Osteoporos Int DOI 10.1007/s00198-014-3012-y

REVIEW

Is calcaneal quantitative ultrasound useful as a prescreen stratification tool for osteoporosis? K. Thomsen & D. B. Jepsen & L. Matzen & A. P. Hermann & T. Masud & J. Ryg

Received: 4 December 2014 / Accepted: 17 December 2014 # International Osteoporosis Foundation and National Osteoporosis Foundation 2015

Abstract Calcaneal quantitative ultrasound (QUS) is attractive as a prescreening tool for osteoporosis, alternative to dualenergy X-ray absorptiometry. We investigated the literature of the usability of calcaneal QUS. We found large heterogeneity between studies and uncertainty about cutoff, device, and measured variable. Despite osteoporosis-related fractures bei n g a m a j o r h ea l t h i s s u e , os t e o p o r o s i s r em a i n s underdiagnosed. Dual-energy X-ray absorptiometry (DXA) of the hip or spine is currently the preferred method for diagnosis of osteoporosis, but the method is limited by low accessibility. QUS is a method for assessing bone alternative to DXA. The aim of this systematic review was to explore the usability of QUS as a prescreen stratification tool for assessment of osteoporosis. Studies that evaluated calcaneal QUS with DXA of the hip or spine as the gold standard was included. We extracted data from included studies to calculate number of DXAs saved and misclassification rates at cutoffs equal to high sensitivity and/or specificity. The number of DXAs saved and percentage of persons misclassified were

measures of usability. We included 31 studies. Studies were heterogeneous regarding study characteristics. Analyses showed a wide spectrum of percentage of DXAs saved (2.7– 68.8 %) and misclassification rates (0–12.4 %) depending on prescreen strategy and study characteristics, device, measured variable, and cutoff. Calcaneal QUS is potentially useful as a prescreen tool for assessment of osteoporosis. However, there is no consensus of device, variable, and cutoff. Overall, there is no sufficient evidence to recommend a specific cutoff for calcaneal QUS that provides a certainty level high enough to rule in or out osteoporosis. Calcaneal QUS in a prescreen or stratification algorithm must be based on device-specific cutoffs that are validated in the populations for which they are intended to be used.

Electronic supplementary material The online version of this article (doi:10.1007/s00198-014-3012-y) contains supplementary material, which is available to authorized users.

Introduction

K. Thomsen (*) : T. Masud : J. Ryg Institute of Clinical Research, University of Southern Denmark, Sdr. Boulevard 29 Entrance 112, 7th floor, 5000 Odense C, Denmark e-mail: [email protected] D. B. Jepsen : L. Matzen : J. Ryg Department of Geriatric Medicine, Odense University Hospital, Sdr. Boulevard 29 Entrance 112, 7th floor, 5000 Odense C, Denmark A. P. Hermann Department of Endocrinology, Odense University Hospital, Sdr. Boulevard 29 Entrance 93, 5000 Odense C, Denmark T. Masud Nottingham University Hospital Trust, City Hospital Campus, Derby Road, Nottingham NG7 2UH, UK

Keywords Calcaneal quantitative ultrasound . Dual-energy X-ray absorptiometry . Osteoporosis . Prescreening

Fractures related to osteoporosis are widely recognized as an important health problem because of their significant morbidity, mortality, and cost. The prevalence of osteoporosis in the European Union (EU) is estimated at 27.6 million and is three to four times higher in women over the age of 50 than in men [1]. Worldwide, nearly 9 million estimated fractures annually are related to osteoporosis [2]. According to the WHO consensus report, osteoporosis is defined as “a disease characterized by low bone mass and microarchitectorial deterioration of bone tissue, leading to enhanced bone fragility and consequent increase in fracture risk”[3]. The operational definition of osteoporosis is based on a bone mineral density (BMD) with a value that is 2.5 SD or

Osteoporos Int

more below the young female adult mean [3]. The current standard method for assessment of BMD is dual-energy X-ray absorptiometry (DXA) of the hip and/or spine [4]. Despite osteoporosis-related fractures being a major health issue, osteoporosis remains underdiagnosed [5]. Low accessibility to DXA could be one of many explanations. Calcaneal quantitative ultrasound (QUS) is an alternative technique for assessing bone. Compared to DXA, QUS has the advantages of being cheaper, portable, and free of ionizing radiation [6]. The method assesses bone by measuring the propagation of ultrasound waves at varying frequencies. Two variables are routinely measured, velocity and attenuation. Measures of velocity are termed speed of sound (SOS) or velocity of sound (VOS), and attenuation is termed broadband ultrasound attenuation (BUA) [7]. Velocity and attenuation have been combined through different algorithms to form a combined score called the stiffness index (SI) or quantitative ultrasound index (QUI). Calcaneus is the most studied skeletal site for QUS assessment because of the high percentage of trabecular bone and its easy accessibility [8]. A new test can serve one of three roles. One role of the new test could be as a replacement for the current diagnostic method. Another potential role is the new test used before the existing test, in a triage or prescreen algorithm. The third role is that the new test can be used in addition to the existing method [9]. The ability of calcaneal QUS to replace current diagnostic method has been previously evaluated. Several studies have compared the ability of QUS and DXA to predict fracture. The risk of fracture is increased 1.5–2.5 times for every one standard deviation decrease in QUS-measured variable, which is comparable to DXA of the hip and spine [10–12]. However, the ability of QUS to replace DXA is limited by the lack of consensus of diagnostic criteria for osteoporosis using QUS and by uncertainties about treatment decisions based on QUS measurements since there is no direct evidence that patients identified by QUS will benefit from treatment [13, 14]. The usefulness of calcaneal QUS in a prescreen algorithm has been previously studied in a meta-analysis, which concluded that this technique was not sufficiently reliable to rule in or out DXA-determined osteoporosis at commonly used thresholds [15]. The analyses were limited by large heterogeneity between studies and were restricted to Hologic Sahara and the QUI variable. The usefulness of a test as a prescreen method is influenced by the main purpose of the test. For osteoporosis, the main purpose of a prescreen test is to filter out those with a very low risk of having the disease and restrict further investigation with DXA to those with a high risk of osteoporosis. For that purpose, a high sensitivity is required. Other researchers have suggested another triage approach selecting two cutoffs at device-specific sensitivity and specificity levels of 90 or

