German DVO risk score identified more patients requiring treatment compared to FRAX score in a retrospective analysis of women evaluated for osteoporosis

German DVO risk score identified more patients requiring treatment compared to FRAX score in a retrospective analysis of women evaluated for osteoporosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report German DVO risk score identified more patients requiring treatment compared to FRAX score in a retrospective analysis of women evaluated for osteoporosis Anna Frank, Judith Charlotte Witzel, Christina Heppner, Annette Lamersdorf, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4949818/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In a retrospective study of 555 female patients, we compared osteoporosis-specific fracture risk probabilities and treatment recommendations according to the German DVO guidelines with those resulting from the internationally implemented FRAX score. We present the differences between both scores, which also identified different individual patients as in need of therapy. Purpose Fracture risk determination is essential when recommending treatment in osteoporosis management. This study compares and contrasts the risk probabilities of major osteoporotic and hip fractures calculated by the DVO score established in German-speaking countries with those of the FRAX tool. Methods We retrospectively analysed data from 555 female patients (mean age 64.2 ± 10.3 years) evaluated for osteoporosis. For the DVO score, we set the therapy threshold of > 30% for vertebral and hip fractures as suggested by DVO guidelines before 2023. Major osteoporotic fracture (MOF) and hip fracture risk (HF) were calculated based on corresponding FRAX scores. We applied the internationally most common therapy threshold of ≥ 20% for MOF and ≥ 3% for HF and subsequently determined the “DVO-equivalent risk levels” for FRAX-based assessment. Results Based on DVO score, 52.8% of women had a 10-year risk of hip and vertebral fractures > 30%. Most patients were identified by HF ≥ 3% without BMD (56%). The 14.6% of patients identified for treatment only by DVO score presented a higher percentage of spinal fractures (38.3% vs. 18.6%), whereas the 10.6% of patients only identified by FRAX including BMD presented a higher percentage of peripheral fractures (40.7% vs. 29.6%). The thresholds for this “DVO-equivalent risk level” for ‘FRAX with BMD’ would be ≥ 10% for MOF and ≥ 2.6% for HF. Given the differences in the DVO and FRAX scores, it would be highly recommendable to consider both scores when assessing individual women for treatment. bone mineral density osteoporosis risk factors therapy threshold 10-year fracture risk fracture risk assessment DVO-score Figures Figure 1 Figure 2 Background Osteoporosis is one of the four most common health problems. Worldwide, 6% of men and 21% of women between 50 and 84 years of age suffer from osteoporosis [ 1 , 2 ]. For the assessment and timely treatment of osteoporosis, the determination of individual fracture risks is becoming more relevant. Lately, the availability of anabolic therapeutic agents has increased the necessity to improve the prediction of fragility fractures and thus target therapeutic interventions in postmenopausal women more effectively [ 3 ]. A number of different tools have been developed to assess fracture risk, taking into account that factors other than areal bone mineral density (BMD) also influence fracture risk [ 4 , 5 ]. The FRAX score is one such tool that was established in 2008 and updated several times to adapt to new developments, especially to include the recency of fractures [ 6 ]. The FRAX score calculates an individual 10-year fracture risk by considering defined clinical risk factors and (optionally) the bone mineral density at the femoral neck. The percentage calculated is a country-specific risk of suffering a major osteoporotic fracture (MOF), including spinal, hip, shoulder, and wrist fracture, or a hip fracture (HF), using an algorithm. FRAX does not propose any therapy thresholds, above which scores patients are recommended treatment. However, the internationally most commonly implemented therapy thresholds for FRAX are ≥ 