Fracture Risk With Multiple Myeloma: A Population-Based Study

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1 JOURNAL OF BONE AND MINERAL RESEARCH Volume 20, Number 3, 2005 Published online on November 29, 2004; doi: /JBMR American Society for Bone and Mineral Research Fracture Risk With Multiple Myeloma: A Population-Based Study L Joseph Melton III, 1 Robert A Kyle, 2 Sara J Achenbach, 3 Ann L Oberg, 3 and S Vincent Rajkumar 2 ABSTRACT: Pathologic fractures, especially of the axial skeleton, are extremely common in patients with multiple myeloma and cluster around the time of diagnosis. Osteoporotic fractures seem to be less of a problem in these patients. Introduction: It is generally believed that fractures are common in patients with multiple myeloma as a result of lytic bone lesions, generalized bone loss, and/or elevated bone turnover from excessive cytokine production, but the actual risk of pathologic versus osteoporotic fractures has not been quantified. Materials and Methods: In a population-based retrospective cohort study, 165 Olmsted County, MN, residents with myeloma diagnosed from 1945 to 2001 (55% men; mean age, 70.7 ± 11.1 years) were followed for 537 person-years. The relative risk of fractures was assessed by standardized incidence ratios (SIRs), and risk factors were evaluated in proportional hazards models. Results: Altogether, 134 patients experienced 463 fractures. In the year before diagnosis, 16 times more fractures were observed than expected, mostly pathologic fractures of the vertebrae and ribs. Subsequently, there was a 9-fold increase in fracture risk. However, 69% of these fractures were pathologic, and another 11% were found incidentally on myeloma monitoring. With the latter two groups excluded, subsequent fracture risk was elevated 3-fold, with a 2-fold increase in the risk of an osteoporotic fracture. In multivariate analyses, the predictors of overall fracture risk were oral corticosteroid use and elevated serum calcium levels, whereas pathologic fractures were additionally predicted by use of chemotherapy. Conclusion: There is a dramatic increase in fractures around the time of diagnosis of myeloma, most of which are pathologic fractures. The most important predictor of overall fracture risk is oral corticosteroid use. J Bone Miner Res 2005;20: Published online on November 29, 2004; doi: /JBMR Key words: multiple myeloma, cohort study, epidemiology, osteoporosis, vertebral fracture INTRODUCTION MULTIPLE MYELOMA HAS long been recognized as an important cause of pathologic fractures, especially of the axial skeleton. Although the fractures have typically been attributed to lytic bone lesions, (1) the exact nature of the association is not entirely clear. Thus, myeloma patients can also have generalized bone loss, (2 8) although less severely affected patients may have little bone loss outside the spine. (9 11) The extent to which such bone loss is caused by concomitant chemotherapy (12) or risk factors for osteoporosis (6) has not been resolved. Moreover, most myeloma patients are of advanced age, (13) and fractures are common in the elderly in any event. (14) Finally, the association of myeloma with fractures may be exaggerated to the extent that skeletal problems bring patients to clinical attention in the first place. (15) To address these issues, we determined the long-term risk of fracture at all skeletal sites among the inception cohort of Olmsted County, MN, residents first The authors have no conflict of interest. diagnosed with multiple myeloma from 1945 to Our specific objectives were to define the timing of the myeloma diagnosis relative to the occurrence of fractures; to quantify the contribution of pathologic fractures to overall fracture risk; to estimate the risk of osteoporotic fractures, exclusive of pathologic fractures; and to identify the patient characteristics most closely associated with fractures of different types. These data are germane to nearly 15,000 Americans who develop multiple myeloma each year. (16) MATERIALS AND METHODS Olmsted County is well suited for disease association studies such as this because comprehensive medical records for the residents are available for review and are accessible through a centralized index to diagnoses made by essentially all medical care providers used by the local population. (17) After approval by Mayo s Institutional Review Board, we used this unique database (the Rochester Epidemiology Project) to identify the 165 patients who resided in Olmsted County when diagnosed with multiple myeloma 1 Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota, USA; 2 Division of Hematology, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA; 3 Division of Biostatistics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota, USA. 487

