Gynecological Endocrinology
ISSN: 0951-3590 (Print) 1473-0766 (Online) Journal homepage: http://www.tandfonline.com/loi/igye20
Osteoporosis's Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study Stefano Lello, Roberto Sorge, Nicola Surico & OMERO Study Group To cite this article: Stefano Lello, Roberto Sorge, Nicola Surico & OMERO Study Group (2015): Osteoporosis's Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study, Gynecological Endocrinology To link to this article: http://dx.doi.org/10.3109/09513590.2015.1063605
Published online: 14 Jul 2015.
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Date: 10 November 2015, At: 11:56
http://informahealthcare.com/gye ISSN: 0951-3590 (print), 1473-0766 (electronic) Gynecol Endocrinol, Early Online: 1–7 ! 2015 Informa UK Ltd. DOI: 10.3109/09513590.2015.1063605
ORIGINAL ARTICLE
Osteoporosis’s Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study Stefano Lello1, Roberto Sorge2, and Nicola Surico3 for OMERO Study Group* Department of Woman and Child Health, Catholic University of Rome, Rome, Italy, 2Laboratory of Biometry, University of Tor Vergata, Rome, Italy, and 3Department of Gynecology and Obstetrics, University of Novara, Novara, Italy
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Abstract
Keywords
Osteoporosis (OP) and related fractures are well-known severe conditions affecting quality of life and life expectancy of postmenopausal women, with high economic costs in Europe. On behalf of The Italian Society of Gynecology and Obstetrics (Societa` Italiana di Ginecologia ed Ostetricia, SIGO), the Osteoporosis’s Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study, a national multicenter study on clinical risk factors of OP was organized, using FRAXÕ tool as a reference. Here, data from this study are presented, showing an important portion of Italian postmenopausal women affected by osteopenia/OP at high risk of fracture and the need to do prevention and/or treatment. Gynecologist can be a primary specialist in this important challenge.
FRAXÕ , menopause, osteoporosis
Introduction Osteoporosis (OP) is a systemic skeletal disorder characterized by loss of bone strength and subsequent increased susceptibility to fragility fractures. Bone strength reflects the integration of bone quality (BQ) and bone mineral density (BMD) [1,2]. Nowadays, major osteoporotic fractures are a social and economic burden. International Osteoporosis Foundation estimated osteoporotic fractures in Europe in 2000 were 3.79 million, of which 890 000 were hip fractures; the total direct costs resulting from these fractures were estimated at euros 31.7 billions, though expected to increase to 76.7 billion euros by 2050, according to demographic changes [3]. However, OP remains under-diagnosed and under-treated, with a minority of
*OMERO Study Group: Andrea Tranquilli (deceased) (Ancona), Angelo Turi (Ancona), Daniele Agostinelli (Bari), Sergio Messini (Bolzano), Alessandro Gambera (Brescia), Massimo Stomati (Brindisi), Anna Maria Paoletti (Cagliari), Silvana Sanna (Cagliari), Maria Durante (Campobasso), Ignazia Roccu (Campobasso), Paolo Scollo (Catania), Franca Nocera (Catania), Enrica Ronca (Cremona), Sandra Bucciantini (Firenze), Sonia Baldi (Firenze), Sandra Nosari (Genova), Annunziata Marra (Lecce), Rosario D’Anna (Messina), Luisa Barbaro (Messina), Carlo Mapelli (Milano), Raffaella Chionna (Milano), Angelo Cagnacci (Modena), Costantino Di Carlo (Napoli), Carmine Nappi (Napoli), Livio Leo (Novara), Marina Pandolfo (Palermo), Rossella Nappi (Pavia), Silvia Tonani (Pavia), Angelamaria Becorpi (Firenze), Carmelina Santilli (Pescara), Silvia Maffei (Pisa), Barbara Del Bravo (Pisa), Marco Gambacciani (Pisa), Antonio Amorosi (Potenza), Rosalbino Mantuano (Ravenna), Anna Pasi (Ravenna), Francesca Guardianelli (Roma), Anna Capozzi (Roma), Roberto Frantellizzi (Roma), Giovanni Scambia (Roma), Paola Villa (Roma), Maurizio Zaza (Roma), Rosalba Percuoco (Roma), Fulvio Leoni (Roma), Salvatore Dessole (Sassari), Giampiero Capobianco (Sassari), Chiara Benedetto (Torino), Mario Gallo (Torino), Diego Marchesoni (Udine), Monica Della Martina (Udine). Address for correspondence: Stefano Lello, Department of Woman and Child Health, Catholic University of Rome, Largo Agostino Gemelli 1, Rome 00168, Italy. E-mail: [email protected]
History Received 17 May 2015 Accepted 14 June 2015 Published online 14 July 2015
patients at high fracture risk identified for treatment [4] and a persistent low adherence to therapies [5,6]. On the other hand, various data demonstrated BMD is not the single determinant of bone strength/fracture risk. National Osteoporosis Risk Assessment (N.O.R.A.) study showed the absolute number of fractures was higher in patients classified by DXA measurement as ‘‘osteopenic’’ than in those considered ‘‘osteoporotic’’ [7]. Therefore, evaluation of associated clinical risk factors may better define the risk profile of each patient. World Health Organization FRAXÕ (http://www.shef.ac.uk/ FRAX) algorithm integrates BMD values with clinical risk factors to give an estimate of 10-year absolute risk of major osteoporotic fracture (vertebra, humerus, wrist, hip) and hip fracture. In particular, femoral neck BMD (optional) may increase the fracture risk prediction power of FRAX [8,9]. Moreover, both National Osteoporosis Foundation (NOF) [10] and World Health Organization (WHO) [11,12] made recommendations about the prevention and treatment of at high-risk patients. The aim of this study was to evaluate the frequency of risk factors and the 10-year risk of osteoporotic fractures in Italy, in a gynecological setting, using FRAXÕ as a tool to assess skeletal health in peri- and postmenopausal women.
Materials and methods This was a multicenter (42 centers), prospective, nationwide trial sponsored by the Italian Society of Gynecology and Obstetrics (Societa` Italiana di Ginecologia ed Ostetricia, SIGO) on risk factors for OP and related fractures using WHO FRAXÕ [12]. FRAXÕ is an algorithm to evaluate the 10-year absolute probability of hip or major osteoporotic fracture (fracture of hip, spine, wrist, humerus) considering age, gender, race and clinical profile, with or without BMD value (grams/cm2), usually measured at femoral neck. In our study, besides femoral neck BMD (reported in the text as hip BMD), we included, when DXA was available, also spine (lumbar) BMD, to compare the effect of hip and spine BMD on FRAX model results.
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Study population consisted of three age subgroups: 45–55-years-old (subgroup 1); 55–65-years-old (subgroup 2), and 65–75-years-old (subgroup 3). Subjects were recruited following a sampling chart. Clinical risk factors (including those reported in FRAX model: age, sex, height, weight, previous fracture, parental hip fracture, current smoking, use of glucocorticoids, rheumatoid arthritis, secondary OP, alcohol consumption, and femoral neck BMD (if available) were assessed for each subject by a questionnaire. All information were sent by an on-line platform to a centralized data management to be evaluated by a statistician (R. S.). All data were analyzed using SPSS version 15 for Windows. Descriptive indexes of numerical values are expressed as percentage, while the indexes of normal variables as mean and standard deviations (M ± SD). Tests of statistical comparison, both parametric and non-parametric (ANOVA, Bonferroni test, Student’s t test), were considered significant when p50.05. We collected 1768 subjects from different areas in Italy. The research protocol was approved by local ethical committees, and written informed consent was obtained for each patient. Statistical power of the study was determined.
Results Descriptive analyses of the sample are shown in Table 1. Statistical power of the study was calculated to be 86%. Body weight, height and body mass index (BMI) (Table 1) were different among subgroups. We observed lower BMI in the first age subgroup versus second and third subgroup (p50.001).