20% for MOF and ≥ 3% for HF [ 7 – 9 ]. The score commonly used in German-speaking countries is based on the German guidelines for diagnostics and treatment of osteoporosis developed by the Dachverband Osteologie (German Confederation of Osteologists, DVO ). Founded on these guidelines, the DVO score is a multistep approach (Table 1 ) to classify patients in groups of 10-year fracture-risk probabilities of suffering a hip or clinical vertebral fracture. Starting with a set of forty risk factors, patients are assessed whether their 10-year fracture risk is 20%. Patients with a 10-year fracture probability > 20% are advised to undergo further diagnostics including bone mineral density measurement via dual-energy absorptiometry (DXA). Depending on the resulting BMD in combination with the risk factors, patients are then stratified further into groups with either a risk between 20% and 30% or > 30%. All patients with a 10-year fracture risk of > 30% are recommended specific treatment for osteoporosis [ 10 – 12 ]. The first edition of these guidelines was published in 2003 and was revised in 2006, 2009, 2014, and 2017, in accordance with the relevant literature. In 2023, a new DVO score was published, representing a major change in risk assessment by calculating the 3-year fracture risk for 10-year fracture-risk probabilities of suffering a hip or clinical vertebral fracture and adapting different risk categories [ 13 , 14 ]. Table 1 Comparison of DVO and FRAX score DVO score FRAX score Many (version 2017 = 40) risk factors listed in the DVO guidelines 12 risk factors, DXA value optional Different fracture types Prior fractures DXA at lumbar spine OR total femur OR femoral neck DXA at femoral neck only, optional Step-by-step evaluation of the 10-year fracture probability One step to the 10-year fracture probability Consistent therapy threshold > 30% No therapy threshold set by tool Dependent variable: 10-year fracture incidence of hip and vertebral fracture Dependent variable: 10-year fracture probability of major osteoporotic fracture or hip fracture Published 10-year fracture risk calculation method 10-year fracture risk calculation algorithm Additional risk factors with direct therapy recommendation Aims: Prior to the development of the new DVO score, it was in discussion as to whether German-speaking countries would also apply FRAX score in the clinical care of patients with osteoporosis. We were therefore interested to answer the question of how the respective FRAX score would have characterized women treated according to the DVO score prior to 2023. In this retrospective study, we compared risk scores and treatment recommendations in Germany on the basis of DVO score with the internationally employed FRAX fracture-risk assessment tool effective at the time of clinical presentation in a cohort of women evaluated for osteoporosis in an endocrinology centre in Germany. Furthermore, we assessed therapy thresholds for FRAX frequently employed internationally (≥ 20% for MOF and ≥ 3% for HF) [ 12 ] and adapted these to our study group to compare them to the therapy recommendations based on DVO score. Owing to the fact that our patients were treated according to DVO score during the subsequent years, it is not possible to conclude which score is more accurate regarding fracture risk prediction. Methods Patients This seven-year retrospective study bases on data recorded between July 2007 and June 2014 at MVZ endokrinologikum Göttingen, which is an endocrinological centre specialising in the diagnosis and treatment of patients with osteoporosis. Patients were mainly referred from other clinics or practices for evaluation of secondary osteoporosis, fracture risk, and treatment consideration. Out of 710 female patients (age 40–91 years) identified, 555 met the study criteria including a complete set of data on DVO score, clinical risk factors for the FRAX score, and a DXA measurement of the femoral neck on at least one side. Of these 555 patients, 500 also underwent DXA measurement of the lumbar spine. All data were documented and validated by a physician. All patients provided informed consent to use of their individual data in an anonymized form for research purposes. The