95 % [16, 17]. This practice could identify those with a high and low risk of the disease and restrict further testing to those who cannot be sufficiently categorized. In order to assess if calcaneal QUS is beneficial, the percentage of persons who do not need additional testing (DXA spine and hip) is important. Furthermore, from a clinical perspective, the clinician needs to know the cutoff levels that provide enough assurance to either rule in or out osteoporosis. The aim of this study was to perform a systematic review firstly, to explore the relationship between cutoff and accuracy of calcaneal QUS to identify postmenopausal women with DXA-determined osteoporosis and secondly to investigate the ability of QUS to reduce the number of patients who need referral for DXA at cutoffs corresponding to 90–95 % certainty levels.

Method Data sources A systematic literature search was conducted June 1, 2014. The search included search engines: EMBASE and MEDLINE, using the following keywords: (heel OR calcaneus OR calcaneal) AND (osteoporosis OR bone mineral density OR bone densitometry) AND (ultrasound OR ultrasonic OR ultrasonography OR ultrasonographic) AND (dxa OR dexa OR “dual-energy X-ray absorptiometry”). The age limit for the search was above 19 years. The searches were supplemented by reviewing reference lists from relevant review articles. Study selection Studies were eligible for the review if they met all of the following inclusion criteria: (a) the population studied was postmenopausal women or women above the age of 45 years, (b) the index test was calcaneal QUS and the reference test DXA of the hip and/or spine, (c) the study provided sufficient data for assessment of diagnostic accuracy, i.e., true-positive, false-positive, true-negative, and false-negative counts for the index test, and (d) target condition was osteoporosis defined by T-score at the hip and/or spine of 2.5 SD or more below the young female adult mean. Articles other than written in English, German, or Scandinavian languages and all reviews were excluded. The titles and abstracts of the references were identified, and irrelevant studies were eliminated (KT). Full publications were retrieved for any citation that potentially met the inclusion criteria. Two reviewers (KT, DJ) independently reviewed the full publications and selected the studies according to predefined criteria as above. Disagreements were resolved by consensus and, if necessary, by adjudication from another coauthor (JR).

Osteoporos Int

Assessment of methodological quality Quality assessment of the included studies was performed using the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS2), which is a tool validated and recommended by the Cochrane Diagnostic Accuracy Test working group [18, 19]. The tool consists of four key domains: (1) patient selection, (2) index test, (3) reference test, and (4) flow and timing. Each domain is assessed in terms of the risk of bias, and the first three domains are also assessed in terms of concerns of applicability. We modified the tool by removing a question about blinding the test interpreter to the results of the reference standard, since test results are objective and not influenced by the interpreter. Results are presented in a table as suggested by the tool. Data extraction Information on study population, sample size, recruitment, prevalence of osteoporosis, and criteria for exclusion was extracted. Moreover, we extracted information of the index and reference test devices, bone variables, any reported thresholds, T-score reference population, and osteoporosis definition used. Data required for calculating true-positive (TP), false-positive (FP), true-negative (TN), and falsenegative (FN) counts for the index test were extracted. Statistics The measurements of QUS cannot be compared across devices because of a large degree of technical diversity of QUS devices and variables [17]. In order to establish an overview of the spectrum of accuracy results, we computed a forest plot of the sensitivity and specificity with the corresponding 95 % CI for device- and variable-specific subgroups and different cutoffs. Since heterogeneity between studies was high, a summary score was not computed. To evaluate the performance of calcaneal QUS as a prescreen tool at cutoffs corresponding to sensitivity or specificity levels ≥90 %, analyses were restricted to studies that reported either sensitivity and/or specificity >85 %, not to miss borderline cases. We evaluated calcaneal QUS as a DXA-saving prescreen tool, according to three different triage algorithms: 1. Low-risk stratification (LRS): Calcaneal QUS must identify persons with low risk of having osteoporosis, and these persons will not need DXA. Studies using cutoffs high enough (upper cutoff) to ensure a sensitivity >85 % were included in these analyses. A high sensitivity is required to minimize number misclassified as low risk of osteoporosis (false negative). Persons with bone measurements above this upper

cutoff were classified low risk. The percentage of savable DXAs and the misclassification rate are calculated as described in appendix. 2. High-risk stratification (HRS): Calcaneal QUS must identify persons with high risk of having osteoporosis, and these persons will not need DXA. Studies using cutoffs low enough (lower cutoff) to ensure specificity >85 % were included in these analyses. A high specificity is required to minimize number misclassified as high risk of osteoporosis (false positive). Persons with bone measurements below this lower cutoff were classified high risk. The percentage of savable DXAs and the misclassification rate are calculated as described in appendix. 3. Combined strategy (CS): Combining LRS and HRS will identify three groups, one with low risk of osteoporosis (LRS), one with high risk of osteoporosis (HRS), and one equivocal for those who are not classified either high or low risk of osteoporosis, and these will require referral for DXA. The percentage of savable DXAs and the misclassification rates are calculated as described in appendix. We followed the analytical methods and standards according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and the guidelines of Diagnostic Test Accuracy Working Group by the Cochrane Collaboration, and we assessed the methodological quality of the included studies [19, 20].

