Bone mass measurement: Prediction of risk

Bone Mass Measurement: R. WASNICH, M.D.,

Prediction

Honolulu, Hawaii

Accurate assessment of individual fracture risk requires measurement of bone mass (density). Another strong risk factor for identifying women or men who will develop fractures in the near future is the presence of previous (spine and nonspine) fractures. However, the occurrence of a low-trauma fracture almost anywhere in the skeleton is indicative of a more advanced stage of disease and is associated with a substantial, further increase in fracture risk, independent of bone mass. Thus, prevention of the first fracture should receive priority. In a clinical setting, initial assessment of bone mass can be combined with other, known risk factors and projected over the patient’s remaining life expectancy, to estimate future, cumulative fracture probability. Estimates such as “remaining lifetime fracture probability” can also approximate the impact and cost-effectiveness of treatment, allowing for more objective and rational therapeutic planning for individual patients.

From the Hawaii Osteoporosis Center, Honolulu, Hawaii. Requests for reprints should be addressed to: R. Wasnich, M.D., Hawaii Osteoporosis Center, 401 Kamakee Street, Honolulu, Hawaii 96814.

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one mass (or density) is clinically useful for one reason: it is a strong risk factor for fractures. Assessment of risk factors has two different, albeit interrelated, purposes. First, risk factors help to elucidate the etiology of the disease, which in turn may lead to public health measures that prevent or reduce disease occurrence. Nutritional deficiency and physical inactivity are good examples of risk factors for osteoporosis, and correction or modification of these risk factors can be recommended for the entire population. Our knowledge of these and many other risk factors is based not so much on a demonstrated relationship to fracture incidence, but rather on their relationship to bone mass, or bone loss. Thus, bone mass serves as a surrogate measurement for multiple other risk factors, many of which cannot be easily measured; for example, adolescent calcium intake may exert a strong influence on attainment of peak bone mass, but it may be difficult, or impossible, to retrospectively estimate in a 50-year-old patient. Current bone mass represents the composite, cumulative effect of many risk factors, both past and present, and including both genetic and lifestyle influences. This may partly explain why a number of studies have concluded that “clinical” risk factors, such as body size, age, diet, and physical activity, are not strong enough to identify individual patients with either low bone mass or high, future fracture probability. Because bone mass serves as a surrogate for many other risk factors, and because bone mass has such a strong relationship to fracture incidence, it might better be considered a “risk indicator” [l]. In this context it is more analogous to measurements of blood pressure. When used as a risk indicator, bone mass demonstrates the second purpose of risk factors, namely, to identify individuals at greatest risk of future fractures, who would most benefit from intervention. In this article, the focus is on bone mass measurements as a clinical risk indicator, as opposed to its use for investigating the etiology of osteoporosis. It is not the purpose of this presentation to discuss the theoretical or technical aspects of bone mass measurements.

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BONE MASS MEASUREMENTAND SPINE FRACTURE

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TABLE I

Both cross-sectional and prospective studies have documented significant associations between low bone mass and increased fracture risk [2]. Both spine and a variety of nonspine fractures, including hip, have been studied, and a variety of different bone mass measurement sites and techniques have been validated. Two prospective studies have documented a relationship to spine fracture incidence. In the Hawaii Osteoporosis Study, the rate of new vertebral fractures increased 2.0-2.4-fold for each standard deviation (SD) decrease in baseline bone density (including linea?* density measurements of the distal and proximal radius, and area density measurements of the calcaneus and lumbar spine) [3,4]. Height, weight, and body mass index were not significant predictors of vertebral fracture incidence, after adjusting for bone mass. In another prospective study involving participants in a clinical trial, 423 postmenopausal women (mean age 65 years) with one to four existing spine fractures were followed for an average of 2.9 years. Baseline bone density was measured at the spine and hip using dual photon absorptiomety and at the spine using quantitative computed tomography. In agreement with the Hawaii study, the rate of new vertebral fractures was 2.0-2.4 times greater with each SD decrement of bone density, adjusted for age and drug treatment [5]. In both studies, bone density measurements remote from the fracture site predicted the risk of spine fractures as well as measurements of the spine itself. Both studies also found that fracture risk increases progressively, and approximately exponentially, with decreasing levels of bone density. Thus, women with bone density equal to the mean or 1 or 2 SD below the mean have approximately two, four, or eight times greater risk, as compared with women with bone density 1 SD above the mean. Both prospective studies discussed here involved postmenopausal women. Men also experience agerelated bone loss, but the magnitude is less than that observed among postmenopausal women [6,7]. Cross-sectional studies have reported osteoporosis risk factors among men [E&10], but no prior prospective studies have examined the relationship between bone mass and fracture incidence among elderly men. At this conference data from the Hawaii study have been reported, indicating that vertebral fractures among men are also associated with low bone mass [II]. The magnitude of association appears to be similar to that observed for women. For each 1 SD decrease in bone mass, mea-