2 488 from 1945 to (18) Review of their medical records for research was authorized in accordance with Minnesota privacy law. (19) All of them had a clinical picture compatible with multiple myeloma and met the following criteria, which were consistent across time: (1) 10% or more abnormal plasma cells in the bone marrow or histologic proof of plasmacytoma and (2) at least one of the following three features: monoclonal protein (M-protein) in the serum, M- protein in the urine, or lytic bone lesions/pathologic fractures. Patients with smoldering myeloma (e.g., Durie- Salmon Stage I (20) ) were not included. Otherwise, because of complete community coverage and redundancy of the data system, (17) we believe that myeloma case ascertainment in this population is complete. (18) After additional approval by the Institutional Review Board, these patients were followed forward in time through their linked medical records in the community (retrospective cohort study) until death or the most recent clinical contact. All inpatient and outpatient records at any local provider of medical care were searched by trained nurse abstractors for the occurrence of any fracture. Mayo Clinic records, for example, contain the details of every inpatient hospitalization, every outpatient office or clinic visit, all emergency room and nursing home care, as well as all laboratory results and all radiographic and pathology reports, including autopsies, and all correspondence with each patient. (17) The records contained the clinical history and the radiologist s report of each fracture, but the original radiographs were not available for review. Thus, the diagnosis of vertebral fracture was accepted on the basis of a radiologist s report of compression or collapse of one or more thoracic or lumbar vertebrae. (21) Ascertainment of clinically evident fractures is also believed to be complete. Fractures were classified according to the circumstances of the injury: by convention, daily activities and falls from standing height or less were considered moderate trauma, whereas motor vehicle accidents and falls from a greater height were deemed severe trauma. In addition, based on review of complete contemporary medical record documentation, we distinguished fractures that were attributed by the attending physicians to a specific pathological lesion, mainly multiple myeloma (pathologic fractures), and we also identified fractures that were only discovered because of radiographic monitoring of myeloma patients for skeletal lesions (incidental fractures). The influence of myeloma on fracture risk was evaluated using four basic methods of analysis, all carried out in SAS (SAS Institute, Cary, NC, USA). The primary analysis compared the number of fractures observed at each skeletal site (based on the first fracture of a given type per person) to the number expected in this cohort during their follow-up in the community, that is, standardized incidence ratios (SIRs). Expected numbers were derived by applying calendar year-, age-, and sex-specific incidence rates from the local population for these fractures (21 28) to the calendar year-, age-, and sex-specific person-years of follow-up in the myeloma cohort and summing over the strata. 95% CIs for the SIRs were calculated, assuming the expected rates are fixed and the observed fractures follow a Poisson distribution. (29) This methodology was extended to include the period before myeloma diagnosis. The expected fractures (from 10 years before up to 10 years after diagnosis) were estimated using a generalized additive model assuming a Poisson error structure with an offset term for the expected rate and the terms, age, sex, and time from diagnosis. Time from the diagnosis date was modeled using a natural spline with nodes every 30 days for time periods within 5 years of diagnosis and every year for time periods >5 years before or after the diagnosis date. In the second method of analysis, the cumulative incidence of a new fracture (1 minus the probability of survivalfree-of-fracture) was projected for up to 10 years after the myeloma diagnosis date using product-limit methods. (30) In the customary approach, patients who die are censored; when the death rate is high, this overestimates cumulative fracture incidence as perceived by attending physicians. Therefore, we treated death as a competing event in this analysis. (31) In addition, patients were censored if lost to follow-up, but this happened infrequently in this cohort. Kaplan-Meier methods were also used to assess survival, with expected death rates from the Minnesota white population. Observed and expected cumulative incidence estimates, as well as survival curves, were compared using the log-rank test. (32) In the final approach, Andersen-Gill time-to-fracture regression models (33) were used to assess the impact of various covariates (e.g., age, calendar year of diagnosis, corticosteroid use, other causes of secondary osteoporosis) on the subsequent risk of fracture among the myeloma patients. These models allow for use of multiple fractures per subject, while appropriately accounting for the correlation. Univariate relationships between the risk of specific fractures and each clinical characteristic under consideration were first assessed. Stepwise methods with forward selection and backward elimination were used to choose independent variables for the final models. The dependent variable was time until fracture, and the independent variables were age, sex, and the clinical characteristics at baseline; the various drug exposures were handled as time-dependent variables, as were pathologic fractures. For both univariate and multivariate models, the assumption of proportional hazards was examined and was not