Results Study selection (Fig. 1) The flowchart describing the study selection process is shown in Fig. 1. The search provided 924 citations. After adjusting for duplicates, 568 remained. Of these, 404 were discarded after reviewing title and abstract, because the paper clearly did not meet inclusion criteria. Another 32 citations were discarded due to language criteria. Additional seven citations were identified by checking references of relevant reviews. The full texts of remaining 132 citations were examined in detail, and 31 citations met the inclusion criteria. Study design characteristics (Tables 1, 2, 3, and 4) The studies included in the review were divided into subgroups according to the manufacturer and device of the index test. Thirteen studies evaluated the accuracy of Achilles, Achilles Plus, Achilles Express, or Achilles Insight [21–33]. Twelve studies evaluated Hologic Sahara [34–45], and six

Osteoporos Int Fig. 1 Flowchart of literature search. Search terms: (heel OR calcaneus OR calcaneal) AND (osteoporosis OR bone mineral density OR bone densitometry) AND (dxa OR dexa OR “dualenergy X-ray absorptiometry”). 1 Some studies excluded for more than one reason, 2true positive, 3 false positive, 4true negative, 5 false negative

Literature search: EMBASE 1974-june2014 (n=487) MEDLINE up till June 2014 (n=437) Reference list from relevant reviews (n=7)

Excluded duplicates (n=363)

Citations screened, from title or title and abstract (n=568) Excluded Not relevant (n=404) Other languages than English, German, Danish, Swedish or Norwegian (n=32) Full-text articles assessed for eligibility (n=132)

Excluded1 Not relevant population: a. Men and women (n=21) b.Not postmenopausal women (n=32) Fracture as reference (n=7) Wrong osteoporosis definition (n=4) No relevant measures (n=12) Only correlation reported (n=22) Not sufficient data to calculate TP2, FP3, TN4, FN5 (n=10)

Included (n=31)

studies evaluated CUBA Clinical or CUBA MarkII [27, 46–50], and three studies used other devices [22, 38, 51]. Three studies investigated more than one device [22, 27, 38]. The studies were heterogeneous in regard to settings, some samples being recruited from the general population through either registries, invites to study participation, or when visiting their general practitioner and other samples being recruited among women attending a BMD testing center. Two studies did not report the setting [23, 28]. Most studies (n=14) investigated women referred for BMD testing [29, 30, 33, 35, 46, 37–39, 27, 31, 44, 32, 48, 45]. Eight studies reported exclusion of participants with diseases or taking medication known to affect bone metabolism [35–37, 25, 26, 42, 29, 33], 10 did not exclude such participants [34, 21, 22, 46, 23, 38, 28, 43, 30, 32], and 13 studies did not describe any exclusion criteria [24, 39, 27, 40, 41, 51, 47, 44, 48, 49, 45, 50]. DXA T-score ≤−2.5 at the lumbar spine and/or hip was the most frequently

used reference site for diagnosis of osteoporosis (n=20) [34, 21, 35, 46, 37, 38, 25, 27, 40–42, 47, 43, 31, 32, 48, 45, 50, 23, 51], nine studies used the hip only [22, 36, 24, 39, 26, 28, 44, 33, 49], one study used the lumbar spine only [38], and one study did not report the reference site [30]. For studies that evaluated Achilles devices (n=13), sample sizes ranged from 40 to 500, and the prevalence of osteoporosis ranged from 9.8 to 54 %. SI T-score was the variable evaluated by most studies of the Achilles studies (n=10) [21, 23–32] (Table 1). For studies that evaluated Hologic Sahara (n=12), sample sizes ranged from 38 to 772, and the prevalence of osteoporosis ranged from 7.1 to 59 %. QUI was the variable evaluated by most studies (n=5) [35, 36, 41–43] (Table 2). For studies that evaluated CUBA (n=6), sample sizes ranged from 46 to 326, and the prevalence of osteoporosis ranged from 14 to 59 %. Most studies evaluated BUA [46–50] (Table 3).

18.6

27

43

17

Recruited from population-based study

Stratified random sample from computerized population register

Patients referred for BMD testing Consecutively recruited

Edelmann-Schäfer (2010) Germany [24]

Gudmundsdottir (2005) Iceland [26]

Martini (2004) Italy [29]

Consecutively recruited Pongchaiyakul among women referred (2007) for BMD testing Thailand [33] Bachmann Women referred from (2000) USA [21] physician or self-referred Consecutively recruited

Achilles 12.7

22

314

36

34.5

39

300

300

Panichkul (2003) Thailand [30]

Consecutively recruited among women referred for BMD testing

Consecutively recruited from 116 Family Medicine Clinic

Gemalmaz (2007) Turkey [25]

186

NA

Dane (2008) Turkey [23]

Achilles express

50

35.8

279

B. Fracture population, women recruited from orthopedic fracture clinic and metabolic bone clinic

40

9.8

Clowes (2006) UK [22]

500

No

Yes

No

Yes

No

Yes

Yes

Na

No

No

45–89

38–85

38–85

(57.3)

(59.5)

48–72

70–85

62–87

55–80

55–80

Participants Prevalence of Exclusion Age range (n) osteoporosis criteriaa (mean) %

A. population based, women recruited from GP list

Achilles Plus

Sample recruitment

Characteristics of studies evaluating Achilles devices

Author, year, country [reference]

Table 1

Acclaim QDR 4500 Hologic

Acclaim QDR 4500 Hologic

DXA device manufacturer

Manufacturer database

Sheffield population

Sheffield population

DXA T-score reference population

NA

NA

NA

Lunar DPX-L

Spine: manufacturer database Femur: NHANES

Manufacturer QDR 4500 Hologic NA database

Manufacturer QDR 4500 database Hologic

NA

QDR 4500 Hologic Manufacturer database

Lunar DPX

QDR 4500 Hologic NA

Manufacturer DEXA QDR database 4000 Hologic

NA

NA

NA

Manufacturer Lunar DPX-L data base

NA

NA

QUS T-score reference population

Lumbar spine or hip

Femoral neck

NA

Lumbar spine or femoral neck

Lumbar spine or hip

Lumbar spine

Total hip

Femoral neck

Total hip

Total hip

42

23

61 24

−2.5 SI T-score −1.0 −2.5

T-score

83

79.5

24

−2.5 SI T-score −2.5

31 SI

48 SI T-score −2.2

42

53 SI T-score −1.4

83

11

−3.0

SI

14

−2.5

55

18

−2.0

1553

19

−1.5

88

20

−1.0

SOS

20

−0.5

BUA

20

0

35

−3.0 SI SD

42

−2.5

3

−3.68 5

15

65

24

16

9

25

31

20

18

9

6

2

1

0

0

0

12

5

2

3

0

0

20

45

144 8

36

16

77

31

38

34

52

71

63

3

3

5

10

13

17

18

44

74

94

12

45

71

4

78

100 4

9

80

7

8 SI T-score −2.0

35 252 2

22

8

SI T-score −2.5

38

225

101

226

177

116

45

38

79

61

42

50

17

17

15

10

7

3

2

81

51

31

32

27

23

79

170

99

172

199

429

248

433

FN TN (n) (n)