As for fracture presence according to the age groups, the older the subjects the more frequent the fractures. In particular, all major osteoporotic fractures were significantly increased in the oldest class versus the other ones (p ¼ 0.001). Moreover, observing the fracture as a dichotomic variables (yes/not), we found 16% of the total sample had a story of previous fracture, with a significant increase in the third subgroup (23.9% of the subjects within group; 42.9% of the total study subjects with fracture) in comparison with first subgroup (9.3% of the subjects within group; 21.3% of the total subjects with fracture) (p ¼ 0.001). Moreover, 17.7% of total subjects reported parental hip fracture. This percentage resulted significantly higher in the oldest age subgroup than in the others (first subgroup: 13.1%; second subgroup: 16.6%; third subgroup: 24.9%; p ¼ 0.001). Corticosteroids (CS) were used by 4.8% of subjects, without significant differences among subgroups. A mean percentage of 2.0% of women showed a diagnosis of rheumatoid arthritis (p ¼ 0.257 among subgroups). A total of 89.9% of women was menopausal (100% in third-age subgroup, 98.9% in second, and 74.1% in first subgroup; p ¼ 0.001). Taking into account postmenopausal years, there was an increase from first to third age subgroup, with significant differences (p ¼ 0.001; 4.0 ± 5.2 for first subgroup; 10.6 ± 6.7 for second subgroup; 19.9 ± 6.1 for third subgroup). Milk intake was reported in 72.1% of total population, with a higher percentage of users in third subgroups (77.9%) versus first subgroup (67.1%) (p ¼ 0.001), but with a similar number of cups
Table 1. Geographic division, age, and anthropometric variables (weight, height, body mass index) of study sample.
Geographic division
1st subgroup 45.1–55 years (mean ± SD)
2nd subgroup 55.1–65 years (mean ± SD)
3rd subgroup 65.1–75 years (mean ± SD)
Total sample (mean ± SD)
1. North-west
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
123 50.8 ± 3.0 65.0 ± 12.0 161.5 ± 6.1 24.9 ± 4.4
121 60.5 ± 3.0 67.1 ± 13.4 160.8 ± 5.9 26.0 ± 5.4
80 69.8 ± 2.6 68.4 ± 13.2 160.6 ± 6.1 26.5 ± 4.6
324 59.1 ± 8.0 66.6 ± 12.8 161.0 ± 6.0 25.7 ± 4.9
2. North-east
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
25 51.3 ± 2.9 61.3 ± 8.5 162.8 ± 5.9 23.2 ± 3.3
23 60.5 ± 3.2 71.2 ± 15.1 163.7 ± 5.7 26.6 ± 5.7
16 69.9 ± 2.8 65.7 ± 10.5 161.6 ± 6.3 25.2 ± 3.8
64 59.3 ± 7.9 65.9 ± 12.3 162.8 ± 5.9 24.9 ± 4.6
3. Center
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
262 51.2 ± 2.7 62.9 ± 11.0 162.5 ± 6.3 23.8 ± 4.2
238 60.5 ± 3.1 65.3 ± 10.8 159.9 ± 6.1 25.6 ± 4.1
246 70.2 ± 2.7 65.4 ± 11.8 159.5 ± 6.1 25.8 ± 4.4
746 60.4 ± 8.3 64.5 ± 11.3 160.7 ± 6.3 25.0 ± 4.3
4. South
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
116 51.2 ± 2.8 65.3 ± 11.6 160.4 ± 6.1 25.4 ± 4.3
115 60.0 ± 2.8 69.5 ± 12.4 159.0 ± 6.5 27.4 ± 4.6
85 69.6 ± 2.9 66.4 ± 10.9 157.6 ± 6.3 26.8 ± 4.3
316 59.3 ± 7.8 67.1 ± 11.8 159.1 ± 6.4 26.5 ± 4.5
5. Islands
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
122 50.9 ± 2.8 62.9 ± 10.0 159.7 ± 5.3 24.6 ± 3.7
116 60.2 ± 3.0 64.5 ± 10.6 158.4 ± 5.4 25.8 ± 4.4
80 69.3 ± 2.6 64.6 ± 9.5 157.9 ± 5.6 25.9 ± 3.7
318 58.9 ± 7.8 63.9 ± 10.1 158.8 ± 5.5 25.4 ± 4.0
ITALY
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
648 51.1 ± 2.8 63.7 ± 11.1 161.4 ± 6.1 24.5 ± 4.2
613 60.3 ± 3.0 66.5 ± 11.9 159.8 ± 6.1 26.1 ± 4.6
507 69.9 ± 2.7 65.9 ± 11.6 159.2 ± 6.1 26.1 ± 4.3
1768 59.7 ± 8.1 65.3 ± 11.6 160.2 ± 6.2 25.5 ± 4.5
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per day (mean ± SD: 1.3 ± 1.0; 1.4 ± 1.1; 1.4 ± 1.1, for first, second, and third subgroup, respectively; p ¼ 0.311). Cheese and dairy products were used by 91% of the subjects, with a lower rate of servings/week in the oldest subgroup (2.7 ± 1.6 versus mean value 3.0 ± 1.9) (p ¼ 0.001). Lactose intolerance was reported by 8.1% of the subjects (no difference in percentage among different subgroups (1st: 9.0%; 2nd: 7.3%; 3rd: 8.1%; p ¼ 0.579). Current smoking was reported by a mean of 19.3% of total subjects, with a higher rate in youngest subgroups (25.6%) in comparison with second (18.3%) and third (18.5%) subgroups (p ¼ 0.001). Regarding the pack number/year, even if there were less smokers among older subjects, those who were smokers used significantly more packs/year (18.7 ± 23.0) than the first subgroup (13.4 ± 10.5) (p ¼ 0.022). A total of 21.9% of subjects declared current alcohol intake, with mean consumption of 1.4 ± 0.6 glass/d, without significant differences among subgroups (p ¼ 0.123). Evaluation of single clinical risk factors and FRAXÕ scores Femoral neck BMD is the skeletal region currently validated for FRAX use [12]. We used also, when available, lumbar spine BMD (LS-BMD) to compare the results with those obtained with hip BMD. For many subjects there were both hip BMD and lumbar spine BMD (n ¼ 536), with smaller number including only LS-BMD (n ¼ 280); hip BMD was reported in 765 patients. Following statistical tests are for independent data. Overall, we calculated 2304 FRAXÕ scores (828, 791, 685 for first, second and third subgroup, respectively). Significant difference for BMD values (Figure 1) among third subgroup (the lowest values), and first and second subgroups (p ¼ 0.001, respectively) was measured. Moreover, in third subgroup there was significant difference between LS-BMD versus hip-BMD (p ¼ 0.016).
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FRAXÕ scores for major osteoporotic fractures and hip fracture calculated with and without BMD values are reported in Table 2. FRAXÕ scores for major osteoporotic fractures increased significantly both for age subgroups (p ¼ 0.001) and for DXA BMD data (p ¼ 0.01). Moreover, an interaction effect exists between age subgroups and FRAXÕ data calculated with vertebral, hip-BMD and no DXA data (p ¼ 0.004). There was no statistical difference for major osteoporotic fractures FRAX score with spine BMD or no DXA data, while there was a significant difference between FRAXÕ score calculated with hip-BMD, on one hand, and no DXA data or spine BMD, on the other hand. Hip fracture FRAXÕ data were statistically different both for age subgroups (p ¼ 0.001) and for presence/absence of BMD values (p ¼ 0.001) (Figure 2). Thus, FRAXÕ values calculated without BMD were different in comparison with those calculated with LSBMD or hip-BMD. T-score values for hip and spine showed significant differences among three subgroups of age (Table 3). Among hip T-scores, 75.4% showed osteopenia or OP, mostly in the oldest subgroups (p ¼ 0.001). In particular, 47.3% of women were osteopenic (low bone mass), and 28.1% osteoporotic. These percentages, in first-, second-, and third-age subgroup, were respectively, 38.2%, 34.6%, and 27.2% for osteopenic values, and 18.6%, 29.4%, and 45.9% for OP, with an important increase for second and third subgroups versus first age subgroup (p ¼ 0.001). According to LS T-score, 75.1% of subjects had a pathological values, with significant worsening in older subgroups (p ¼ 0.001), 57.6% of total subjects being classified as osteopenic, and 17.5% as osteoporotic; osteopenic range was present in 58.9%, 60.7%, and 52.4%, in first, second, and third subgroup, respectively, while osteoporotic values were reported for 9.5%, 12.8%, and 32.5%, respectively (p ¼ 0.001). Looking at hip and vertebral T-score values according to Tscore classes (i.e. normal, osteopenia, and OP), hip T-score determined a significantly higher number of OP diagnosis in comparison with vertebral T-score as diagnosed by DXA measurement (57.4% versus 42.6%, respectively; p ¼ 0.001 for difference). Among all clinical risk factors, smoking (yes/no) provided a significant difference in FRAXÕ score values both for major osteoporotic fractures and hip fracture (p ¼ 0.001); alcohol factor showed a similar effect to smoking on FRAXÕ both for major osteoporotic fractures and hip fracture (p ¼ 0.001 for presence/ absence of alcohol within each subgroup). CS impacted on FRAXÕ for major osteoporotic fracture (corticosteroid present versus absent: p ¼ 0.001). Previous fractures determined a significant difference in terms of FRAXÕ score both for major osteoporotic fractures and for hip fracture (p ¼ 0.001 for presence versus absence of previous fracture). Another important risk factor was hip parental fracture; significant differences were found among age subgroups (p50.05). Hip parental fractures increased significantly FRAXÕ score both for major osteoporotic fracture and hip fracture (risk calculated with and without hip parental fracture in family hystory of the subjects: p ¼ 0.001 for first versus second versus third subgroup, and for presence versus absence of parental fracture: p ¼ 0.001 only in second and third subgroup). Evaluation of the outcome of FRAX’s use in an Italian population
Figure 1. LS-BMD and Hip-BMD values measured by DXA for age subgroups (*p ¼ 0.001 for difference between first and third subgroups, and ^p ¼ 0.016 for difference in second and third subgroups within LS-BMD versus Hip-BMD).