violated for the variables considered. RESULTS MELTON ET AL. All but two of the Olmsted County residents with multiple myeloma were white, reflecting the racial composition of the community (98% white in 1980). Their mean age at diagnosis was 70.7 ± 11.1 (SD) years (median, 72.5 years; range, years), and 90 (55%) were men. The clinical characteristics of these patients are delineated in Table 1. On average, these patients had been attended in the community for 36 years (median, 39 years) before recognition of their myeloma and for 3.3 years afterward (median, 1.7 years). Altogether, 463 different fractures were observed in these patients: 238 before and 225 after the diagnosis of myeloma. To obtain some sense of the relative timing, we compared the number of fractures observed with the number expected from 10 years before the diagnosis of my-

3 MYELOMA AND FRACTURES 489 TABLE 1. CLINICAL CHARACTERISTICS OF 165 OLMSTED COUNTY, MN, RESIDENTS DIAGNOSED WITH MULTIPLE MYELOMA IN Baseline variables Value Time-dependent variables Value Prior osteoporotic fracture (% yes) 25.5 Pathologic fracture (% ever) 53.9 Bone lesions on X-ray (% yes) 52.1 Corticosteroid use (% ever) 72.1 Hemoglobin (median g/dl) 11.4 Any chemotherapy use (% ever) 74.5 Serum calcium (median mg/dl) 9.6 Nitrosourea use (% ever) 24.8 Serum creatinine (median mg/dl) 1.2 Cytotoxic antibiotic use (% ever) 23.6 Serum M-spike (median mg/dl) 2.8 Alkylating agent use (% ever) 66.7 Serum heavy chain (% IgG) 56.8 Vinca alkaloid use (% ever) 27.3 Serum heavy chain (% IgA) 22.7 Other chemotherapy agents (% ever) 14.5 Serum light chain (% kappa) 56.1 Anticoagulant use (% ever) 7.9 Serum light chain (% lambda) 40.2 Anticonvulsant use (% ever) 1.8 Urine M-spike (median g/24 h) 0.2 Diuretic use (% ever) 29.1 Bone marrow plasma cells (median %) 40.0 Thyroid replacement use (% ever) 11.5 Height (median cm) Statin use (% ever) 1.8 Weight (median kg) 70.7 Bisphosphonate use (% ever) 7.9 Risk factor for falling (% yes) 70.3 Estrogen use (% ever in women) 18.7 Risk factor for secondary osteoporosis (% yes) 61.2 Bilateral oophorectomy (% yes in women) 21.3 Smoked cigarettes (% yes of known) 47.0 Used alcohol (% yes of known) 64.6 Limited activity (% yes) 29.7 eloma to 10 years afterward (shown in Fig. 1). More than 1 year before the recognition of myeloma, there was some elevation in fracture risk (SIR, 1.5; 95% CI, ), but there were 16 times (95% CI, 13 19) more fractures observed than expected in the year immediately preceding diagnosis. In this group, the median time between fracture and diagnosis was 18 days, and 61% occurred within 6 weeks before the diagnosis of myeloma. The majority (57%) of these were pathologic fractures caused by lytic bone lesions, mainly in the vertebrae and ribs. Were the pathologic fractures to be excluded, however, there was still an excess of fractures in the year before diagnosis (SIR, 6.9; 95% CI, ). The primary analysis focused on fracture risk after the diagnosis of multiple myeloma. These 165 subjects were followed subsequently for a total of 537 person-years. Survival was clearly impaired in this cohort: after 10 years, only 9% remained alive compared with an expected 55% (p < 0.001). Follow-up was essentially complete: 92% of the subjects were followed until death (median, 1.5 years of followup per subject), and the median duration of follow-up among survivors was 4.3 years. During this period of observation, 96 subjects experienced 225 different fractures (Table 2). Sixty-nine patients had no subsequent fracture, whereas 35 patients had a single fracture, 26 had two, 16 had three, and 19 had four or more. After 10 years of follow-up, an actuarially estimated 58% of these patients had experienced at least one new fracture compared with an expected 6% (p < 0.001) as shown in Fig. 2. Only 3 fractures (1%) were caused by severe trauma (e.g., fall from a height), and 60 more (26%) were attributed to moderate trauma (Table 2). Of these, 16 fractures were caused by a fall from standing height or less, whereas 44 (mostly vertebral and rib fractures) occurred spontaneously in the course of everyday activities. However, the majority of fractures (156, 69%) resulted from a specific pathological lesion FIG. 1. Ratio of observed to expected fracture incidence (and 95% CI) by time before and after the diagnosis of multiple myeloma among 165 Olmsted County, MN, residents initially diagnosed in (lines at the bottom of the figure indicate the occurrence of fractures). (almost all in the axial skeleton, especially the vertebrae and ribs), and the etiology of the remaining 6 fractures was uncertain. Compared with expected rates, there was a 9-fold increase (95% CI, ) in overall fracture risk after the diagnosis of myeloma. The increase was statistically significant among men (SIR, 10; 95% CI, ) as well as women (SIR, 7.9; 95% CI, ). The relative risk of fractures at specific skeletal sites for men and women separately is delineated in Table 3. For both sexes combined, statistically significant increases were seen for most fractures in the axial skeleton, particularly the vertebrae (SIR, 33; 95% CI, 25 41). Overall, the relative risk of any axial fracture was 14 (95% CI, 11 17) compared with only 2.0 (95% CI, ) for all limb fractures combined.