Relative Risks for Differences in Bone Mass of 1 SD Above and Below the Mean Fracture Site

All*

Spinet

Wris@

*Data from [2]. tData from 141. SData from 1141.

sured at the calcaneus, distal radius, and proximal radius, spine fracture risk increases approximately 2-fold.

BONE MASS MEASUREMENTAND NONSPINE FRACTURE Multiple, prospective studies of postmenopausal women have observed associations between low bone density and nonspine fractures [12-191. The largest such study is the Study of Osteoporotic Fractures, a multicenter study of nearly 10,000 women with a mean initial age of 72 years. During a follow-up of 2.2 years, 841 nonspine fractures occurred among 753 women 1181. Fracture incidence of the wrist, foot, humerus, hip, rib, toe, leg, pelvis, hand, and clavicle were significantly related to reduced bone mass. These fractures represented 74% of nonspine fractures. For each 1 SD decrease in bone density, there was an approximate 1.6-fold increased risk of nonspine fractures. Other prospective studies have generally found associations of similar magnitude between bone density and nonspine fracture risk, including the Hawaii Ostepporosis Study (Table I). As with spine fractures, most methods of measuring bone density appear to be comparable in their ability to predict nonspine fractures, regardless of the skeletal site that is measured, or the fracture site being predicted. The Study of Osteoporotic Fractures did report that hip bone density predicted hip fracture risk significantly better than did radius density, but not better than did calcaneal density. On the other hand, measurement of the distal radius was not a significantly better predictor of wrist fracture, compared to measurements of the lumbar spine, femoral neck, or calcaneus.

HETEROGENEOUS DISTRIBUTIONOF BONE MASS? In general, these data indicate that osteoporosis is a systemic disorder in most individuals, and bone

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mass measured distant to the fracture site reflects a deficit comparable to measurements at the fracture site. However, previous studies have also suggested some heterogeneity, particularly in regard to postmenopausal bone loss [20]. This issue has been explored in the Hawaii Osteoporosis Study cohort by converting bone mass measurements at four skeletal sites to age-adjusted Z-scores and then classifying the women into lower, middle, and upper tertiles for each measurement site [21]. Of the women with low bone mass at one site, >85% had evidence of more extensive osteopenia (21 additional low bone mass site). Further, the probability of sustaining a spine fracture increased approximately 1.3-fold for each additional low bone mass site. Thus, women with four low bone mass sites had six times the spine fracture risk of women with no low bone mass sites. These results are consistent with two previous reports suggesting that combining information from bone density measurements of different regions of the skeleton will improve the ability to predict spine fractures [3,5]. It is of interest to examine those women who have a more heterogeneous distribution of bone mass. Approximately 15% of the Hawaii women had low bone mass at some site(s) but high bone mass at other site(s). Their actual risk of spine fracture appears to be intermediate. The reasons for heterogeneity in this subset require further investigation, but possibilities include differential bone loss [22], localized disease effects, differential bone growth [23,24], sports involving preferential appendicular use [25], and differential errors in mea-

NoNE /m/ 10.2

/

/

1.0

HIGH

/

/

4.4

MEDIUM

14.9

/

/

25.1

7.4

/

/

LOW

Figure 1. Influences of bone mass and previous fractures on fracture rate. Bone mass was categorized into three groups of equal numbers of subjects (high, medium, low). The number at the bottom of each bar indicates the rate of new verte. bra1 fractures, relative to the rate among women in the highest bone mass category without any previous fractures. Thus, women with low bone mass and one previous fracture at baseline develop new fractures at a rate 25 times faster than women with high bone mass and no previous fractures. Women with 22 previous fractures and low bone mass (not shown) had a fracture rate 75 times greater than the reference group. (Copyright 1993 by Hawaii Osteoporosis Foundation, used with permission.)

