenia >50% with abnormal BMD report anxiety ~25% limit activities to avoid falling

27 Potential uses of a marker Diagnosis Indication for treatment Enrollment in Phase III trials Drug labeling Target for drug development

28 The problem with treatment based on a marker: Women with the same BMD have different risk Femoral neck T-score = -2.5 Age Hip fx risk % % & smoker 8.0%

29 Older women without osteoporosis have a high risk Femoral neck T-score = -2.5 Age Hip fx risk % % & smoker 8.0% & T= %

30 Why absolute risk Assuming treatment produces similar reductions in relative risk. Patients with higher absolute risk of the outcome will have proportionally greater reductions in risk

31 Higher risk means greater benefit Treatment reduces risk 40% Age Hip fx risk Benefit % 0.7% % 2.0% & smoker 8.0% 3.2% & T= % 2.1%

32 Treatment based on marker (BMD) cut point leads to over- and under treatment Guidelines: treat BMD T <-2.5 Many young women with low risk get drug therapy Millions of older women with a high risk but BMD T>-2.5 are not treated Guidelines are moving to treatment thresholds based on risk

33 Treatment threshold Treatment threshold is the risk of the outcome (fractures or mobility disability) above which treatment is cost-effective The treatment threshold is derived from cost-effectiveness analysis

34 % Risk/10 Years Treatment Thresholds are Levels of Risk High risk Benefits of treatment outweigh costs Low risk Costs outweigh benefits Treatment Threshold

35 New guidelines based on risk US NOF Guidelines: Based on cost-effectiveness analysis for alendronate For women with low bone mass: Treat if the 10 year risk is: 20% for major clinical fractures 3% for hip fracture

36 UK guidelines are based entirely on fracture risk

37 Estimating risk WHO sponsored project Combined risk factor data from many cohorts around the world FRAX (Fracture Risk Index) 9 risk factors BMD is not needed for risk assessment

38

39 BMD T-score for enrollment in registration trials BMD T-score <-2.5 Became the entry criteria for most trials Became an indication for treatment

40 BMD T-score for enrollment in registration trials BMD T-score <-2.5 Became the entry criteria for most trials Became an indication for treatment However, Trials excluded older women with high risk of fracture but T-score > -2.5 Big evidence gap: What are the benefits of drug therapy for these millions of women?

41 Absolute risk determines enrollment in clinical trials Determines the number of events Determines the power and sample size Enrollment should be based on absolute risk of fracture

42 Does the level of the biomarker matter? Perhaps those with lower BMD (or decreased strength) have greater relative risk reduction If so, then requiring low BMD would increase the size of the effect And decrease the sample size

43 Diagnosis Potential uses of a marker Indication for treatment Enrollment in Phase III trials Drug labeling Target and surrogate marker for drug development

44 Validating surrogate markers Valid surrogate markers would make drug development more efficient FDA approval based on validated surrogate endpoints would reduce size and cost of registration trials

45 Validating surrogate markers Show that change in the marker in individuals predicts reduction in risk Established by Percent of Treatment Effect Explained (PTE) Must measure change in the marker from baseline to a follow-up PTE =100%: all the efficacy is due to change in the marker PTE = 0%: efficacy is not due to change in the marker

46 Change in BMD is a poor surrogate PTE is <25% for most effective drugs Adding markers for bone resorption and formation substantially improves PTE Drug development now uses several markers besides BMD

47 Sarcopenia

48 Sarcopenia

49 Potential uses of a marker cut-point Diagnosis Indication for treatment Enrollment in Phase III trials? Drug labeling Target for drug development

50 Start with Clinical Sarcopenia Disability Associated with slowness, weakness, low mass Needs work-up for causes and treatment Goal: prevention of worse outcomes

51 Marker Sarcopenia In people without disability For prevention Sarcopenia is a risk factor for. The most important step is to define the main outcome Mobility disability is attractive: important and common

52 Defining Marker Sarcopenia is valuable Increase the clinical recognition of the importance of muscle weakness Diagnosis code for billing Reimbursement for measurement of muscle function One criterion for enrollment in trials A starting point for FDA and clinical trials

53 Choosing a cut-point for Marker Sarcopenia The association between a marker (strength) and disability is continuous No natural biological thresholds Based on consensus of influential organizations

54 Beware The marker and cut points will be widely used to call disease T-scores will lead to a high prevalence of disease in older people More generous cut points for mild sarcopenia will lead to an epidemic of labeling

55 Potential uses of a sarcopenia marker Diagnosis Indication for treatment Enrollment in Phase III trials? Drug labeling Target for drug development

56 Treatment will eventually be based treatment thresholds Marker Sarcopenia is a risk factor for disability Other risk factors also determine risk of disability

57 Patients with the same strength, mass, gait speed will have different risk of disability Patients with strength = MM Age Disability /10 years 60 years 5% 70 years 10% & diabetes 15% & smoker 20%

58 Mobility Risk Index (MAX) will be useful Risk factors may include Strength Walking speed Age BMI Comorbidities (diabetes) Risk factors (smoking)

59 Mobility Risk Index (MAX) will be useful Risk factors may include Strength Walking speed Age BMI Comorbidities (diabetes) Risk factors (smoking) Contact Peggy Cawthon

60 Designing prevention trials Requires a consensus primary outcome Enrollment is based on risk of that outcome Estimate of risk should include a marker (strength) responsive to treatment Determines effect size

61 Diagnosis Potential uses of a marker Enrollment in Phase III clinical trials Indication and treatment guidelines Drug labeling Target and surrogate marker for drug development

62 Designing trials to validate better surrogate markers Effective treatments may work in several ways there will be many surrogates mitochondria, damage repair, calcium flux Validating surrogate markers requires collecting samples and measurements at baseline and follow-up in all subjects

63 Important characteristics of the marker depends on the purpose Diagnosis Treatment decisions & trial enrollment Drug development

64 For diagnosis Widely available, low cost Strength of association with risk (fracture, disability) Precision is less important

65 Hip BMD is sufficient. Once BMD is known, other BMDs do not add to prediction of hip or nonspine fractures

66 For diagnosis of sarcopenia Grip strength, walking speed, DXA widely available and inexpensive How strongly associated with disability? Once strength is known, do other measures improve prediction?

67 For treatment decisions, indications and enrollment in trials Widely available, low cost Strength of association with risk Precision is much less important

68 For surrogate markers (and monitoring effects of treatment) Accurate measure of underlying biology Strength of association with risk Precision is very important

69 Summary A biomarker cut point will not serve all purposes

70 Diagnosis Start with clinical Sarcopenia based on disability, slowness and weakness For Marker Sarcopenia: Choice of marker and cut point is based on consensus Acknowledge the limits: it is a risk factor, not a disease Beware of T-scores, labeling, over treatment

71 For treatment and clinical trials Agree on a main outcome Pool data for MAX Eventually, develop treatment thresholds based on cost effectiveness of therapies Base enrollment for phase III trials on estimated risk of disability, including a marker responsive to treatment

72 For drug development Assess many markers in trials with clinical outcomes Collect samples, images, and measurements at baseline and follow-up in all patients in all trials with clinical outcomes A collaborative effort across sponsors

73 Thank you

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