local ethics review board in Göttingen approved this approach with their decision dated 18 February 2007 (Ref. 18-2-07). Data Available data on general patient information (age, height and loss of height, body mass), medical history (medication, illnesses, lifestyle factors, risk factors for osteoporosis), family and fracture history (previously experienced, pathological and/or traumatic, fracture side), as well as laboratory parameters and DXA measurements were collected from the patients’ electronic medical records (Medistar) retrospectively. DXA was used to measure BMD and T-score at the femoral neck, the total femur, and the lumbar spine (L1-L4). Whereas 57.4% of the DXA procedures were performed at MVZ endokrinologikum Göttingen using a GE Lunar Prodigy densitometer (GE Healthcare GmbH), the other 42.6% were performed in other radiological centres. We used the minimum T-score (and not BMD) at the femoral neck to calculate the respective FRAX score. Analysis : To calculate the FRAX 10-year fracture risks for a MOF and HF, respectively, we utilised the web-based data interface of the country-specific version of the risk calculator for Germany, which is available on the University of Sheffield website ( https://www.sheffield.a.uk/FRAX/tool.aspx?lang=de ). The required data include age, body mass, previous fracture, parental history of hip fracture, current smoking, long-term use of oral glucocorticoids, rheumatoid arthritis, daily alcohol consumption, other causes of secondary osteoporosis, and optionally the minimum T-score of the left and right femoral neck. We implemented therapy thresholds for FRAX scores of ≥ 20% for a MOF and ≥ 3% for a HF [ 12 ]. Subsequently, we compared the calculated FRAX scores with the recommendations based on the DVO guidelines. All patients’ data were used to determine the 10-year fracture probability for hip or vertebral fractures, referring to the edition of the DVO guidelines available during the year of first presentation to the MVZ endokrinologikum for osteoporosis evaluation. The DVO guidelines suggest a step-by-step procedure to estimate 10-year fracture probabilities. By taking into account the presence of various risk factors and their different impact on fracture risk, the fracture risk is initially determined as lying below or above 20%. All patients with 10-year fracture risk > 20% are recommended to undergo DXA measurement at all three sites. The DVO guidelines provide a therapy-indication table based on gender, age, a number of BMD-independent risk factors, and DXA T-score that can be used to determine whether the 10-year fracture risk exceeds 30%. All patients with a 10-year probability > 30% are recommended specific anti-osteoporotic treatment. Statistical analysis was performed with the software packages IBM SPSS Statistics Version 25 and Microsoft Excel 365, using descriptive statistics as well as Wilcoxon signed-ranked and McNemar tests. The McNemar test was specifically used to test the agreement of therapy recommendations. The significance level was set at p < 0.05. Furthermore, we used a confusion matrix to analyse and visualize the sensitivities and specificities of the DVO and FRAX scores based on therapy recommendations and the prevalence of spinal fractures. Owing to the fact that women were treated according to their fracture risk, we cannot evaluate the true incidence of new fractures. Therefore, we cannot conclude which score predicts the actual fracture incidence more accurately from our data. Results In total, 555 female patients with a complete set of data were analysed. Table 2 summarises the baseline characteristics of the included patients. The two scores approach risk factors differently. Smoking, glucocorticoid intake, rheumatoid arthritis, and alcohol consumption are treated as causes of secondary osteoporosis in DVO, whereas these risk factors have to be entered separately into the FRAX interface. Focussing on the secondary osteoporosis causes according to FRAX, the onset of menopause prior to the age of forty-five was the most common (95.23%). The most common secondary cause in DVO was vitamin-D deficiency in 28 of 116 patients (24.13%). Table 2 Baseline characteristics of patients