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suring bone mass. Spine bone mass, for example, can be artifactually increased by aortic calcification and degenerative/hypertrophic arthritis [26]. Despite evidence of some heterogeneity at the individual level, population screening with any of the four bone sites (calcaneus, distal radius, proximal radius, and lumbar spine) succeeded in identifying women who, as a group, had a low average bone mass at all four sites [21].

ADDITIONALRISK FACTORS Several additional risk factors have been shown to be independently associated with fracture risk (following adjustment for bone mass), indicating that not all risk factors are expressed via bone mass. Most studies have found an approximate doubling of fracture risk for each lo-year increase in age, following adjustment for bone mass. As noted below, some or all of the age-related increase in vertebral fracture risk may be accounted for by previous fractures. Most fractures among the elderly are associated with mild-to-moderate trauma [18,27-291, although nontraumatic spine fractures appear to be frequent. Variables related to falls or fall protection, including slow gait, weak triceps strength, and weak leg muscles are risk factors for hip fractures, independent of bone mass [30]. It nevertheless appears that most fractures occur among people with low bone mass [31,32]. Thus, preservation of bone mass is likely to prevent many fractures, even if falls cannot be completely eliminated. Another substantial and independent risk factor for future fractures is the presence of existing (previous) fractures. Gardsell et aZ [33] found that previous spine, wrist, and hip fractures were independent predictors of future fragility fractures after adjusting for bone mass and falls, with odds ratios of approximately 2.1-3.1 for previous spine fractures and odds ratios of approximately 1.5-2.4 for previous hip and wrist fractures. In the Hawaii study of Japanese-Americans, women with a single previous vertebral fracture at baseline experienced subsequent spine fractures at a rate 2.6-3.0 times greater than women without previous fractures, independent of bone mass 141. Women with two or more previous fractures developed new fractures at approximately 6.8-9.0 times the rate of women without previous fractures. Thus, each previous fracture had an effect on fracture risk slightly greater than the effect of 1 SD decrease in bone mass. Women with both low bone mass (lowest tertile) and one previous fracture at baseline had a 25-fold increased risk of subsequent spine fractures, compared to women with high bone mass and no previous fractures (Figure 1). The

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TABLE II Cumulative Fracture Risk and Cost-Effectiveness of Prevention Initial Bone Density Percentile*

initial Age

Untreated RLFF’

95th

50

0.5

80 50 80 50 80 50 80

0.7 1.5 0.3 2.5 0.5 5.0 1.1

75th 40th 10th

Number of Fractures Prevented (per person)

0.4 0.03 1.2 0.1 2.0 0.2 3.8 0.4

Cost per Fracture Prevented

$17,700 $62,050 $5,550 517,500 $3,400 $9,650 $1,800 $4,500

is analysis assumes the usual bone loss rate wrll be reduced 90% by treatment, and !atment will continue from the initial age through the remainder of life. *Percentile sed on the distribution of bone density of women at age 50. [Adapted from [37] and

L381.1

Figure 2. The contribution

of etiologic risk factors and clinical risk Indicators

bone mass, and existing fractures)

to Remaining Lifetime

Fracture

(tails,

Probability

(RLFP).

clinical trial discussed previously also found a strong relationship between the number of previous vertebral fractures at baseline and the rate of subsequent spine fractures, similar to the Hawaii study [5]. Two potential mechanisms for this phenomenon have been suggested. The first possibility is that previous fractures serve as a surrogate indicator of some aspect of defective bone quality. The second possibility is mechanical: deformation of one vertebral body may alter the weight distribution, increasing the load borne by other vertebrae. In the Hawaii study, the magnitude of increased risk was similar for both wedge and crush type deformities [4]. Some new fractures occurred adjacent to existing fractures, but new, noncontiguous fractures were also observed. Noncontiguous spinal fractures have been reported for fractures caused by violent trauma [34,35], suggesting that some regions of the spine are more susceptible to fracture. This could potentially be related to variable load distribution, the shape of the spine, or intraspinal variations in bone mass and strength. More recent data from the Hawaii Osteoporosis Study indicate that previous nonspine fractures are also independent predictors of the risk of incident spine fractures [36]. This association is independent of both bone mass and previous spine fractures but November