We evaluated the impact of FRAXÕ model both on subjects with available BMD value (vertebral or hip BMD) and on subjects without BMD. We determined the number of subjects who should be treated, according to FRAXÕ ’s threshold for 10-years hip
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Table 2. FRAX score (for major osteoporotic fracture and hip fracture) calculated with or without DXA (Hip or LS) BMD data.
Age subgroups*
FRAX score without DXA BMD
FRAX score with LS BMD
FRAX score with hip BMD
FRAX score for major osteoporotic fracture
FRAX score for hip fracture
FRAX score for major osteoporotic fracture
FRAX score for hip fracture
FRAX score for major osteoporotic fracture
FRAX score for hip fracture
*,**1st group (45.1–55 years)
N Mean ± SD
276 7.32 ± 6.71
276 2.38 ± 4.55
291 5.66 ± 1.77
291 1.43 ± 0.63
180 6.22 ± 4.89
180 1.70 ± 3.72
***2nd group (55.1–65 years)
N Mean ± SD
243 8.70 ± 6.41
243 2.77 ± 3.58
284 8.75 ± 4.66
284 2.38 ± 0.66
178 9.08 ± 7.59
178 2.60 ± 5.95
3rd subgroup (65.1–75 years)
N Mean ± SD
204 12.01 ± 8.65
204 5.09 ± 5.90
241 18.87 ± 9.69
240 10.07 ± 6.44
178 21.50 ± 18.13
178 12.04 ± 17.18
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*p ¼ 0.05 among age subgroups; **p ¼ 0.001 for subgroup 1 versus subgroups 2 and 3; ***p ¼ 0.001 for subgroup 2 versus subgroup 3.
FRAXÕ score for major osteoporotic fractures, calculated without BMD value, showed a percentage 20% in 3.3%, 5.8%, and 17.2%, in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup, and between second and third subgroup). A hip fracture FRAXÕ Score 3%, calculated without BMD value, was reported in 6.5%, 11.9% and 39.2% in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup, and between second and third subgroup). FRAXÕ score values distribution for hip fracture risk calculated without BMD, with hip or spine BMD, in age subgroups (cut-off 3%) are reported in Figure 3(A). FRAX score values distribution for major osteoporotic fractures risk found without BMD, with hip or spine BMD in the age subgroups (cut-off 20%), are reported in Figure 3(B).
Discussion and conclusions
Figure 2. FRAX score for hip fracture calculated without DXA BMD value, with hip BMD, and LS-BMD (*p ¼ 0.001 for subgroup 3 versus 1 and 2; ^p ¼ 0.001 in third subgroups within no DXA versus hip-BMD versus LS-BMD).
fracture risk (3%) and for major osteoporotic fractures risk ( 20%). Overall, 4.8% in first subgroup, 7.0% in second subgroup, and 29.5% in third group showed a major osteoporotic fractures FRAXÕ score 20% calculated with spine BMD (p ¼ 0.001 for difference between first and second and **between second and third subgroup). Hip fracture FRAXÕ Score 3%, calculated with spine BMD, was found in 15.8%, 22.2%, and 43.2% in the first, second, and third age subgroup, respectively (p ¼ 0.001 for difference first versus and second and third subgroup, and between second and third subgroup). Major osteoporotic fracture FRAXÕ score calculated with hip BMD showed a percentage 20% in 6.9%, 10.6%, and 32.5% in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup, and between second and third subgroup). FRAXÕ score for hip fracture, calculated using hip BMD, was 3% in 19.9%, 24.2%, and 47.5%, in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup and between second and third subgroup).
We evaluated the characteristics and risk factors for OP and related fractures in a population from different regions of Italy. FRAXÕ is an algorithm [12] which uses clinical risk factors to estimate an individual’s 10-year osteoporotic fracture (both major osteoporotic fractures and hip fracture) probability. FRAXÕ tool is useful to identify individuals who should be candidates for BMD screening or pharmacological intervention. FRAX is also used for guideline development and health economic applications [9,13]. FRAXÕ should not be considered as a gold standard in a subject’s evaluation, but rather as a reference clinical basis. Therefore, FRAXÕ does not substitute clinical judgment for each clinical case. BMD testing alone is not an absolute marker of OP and related fracture risk. In our sample, a total of 282 previous fractures was reported, with a higher percentage in the third age subgroup as expected (23.9% of the subjects within group; 42.9% of the total subjects with fracture), and a lower percentage in second and first subgroup. This difference was significant between first and third subgroup (p ¼ 0.001). Previous fracture is a potent risk factor for other fractures [14–16], so the third subgroup resulted at higher risk not only for age, but also for this factor at baseline. Also fractures at different sites other than hip, spine and wrist are predictor of subsequent fractures [17] (see Table 2). Parental hip fracture [RR for subsequent fracture ¼ 1.40 (95% CI ¼ 1.09–1.80)] [9], was reported in 17.7% of total subjects (more frequently in third subgroup). A low percentage of women (2%) reported a condition of rheumatoid arthritis, a known risk factor for OP and fracture [18], in line with the gynecological setting of our study, presenting a
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Table 3. T-score values (hip and vertebral) according to age subgroups. Hip T-score Age subgroups
Vertebral T-score
Normal Osteopenia Osteoporosis Normal Osteopenia Osteoporosis (41) (between 1 and 2.5) (52.5) Total (41) (between 1 and 2.5) (52.5) Total 80 33.2 47.1
125 51.9 38.2
36 14.9 18.6
241 100.0 34.9
90 31.6 44.1
168 58.9 35.5
27 9.5 18.8
285 100.0 34.7
2nd subgroup (55.1–65 years) N % subgroup % T-score
53 22.6 31.2
113 48.1 34.6
69 29.4 35.6
235 100.0 34.0
77 26.6 37.7
176 60.7 37.2
37 12.8 25.7
290 100.0 35.3
3rd subgroup (65.1–75 years) N % subgroup % T-score
37 17.2 21.8
89 41.4 27.2
89 41.4 45.9
215 100.0 31.1
37 15.0 18.1
129 52.4 27.3
80 32.5 55.6
246 100.0 30.0
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1st subgroup (45.1–55 years) N % subgroup % T-score
Figure 3. (A) FRAXÕ score for hip fracture according to age subgroups, calculated without BMD, with hip BMD, and with spine BMD. (B) FRAX score for major osteoporotic fractures according to age subgroups, calculated without BMD, with hip and spine BMD.
low number of patients with chronic inflammatory diseases, including rheumatoid arthritis. Smoking [19–21] was present for 19.3% of all subjects, with higher packs/year consumption for third subgroup; this is interesting, since a dose–response and a progressively increasing risk of hip fracture with age (probably for a longer duration of exposure) [9] was reported. Alcohol consumption [22] was reported by 21.9% of total sample without difference among subgroups. The mean consumption was 1.4 ± 0.6 glass/d, an intake to be considered low [9].