Baseline characteristics of patients n MVZ endokrinologikum Göttingen Age in years ± SD 555 64.21 (± 10.3) BMI in kg/m 2 ± SD 555 24.94 (± 4.66) Prior fracture 292 52.61% Parental hip fractures 77 13.87% Current smoking 91 16.40% Oral glucocorticoids (current intake > 5mg) 93 16.76% Rheumatoid arthritis 39 7.03% Alcohol three or more units a day 48 8.65% Femoral neck T-score 555 -1.86 (± 0.98) Secondary osteoporosis (as described in FRAX) 126 22.70% Secondary osteoporosis (as described in DVO) 116 20.90% All 555 patients had at least one documented T-score at the femoral neck. The average T-score at the femoral neck was − 1.86 ± 0.98 and thus higher than the average T-score at the lumbar spine of -2.21 ± 1.23. Taking into account the lowest T-score of all the three measurement sites, the mean value of -2.51 ± 0.99 was even lower than at the lumbar spine. When only patients with any prior fracture were analysed, the minimum T-score at the femoral neck was significantly lower (p < 0.01, Wilcoxon test) than in those without any fracture (femoral T-score − 1.99 ± 0.93 versus − 1.72 ± 1.01). Figure 1 illustrates fracture risk probabilities (vertical axis) according to the DVO score in our study population. The DVO score identified 52.8% (293 out of 555) as having a 10-year fracture risk of suffering a hip or vertebral fracture > 30%. We identified a secondary cause of osteoporosis in 22.9% (67 out of 293) of these patients (12.1% of the total 555 patients). The mean 10-year fracture probabilities according to FRAX were significantly higher when including BMD, both for MOF (p < 0.001) and HF (p < 0.001). We additionally calculated the mean individual FRAX 10-year fracture probability within the subgroups of 30% fracture risk according to the DVO score. The mean FRAX score fracture probabilities with and without BMD proved to be lower than those determined for the DVO scores in all groups. Hence, the FRAX score identified fewer patients at risk. The mean FRAX score fracture probabilities for patients with a DVO score > 30% without BMD proved to be 18.2 ± 11.4 for FRAX MOF and 8.9 ± 9.5 for FRAX HF. Including BMD they were 17.4 ± 10.8 for FRAX MOF and 8.1 ± 9.1 for FRAX HF. Considering the fact that the DVO score identified 52.8% of patients in need of therapy, we calculated FRAX score thresholds that would identify the same percentage of patients. We found the adapted therapy thresholds for MOF to be markedly lower (without BMD 11.0%, with BMD 10.0%) in value in our female study population than internationally employed thresholds of ≥ 20%. Looking at the internationally common therapy threshold of ≥ 3% for HF, our adapted therapy threshold without BMD was higher (3.4%), whereas the value with BMD (2.6%) was below the internationally implemented threshold. We again applied the commonly used therapy thresholds for FRAX to compare the therapy indications for both the DVO and FRAX scores (Fig. 2 ) and statistically determined whether the respective differences were significant or not. The most patients were identified by the FRAX score as requiring treatment adopting a threshold of 3% for HF without BMD followed by the DVO score, with the small difference being statistically insignificant (p = 0.705). The fewest patients were recommended treatment by the FRAX score based on a therapy threshold of≥ 20% for MOF with or without BMD. All FRAX scores, except FRAX for HF without BMD showed a significant (p < 0.05) difference regarding their therapy recommendations in respect to the DVO score. Aiming to determine the overlap of patients identified by each score, the greatest percentage concordance of 39.3% for women with therapy recommended was found between FRAX HF ≥ 3% without BMD and DVO. However, both scores identified different individual women in need of therapy. The FRAX score classified 16.8% of patients as requiring therapy not identified by DVO score. In comparison, 13.5% were identified by DVO but not by FRAX. Furthermore, FRAX HF ≥ 3% with BMD identified 72.4% of the patients recommended treatment according to the DVO score. The FRAX score for MOF ≥ 20% with BMD identified the fewest individual patients also identified by DVO score as requiring treatment. Table 