4 490 MELTON ET AL. TABLE 2. DISTRIBUTION OF FRACTURES AMONG 165 OLMSTED COUNTY, MN, RESIDENTS AFTER A DIAGNOSIS OF MULTIPLE MYELOMA IN , BY FRACTURE SITE AND CAUSE Fracture cause Severe trauma Fall from standing Spontaneous Pathological Uncertain All causes Fracture site n %* n %* n %* n %* n %* n % Skull/face 0 (0) 1 (100) 0 (0) 0 (0) 0 (0) 1 (0.4) Hands/fingers 2 (40) 1 (20) 0 (0) 1 (20) 1 (20) 5 (2.2) Distal forearm 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0.0) Proximal humerus 0 (0) 1 (50) 0 (0) 1 (50) 0 (0) 2 (0.9) Other arm 0 (0) 0 (0) 0 (0) 5 (100) 0 (0) 5 (2.2) Clavicle/scapula/sternum 0 (0) 0 (0) 1 (8) 10 (83) 1 (8) 12 (5.3) Ribs 1 (2) 3 (5) 8 (13) 45 (75) 3 (5) 60 (26.7) Thoracic/lumbar vertebrae 0 (0) 1 (1) 35 (30) 82 (69) 0 (0) 118 (52.4) Cervical vertebrae 0 (0) 0 (0) 0 (0) 2 (100) 0 (0) 2 (0.9) Pelvis 0 (0) 2 (29) 0 (0) 5 (71) 0 (0) 7 (3.1) Proximal femur 0 (0) 5 (71) 0 (0) 2 (29) 0 (0) 7 (3.1) Other leg 0 (0) 1 (25) 0 (0) 3 (75) 0 (0) 4 (1.8) Feet/toes 0 (0) 1 (50) 0 (0) 0 (0) 1 (50) 2 (0.9) All sites 3 (1.3) 16 (7.1) 44 (19.6) 156 (69.3) 6 (2.7) 225 (100) * Percentage (%) of each type of fracture. Percentage (%) of total. FIG. 2. Observed vs. expected cumulative incidence (p < 0.001) of any fracture among 165 Olmsted County, MN, residents after an initial diagnosis of multiple myeloma in , with death considered a competing risk. As previously noted, however, 156 of the 225 subsequent fractures were pathological. Fifty-three percent of these occurred within 1 year after diagnosis, and 67% within 2 years. When pathologic fractures were excluded, the overall risk of a subsequent fracture was still elevated but not to the same degree (SIR, 3.4; 95% CI, ). An additional 24 fractures (22 vertebral and 2 rib fractures) were only discovered incidentally in the course of myeloma monitoring. When these also were excluded, the overall risk of fracture was still elevated (SIR, 2.8; 95% CI, ). However, the fractures that might properly be ascribed to osteoporosis include only those caused by minimal or moderate trauma. These data are also shown in Table 3. With the pathologic and incidental fractures excluded, the risk of any subsequent moderate trauma vertebral fracture was elevated 4-fold (95% CI, ) compared with 33-fold when all thoracic and lumbar spine fractures were included. The only other statistically increased risk was for rib fractures (SIR, 4.5; 95% CI, ). The risk of any osteoporotic fracture (hip, spine, or wrist fracture caused by moderate trauma but not pathologic nor incidental) was somewhat elevated (SIR, 2.1; 95% CI, ). After 10 years, an estimated 9% of the myeloma patients had experienced at least one new osteoporotic fracture compared with an expected 5% (p 0.036). The predictors of these fractures were assessed in multivariate models. The initial analysis excluded laboratory values that were missing on some patients in this historical cohort dating back to The main independent predictors of any subsequent fracture among the myeloma patients were a history of prior pathologic fractures (hazard ratio [HR], 1.8; 95% CI, ) and use of oral corticosteroids for more than the median duration ( 91 days; HR, 1.6; 95% CI, ). Any use of corticosteroids was of marginal significance (p 0.053). In this analysis, there was no additional, independent effect of cumulative corticosteroid dose (median, 4793 mg prednisone equivalent). When laboratory values were allowed in the model, fracture risk was also positively associated with the serum calcium level at diagnosis (HR, 1.2; 95% CI, ). Serum monoclonal protein (M-spike) results were not associated with fracture risk even in the univariate analysis, nor were heavy chain or light chain types (data not shown). There was no independent association of overall fracture risk with the other variables listed in Table 1. There was a suggestion that the likelihood of fracture declined in more recent years, but this effect was not statistically significant. Pathologic fractures, specifically, also were predicted by history of a previous pathologic fracture (HR, 2.0; 95% CI, ), as well as by any use of chemotherapy (HR, 2.1; 95% CI, ). In univariate analyses, the risk of pathologic fractures was elevated among patients exposed to nitrosoureas (e.g., carmustine; HR, 2.1; 95% CI, ), cy-