Milk intake resulted for 72.1% of total population, with a higher percentage of users in third subgroups (77.9%) versus first subgroup (67.1%) (p ¼ 0.001), but with a similar number of cups per day (mean ± SD: 1.3 ± 1.0; 1.4 ± 1.1; 1.4 ± 1.1, for first, second, and third subgroup, respectively; ANOVA one-way; p ¼ 0.311). Even if a factor traditionally thought to be important for skeletal health, milk intake has controversial and inconclusive data reported [22–24]. Cheese and dairy products were used by 91% of the subjects, with a lower rate of servings/week in the oldest subgroup (2.7 ± 1.6 versus mean value 3.0 ± 1.9) (p ¼ 0.001). This number is near recommended intake of three servings/day [25]. Hip T-score values was in osteopenic or osteoporotic range in 75.4% of total sample, with worse values, as expected, in third subgroup (p ¼ 0.001); 47.3 of subjects were in osteopenic (low bone mass) range, and 28.1% in osteoporotic range. For first, second, and third subgroup, the percentages were, respectively, 38.2%, 34.6%, and 27.2% for osteopenic values, and 18.6%, 29.4%, and 45.9% for OP diagnosis (p ¼ 0.001 for difference between second and third subgroups versus first). According to Clinician’s Guide to Prevention and Treatment of OP recently published by NOF [10], it is recommended to pharmacologically treat subjects with T-scores52.5 at the femoral neck, total hip or lumbar spine by DXA. Thus, in third age subgroup in our study, for example, nearly half of patients should be pharmacologically treated, and the same applies to about 1 of 3 (29.4%) in second subgroup, and about 1 of 5 in first subgroup (18.6%). Considering vertebral T-score other interesting considerations emerged; actually, 75.1% of total sample had osteopenic (low bone mass, a significant risk factor as demonstrated in NORA study) or osteoporotic values, with a significant worsening in older subgroups (p ¼ 0.001). A total of 57.6% of total subjects were classified osteopenic, and 17.5% osteoporotic. Osteopenic range was present in 58.9%, 60.7%, and 52.4%, in first, second, and third subgroup, while osteoporotic BMD values were reported for 9.5%, 12.8%, and 32.5%, respectively (p ¼ 0.001). Again, according to NOF [9], the portion of osteoporotic subjects should be treated; thus, more than one-third of postmenopausal patient 65–75-years-old in an Italian population should receive pharmacological treatment according to spine BMD. According to hip and vertebral T-score values for different T-score classes (i.e. normal, osteopenic, and osteoporotic), hip T-score determined a significantly higher number of OP diagnosis in comparison with vertebral T-score measured by DXA (57.4% versus 42.6%, respectively; p ¼ 0.001). Also the presence of corticosteroid use, 4.8% in total population, a well-known risk factor [26,27], had a significant impact on FRAX score for major osteoporotic fracture (p ¼ 0.001), and previous fractures, another factor known to increase the risk of subsequent fractures [28], determined a
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significant difference in terms of FRAX score both for major osteoporotic fractures and for hip fracture (p ¼ 0.001 for presence versus absence of previous fracture). Parental fracture was important in determining an increase of FRAX score both for 10-year hip fracture risk (p ¼ 0.001 in second and third subgroup versus no hip parental fracture) and for hip fracture risk. Taking into account the threshold values of FRAX model both for 10-year probability of major osteoporotic fracture (hip, clinical spine, humerus or wrist fracture; 20%) and hip fracture ( 3%), we determined subjects to be treated for preventing osteoporotic fractures, using both femoral neck BMD and LS-BMD. Thus, 4.8% in first, 7.0% in second, and 29.5% in third groups showed a major osteoporotic fractures FRAX score 20% calculated with spine BMD (p ¼ 0.001 for difference between first and second and second and third subgroup). Hip fracture FRAX Score 3%, calculated with spine BMD, was found in 15.8%, 22.2%, and 43.2% in the first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and second subgroups and second and third subgroups). FRAX score calculated with hip BMD showed a 10-year major osteoporotic fractures risk 20% in 6.9%, 10.6%, and 32.5% in first, second, and third age subgroups, respectively (p ¼ 0.001) for difference between first and third and second and third subgroup). FRAX score for hip fracture 3%, calculated with hip BMD, was found in 19.9%, 24.2%, and 47.5%, in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third and second and third subgroups). The trend of percentage of risk is similar in FRAX score calculated with spine BMD and hip BMD, even if the percentages with hip BMD were generally higher. Of major interest, the percentage of subjects at significant 10year risk 20% for fracture assessed with FRAX model using femoral neck (hip) BMD was 10.6% for major osteoporotic fracture in second subgroup and 32.5% (more than one of the three subjects) in third subgroup. More impressively, FRAX score 3% for hip fracture calculated with femoral neck BMD was 19.9% (nearly one of five) in first subgroup, 24.2% (more than one of five) in second subgroup, and 47.5% (nearly one of two) in third subgroup. These data are very impressive, pointing out OP remains an under-diagnosed and under-treated disease, with a minority of patients at high fracture risk identified for treatment [4]. Our results, produced in a gynecological setting, allow us to draw some conclusions: (1) Gynecologist is the specialist able to do a real primary prevention and therapy of OP, since this specialist meets, in everyday clinical practice, younger peri-postmenopausal and older post-menopausal women at low-, medium-, and high risk for fracture. (2) It is important to assess the risk profile for each woman in peri- and post-menopause to find a strategy for prevention/ treatment in the high-risk subjects; FRAXÕ score provides an easy and reliable tool for identifying these subjects. (3) According to National Osteoporosis Guide for OP prevention and treatment [10], in our study a high percentage of patients with –2.5 T-score should be treated in an Italian population within an age range 45–75 years, with an obvious increase of high-risk patients in older groups. (4) According to FRAX score, 47.5% of subjects in age range 65–75 years are at high 10-year risk for hip fracture in our study. These data should be taken into account in making prevention strategies and treatment regimens.
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Declaration of interest This study was supported through a research grant by Pfizer Inc. to SIGO. The authors declare no conflicts of interests. The authors alone are responsible for the content and writing of this article.
References 1. NIH consensus development panel on osteoporosis prevention, diagnosis, and therapy, JAMA 2001;285:785–95. 2. Seeman E. Bone quality. Adv Osteoporos Fract Manag 2002;2:2–8. 3. Reginster JY, Burlet N. Osteoporosis: a still increasing prevalence. Bone 2006;38:S4–9. 4. Stro¨m O, Borgstro¨m F, Kanis JA, et al. Osteoporosis: burden, health care provision and opportunities in the EU: a report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 2011;6:59–155. 5. Tosteson AN, Grove MR, Hammond CS, et al. Early discontinuation of treatment for osteoporosis. Am J Med 2003;115:209–16. 6. Caro JJ, Ishak KJ, Huybrechts KF, et al. The impact of compliance with osteoporosis therapy on fracture rates in actual practice. Osteoporos Int 2004;15:1003–8. 7. Siris ES, Chen YT, Abbott TA, et al. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med 2004;164:1108–12. 8. Kanis JA, Oden A, Johnell O, et al. The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women. Osteoporos Int 2007;18: 1033–46. 9. Kanis JA, Hans D, Cooper C, et al. Interpretation and use of FRAX in clinical practice. Osteoporos Int 2011;22:2395–411. 10. National Osteoporosis Foundation. Clinician’s guide to prevention and treatment of osteoporosis. Washington (DC): National Osteoporosis Foundation; 2014. 11. World Health Organization. Assessment of osteoporosis at the primary health care level. Geneva: WHO; 2007. Available from: www.who.int/chp/topics/rheumatic/en/index.html [last accessed 13 Feb 2015]. 12. Kanis JA, on behalf of the World Health Organization Scientific Group. Assessment of osteoporosis at the primary healthcare level. Technical report. WHO Collaborating Centre, University of Sheffield, UK; 2008. Available from: http://www.shef.ac.uk/ FRAX/index.htm; FRAXÕ http://www.shef.ac.uk/FRAX [last accessed 13 Feb 2015]. 13. Kanis JA, Oden A, Johansson H, et al. FRAXÕ and its applications to clinical practice. Bone 2009;44:734–43. 14. Kanis JA, Johnell O, De Laet C, et al. A meta-analysis of previous fracture and subsequent fracture risk. Bone 2004;35:375–82. 15. Klotzbuecher CM, Ross PD, Landsman PB, et al. Patients with prior fractures have an increased risk of future fractures: a summary of the literature and statistical synthesis. J Bone Miner Res 2000;15: 721–39. 16. Lindsay R, Silverman SL, Cooper C, et al. Risk of new vertebral fracture in the year following a fracture. JAMA 2001;285:320–3. 17. Gehlbach S, Saag KG, Adachi JD, et al. Previous fractures at multiple sites increase the risk for subsequent fractures: the global longitudinal study of osteoporosis in women. J Bone Miner Res 2012;27:645–53. 18. Hauser B, Riches PL, Wilson JF, et al. Prevalence and clinical prediction of osteoporosis in a contemporary cohort of patients with rheumatoid arthritis. Rheumatology (Oxford) 2014;53:1759–66. 19. Waugh EJ, Lam MA, Hawker GA, et al. Risk factors for low bone mass in healthy 40–60 year old women: a systematic review of the literature. Osteoporos Int 2009;20:1–21. 20. Kanis JA, Johnell O, Oden A, et al. Smoking and fracture risk: a meta-analysis. Osteoporos Int 2005;16:155–62. 21. Krall EA, Dawson-Hughes B. Smoking increases bone loss and decreases intestinal calcium absorption. J Bone Miner Res 1999;14: 215–20. 22. Kanis JA, Johansson H, Oden A, et al. A meta-analysis of milk intake and fracture risk: low-utility for case finding. Osteoporos Int 2005;16:799–804. 23. Bonjour JP, Brandolini-Bunlon M, Boirie Y, et al. Inhibition of bone turnover by milk intake in postmenopausal women. Br J Nutr 2008; 100:866–74.