4 depicts the patient-specific differences in the two scores with the greatest overlap (38.2% of the total population) but also with women unidentified by each score. We compared the parameters of patients identified by both DVO and FRAX HF with BMD with those of each single score to describe the difference in the risk profile of each score. Table 3 Comparison of risk factors in patient groups identified as in need of therapy by DVO and FRAX HF with BMD, only by DVO score and only by FRAX HF with BMD. Risk factors of patients DVO and FRAX HF with BMD overlap (n = 212) DVO only (n = 81) FRAX HF with BMD only (n = 59) Prior fracture 69.8% 49.4% 62.7% • Spinal fracture 42.0% 38.3% 18.6% • Peripheral fractures at the age of 50 years 49.1% 29.6% 40.7% Parent hip fractures 18.4% 13.6% 8.5% Current smoking 18.9% 13.6% 22.0% Oral glucocorticoids (current intake > 5 mg) 23.1% 11.1% 16.9% Rheumatoid arthritis 11.3% 2.5% 5.1% Alcohol three units or more 9.9% 8.6% 10.2% Secondary osteoporosis 20.8% 28.4% 15.3% Femoral neck T-score -2.5 ± 0.7 -1.4 ± 0.7 -2.3 ± 0.7 Total femur T-score -2.4 ± 0.8 -1.5 ± 0.9 -2.0 ± 0.9 Lumbar spine T-score -2.7 ± 1.1 -2.4 ± 1.4 -2.1 ± 1.2 We conclude from our results that a number of risk factors have differing influence on the scores, resulting in different treatment recommendations to patients. Those only identified by the DVO score presented double the number of prior spinal fractures (38.3% vs. 18.6%) and a higher percentage of parental hip fractures (13.6% vs. 8.5%), whereas the prevalence of peripheral fractures was around 11 percentage points higher in those identified only by the FRAX score (40.7% vs. 29.6%). Looking at risk factors other than fracture history, those patients only identified by FRAX HF with BMD were found to have a higher percentage prevalence of the risk factor “current smoking” (22% vs. 16.6%). In addition, the risk factor “rheumatoid arthritis” was 5.1% vs. 2.5% in DVO-score. On the other hand, patients identified by the DVO score presented secondary osteoporosis more often (28.4% vs. 15.3%). To analyse the respective sensitivities and specificities of the DVO and FRAX scores with respect to the predictive value of prevalent spinal fractures, we used a confusion matrix. In comparison, the DVO score proved to have a greater and significant sensitivity (0.8, p < 0.001), precision (0.41, p = 0.002), negative predictive value (0.86, p < 0.001), and accuracy (0.63, p < 0.001) than the FRAX score for HF with BMD (sensitivity (0.67, p < 0.001), precision (0.37, p < 0.001), negative predictive value (0.82, p < 0.001), accuracy (0.60, p < 0.001)). Specificity was nearly identical between FRAX (0.58, p = 0.002) and DVO score 0.57 (p = 0.004). Discussion In this single-centre retrospective study, we compared the respective fracture risks calculated by the DVO and FRAX scores with and without bone mineral density measurements in 555 female patients evaluated for osteoporosis in an endocrinological healthcare centre between 2007 and 2014. The study population was not a representative sample of the female population, presenting a higher risk of suffering from osteoporosis compared to the general population. The FRAX and DVO scores applied for these women differ in the number of risk factors assessed and their algorithms of 10-year fracture-risk calculation. The FRAX score uses an algorithm to calculate the 10-year fracture probability of a MOF or HF. The score may be used without DXA measurements, or with BMD or T-score values (using a female reference population applied to men and women alike). In contrast, the DVO score used during the investigated period presents a step-by-step, replicable 10-year fracture assessment of the risk of suffering a hip or vertebral fracture and is based on the T-score (also using a female reference population). The DVO therapy threshold is set at a fixed fracture-risk level and the guidelines recommend specific anti-osteoporotic therapy for patients when their 10-year fracture probability of suffering a hip or vertebral fracture > 30%. The FRAX therapy thresholds employed vary across countries. A systematic review revealed that the most common therapy threshold for MOF is ≥ 20% and for HF ≥ 3% [ 