203 2

18

FP (n)

−2.94 8

96

1529

96 29

22 108

47

1529 94

14

47

108 1486

11

94

QUS TP cutoff (n)

1486

SOS

BUA

SOS

BUA

DXA osteoporosis QUS variable definition T-score ≤−2.5

Osteoporos Int

The sample sizes of studies evaluating other devices (n=3) ranged from 106 and 599 participants, and the prevalence of osteoporosis from 7.8 and 62 %. These studies investigated various variables and cutoffs (Table 4). Study quality evaluation (Table 5) Study quality was evaluated according to the QUADAS2 tool. Generally, there was little concern about the applicability of the studies. Regarding risk of bias, there were some remarks within each domain. Domain 1: patient selection, 18 studies did not report sufficiently how participants were selected for the study, and/or there was little information about recruitment [34, 46, 23, 37, 24, 39, 26, 27, 40, 51, 28, 42, 47, 43, 31, 44, 48, 49]. Domain 2: index test, 18 studies did not use a predetermined cutoff potentially leading to overoptimistic estimates of test performance, thus a high risk of bias [35, 22, 46, 23, 36–38, 27, 40, 41, 28, 42, 47, 43, 30, 31, 48, 49]. Domain 3: reference tests, few studies (n=3) did not describe the definition of osteoporosis, and it was unclear if T-score ≤−2.5 SD was the threshold used [40, 30, 33]. Domain 4: flow and timing, the time interval between index and reference test was rarely described. Few studies described nonparticipants or dropouts. The risk of partial and differential verification bias is generally considered low; i.e., no studies described a design where the result of the index test influenced the decision on whether to perform the reference test or assess participants with different reference standards.

Diseases or taking medication known to affect bone metabolism

Relationship between cutoff and accuracy (Fig. 2)

a

QUS quantitative ultrasound, DXA dual-energy X-ray absorptiometry, TP true positive, FP false positive, TN true negative, FN false negative, GP general practitioner, NA not available, BUA broadband ultrasound attenuation, SOS speed of sound, SI stiffness index, BMD bone mass density

123 14 27 −2.9

7 79 63 SI T-score −1.6

Spine: Manufacturers Lumbar spine or database total hip or Femur: NHANES femoral neck GE Lunar Prodigy or Hologic discovery NA 55–70 34 207 Women referred for BMD testing Harrison (2006) UK [27]

Achilles Insight

44 Pocock (2000) Australia [32]

358

No

NA

NA >65

Lunar DPX-IQ or Lunar Expert

Manufacturer GE Lunar Expert database 33–86 54 99

Prospectively recruited from metabolic bone clinic Randomly recruitment of patients referred for BMD

–

43

58

110 20 138 90 SI T-score −2.5

30

30 20

16

34 −2.5

15

38 SI T-score −2.4

Manufacturer UK normal reference NA

Lumbar spine or femoral neck or total hip Lumbar spine or hip

15

174 174 11 61 SI T-score −1.7 Fem. neck NA Lunar instrument 45–80 (58) NA NA

Larijani (2005) Iran [28] Pearson (2003) UK [31]

No 17.1 420

Sample recruitment Author, year, country [reference]

Table 1 (continued)

Participants Prevalence of Exclusion Age range (n) osteoporosis criteriaa (mean) %

QUS T-score reference population

DXA device manufacturer

DXA T-score reference population

DXA osteoporosis QUS variable definition T-score ≤−2.5

QUS TP cutoff (n)

FP (n)

FN TN (n) (n)

Osteoporos Int

Figure 2a, b shows the relationship between cutoff and accuracy, presenting sensitivity and specificity with 95 % confidence interval at different cutoffs. The studies evaluated various different variables. We focused our analyses on the devices and variables evaluated by most studies: Hologic Sahara and Achilles devices and QUI and SI variables, respectively. Results of each device displayed a pattern of an inverse relationship between sensitivity and specificity. When cutoff rose, the sensitivity increased, while specificity decreased. Achilles was evaluated by six studies with cutoffs ranging from SI T-score equal to −2.5 to −1.0. Sensitivity ranged from 34.8 to 88.4 %. Specificity ranged from 41.2 to 91.8 %. Three studies evaluated the device, using the same variable and cutoff (SI T-score=−2.5) [21, 31, 32]. The sensitivity ranged from 34.8 to 87.3 %. The specificity ranged from 55.0 to 91.8 %. Achilles Express was evaluated in three studies with cutoff ranging from −2.5 to −1.4. Sensitivity ranged from 39.3 to 77.5 %. Specificity ranged from 50 to 91.7 %. Two studies

Volunteers recruited by newspaper advertisement

44

103

110

190 Women consecutively recruited from GP Randomly recruited 722 from community

Lippuner, 2000, Recruited by GP Switzerland [42]

Kung, 2003, Hongkong [41]

Hodson, 2003, UK [40]

30

38

16.3

59

106

Women referred for DXA Consecutively recruited Felder, 2000, Women referred Switzerland [39] for DXA Consecutively recruited

Falgarone, 2004, France [38]

55.8

267

36

18.5

221

137

30

312

Yes

NA

NA

NA

No

Yes

Yes

Yes

No

NA

Manufacturer reference population

NA

NA

NA

44–80 (61.5) NA

43–81 (NA)

60–69 (NA)