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24. Sahni S, Mangano KM, Tucker KL, et al. Protective association of milk intake on the risk of hip fracture: results from the Framingham Original Cohort. J Bone Miner Res 2014;29:1756–62. 25. Rizzoli R. Dairy products, yogurts, and bone health. Am J Clin Nutr 2014;99:1256S–62S. 26. van Staa TP, Leufkens HG, Abenhaim L, et al. Use of oral corticosteroids and risk of fractures. J Bone Miner Res 2000;15: 993–1000.
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27. Kanis JA, Johansson H, Oden A, et al. A meta-analysis of prior corticosteroid use and fracture risk. J Bone Miner Res 2004;19: 893–9. 28. Black DM, Arden NK, Palermo L, et al. Prevalent vertebral deformities predict hip fractures and new vertebral deformities but not wrist fractures. Study of Osteoporotic Fractures Research Group. J Bone Miner Res 1999;14:821–8.
ISSN: 0951-3590 (Print) 1473-0766 (Online) Journal homepage: http://www.tandfonline.com/loi/igye20
Osteoporosis's Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study Stefano Lello, Roberto Sorge, Nicola Surico & OMERO Study Group To cite this article: Stefano Lello, Roberto Sorge, Nicola Surico & OMERO Study Group (2015): Osteoporosis's Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study, Gynecological Endocrinology To link to this article: http://dx.doi.org/10.3109/09513590.2015.1063605
Published online: 14 Jul 2015.
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Date: 10 November 2015, At: 11:56
http://informahealthcare.com/gye ISSN: 0951-3590 (print), 1473-0766 (electronic) Gynecol Endocrinol, Early Online: 1–7 ! 2015 Informa UK Ltd. DOI: 10.3109/09513590.2015.1063605
ORIGINAL ARTICLE
Osteoporosis’s Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study Stefano Lello1, Roberto Sorge2, and Nicola Surico3 for OMERO Study Group* Department of Woman and Child Health, Catholic University of Rome, Rome, Italy, 2Laboratory of Biometry, University of Tor Vergata, Rome, Italy, and 3Department of Gynecology and Obstetrics, University of Novara, Novara, Italy
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Abstract
Keywords
Osteoporosis (OP) and related fractures are well-known severe conditions affecting quality of life and life expectancy of postmenopausal women, with high economic costs in Europe. On behalf of The Italian Society of Gynecology and Obstetrics (Societa` Italiana di Ginecologia ed Ostetricia, SIGO), the Osteoporosis’s Menopausal Epidemiological Risk Observation (O.M.E.R.O.) study, a national multicenter study on clinical risk factors of OP was organized, using FRAXÕ tool as a reference. Here, data from this study are presented, showing an important portion of Italian postmenopausal women affected by osteopenia/OP at high risk of fracture and the need to do prevention and/or treatment. Gynecologist can be a primary specialist in this important challenge.
FRAXÕ , menopause, osteoporosis
Introduction Osteoporosis (OP) is a systemic skeletal disorder characterized by loss of bone strength and subsequent increased susceptibility to fragility fractures. Bone strength reflects the integration of bone quality (BQ) and bone mineral density (BMD) [1,2]. Nowadays, major osteoporotic fractures are a social and economic burden. International Osteoporosis Foundation estimated osteoporotic fractures in Europe in 2000 were 3.79 million, of which 890 000 were hip fractures; the total direct costs resulting from these fractures were estimated at euros 31.7 billions, though expected to increase to 76.7 billion euros by 2050, according to demographic changes [3]. However, OP remains under-diagnosed and under-treated, with a minority of
*OMERO Study Group: Andrea Tranquilli (deceased) (Ancona), Angelo Turi (Ancona), Daniele Agostinelli (Bari), Sergio Messini (Bolzano), Alessandro Gambera (Brescia), Massimo Stomati (Brindisi), Anna Maria Paoletti (Cagliari), Silvana Sanna (Cagliari), Maria Durante (Campobasso), Ignazia Roccu (Campobasso), Paolo Scollo (Catania), Franca Nocera (Catania), Enrica Ronca (Cremona), Sandra Bucciantini (Firenze), Sonia Baldi (Firenze), Sandra Nosari (Genova), Annunziata Marra (Lecce), Rosario D’Anna (Messina), Luisa Barbaro (Messina), Carlo Mapelli (Milano), Raffaella Chionna (Milano), Angelo Cagnacci (Modena), Costantino Di Carlo (Napoli), Carmine Nappi (Napoli), Livio Leo (Novara), Marina Pandolfo (Palermo), Rossella Nappi (Pavia), Silvia Tonani (Pavia), Angelamaria Becorpi (Firenze), Carmelina Santilli (Pescara), Silvia Maffei (Pisa), Barbara Del Bravo (Pisa), Marco Gambacciani (Pisa), Antonio Amorosi (Potenza), Rosalbino Mantuano (Ravenna), Anna Pasi (Ravenna), Francesca Guardianelli (Roma), Anna Capozzi (Roma), Roberto Frantellizzi (Roma), Giovanni Scambia (Roma), Paola Villa (Roma), Maurizio Zaza (Roma), Rosalba Percuoco (Roma), Fulvio Leoni (Roma), Salvatore Dessole (Sassari), Giampiero Capobianco (Sassari), Chiara Benedetto (Torino), Mario Gallo (Torino), Diego Marchesoni (Udine), Monica Della Martina (Udine). Address for correspondence: Stefano Lello, Department of Woman and Child Health, Catholic University of Rome, Largo Agostino Gemelli 1, Rome 00168, Italy. E-mail: [email protected]
History Received 17 May 2015 Accepted 14 June 2015 Published online 14 July 2015
patients at high fracture risk identified for treatment [4] and a persistent low adherence to therapies [5,6]. On the other hand, various data demonstrated BMD is not the single determinant of bone strength/fracture risk. National Osteoporosis Risk Assessment (N.O.R.A.) study showed the absolute number of fractures was higher in patients classified by DXA measurement as ‘‘osteopenic’’ than in those considered ‘‘osteoporotic’’ [7]. Therefore, evaluation of associated clinical risk factors may better define the risk profile of each patient. World Health Organization FRAXÕ (http://www.shef.ac.uk/ FRAX) algorithm integrates BMD values with clinical risk factors to give an estimate of 10-year absolute risk of major osteoporotic fracture (vertebra, humerus, wrist, hip) and hip fracture. In particular, femoral neck BMD (optional) may increase the fracture risk prediction power of FRAX [8,9]. Moreover, both National Osteoporosis Foundation (NOF) [10] and World Health Organization (WHO) [11,12] made recommendations about the prevention and treatment of at high-risk patients. The aim of this study was to evaluate the frequency of risk factors and the 10-year risk of osteoporotic fractures in Italy, in a gynecological setting, using FRAXÕ as a tool to assess skeletal health in peri- and postmenopausal women.