weaker than the relationship between previous and concurrent spine fractures. These findings suggest the possibility that previous fractures may be surrogate indicators of defects in bone quality not reflected by a single measurement of bone mass. On the other hand, the presence of previous fractures could also be associated with an increased risk of falls, or other risk factors. Estimates of future fracture risk based on a single measurement of bone mass necessarily underestimate actual risk, because bone loss is a cumulative process, and women live an average of >30 years after the menopause. One approach for estimating cumulative risk of future fractures is to calculate the Remaining Lifetime Fracture Probability (RLFP) (Figure 2) [37]. As shown in Table II, RLFP varies considerably, depending on initial age and bone mass. This approach also permits estimation of potential treatment effects on future fracture probability. Older women have fewer years of bone loss and therefore less opportunity to reduce bone loss and fracture risk. Nevertheless, these estimates suggest that pharmacologic treatment to reduce bone loss may be cost-effective for many older women, particularly those who are already at high fracture risk. Also, new treatments that increase bone mass may further improve cost-effectiveness at older ages.

REFERENCES 1. Miettinen OS. Theoretical epidemrology. New York: John Wiley & Sons, 1985. 2. Ross PD, Davis JW, Vogel JM, Wasnich, RD. A critical review of bone mass and the risk of fractures in osteoporosrs [see comments]. Caicif Tissue Int 1990; 46: 14961. 3. Wasnich RD, Ross PD, MacLean CJ, Vogel JM, Davis JW. A comparison of single and multi-srte BMC measurements for assessment of spine fracture probability. J NW Med 1989; 30: 1166-71. 4. Ross PD, Davis JW, Epstein R, Wasmch RD. Pre-existing fractures and bone mass predict vertebral fracture incidence in women. Ann Intern Med 1991; 114: 919-23.

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5. Ross PD, Genant HK, Davis JW, Miller P, Wasnich RD. Osteoporosis 1993; 3: 120-7.

International

6. Davis JW, Ross PD, Vogel JM, Wasnich, RD. Age-related changes in bone mass among Japanese-American men. Bone Miner 1991; 15: 227-36. 7. Orwoll ES, Oviatt SK, McClung MR, Deftos U, Sexton G. The rate of bone mineral loss in normal men and the effects of calcium and cholecalciferol supplementation. Ann Intern Med 1990; 112: 229-34. 8. Seeman E, Melton LJ III, O’Fallon WM, Riggs BL. Risk factors for spinal osteoporoSIS in men. Am J Med 1983; 75: 977-83. 9. Grisso JA, Chiu GY, Maislin G, Steinmann WC, Portale J. Risk factors fractures in men: a preliminary study. J Bone Miner Res 1991; 6: 865-8.

for hip

10. Baillie SF, Davison CE, Johnson FJ, Francis RM. Pathogenesis of vertebral fractures in men. Age Ageing 1992; 21: 139-41.

crush

11. Ross PD, Yhee YK, Davis JW, Wasnich RD. Proceedings of the Fourth International Symposrum on Osteoporosis. Osteopress ApS, Copenhagen, Denmark [in press]. 12. Black DM, Cummings SR, Genant HK, Nevitt MC, Palermo L, Browner W. Axial and appendicular bone density predict fractures in older women. J Bone Miner Res 1992; 7: 633-8. 13. Cooper C, Hannaford P, Croft P, Kay CR. Oral contraceptive tures in women: a prospective study. Bone 1993; 14: 41-5.

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14. Cummings SR, Black D, Nevitt MC, Browner WS, Cauley JA, Genant HK, Mascioli SR, Scott JC, Seeley DG, Steiger P, Vogt TM. Appendicular bone density and age predict hip fracture in women. The Study of Osteoporotic Fractures Research Group [see comments]. JAMA 1990; 263: 665-8. 15. HUI SL, Slemenda CW, Johnston CC Jr. Basellne measurement of bone mass predicts fracture in white women. Ann Intern Med 1989; 111: 355-61. 16. Porter RW, Miller CG, Grainger D, Palmer SB. Prediction of hip fracture in elderly women: a prospective study [see comments]. Br Med J 1990; 301: 638-41. 17. Smith DM, Khairi MRA, Johnston CC Jr. The loss of bone mineral with aging and its relationship to risk of fracture. J Clin Invest 1975; 56: 311-8. 18. Seeley DG, Browner WS, Nevitt MC, Genant HK, Scott JC, Cummings SR. Which fractures are associated with low appendicular bone mass in elderly women? The Study of Osteoporotic Fractures Research Group. Ann Intern Med 1991; 115: 83742. 19. Wasnich RD, Ross Pd, Heilbrun LK, Vogel JM. Prediction of postmenopausal fracture risk with use of bone mineral measurements. Am J Obstet Gynecol 1985; 153: 745-51. 20. Riggs BL, Wahner HW, Melton Ill JL, Richelson LS, Judd HL, Offord KP. Rates of bone loss in the appendicular and axial skeletons of women. Evrdence of substantial vertebral bone loss before menopause. J Clin invest 1986; 77 1487-91.