>65 years

Manufacturer reference population

NA

NA

QDR 1000 Hologic Local reference

QDR 4500 Hologic NA

NA

Lunar expert

Manufacturer reference population QDR 4500 Hologic NA

Lunar Expert-XL

QDR 4500 SL Hologic

National reference data

Lumbar spine, femoral neck or total hip Lumbar spine, femoral neck or total hip Lumbar spine, femoral neck

Hip

Lumbar spine, femoral neck or total hip Lumbar spine or hip

QUI

Femoral neck

27 26

−1.66 −1.72

48

50

55

14

13

13

71

36

101 56 91 66 33

148 112 1

−1.3 −1.5 −1.9 −2.5 95.5

30

22

−1.7 T-score

27

2

7

34

32

56

51

57

11

11

QUI

94

30

28

3

49

314

11

−2.5 SI (T-score)

40

7

7

74 79

QUI/T-score 75.7/–2.35 187 136 85

13

−2.5 SOS

1

29

29

20 26

132

5

−2.5 BUA

13 8

14 125 115

9

59

1551.5

SOS

59

24 71.70

SOS BUA

58 1533

BUA

3

146 104 3 24

1579 1490

6 122 115

27

3

92

77

62

47

21

116 111

83

58

42.0

7

26

48

30

119 71

−1.0

4

145 97

0.05

41

12 118 115

146 106 3 31

0.650

3

11

124

121

117

202

157

70

TN (n)

118 113 0.305

5

31

27

−1.61

16

61

148 107 1

23

−2.0

60.3

58

−1.0

FN (n)

148 10

FP (n)

115.6

84

TP (n)

0

QUS cutoff

SOS

BUA

Est. BMD (T-score)

Est. BMD

T-score (QUI)

Lumbar spine or hip

T-score est. BMD

DXA T-score DXA osteoporosis QUS reference population definition T-score variable ≤−2.5

QDR 4500 Hologic Spine: manufacturer Lumbar spine, reference femoral neck Hip: NHANES or total hip

DXA Device Manufacturer

Local reference QDR 4500a data Hologic

Manufacturer reference population

QUS T-score reference population

47–85 (65.4) NA

NA (63)

65–(72.6)

50–75 (NA)

50–85 (62)

Exclusion Age range Participants Prevalence (n) of osteoporosis cri-teriaa (mean) %

Dubois, 2001, The Women referred Netherlands [37] for DXA by GP

Postmenopausal women referred for DXA, consecutively recruited Diez-Pérez, Postmenopausal 2003, Spain [36] women, consecutively recruited from a routine clinical visit at three primarycare centers

Boonen, 2005, Belgium [35]

Ayers, 2000 USA [34]

Hologic Sahara

Sample recruitment

Characteristics of studies evaluating Hologic Sahara

Author, year, country [reference]

Table 2

Osteoporos Int

evaluated the device using the same variable and cutoff (SI Tscore=−2.5) [25, 30]. Sensitivity ranged from 39.3 to 60.0 %. Specificity ranged from 59.2 to 91.7 %. Achilles Plus was evaluated by three studies with cutoffs ranging from −3.7 to 0. Sensitivity ranged from 55 to 100 %. Specificity ranged from 10.0 to 100 %. Three studies evaluated the device using the same variable and cutoff (SI T-score=−2.5) [24, 26, 29]. Sensitivity ranged from 70.0 to 100 %, and specificity ranged from 40.8 to 85 %. Hologic Sahara was evaluated by five studies with QUI cutoffs ranging from 60.3 to 115.6. Sensitivity ranged from 20.8 to 100 %. Specificity ranged from 9.3 to 95.8 %. No cutoffs were evaluated more than once. Prescreen approach (Figs. 3 and 4, Tables 6, 7, and 8)

Diseases or taking medication known to affect bone metabolism

We evaluated the ability of calcaneal QUS to reduce the need for DXAs according to three different prescreen algorithms.

a

QUS quantitative ultrasound, DXA dual-energy X-ray absorptiometry, TP true positive, FP false positive, TN True negative, FN false negative, GP general practitioner, NA not available, BUA broadband ultrasound attenuation, SOS speed of sound, Est. BMD estimated BMD, QUI quantitative ultrasound index, BMD bone mass density

65

70 26

14

6

13

18

−2.5

Est. BMD NA (61) NA 28

NA

QDR 4500 Hologic NA

Lumbar spine or hip

−1.9

18

11

25 11 2 −2.5 T-score >50 NA 34.2

Recruited from bone 38 and mineral clinic 115 Consecutively recruited from Bone Density Test Center Pfister, 2003, USA [44] Varney, 1999, USA [45]

NA

Hologic 1000

NA

Hip

30 110.5

0

203 27 99.5

247 0

24 89.2

187 3

338

290

350

18

100 6

12

389

82.2

52

15

27

15 79.6

40

3 63.1

1

43 2 34 31 99 QUI

QDR 4500 Hologic Spine: manufacturer Lumbar spine reference or hip Hip: NHANES NA 45–55 (NA) 7.1 420 Advertisement Nairus, 2000, USA [43]

No

Exclusion Age range Participants Prevalence (n) of osteoporosis cri-teriaa (mean) % Sample recruitment Author, year, country [reference]

Table 2 (continued)

QUS T-score reference population

DXA Device Manufacturer

DXA T-score DXA osteoporosis QUS reference population definition T-score variable ≤−2.5

QUS cutoff

TP (n)

FP (n)

FN (n)

TN (n)

Osteoporos Int

1. LRS Fifteen studies evaluated calcaneal QUS at cutoffs corresponding to sensitivity >85 %. Across devices and different cutoffs, the percentage of savable DXAs ranged from 2.6 to 62.8 % (Fig. 3). Misclassification rates ranged from 0 to 6.6 % of the study sample (data not shown). 2. HRS Fifteen studies evaluated calcaneal QUS at cutoffs corresponding to specificity >85 %. Across devices and different cutoffs, the percentage of savable DXAs ranged from 1 to 44 % (Fig. 4). Misclassification rates ranged from 0 to 12.4 % of the study sample (data not shown). 3. CS Eight studies reported two cutoffs corresponding to sensitivity >85 % and specificity >85 %, respectively. It was possible to evaluate the method in a triage approach, with stratification into three groups. The percentage of possible savable DXAs ranged from 13.9 to 72.1 %. The misclassification rates ranged from 0 to 11 % of the study sample (Tables 6, 7, and 8).