Materials and methods This was a multicenter (42 centers), prospective, nationwide trial sponsored by the Italian Society of Gynecology and Obstetrics (Societa` Italiana di Ginecologia ed Ostetricia, SIGO) on risk factors for OP and related fractures using WHO FRAXÕ [12]. FRAXÕ is an algorithm to evaluate the 10-year absolute probability of hip or major osteoporotic fracture (fracture of hip, spine, wrist, humerus) considering age, gender, race and clinical profile, with or without BMD value (grams/cm2), usually measured at femoral neck. In our study, besides femoral neck BMD (reported in the text as hip BMD), we included, when DXA was available, also spine (lumbar) BMD, to compare the effect of hip and spine BMD on FRAX model results.
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Study population consisted of three age subgroups: 45–55-years-old (subgroup 1); 55–65-years-old (subgroup 2), and 65–75-years-old (subgroup 3). Subjects were recruited following a sampling chart. Clinical risk factors (including those reported in FRAX model: age, sex, height, weight, previous fracture, parental hip fracture, current smoking, use of glucocorticoids, rheumatoid arthritis, secondary OP, alcohol consumption, and femoral neck BMD (if available) were assessed for each subject by a questionnaire. All information were sent by an on-line platform to a centralized data management to be evaluated by a statistician (R. S.). All data were analyzed using SPSS version 15 for Windows. Descriptive indexes of numerical values are expressed as percentage, while the indexes of normal variables as mean and standard deviations (M ± SD). Tests of statistical comparison, both parametric and non-parametric (ANOVA, Bonferroni test, Student’s t test), were considered significant when p50.05. We collected 1768 subjects from different areas in Italy. The research protocol was approved by local ethical committees, and written informed consent was obtained for each patient. Statistical power of the study was determined.
Results Descriptive analyses of the sample are shown in Table 1. Statistical power of the study was calculated to be 86%. Body weight, height and body mass index (BMI) (Table 1) were different among subgroups. We observed lower BMI in the first age subgroup versus second and third subgroup (p50.001).
As for fracture presence according to the age groups, the older the subjects the more frequent the fractures. In particular, all major osteoporotic fractures were significantly increased in the oldest class versus the other ones (p ¼ 0.001). Moreover, observing the fracture as a dichotomic variables (yes/not), we found 16% of the total sample had a story of previous fracture, with a significant increase in the third subgroup (23.9% of the subjects within group; 42.9% of the total study subjects with fracture) in comparison with first subgroup (9.3% of the subjects within group; 21.3% of the total subjects with fracture) (p ¼ 0.001). Moreover, 17.7% of total subjects reported parental hip fracture. This percentage resulted significantly higher in the oldest age subgroup than in the others (first subgroup: 13.1%; second subgroup: 16.6%; third subgroup: 24.9%; p ¼ 0.001). Corticosteroids (CS) were used by 4.8% of subjects, without significant differences among subgroups. A mean percentage of 2.0% of women showed a diagnosis of rheumatoid arthritis (p ¼ 0.257 among subgroups). A total of 89.9% of women was menopausal (100% in third-age subgroup, 98.9% in second, and 74.1% in first subgroup; p ¼ 0.001). Taking into account postmenopausal years, there was an increase from first to third age subgroup, with significant differences (p ¼ 0.001; 4.0 ± 5.2 for first subgroup; 10.6 ± 6.7 for second subgroup; 19.9 ± 6.1 for third subgroup). Milk intake was reported in 72.1% of total population, with a higher percentage of users in third subgroups (77.9%) versus first subgroup (67.1%) (p ¼ 0.001), but with a similar number of cups
Table 1. Geographic division, age, and anthropometric variables (weight, height, body mass index) of study sample.
Geographic division
1st subgroup 45.1–55 years (mean ± SD)
2nd subgroup 55.1–65 years (mean ± SD)
3rd subgroup 65.1–75 years (mean ± SD)
Total sample (mean ± SD)
1. North-west
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
123 50.8 ± 3.0 65.0 ± 12.0 161.5 ± 6.1 24.9 ± 4.4
121 60.5 ± 3.0 67.1 ± 13.4 160.8 ± 5.9 26.0 ± 5.4
80 69.8 ± 2.6 68.4 ± 13.2 160.6 ± 6.1 26.5 ± 4.6
324 59.1 ± 8.0 66.6 ± 12.8 161.0 ± 6.0 25.7 ± 4.9
2. North-east
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
25 51.3 ± 2.9 61.3 ± 8.5 162.8 ± 5.9 23.2 ± 3.3
23 60.5 ± 3.2 71.2 ± 15.1 163.7 ± 5.7 26.6 ± 5.7
16 69.9 ± 2.8 65.7 ± 10.5 161.6 ± 6.3 25.2 ± 3.8
64 59.3 ± 7.9 65.9 ± 12.3 162.8 ± 5.9 24.9 ± 4.6
3. Center
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
262 51.2 ± 2.7 62.9 ± 11.0 162.5 ± 6.3 23.8 ± 4.2
238 60.5 ± 3.1 65.3 ± 10.8 159.9 ± 6.1 25.6 ± 4.1
246 70.2 ± 2.7 65.4 ± 11.8 159.5 ± 6.1 25.8 ± 4.4
746 60.4 ± 8.3 64.5 ± 11.3 160.7 ± 6.3 25.0 ± 4.3
4. South
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
116 51.2 ± 2.8 65.3 ± 11.6 160.4 ± 6.1 25.4 ± 4.3
115 60.0 ± 2.8 69.5 ± 12.4 159.0 ± 6.5 27.4 ± 4.6
85 69.6 ± 2.9 66.4 ± 10.9 157.6 ± 6.3 26.8 ± 4.3
316 59.3 ± 7.8 67.1 ± 11.8 159.1 ± 6.4 26.5 ± 4.5
5. Islands
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
122 50.9 ± 2.8 62.9 ± 10.0 159.7 ± 5.3 24.6 ± 3.7
116 60.2 ± 3.0 64.5 ± 10.6 158.4 ± 5.4 25.8 ± 4.4
80 69.3 ± 2.6 64.6 ± 9.5 157.9 ± 5.6 25.9 ± 3.7
318 58.9 ± 7.8 63.9 ± 10.1 158.8 ± 5.5 25.4 ± 4.0
ITALY
N Age (years) Weight (kg) Height (cm) BMI (kg/m2)
648 51.1 ± 2.8 63.7 ± 11.1 161.4 ± 6.1 24.5 ± 4.2
613 60.3 ± 3.0 66.5 ± 11.9 159.8 ± 6.1 26.1 ± 4.6
507 69.9 ± 2.7 65.9 ± 11.6 159.2 ± 6.1 26.1 ± 4.3
1768 59.7 ± 8.1 65.3 ± 11.6 160.2 ± 6.2 25.5 ± 4.5
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per day (mean ± SD: 1.3 ± 1.0; 1.4 ± 1.1; 1.4 ± 1.1, for first, second, and third subgroup, respectively; p ¼ 0.311). Cheese and dairy products were used by 91% of the subjects, with a lower rate of servings/week in the oldest subgroup (2.7 ± 1.6 versus mean value 3.0 ± 1.9) (p ¼ 0.001). Lactose intolerance was reported by 8.1% of the subjects (no difference in percentage among different subgroups (1st: 9.0%; 2nd: 7.3%; 3rd: 8.1%; p ¼ 0.579). Current smoking was reported by a mean of 19.3% of total subjects, with a higher rate in youngest subgroups (25.6%) in comparison with second (18.3%) and third (18.5%) subgroups (p ¼ 0.001). Regarding the pack number/year, even if there were less smokers among older subjects, those who were smokers used significantly more packs/year (18.7 ± 23.0) than the first subgroup (13.4 ± 10.5) (p ¼ 0.022). A total of 21.9% of subjects declared current alcohol intake, with mean consumption of 1.4 ± 0.6 glass/d, without significant differences among subgroups (p ¼ 0.123). Evaluation of single clinical risk factors and FRAXÕ scores Femoral neck BMD is the skeletal region currently validated for FRAX use [12]. We used also, when available, lumbar spine BMD (LS-BMD) to compare the results with those obtained with hip BMD. For many subjects there were both hip BMD and lumbar spine BMD (n ¼ 536), with smaller number including only LS-BMD (n ¼ 280); hip BMD was reported in 765 patients. Following statistical tests are for independent data. Overall, we calculated 2304 FRAXÕ scores (828, 791, 685 for first, second and third subgroup, respectively). Significant difference for BMD values (Figure 1) among third subgroup (the lowest values), and first and second subgroups (p ¼ 0.001, respectively) was measured. Moreover, in third subgroup there was significant difference between LS-BMD versus hip-BMD (p ¼ 0.016).