12 , 15 ]. There are nearly no data published with the German DVO score in comparison with the FRAX score [ 16 , 17 ]. To better analyse the similarities and differences of the scores, we compared both scores with respect to their indication for anti-osteoporotic treatment. As already stated above, we were not able to determine which score predicted the 10 -year fracture risk more accurately with this approach. In accordance with the version of the DVO guidelines applied, patients were recommended further treatment when the estimated 10-year fracture risk is ≥ 30%. Comparing the 10-year fracture risks that FRAX calculated to those determined by the DVO guidelines, only the FRAX score for HF without BMD was similar. The FRAX score for MOF both with and without BMD indicated a lower risk than the DVO score. This may have a number of different reasons: Firstly, the estimated fracture outcomes are not the same. The DVO score estimates fracture risks based on prevalent hip and vertebral fractures, whereas FRAX only estimates the risk dependent on clinical fractures including those of the shoulder and forearm in the MOF category and not including spinal fractures. Furthermore, our study population represented females suffering from severe forms of osteoporosis, with a high number (52.6%) of prior fractures including those of the spine. Interestingly, below the age of 65 years, the fracture risk calculated by FRAX was higher in terms of percentage when including BMD compared to FRAX without BMD (data not shown). This relationship reversed for women above the age of 65 years, with higher percentages for FRAX without BMD. This perhaps reflects the changing influence of BMD in FRAX score calculation, possibly caused by the increasing importance of the different risk factors during aging. There was no further increase in FRAX scores after the age of 80 years perhaps owing to the inclusion of mortality risk in the FRAX score calculation. Taking the internationally common therapy thresholds of 10-year fracture risk ≥ 20% for MOF and ≥ 3% for HF into account, there was no significant difference between the therapy recommendations resulting from the DVO and FRAX HF ≥ 3% with BMD scores. However, the individual patients identified were not the same and there were patients only identified either by FRAX or by DVO as requiring treatment. If exactly those 52.8% of patients identified by the DVO score as in need of therapy were to be treated according to the FRAX scores, the therapy thresholds would need to be ≥ 2.6% with BMD and ≥ 3.4% without BMD for HF. The adapted therapy thresholds nearly match or even exceed the internationally recommended therapy threshold of ≥ 3% for HF. For the FRAX MOF scores, the adapted therapy thresholds for the 52.8% of patients identified by the DVO score as in need of therapy strongly differ (≥ 10% without BMD; ≥ 11% with BMD) from the internationally recommended therapy threshold of ≥ 20%. This implies that female patients in Germany are treated at an earlier time point and at lower fracture risk compared to other European countries implementing FRAX. As demonstrated in previous studies, the FRAX score appears to discriminate better for HF than for MOF [ 17 – 19 ]. There might be several reasons for the difference between the FRAX and DVO scores and the differing therapy recommendations for the patients in our study population. One explanation might be that the DVO implements the lowest T-score of all measurement sites, and specifically including the spine. DXA measurement of the total femur or femoral neck have the best predictive value for hip fractures, whereas the measurement of the lumbar spine has a better predictive value for vertebral fractures [ 20 ]. Several epidemiological studies failed to demonstrate the improvement of fracture risk stratification by using the lowest T-score of several measurement sites including the spine versus taking T-score of the hip alone [ 21 , 22 ]. An epidemiological study from Canada even revealed an overestimation of the fracture risk by taking the lumbar spine instead of femoral neck as an BMD parameter for FRAX. One might discuss whether the DVO score overestimates 10-year fracture risks by using the