5 MYELOMA AND FRACTURES 491 TABLE 3. FRACTURES OBSERVED (Obs)* AMONG 165 OLMSTED COUNTY, MN, RESIDENTS AFTER A DIAGNOSIS OF MULTIPLE MYELOMA IN COMPARED WITH THE NUMBERS EXPECTED (Exp) AND SIRs, WITH 95% CI Both sexes (Non-pathological, non-incidental fractures due to moderate trauma) Both sexes (All fractures) Women (All fractures) Men (all fractures) Obs Exp SIR (95% CI) Obs Exp SIR (95% CI) Obs Exp SIR (95% CI) Obs Exp SIR (95% CI) Fracture site Skull/face (0 9.5) (0.1 29) ( ) (0.1 18) Hands/fingers (0.9 13) (0.4 13) (1.39 4) (0.4 13) Distal forearm (0 11) (0 2.8) (0 2.2) ( ) Proximal humerus (0.1 16) ( ) ( ) ( ) Other arm (2.0 28) (0.6 17) (2.2 16) ( ) Clavicle/scapula/sternum (6.0 31) (3.0 29) (6.6 24) ( ) Ribs (9.8 22) (8.8 22) (11 20) ( ) Thoracic/lumbar vertebrae (34 67) (17 34) (25 41) ( ) Cervical vertebrae (0 21) (2.6 76) (0.9 26) (0.0 25) Pelvis (2.2 31) (1.3 12) (2.4 13) ( ) Proximal femur ( ) ( ) ( ) ( ) Other leg ( ) ( ) ( ) ( ) Feet/toes (0 7.9) ( ) ( ) (0.5 16) Any site (7.6 14) (5.8 10) (7.2 11) ( ) * Note that the number of fractures observed at specific skeletal sites may differ from those reported in Table 1 because only the first fracture of each type per patient was counted in this analysis. totoxic antibiotics (e.g., adriamycin; HR, 2.0; 95% CI, ) and alkylating agents (e.g., melphalan, alkeran; HR, 2.2; 95% CI, ); similar associations with vinca alkaloids (e.g., vincristine; HR, 1.6; 95% CI, ) and other chemotherapy agents (HR, 1.3; 95% CI, ) were not statistically significant. In the multivariate analysis, anticoagulant use was also an independent predictor of pathologic fractures (HR, 2.4; 95% CI, ), as was the serum calcium level at baseline (HR, 1.2; 95% CI, ) when laboratory values were allowed to enter the model. The independent predictors of an osteoporotic fracture, on the other hand, were history of a prior osteoporotic fracture (HR, 3.6; 95% CI, ) as well as use of thyroid replacement therapy (HR, 5.7; 95% CI, ). In addition, use of anticonvulsants (HR, 18; 95% CI, ) or statins (HR, 11; 95% CI, ) was significantly associated with fracture risk, but only three patients were exposed to each drug. Higher serum calcium level was not a predictor of osteoporotic fractures; indeed, the effect, although not statistically significant, was protective in the univariate analysis (HR, 0.8; 95% CI, ). DISCUSSION In this first population-based study, we confirm the longstanding clinical impression that fracture risk is dramatically elevated among patients with multiple myeloma. Of interest, however, is the observation that the risk was concentrated around the time of initial diagnosis. In fact, it appeared that the condition often came to clinical attention because of a fracture. As also expected, two-thirds of the fractures observed were pathologic fractures caused by the myeloma process itself. This is in contrast to the community situation, where only 2% of all fractures among adults are pathological, and most are caused by metastatic malignancy. (28) Finally, the risk of limb fractures was not elevated to the same extent as fractures of the axial skeleton, presumably because of the absence of hematopoietic marrow at peripheral skeletal sites among older adults. (7) Seventy-eight percent of all fractures in this cohort occurred in the axial skeleton, and this also differs from the general population, where axial fractures comprise only one-third of the total. (28) However, axial fractures in multiple myeloma were