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FRAXÕ scores for major osteoporotic fractures and hip fracture calculated with and without BMD values are reported in Table 2. FRAXÕ scores for major osteoporotic fractures increased significantly both for age subgroups (p ¼ 0.001) and for DXA BMD data (p ¼ 0.01). Moreover, an interaction effect exists between age subgroups and FRAXÕ data calculated with vertebral, hip-BMD and no DXA data (p ¼ 0.004). There was no statistical difference for major osteoporotic fractures FRAX score with spine BMD or no DXA data, while there was a significant difference between FRAXÕ score calculated with hip-BMD, on one hand, and no DXA data or spine BMD, on the other hand. Hip fracture FRAXÕ data were statistically different both for age subgroups (p ¼ 0.001) and for presence/absence of BMD values (p ¼ 0.001) (Figure 2). Thus, FRAXÕ values calculated without BMD were different in comparison with those calculated with LSBMD or hip-BMD. T-score values for hip and spine showed significant differences among three subgroups of age (Table 3). Among hip T-scores, 75.4% showed osteopenia or OP, mostly in the oldest subgroups (p ¼ 0.001). In particular, 47.3% of women were osteopenic (low bone mass), and 28.1% osteoporotic. These percentages, in first-, second-, and third-age subgroup, were respectively, 38.2%, 34.6%, and 27.2% for osteopenic values, and 18.6%, 29.4%, and 45.9% for OP, with an important increase for second and third subgroups versus first age subgroup (p ¼ 0.001). According to LS T-score, 75.1% of subjects had a pathological values, with significant worsening in older subgroups (p ¼ 0.001), 57.6% of total subjects being classified as osteopenic, and 17.5% as osteoporotic; osteopenic range was present in 58.9%, 60.7%, and 52.4%, in first, second, and third subgroup, respectively, while osteoporotic values were reported for 9.5%, 12.8%, and 32.5%, respectively (p ¼ 0.001). Looking at hip and vertebral T-score values according to Tscore classes (i.e. normal, osteopenia, and OP), hip T-score determined a significantly higher number of OP diagnosis in comparison with vertebral T-score as diagnosed by DXA measurement (57.4% versus 42.6%, respectively; p ¼ 0.001 for difference). Among all clinical risk factors, smoking (yes/no) provided a significant difference in FRAXÕ score values both for major osteoporotic fractures and hip fracture (p ¼ 0.001); alcohol factor showed a similar effect to smoking on FRAXÕ both for major osteoporotic fractures and hip fracture (p ¼ 0.001 for presence/ absence of alcohol within each subgroup). CS impacted on FRAXÕ for major osteoporotic fracture (corticosteroid present versus absent: p ¼ 0.001). Previous fractures determined a significant difference in terms of FRAXÕ score both for major osteoporotic fractures and for hip fracture (p ¼ 0.001 for presence versus absence of previous fracture). Another important risk factor was hip parental fracture; significant differences were found among age subgroups (p50.05). Hip parental fractures increased significantly FRAXÕ score both for major osteoporotic fracture and hip fracture (risk calculated with and without hip parental fracture in family hystory of the subjects: p ¼ 0.001 for first versus second versus third subgroup, and for presence versus absence of parental fracture: p ¼ 0.001 only in second and third subgroup). Evaluation of the outcome of FRAX’s use in an Italian population
Figure 1. LS-BMD and Hip-BMD values measured by DXA for age subgroups (*p ¼ 0.001 for difference between first and third subgroups, and ^p ¼ 0.016 for difference in second and third subgroups within LS-BMD versus Hip-BMD).
We evaluated the impact of FRAXÕ model both on subjects with available BMD value (vertebral or hip BMD) and on subjects without BMD. We determined the number of subjects who should be treated, according to FRAXÕ ’s threshold for 10-years hip
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Table 2. FRAX score (for major osteoporotic fracture and hip fracture) calculated with or without DXA (Hip or LS) BMD data.
Age subgroups*
FRAX score without DXA BMD
FRAX score with LS BMD
FRAX score with hip BMD
FRAX score for major osteoporotic fracture
FRAX score for hip fracture
FRAX score for major osteoporotic fracture
FRAX score for hip fracture
FRAX score for major osteoporotic fracture
FRAX score for hip fracture
*,**1st group (45.1–55 years)
N Mean ± SD
276 7.32 ± 6.71
276 2.38 ± 4.55
291 5.66 ± 1.77
291 1.43 ± 0.63
180 6.22 ± 4.89
180 1.70 ± 3.72
***2nd group (55.1–65 years)
N Mean ± SD
243 8.70 ± 6.41
243 2.77 ± 3.58
284 8.75 ± 4.66
284 2.38 ± 0.66
178 9.08 ± 7.59
178 2.60 ± 5.95
3rd subgroup (65.1–75 years)
N Mean ± SD
204 12.01 ± 8.65
204 5.09 ± 5.90
241 18.87 ± 9.69
240 10.07 ± 6.44
178 21.50 ± 18.13
178 12.04 ± 17.18
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*p ¼ 0.05 among age subgroups; **p ¼ 0.001 for subgroup 1 versus subgroups 2 and 3; ***p ¼ 0.001 for subgroup 2 versus subgroup 3.
FRAXÕ score for major osteoporotic fractures, calculated without BMD value, showed a percentage 20% in 3.3%, 5.8%, and 17.2%, in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup, and between second and third subgroup). A hip fracture FRAXÕ Score 3%, calculated without BMD value, was reported in 6.5%, 11.9% and 39.2% in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup, and between second and third subgroup). FRAXÕ score values distribution for hip fracture risk calculated without BMD, with hip or spine BMD, in age subgroups (cut-off 3%) are reported in Figure 3(A). FRAX score values distribution for major osteoporotic fractures risk found without BMD, with hip or spine BMD in the age subgroups (cut-off 20%), are reported in Figure 3(B).
Discussion and conclusions
Figure 2. FRAX score for hip fracture calculated without DXA BMD value, with hip BMD, and LS-BMD (*p ¼ 0.001 for subgroup 3 versus 1 and 2; ^p ¼ 0.001 in third subgroups within no DXA versus hip-BMD versus LS-BMD).
fracture risk (3%) and for major osteoporotic fractures risk ( 20%). Overall, 4.8% in first subgroup, 7.0% in second subgroup, and 29.5% in third group showed a major osteoporotic fractures FRAXÕ score 20% calculated with spine BMD (p ¼ 0.001 for difference between first and second and **between second and third subgroup). Hip fracture FRAXÕ Score 3%, calculated with spine BMD, was found in 15.8%, 22.2%, and 43.2% in the first, second, and third age subgroup, respectively (p ¼ 0.001 for difference first versus and second and third subgroup, and between second and third subgroup). Major osteoporotic fracture FRAXÕ score calculated with hip BMD showed a percentage 20% in 6.9%, 10.6%, and 32.5% in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup, and between second and third subgroup). FRAXÕ score for hip fracture, calculated using hip BMD, was 3% in 19.9%, 24.2%, and 47.5%, in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third subgroup and between second and third subgroup).