Discussion This is the first systematic review investigating the ability of QUS to reduce the number of patients who need referral for DXA at device-specific and clinically relevant cutoffs corresponding to high certainty levels. Our systematic review found firstly that across studies evaluating the same device and variable, there was, as expected, an inverse relationship

Women referred for BMD testing

Recruited from Australian Twin Register and media advertising

Women referred from GP for BMD testing Subsample from a epidemiologic study

Women with low trauma fracture of the wrist. Consecutively recruited from emergency department

Harrison 2006 UK [27]

Naganathan 1999 Australia [47]

Sim 2005 UK [48] Tromp 1999 England [49]

Victor Sim 2000 UK [50]

46 52 59

52 46

14

326

115

34

21.6

Prevalence of osteoporosis %

207

208

Participants (n)

NA

NA

NA

NA

NA

No

Exclusion criteria

50–80 (NA)

65–87 (NA)

40–80 (NA)

45–80 (NA)

55–70 (NA)

29–87 (NA)

Age range (mean)

NA

NA

NA

Local reference

NA

Manufacturers’ database

QUS T-score reference population

QDR 1000W Hologic

QDR 1000W Hologic QDR 2000 Hologic

QDR 450 Hologic

GE Lunar Prodigy or Hologic discovery

QDR 4500

DXA device manufacturer

NA

NA

NA

Hip or spine

Femoral neck

Hip or spine

Lumbar spine or total hip or femoral neck

Lumbar spine or total hip or femoral neck

Spine: Manufacturers’ database femur: NHANES Local reference

Hip or spine

DXA osteoporosis definition T-score ≤−2.5

Manufactures’ database

DXA T-score reference population

44

−1.0

60

1574 BUA

52 SOS

25

12

13

43

21

−2.5 60

38

−1.0

BUA

BUA

VOS T-score

63 4

−1.02

25

−2.27 T-score

−2.5

24

BUA T-score

41

−1.5 −3.5

TP (n)

VOS

QUS cutoff

BUA

QUS variable

3

15

4

7

165

34

87

0

94

14

33

80

FP (n)

2

5

14

10

2

25

8

42

7

45

21

4

FN (n)

16

20

21

55

115

246

193

280

43

123

130

83

TN (n)

a

Diseases or taking medication known to affect bone metabolism

QUS quantitative ultrasound, DXA dual-energy X-ray absorptiometry, TP true positive, FP false positive, TN True negative, FN false negative, GP general practitioner, NA not available, BUA broadband ultrasound attenuation, SOS speed of sound, VOS velocity of sound, BMD bone mass density

Women referred from GP, for BMD testing

Cook, 2005 UK [46]

CUBA MARKII or CUBA Clinical

Sample recruitment

Characteristics of studies evaluating CUBA MarkII and CUBA Clinical

Author, year, country [reference]

Table 3

Osteoporos Int

Endocrinopathy 47–85 (65.4) NA

59

9.8

35.8

500

279

7.8

35.8

279

B. Fracture population: women consecutively recruited from orthopedic fracture clinic and metabolic bone clinic A. Population based, women recruited from GP list B. Fracture population: women consecutively recruited from orthopedic fracture clinic and metabolic bone clinic Selected by age from general population 599

9.8

500

A. Population based, women recruited from GP list

NA

No

No

No

No

50–54 (NA)

55–80 (NA)

55–80 (NA)

55-80 (NA)

55–80 (NA)

NA

NA

NA

NA

NA

NA

UBA 575

QUS2

QUS2

UBIS 5000

UBIS 5000

DTU-ONE

DTU-ONE

DTU-ONE

NA

Hip or spine

Lunar DPX

NA

Femoral neck or spine

Acclaim QDR Sheffield Total hip 4500 Hologic population

Acclaim QDR Sheffield Total hip 4500 Hologic population

Acclaim QDR Sheffield Total hip 4500 Hologic population

Acclaim QDR Sheffield Total hip 4500 Hologic population

QDR 4500 Hologic

Acclaim QDR Sheffield Total hip 4500 Hologic population

96

1552

BUA

BUA

BUA

SOS

BUA

SOS

BUA

4

47

1453

75

34

77.8 96

150 13

4

7 65 82

54.7 35

2

22 32 207

9 75

4

4

77.8 47

25

1453

102

102

9 61

2

22 37 257

54.7 17

96

1502

63.3 96

55.7 39

12

1502

2

22 30 207

6

6

4

63.3 47

26

28

107

9 72

100

9 80

55.7 19

50.8 56 1544.8 56

SOS

51.2 96

35.1 28

20

1528

2

271

51.2 47

2

22 39 329

22 35

47

1552

402

97

170

244

429

170

77

77

170

194

429

244

429

18

16

72

170

79

170

180

429

122

429

FN TN (n) (n)

35.1 14

10

1528

TP FP (n) (n)

BUA

BUA

SOS

BUA

SOS

QUS DXA osteoporosis QUS definition T-score Variable cutoff ≤−2.5

Acclaim QDR Sheffield Total hip 4500 Hologic population

DXA T-score reference population

a

Diseases or taking medication known to affect bone metabolism

QUS quantitative ultrasound, DXA dual-energy X-ray absorptiometry, TP true positive, FP false positive, TN True negative, FN false negative, GP general practitioner, NA not available, BUA broadband ultrasound attenuation, SOS speed of sound, BMD bone mass density

Langton 1999 UK [51]

Clowes 2006 UK [22]

Clowes 2006 UK [22]

55–80 (NA)

No

35.8

NA

279 B. fracture population: women consecutively recruited from orthopedic fracture clinic and metabolic bone clinic Falgarone 2004 Referred for BMD testing 106 France[38] Consecutively recruited

No

55–80 (NA)

A. population based, women recruited from GP list

Clowes 2006 UK [22]

9.8

QUS T-score QUS device DXA device manufacturer reference population

500

Sample recruitment

Author, year, country [reference]

Age range (mean)

Characteristics of studies evaluating various devices Exclusion Participants Prevalence of osteoporosis criteriaa %

Table 4

Osteoporos Int

Osteoporos Int Table 5

Study quality according to QUADAS2 tool:

Study (reference)

(34)

PATIENT SELECTION

low risk

high risk

RISK OF BIAS INDEX REFERENCE TEST STANDARD

? unclear risk

FLOW AND TIMING

?