lowest T-score of all measurement sites. However, not all studies report the number of spinal fractures, because not all patients were admitted to a hospital or underwent an X-ray of the spine. To clarify this assumption, we analysed differences between patients identified by the different scores by comparing patient-specific risk factors. Women identified only by the DVO score as in need of therapy presented more than double the number of spinal fractures than the patients identified only by the FRAX score. This might lead to the assumption that the DVO score is more sensitive when detecting vertebral fractures in female patients by considering the lowest T-scores. Women identified as in need for treatment by the DVO score only also were positive for more secondary osteoporosis risk factors. In contrast, those only identified by the FRAX HF score as in need of treatment had more peripheral fractures at the age of fifty, were more likely to be smokers, took more glucocorticoids, and the T-score at the femoral neck was nearly one point lower compared to those only identified by the DVO score (-2.3 versus − 1.4, respectively). We applied a confusion matrix to analyse the respective sensitivities and specificities of the DVO and FRAX scores with respect to the predictive value using prevalent spinal fractures. There are no valid data on fracture incidence in these women because patients included in this study were treated based on their individual risk after being evaluated. Therefore, we cannot conclude which score predicts the actual fracture incidence more accurately. Whereas the DVO score was more sensitive (0.8 versus 0.67) for patients with prevalent spinal fractures, both scores demonstrated similar specificities (0.57 versus 0.58). In summary, our study demonstrates that the DVO score and FRAX score identified different individual female patients at risk of fracture. In this retrospective study population of females with a higher risk of suffering from osteoporosis compared to the general population, when implementing the most common therapy thresholds for FRAX scores, only the FRAX score for HF without BMD identified a similar percentage of patients compared to the DVO criteria. Female patients in Germany identified by the DVO score as in need of treatment corresponded to a FRAX with BMD hip-fracture risk threshold of ≥ 2.6%, slightly lower than the internationally common therapy threshold of ≥ 3%. However, using the FRAX score for MOF with and without BMD for our study population, the results demonstrate that the German therapy threshold corresponds to ≥ 11% (MOF with BMD) or ≥ 10% (MOF without BMD). Hence, therapy was clearly recommended at a lower risk compared to the internationally common therapy threshold. Conclusion The comparison of the international FRAX score and the German DVO score valid prior to 2023 in a preselected female study population with a higher risk of suffering from osteoporosis compared to the general population revealed clear differences in risk assessment and therapy thresholds. It would therefore be highly recommendable to consider both scores when assessing individual female patients at risk of fracture for treatment. Declarations Author Contribution All authors whose names appear on the submission-made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; or the creation of new software used in the work;-drafted the work or revised it critically for important intellectual content;-approved the version to be published; and-agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. References Shariati-Sarabi Z, Rezaie HE, Milani N et al (2018) Evaluation of Bone Mineral Density in Perimenopausal Period. archives bone joint Surg 6:57–62 Hernlund E, Svedbom A, Ivergard M et al (2013) Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 8:136. 10.1007/s11657-013-0136-1 Kanis JA, Harvey NC, McCloskey E et al (2020) Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures. Osteoporos Int 31:1–12. 10.1007/s00198-019-05176-3 Kanis JA, Melton LJ, Christiansen C et al (1994) The diagnosis of osteoporosis. J Bone Miner Res 9:1137–1141. 10.1002/jbmr.5650090802 Cruz AS, Lins HC, Medeiros RVA et al (2018) Artificial intelligence on the identification of risk groups for osteoporosis, a general review. Biomed Eng Online 17:12. 