more likely pathological than osteoporotic. Indeed, the risk of a subsequent osteoporotic fracture was elevated only 2-fold after a diagnosis of myeloma, which was somewhat less than the 2.5-fold increase in osteoporotic fractures seen among Olmsted County residents with monoclonal gammopathy of undetermined significance (MGUS). (34) The discrepancy may be caused in part by classification of some osteoporotic vertebral fractures as pathological in the setting of myeloma but not in patients with MGUS who, by definition, do not have lytic bone lesions. (35) Despite the 2-fold increase in osteoporotic fractures, generalized osteoporosis would not seem to be a pressing problem in these patients, especially given their short average survival. Indeed, the cumulative incidence of any osteoporotic fracture after 10 years was only 9%. Moreover, the use of bisphosphonate therapy to

6 492 manage lytic bone lesions (36) should also control any elevated bone turnover and/or excessive bone loss from underlying osteoporosis. (37) The risk factors identified for these fractures are not unexpected. The association of corticosteroid use with fracture risk is well established. (38) Likewise, it is not surprising that the risk of a pathologic fracture was linked to prior pathologic fractures and treatment with chemotherapy, which can have adverse effects on bone. (12) Because the majority of all subsequent fractures were pathological, prior pathologic fractures predicted overall fracture risk as well. In particular, those with prior pathologic fractures at the time of the myeloma diagnosis generally represent patients with stage III disease. (20) The association of fractures with hypercalcemia likely reflects the elevated serum calcium levels seen with extensive bone involvement in myeloma. (39) In contrast, it is low serum calcium levels that are linked with osteoporotic fractures. (40) Other studies have documented an increase in osteoporotic fractures associated with a prior history of osteoporotic fractures (41) and with use of anticonvulsants (42) or thyroid replacement therapy. (43) However, the seemingly dramatic increase in fracture risk associated with statin use was based on a very small number of subjects, and much larger studies in the general population have found no such association. (44) This study has a number of strengths. The study subjects represented a large, population-based inception cohort registered at the time their myeloma was first recognized. Because of the unique records linkage system in Rochester, which provides access to the medical records of the entire community, (17) there should be complete ascertainment of myeloma to the extent that the condition came to clinical attention. (18) Clinical characteristics were recorded before any knowledge of resulting fractures, which were documented in the detailed inpatient and outpatient medical records that spanned each subject s entire period of residency in the community. Fracture ascertainment should be nearly complete because the vast majority come to medical attention, (28) and monitoring for skeletal involvement in myeloma detected even asymptomatic rib and vertebral fractures. There are also corresponding limitations of a study based on medical records. In particular, measurements of bone density or biochemical markers of bone turnover were not routinely performed, so the role of bone loss in fracture risk could not be assessed directly. A further limitation may be the generalizability of these data from a small Midwestern community that is predominantly white and better educated than the white population of the United States as a whole. (17) Nonetheless, the incidence of hip fractures in this community is quite comparable with national figures for United States whites generally. (26) Moreover, the incidence of multiple myeloma has been stable in Olmsted County, and rates are