? ?

? ?

? ?

? ?

? ? ? ? ? ? ? ?

(21)

APPLICABILITY CONCERNS PATIENT INDEX REFERENCE SELECTEST STANDARD TION

(35) (22) (46) (23)

?

(36) (37) (24) (38) (39)

?

(25) (26) (27) (40)

? ? ?

?

?

(41) (51) (28) (42)

? ? ?

?

?

(29) (47) (43)

? ? ?

(30) (31) (44)

? ?

? ?

? ?

? ? ?

(32) (33) (48) (49)

? ? ?

(45) (50)

between sensitivity and specificity with increasing cutoff. Few studies evaluated the same device, measured variable, and

? ? ? ?

cutoff. However, between those evaluating the same device, variable, and cutoff, there were huge variations in sensitivity

Osteoporos Int

and specificity, probably due to differences in study design and participant characteristics. Secondly, although there were large variations between studies, several studies reported that at a high certainty level, a considerable proportion of DXAs could be avoided, and therefore, QUS might be suitable in a triage approach. However, there was no consensus on the measured variables and cutoffs used. Given the large variation in populations studied, devices, and cutoffs, the use of calcaneal QUS in a prescreen or stratification algorithm must be based on device-specific cutoffs that are validated in the populations for which they are intended to be used. This is in agreement with recommendations from other researchers, who have argued that the WHO T-score diagnostic criteria cannot be applied to QUS and there is a need for predefined device-specific thresholds [52, 17, 53, 54]. Quality assessment of studies included in this review revealed problems in reporting how study participants were selected, and very few studies described characteristics of nonparticipants and proportions of those who dropped out, making it difficult to evaluate how representative the study samples were. Also, few authors described the time interval between index and reference tests, which might be a problem if time interval is unacceptable long.

The studies included in this review used a wide range of variables and cutoffs evaluating the diagnostic accuracy of calcaneal QUS. The method of selecting cutoffs varied between studies. Some studies used predetermined cutoffs, whereas others used a datadriven process. There is a risk of overoptimistic estimates of test performance, when the selection of the optimal cutoff is data-driven, since measures of diagnostic accuracy are affected by sample size, disease prevalence, and the underlying distribution of the test results [55]. Eighteen studies included in this review used a data-driven process. Generally, with increasing sensitivity or increasing specificity in using stratification approaches, the proportion of people who would need no further testing with DXA is reduced. However, four studies differed by reporting a high percentage of DXAs saved using LRS at very high sensitivities [22, 24, 42, 43], which might be due to a low prevalence of osteoporosis in the samples studied (7.1 % [43], 9.8 % [22], 18.6 % [24]) or small sample sizes (n=43 [24] or n=110 [42]). In order to achieve sufficient statistical power when deciding on appropriate cutoffs, sample size of at least 70 participants in each group (osteoporosis yes/no) has previously been recommended [56]. Only nine studies included in this review

Fig. 2 a Forest plot for studies evaluating Achilles, Achilles Express, and Achilles Plus devices, showing sensitivity and specificity with 95 % confidence interval at different SI T-score cutoffs. b Forest plot for studies

evaluating Sahara Hologic devices showing sensitivity and specificity with 95 % confidence interval at different QUI cutoffs

Osteoporos Int

meet these criteria, and six of these evaluated cutoffs at sensitivity or specificity above 85 % [34, 22, 36, 27, 30, 32]. Four of these studies evaluated the combined strategy [22, 27, 34, 36]. The percentage of DXAs saved reported in these studies ranged from 29 to 57 %. However, one study reported percentages of DXAs saved ranging from 13 to 24 % [36]. This study was characterized by a high prevalence of osteoporosis in the sample studied, and certainty levels were close to 100 %. This review focused on calcaneal QUS as a prescreening and stratification tool. An alternative approach is to use clinical risk factors as a prescreening tool for osteoporosis assessment and the need for DXA. A recent study investigating two such approaches, Fracture Risk Assessment tool (FRAX) without BMD and

Osteoporosis Self-Assessment screening Tool (OST), concluded that they performed well in identifying individuals with low risk of osteoporosis but were not reliable enough to identify individuals at high risk of osteoporosis [57]. Furthermore, comparisons of clinical risk factors and calcaneal QUS revealed that the latter (SI) was more accurate in predicting osteoporosis [58]. No clinical randomized trials are available that evaluate the efficacy of anti-osteoporotic treatment among individuals selected for treatment based on QUS measurements. Many clinicians would therefore be cautious relying treatment decisions on QUS measurements. Using a stratification approach, in which the treatment decision relies on a QUS device-specific threshold for identifying DXA-determined osteoporosis at high

Fig. 3 Percentage of DXAs saved with low-risk stratification. Patients with measurements above cutoff are considered not sick and will not need DXA (cutoff selected to ensure sensitivity above 85 %). Studies are

arranged with decreasing specificity. For each result study reference, device, cutoff, and sensitivity are listed. *Clowes study: fracture population

Osteoporos Int Fig. 4 Percentage of DXAs saved with high-risk stratification. Patients with measurements below cutoff are considered sick and will not need DXA (cutoff selected to ensure specificity above 85 %). Studies are arranged with decreasing specificity. For each result study, device, cutoff, and specificity are listed. *Clowes study: fracture population

certainty levels, may overcome this problem. However, one drawback of the stratification approach is the risk Table 6

of misclassification. With the cutoff set at high certainty levels, the risk of misclassification is lower. Another