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21. Davis JW, Ross PD, Wasnich RD. Evidence for both generalized and regional low bone mass among elderly women. J Bone Min Res (in press). 22. Riis B, Thomsen K, Christiansen C. Does calcium supplementation prevent postmenopausal bone loss? A double-blind, controlled clrnical study. N Engl J Med 1987; 316: 173-7. 23. Drinkwater BL, Nelson KL, Chestnut CS, Bremner QJ, Shainholz S, Southworth MB. Bone mineral content of amenorrheic and eumenorrheic athletes. N Engl J Med 1984; 311: 277-81. 24. Nelson ME, Fisher EC, Catsos PD, Meredith CN, Turksoy RN, Evans WJ. Dret and bone status in amenorrheic runners. Am J Clin Nutr 1986; 43: 910-7. 25. Huddleson AL, Rockwell D, Dulund DN. Bone mass in lifetime tennis athletes. JAMA 1980; 244: 1107-g. 26. Ross PD, Wasnich, RD, Vogel JM. Detection of prefracture spinal osteoporosis using bone mineral absorptiometry. J Bone Miner Res 1988; 3: l-11. 27. Cooper C, Atkinson EJ, O’Fallon WM, Melton !J Ill. Incidence of clinrcally diag nosed vertebral fractures: a population-based study in Rochester, Minnesota, 1985. 1989. J Bone Miner Res 1992; 7: 221-7. 28. Fujrwara S, Mizuno S, Ochi Y, Sasaki H, Kodama K, Russel WJ, Hosoda Y. The incidence of thoracic vertebral fractures in a Japanese population, Hiroshima and Nagasaki, 1958-86. J Clin Epidemiol 1991; 44: 1007-14. 29. Melton LJ III, Cummings SR. Heterogeneity of age-related fractures: rmplications for eprdemiology. Bone Miner 1987; 2: 321-31. 30. Nevitt MC, Cummings SR. In: Christiansen C, et al, eds. Osteoporosis 1990. Copenhagen: Osteopress ApS, 1990; 146-7. 31. Ross PD, Wasnich RD, Heilbrun LK, Vogel JM. Definition of a spine fracture threshold based upon prospective fracture risk. Bone 1987; 8: 271-8. 32. Ryan PJ, Blake GM, Fogelman I. Fracture thresholds in osteoporosrs: rmplications for hormone replacement treatment. Ann Rheum Dis 1992; 51: 1063-5. 33. Gardsell P, Johnell 0, Nilsson BE, Nilsson JA. The predictive value of fracture, disease, and falling tendency for fragility fractures in women. Calcif Tissue Int 1989; 45: 327-30. 34. Powell JN, Waddell JP, Tucker WS, Transfeldt EE. Multiple-level noncontiguous spinal fractures. J Trauma 1989; 29: 1146-51. 35. Henderson RL, Reid DC, Saboe LA. Multiple noncontiguous spine fractures. Multiple noncontiguous spine fractures. Spine 1991; 16: 128-31. 36. Wasnich RD, Davis JW, Ross PD. Both spine and non-spine prevalent fractures Increase the risk of new spine fractures. J Bone Miner Res 1992; 7(Suppl 1): S138. 37. Wasnich RD, Ross PD, Vogel JM, Davrs JW. Osteoporosis. Critique and Practrcum. Honolulu: Banyan Press, 1989. 38. Ross PD, Davis JW, Wasnich RD, Vogel JM. Optimizing treatment regimens for osteoporosis. In: Christiansen C, et al, eds. Osteoporosis 1990. Copenhagen: Osteopress ApS, 1990; 1096-g.

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