comparable with those from the Cancer Surveillance, Epidemiology, and Results System for this region of the country. (18) Despite these potential limitations, these are the only population-based data that quantify the risk of fracture associated with an initial diagnosis of multiple myeloma. ACKNOWLEDGMENTS The authors thank Leona Bellrichard, RN; Marcia Erickson, RN; Barbara Nolte, RN; and Kristine Otto-Higgins, RN, for assistance with data collection and Mary Roberts for help in preparing the manuscript. This project was supported in part by Grants AG-04875, CA-62242, and AR from the National Institutes of Health, U.S. Public Health Service. REFERENCES MELTON ET AL. 1. Callander NS, Roodman GD 2001 Myeloma bone disease. Sem Hematol 38: Mariette X, Khalifa P, Ravaud P, Frija J, Laval-Jeantet M, Chastang C, Brouet JC, Fermand JP 1992 Bone densitometry in patients with multiple myeloma. Am J Med 93: Holmes JA, Evans WD, Cole RJ, Ramsahoye B, Whittaker JA 1994 Dual energy X-ray absorptiometry measurements of bone mineral density in myeloma. Eur J Haematol 53: Roux C, Ravaud P, Cohen-Solal M, de Vernejoul MC, Guillemant S, Cherruau B, Delmas P, Dougados M, Amor B 1994 Biologic, histologic and densitometric effects of oral risedronate on bone in patients with multiple myeloma. Bone 15: Mariette X, Bergot C, Ravaud P, Roux C, Laval-Jeantet M, Brouet J-C, Fermand J-P 1995 Evolution of bone densitometry in patients with myeloma treated with conventional or intensive therapy. Cancer 76: Diamond T, Levy S, Day P, Barbagallo S, Manoharan A, Kwan YK 1997 Biochemical, histomorphometric and densitometric changes in patients with multiple myeloma: Effects of glucocorticoid therapy and disease activity. Br J Haematol 97: Dhodapkar MV, Weinstein R, Tricot G, Jagannath S, Parfitt AM, Manolagas SC, Barlogie B 1998 Biologic and therapeutic determinants of bone mineral density in multiple myeloma. Leuk Lymphoma 32: Diamond T, Levy S, Smith A, Day P, Manoharan A 2001 Non-invasive markers of bone turnover and plasma cytokines differ in osteoporotic patients with multiple myeloma and monoclonal gammopathies of undetermined significance. Intern Med J 31: Ingeberg S, Deding A, Jensen MK 1982 Bone mineral content in myelomatosis. Acta Med Scand 211: Abildgaard N, Brixen K, Kristensen JE, Vejlgaard T, Charles P, Nielsen JL 1996 Assessment of bone involvement in patients with multiple myeloma using bone densitometry. Eur J Haematol 57: Laroche M, Pouillès JM, Dromer C, Attal M, Ribot C 1996 Dual-energy x-ray absorptiometry in patients with multiple myeloma and benign gammopathies. Clin Exp Rheumatol 14: Pfeilschifter J, Diel IJ 2000 Osteoporosis due to cancer treatment: Pathogenesis and management. J Clin Oncol 18: Kyle RA, Gertz MA, Witzig TE, Lust JA, Lacy MQ, Dispenzieri A, Fonseca R, Rajkumar SV, Offord JR, Larson DR, Plevak ME, Therneau TM, Greipp PR 2003 Review of 1027 patients with newly diagnosed multiple myeloma. Mayo Clin Proc 78: Cummings SR, Melton LJ 2002 Epidemiology and outcomes of osteoporotic fractures. Lancet 359: Lahtinen R, Laakso M, Palva I, Virkkunen P, Elomaa I 1992 Randomised, placebo-controlled multicenter trial of clodronate in multiple myeloma. Lancet 340: American Cancer Society 2003 Cancer Facts and Figures American Cancer Society, Atlanta, GA, USA. 17. Melton LJ III 1996 History of the Rochester Epidemiology Project. Mayo Clin Proc 71:

7 MYELOMA AND FRACTURES Kyle RA, Therneau TM, Rajkumar SV, Larson DR, Plevak MF, Melton LJ 2004 Incidence of multiple myeloma in Olmsted County, Minnesota: Trend over six decades. Cancer 101: Melton LJ III 1997 The threat to medical-records research. N Engl J Med 337: Durie BGM, Salmon SE 1975 A clinical staging system for multiple myeloma: Correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival. Cancer 36: Cooper C, Atkinson EJ, O Fallon WM, Melton LJ III 1992 Incidence of clinically diagnosed vertebral fractures: A population-based study in Rochester, Minnesota, J Bone Miner Res 7: Garraway WM, Stauffer RN, Kurland LT, O Fallon WM 1979 Limb fractures in a defined population. I. Frequency and distribution. Mayo Clin Proc 54: Melton LJ III, Sampson JM, Morrey BF, Ilstrup DM 1981 Epidemiologic features of pelvic fractures. Clin Orthop 155: Rose SH, Melton LJ III, Morrey BF, Ilstrup DM, Riggs BL 1982 Epidemiologic features of humeral fractures. Clin Orthop 168: Arneson TJ, Melton LJ III, Lewallen DG, O Fallon WM 1988 Epidemiology of diaphyseal and distal femoral fractures in Rochester, Minnesota, Clin Orthop 234: Melton LJ III, Atkinson EJ, Madhok R 1996 Downturn in hip fracture incidence. Public Health Rep 111: Melton LJ III, Amadio PC, Crowson CS, O Fallon WM 1998 Long-term trends in the incidence of distal forearm fractures. Osteoporos Int 8: Melton LJ III, Crowson CS, O Fallon WM 1999 Fracture incidence in Olmsted County, Minnesota: Comparison of urban with rural rates and changes in urban rates over time. Osteoporos Int 9: Cox DR 1953 Some simple approximate tests for Poisson variates. Biometrika 40: Kaplan EL, Meier P 1958 Non-parametric estimation from incomplete observations. J Am Stat Assoc 53: Gooley TA, Leisenring W, Crowley J, Storer BE 1999 Estimation of failure probabilities in the presence of competing risks: New representations of old estimators. Stat Med 18: Kalbfleisch JD, Prentice RL 1980 The Statistical Analysis of Failure Time Data. John Wiley and Sons, New York, NY, USA. 33. Therneau TM, Grambsch PM 2000 Modeling Survival Data: Extending the Cox Model. Springer-Verlag, New York, NY, USA. 34. Melton LJ III, Rajkumar SV, Khosla S, Achenbach SJ, Oberg AL, Kyle RA 2004 Fracture risk in monoclonal gammopathy of undetermined significance. J Bone Miner Res 19: Kyle RA, Therneau TM, Rajkumar SV, Offord JR, Larson DR, Plevak MF, Melton LJ III 2002 A long-term study of prognosis in monoclonal gammopathy of undetermined significance. N Engl J Med 346: Berenson JR, Hillner BE, Kyle RA, Anderson K, Lipton A, Yee GC, Biermann JS 2002 American Society of Clinical Oncology Clinical Practice Guidelines: The role of bisphosphonates in multiple myeloma. J Clin Oncol 20: Watts NB 2001 Treatment of osteoporosis with bisphosphonates. Rheum Dis Clin North Am 27: van Staa TP, Leufkens HGM, Cooper C 2002 The epidemiology of corticosteroid-induced osteoporosis: A meta-analysis. Osteoporos Int 13: Clines GA, Guise TA 2003 Hypercalcemia in hematologic malignancies and in solid tumors associated with extensive localized bone destruction. In: Favus MJ (ed.) Primer on the Metabolic Bone Diseases and Disorders of Mineral Metabolism, 5th ed. American Society for Bone and Mineral Research, Washington, DC, USA, pp Riggs BL, Khosla S, Melton LJ III 1998 A unitary model for involutional osteoporosis: Estrogen deficiency causes both Type I and Type II osteoporosis in postmenopausal women and contributes to bone loss in aging men. J Bone Miner Res 13: Klotzbuecher CM, Ross PD, Landsman PB, Abbott TA III, Berger M 2000 Patients with prior fractures have an increased risk of future fractures: A summary of the literature and statistical synthesis. J Bone Miner Res 15: Stein E, Shane E 2003 Secondary osteoporosis. Endocrinol Metab Clin North Am 32: Greenspan SL, Greenspan FS 1999 The effect of thyroid hormone on skeletal integrity. Ann Intern Med 130: Bauer DC, Mundy GR, Jamal SA, Black DM, Cauley JA, Ensrud KE, van der Klift M, Pols HAP 2004 Use of statins and fracture: Results of 4 prospective studies and cumulative metaanalysis of observational studies and controlled trials. Arch Intern Med 164: Address reprint requests to: LJ Melton III, MD Division of Epidemiology Department of Health Sciences Research Mayo Clinic 200 First Street S.W. Rochester, MN 55905, USA Received in original form June 21, 2004; revised form August 31, 2004; accepted September 28, 2004.