The combined strategy (CS)–Achilles Devices

Study

Sample Prevalence of Device size osteoporosis n (%)

Measured Certainty level Lower variable sensitivity/specificity cutoff

Clowes [22] Clowesa [22] Clowes [22] Clowesa [22] Edelmann-Schäfer [24] Bachman [21] Harrison [27]

500 279 500 279 43 314 207

BUA BUA SOS SOS SI SI T-score

49 (9.8) 100 (35.8) 49 (9.8) 100 (35.8) 8 (18.6) 69 (22.0) 70 (33.8)

Achilles Plus Achilles Plus Achilles Plus Achilles Plus Achilles plus Achilles Achilles Insight

96/96 96/96 96/95 96/95 100/91 89/92 90/90

Upper cutoff

94 108 94 108 1486 1529 1486 1529 −2.5 −3.68 −2.5 −1.0 −2.9 −1.6

DXAs Misclassification saved rate (%) (%) 55.8 47.3 47.4 43.4 72.1 48.7 51.2

4.0 3.9 4.8 4.7 7.0 4.8 10.1

Achilles Devices. Savable DXAs, misclassification rate, measured variable, upper and lower cutoffs, and certainty level for studies evaluating the combined strategy, with stratification into low-risk, high-risk and equivocal groups a

Clowes: fracture population

Osteoporos Int Table 7

The combined strategy (CS)–Hologic Sahara

Study

Sample size

Prevalence of osteoporosis n (%)

Device

Measured variable

Certainty level sensitivity/specificity

Lower cutoff

Upper cutoff

DXAs saved (%)

Misclassification rate (%)

Diez-Pérez [36] Diez-Pérez [36] Diez-Pérez [36] Ayers [34] Diez-Pérez [36] Nairus [43] Nairus [43]

267 267 267 312 267 420 420

149 (55.8) 149 (55.8) 149 (55.8) 94 (30.1) 149 (55.8) 30 (7.1) 30 (7.1)

Sahara Sahara Sahara Sahara Sahara Sahara Sahara

BUA Est. BMD Est. BMD T-score QUI T-score QUI QUI QUI

99/97 98/97 97/94 89/93 99/96 100/99.7 90/89.7

42 0.305 −2.5 −2.0 60.3 63.1 79.6

95.5 0.65 0.05 0.0 115.6 110.5 99.5

13.9 18.4 24.3 38.0 18.0 27.9 62.1

1.5 2.2 4.1 8.3 2.3 0 10.2

Hologic Sahara. Savable DXAs, misclassification rate, measured variable, upper and lower cutoffs, and certainty level for studies evaluating the combined strategy, with stratification into low-risk, high-risk and equivocal groups

drawback is the inability of QUS to monitor treatment response. DXA is the preferred method for monitoring treatment response, and there is no clear evidence that QUS is useful for monitoring treatment [59]. Bone turnover markers might be an alternative to DXA for monitoring treatment in those started on treatment based on the QUS stratification approach although this is controversial [60, 61]. Our study has some limitations. Firstly, the review was restricted to studies on women older than 45 years or who were postmenopausal, and therefore, the results may not be applicable to younger women and men. Secondly, we only included studies published in English, German, and Scandinavian languages. Thirdly, the results may have been subject to publication bias, although the wide spectrum of accuracy Table 8

results implicates that publication bias does not seem to be a major problem.

Conclusion This systematic review shows that calcaneal QUS is potentially useful as a prescreen tool for assessment of osteoporosis. However, there is no consensus for type of devices, measured variables, or cutoffs. Overall, there is no sufficient evidence to recommend a specific cutoff for calcaneal QUS that provides a certainty level high enough to rule in or out osteoporosis. Calcaneal QUS in a prescreen or stratification algorithm must be based on device-specific cutoffs that are validated in the populations for which they are intended to be used.

The combined strategy (CS)–other devices

Study

Sample Prevalence of Device size osteoporosis n (%)

Measured variable

Certainty level Lower sensitivity/specificity cutoff

Harrison [27] Naganathan [47] Clowes [22] Clowesa [22] Clowes [22] Clowesa [22] Clowes [116] Clowesa [116] Clowes [116] Clowesa [116] Clowes [116] Clowesa [116]

207 326 500 279 500 279 500 279 500 279 500 279

T-score VOS T-score BUA BUA SOS SOS BUA BUA SOS SOS BUA BUA

90/90 88/96 96/95 96/95 96/95 96/95 96/95 96/95 96/95 96/95 96/95 96/95

70 (33.8) 46 (14.1) 49 (9.8) 100 (35.8) 49 (9.8) 100 (35.8) 49 (9.8) 100 (35.8) 49 (9.8) 100 (35.8) 49 (9.8) 100 (35.8)

CUBA Clinical CUBA MarkII DTU-ONE DTU-ONE DTU-ONE DTU-ONE UBIS 5000 UBIS 5000 UBIS 5000 UBIS 5000 QUS 2 QUS 2

−2.27 −2.5 35.1 35.1 1528 1528 55.7 55.7 1453 1453 54.7 54.7

Upper cutoff

DXAs Misclassification saved rate (%) (%)

−1.02 −1.0 51.2 51.2 1552 1552 63.3 63.3 1502 1502 77.8 77.8

43.0 52.8 43.6 32.0 31.2 29.0 57.4 46.2 46.0 41.2 57.0 51.3

10.1 11.0 4.8 4.7 4.8 4.7 4.8 4.7 4.8 4.7 4.8 3.9

CUBA, DTU-ONE, UBIS 5000, QUS2. Savable DXAs, misclassification rate, measured variable, upper and lower cutoffs, and certainty level for studies evaluating the combined strategy, with stratification into low-risk, high-risk and equivocal groups a

Clowes: fracture population

Osteoporos Int Conflicts of interest None.

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