We evaluated the characteristics and risk factors for OP and related fractures in a population from different regions of Italy. FRAXÕ is an algorithm [12] which uses clinical risk factors to estimate an individual’s 10-year osteoporotic fracture (both major osteoporotic fractures and hip fracture) probability. FRAXÕ tool is useful to identify individuals who should be candidates for BMD screening or pharmacological intervention. FRAX is also used for guideline development and health economic applications [9,13]. FRAXÕ should not be considered as a gold standard in a subject’s evaluation, but rather as a reference clinical basis. Therefore, FRAXÕ does not substitute clinical judgment for each clinical case. BMD testing alone is not an absolute marker of OP and related fracture risk. In our sample, a total of 282 previous fractures was reported, with a higher percentage in the third age subgroup as expected (23.9% of the subjects within group; 42.9% of the total subjects with fracture), and a lower percentage in second and first subgroup. This difference was significant between first and third subgroup (p ¼ 0.001). Previous fracture is a potent risk factor for other fractures [14–16], so the third subgroup resulted at higher risk not only for age, but also for this factor at baseline. Also fractures at different sites other than hip, spine and wrist are predictor of subsequent fractures [17] (see Table 2). Parental hip fracture [RR for subsequent fracture ¼ 1.40 (95% CI ¼ 1.09–1.80)] [9], was reported in 17.7% of total subjects (more frequently in third subgroup). A low percentage of women (2%) reported a condition of rheumatoid arthritis, a known risk factor for OP and fracture [18], in line with the gynecological setting of our study, presenting a
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Table 3. T-score values (hip and vertebral) according to age subgroups. Hip T-score Age subgroups
Vertebral T-score
Normal Osteopenia Osteoporosis Normal Osteopenia Osteoporosis (41) (between 1 and 2.5) (52.5) Total (41) (between 1 and 2.5) (52.5) Total 80 33.2 47.1
125 51.9 38.2
36 14.9 18.6
241 100.0 34.9
90 31.6 44.1
168 58.9 35.5
27 9.5 18.8
285 100.0 34.7
2nd subgroup (55.1–65 years) N % subgroup % T-score
53 22.6 31.2
113 48.1 34.6
69 29.4 35.6
235 100.0 34.0
77 26.6 37.7
176 60.7 37.2
37 12.8 25.7
290 100.0 35.3
3rd subgroup (65.1–75 years) N % subgroup % T-score
37 17.2 21.8
89 41.4 27.2
89 41.4 45.9
215 100.0 31.1
37 15.0 18.1
129 52.4 27.3
80 32.5 55.6
246 100.0 30.0
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1st subgroup (45.1–55 years) N % subgroup % T-score
Figure 3. (A) FRAXÕ score for hip fracture according to age subgroups, calculated without BMD, with hip BMD, and with spine BMD. (B) FRAX score for major osteoporotic fractures according to age subgroups, calculated without BMD, with hip and spine BMD.
low number of patients with chronic inflammatory diseases, including rheumatoid arthritis. Smoking [19–21] was present for 19.3% of all subjects, with higher packs/year consumption for third subgroup; this is interesting, since a dose–response and a progressively increasing risk of hip fracture with age (probably for a longer duration of exposure) [9] was reported. Alcohol consumption [22] was reported by 21.9% of total sample without difference among subgroups. The mean consumption was 1.4 ± 0.6 glass/d, an intake to be considered low [9].
Milk intake resulted for 72.1% of total population, with a higher percentage of users in third subgroups (77.9%) versus first subgroup (67.1%) (p ¼ 0.001), but with a similar number of cups per day (mean ± SD: 1.3 ± 1.0; 1.4 ± 1.1; 1.4 ± 1.1, for first, second, and third subgroup, respectively; ANOVA one-way; p ¼ 0.311). Even if a factor traditionally thought to be important for skeletal health, milk intake has controversial and inconclusive data reported [22–24]. Cheese and dairy products were used by 91% of the subjects, with a lower rate of servings/week in the oldest subgroup (2.7 ± 1.6 versus mean value 3.0 ± 1.9) (p ¼ 0.001). This number is near recommended intake of three servings/day [25]. Hip T-score values was in osteopenic or osteoporotic range in 75.4% of total sample, with worse values, as expected, in third subgroup (p ¼ 0.001); 47.3 of subjects were in osteopenic (low bone mass) range, and 28.1% in osteoporotic range. For first, second, and third subgroup, the percentages were, respectively, 38.2%, 34.6%, and 27.2% for osteopenic values, and 18.6%, 29.4%, and 45.9% for OP diagnosis (p ¼ 0.001 for difference between second and third subgroups versus first). According to Clinician’s Guide to Prevention and Treatment of OP recently published by NOF [10], it is recommended to pharmacologically treat subjects with T-scores52.5 at the femoral neck, total hip or lumbar spine by DXA. Thus, in third age subgroup in our study, for example, nearly half of patients should be pharmacologically treated, and the same applies to about 1 of 3 (29.4%) in second subgroup, and about 1 of 5 in first subgroup (18.6%). Considering vertebral T-score other interesting considerations emerged; actually, 75.1% of total sample had osteopenic (low bone mass, a significant risk factor as demonstrated in NORA study) or osteoporotic values, with a significant worsening in older subgroups (p ¼ 0.001). A total of 57.6% of total subjects were classified osteopenic, and 17.5% osteoporotic. Osteopenic range was present in 58.9%, 60.7%, and 52.4%, in first, second, and third subgroup, while osteoporotic BMD values were reported for 9.5%, 12.8%, and 32.5%, respectively (p ¼ 0.001). Again, according to NOF [9], the portion of osteoporotic subjects should be treated; thus, more than one-third of postmenopausal patient 65–75-years-old in an Italian population should receive pharmacological treatment according to spine BMD. According to hip and vertebral T-score values for different T-score classes (i.e. normal, osteopenic, and osteoporotic), hip T-score determined a significantly higher number of OP diagnosis in comparison with vertebral T-score measured by DXA (57.4% versus 42.6%, respectively; p ¼ 0.001). Also the presence of corticosteroid use, 4.8% in total population, a well-known risk factor [26,27], had a significant impact on FRAX score for major osteoporotic fracture (p ¼ 0.001), and previous fractures, another factor known to increase the risk of subsequent fractures [28], determined a
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S. Lello et al.
significant difference in terms of FRAX score both for major osteoporotic fractures and for hip fracture (p ¼ 0.001 for presence versus absence of previous fracture). Parental fracture was important in determining an increase of FRAX score both for 10-year hip fracture risk (p ¼ 0.001 in second and third subgroup versus no hip parental fracture) and for hip fracture risk. Taking into account the threshold values of FRAX model both for 10-year probability of major osteoporotic fracture (hip, clinical spine, humerus or wrist fracture; 20%) and hip fracture ( 3%), we determined subjects to be treated for preventing osteoporotic fractures, using both femoral neck BMD and LS-BMD. Thus, 4.8% in first, 7.0% in second, and 29.5% in third groups showed a major osteoporotic fractures FRAX score 20% calculated with spine BMD (p ¼ 0.001 for difference between first and second and second and third subgroup). Hip fracture FRAX Score 3%, calculated with spine BMD, was found in 15.8%, 22.2%, and 43.2% in the first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and second subgroups and second and third subgroups). FRAX score calculated with hip BMD showed a 10-year major osteoporotic fractures risk 20% in 6.9%, 10.6%, and 32.5% in first, second, and third age subgroups, respectively (p ¼ 0.001) for difference between first and third and second and third subgroup). FRAX score for hip fracture 3%, calculated with hip BMD, was found in 19.9%, 24.2%, and 47.5%, in first, second, and third age subgroups, respectively (p ¼ 0.001 for difference between first and third and second and third subgroups). The trend of percentage of risk is similar in FRAX score calculated with spine BMD and hip BMD, even if the percentages with hip BMD were generally higher. Of major interest, the percentage of subjects at significant 10year risk 20% for fracture assessed with FRAX model using femoral neck (hip) BMD was 10.6% for major osteoporotic fracture in second subgroup and 32.5% (more than one of the three subjects) in third subgroup. More impressively, FRAX score 3% for hip fracture calculated with femoral neck BMD was 19.9% (nearly one of five) in first subgroup, 24.2% (more than one of five) in second subgroup, and 47.5% (nearly one of two) in third subgroup. These data are very impressive, pointing out OP remains an under-diagnosed and under-treated disease, with a minority of patients at high fracture risk identified for treatment [4]. Our results, produced in a gynecological setting, allow us to draw some conclusions: (1) Gynecologist is the specialist able to do a real primary prevention and therapy of OP, since this specialist meets, in everyday clinical practice, younger peri-postmenopausal and older post-menopausal women at low-, medium-, and high risk for fracture. (2) It is important to assess the risk profile for each woman in peri- and post-menopause to find a strategy for prevention/ treatment in the high-risk subjects; FRAXÕ score provides an easy and reliable tool for identifying these subjects. (3) According to National Osteoporosis Guide for OP prevention and treatment [10], in our study a high percentage of patients with –2.5 T-score should be treated in an Italian population within an age range 45–75 years, with an obvious increase of high-risk patients in older groups. (4) According to FRAX score, 47.5% of subjects in age range 65–75 years are at high 10-year risk for hip fracture in our study. These data should be taken into account in making prevention strategies and treatment regimens.
Gynecol Endocrinol, Early Online: 1–7
Declaration of interest This study was supported through a research grant by Pfizer Inc. to SIGO. The authors declare no conflicts of interests. The authors alone are responsible for the content and writing of this article.
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