10.1186/s12938-018-0436-1 McCloskey EV, Harvey NC, Johansson H et al (2022) Fracture risk assessment by the FRAX model. Climacteric: J Int Menopause Soc 25:22–28. 10.1080/13697137.2021.1945027 Kanis JA, Johnell O, Oden A et al (2002) Ten-year risk of osteoporotic fracture and the effect of risk factors on screening strategies. Bone 30:251–258. 10.1016/s8756-3282(01)00653-6 Kanis JA, Oden A, Johnell O et al (2007) 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 18:1033–1046. 10.1007/s00198-007-0343-y Kanis JA, McCloskey EV, Johansson H et al (2010) Development and use of FRAX® in osteoporosis. Osteoporos Int 21:407–413. 10.1007/s00198-010-1253-y Faßbender WJ, Scheidt-Nave C, Pfeilschifter J (2003) Die neuen Leitlinien zur Osteoporose. Dtsch med Wochenschr 128:1615–1617. 10.1055/s-2003-40930 Neuerburg C, Schmidmaier R, Schilling S et al (2015) [Identification, diagnostics and guideline conform therapy of osteoporosis (DVO) in trauma patients: a treatment algorithm]. Der Unfallchirurg 118:913–924. 10.1007/s00113-015-0071-2 Kanis JA, Harvey NC, Cooper C et al (2016) A systematic review of intervention thresholds based on FRAX: A report prepared for the National Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos 11:25. 10.1007/s11657-016-0278-z Siggelkow H, Thomasius F (2024) [Osteoporosis - implications of the new guidelines in practice]. Dtsch Med Wochenschr 149:684–689. 10.1055/a-2127-2927 Schmidmaier R, Hadji P, Kern P et al (2023) Recommendations for the Pharmacological Treatment of Osteoporosis – Update 2023 of the German Osteoporosis Guideline. Osteologie 32:115–122. 10.1055/a-2034-6086 Kanis JA, Compston J, Cooper C et al (2016) SIGN Guidelines for Scotland: BMD Versus FRAX Versus QFracture. Calcif Tissue Int 98:417–425. 10.1007/s00223-015-0092-4 Hadji P, Klein S, Gothe H et al (2013) The epidemiology of osteoporosis–Bone Evaluation Study (BEST): an analysis of routine health insurance data. Dtsch Arztebl Int 110:52–57. 10.3238/arztebl.2013.0052 Witzel JC, Giessel A, Heppner C et al (2023) Discrepancies Between Osteoporotic Fracture Evaluations in Men Based on German (DVO) Osteoporosis Guidelines or the FRAX Score. Experimental and clinical endocrinology & diabetes: official journal. German Soc Endocrinol [and] German Diabetes Association 131:114–122. 10.1055/a-1977-4413 Bolland MJ, Siu AT, Mason BH et al (2011) Evaluation of the FRAX and Garvan fracture risk calculators in older women. J Bone Min Res 26:420–427. 10.1002/jbmr.215 Sandhu SK, Nguyen ND, Center JR et al (2010) Prognosis of fracture: evaluation of predictive accuracy of the FRAX algorithm and Garvan nomogram. Osteoporos Int 21:863–871. 10.1007/s00198-009-1026-7 El Maghraoui A, Roux C (2008) DXA scanning in clinical practice. QJM 101:605–617. 10.1093/qjmed/hcn022 Kanis JA, Johnell O, Oden A et al (2006) The use of multiple sites for the diagnosis of osteoporosis. Osteoporos Int 17:527–534. 10.1007/s00198-005-0014-9 Leslie WD, Lix LM, Tsang JF et al (2007) Single-site vs multisite bone density measurement for fracture prediction. Arch Intern Med 167:1641–1647. 10.1001/archinte.167.15.1641 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4949818","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":344610462,"identity":"579073a9-5d50-4025-a72f-097a70eebbad","order_by":0,"name":"Anna Frank","email":"","orcid":"","institution":"Agaplesion Evangelical Hospital Giessen","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Frank","suffix":""},{"id":344610464,"identity":"6dc8b514-1119-418e-892e-49cbd411ae05","order_by":1,"name":"Judith Charlotte Witzel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYDACZhBRAKISG5gZKkAizA0EtID0GIC1NDYznAGJMBLQwgDRAgQJjM2MbSAGAS0Gx/kPf/hgwMBucDy5/XHhvNpo/naglh8V23BrOczMYDgD6DCDMw8bm2duO5474zBjA2PPmds4tZgBtSTzgLTcAPqFd9ux3AagFmbGNvxaDv+Ba5lzLHc+EVoYmxngWhpqcjcQ0mJ/mNmYscdAglkS6JfZPMcO5G4EajmIzy+S/Qcff/hRYZPMdzz9wWeemrrceecPH3zwowK3FiiQSIYyDoPJA4TUg4AdlK4jRvEoGAWjYBSMMAAA0G1ZqdQHmK8AAAAASUVORK5CYII=","orcid":"","institution":"Agaplesion Evangelical Hospital Giessen","correspondingAuthor":true,"prefix":"","firstName":"Judith","middleName":"Charlotte","lastName":"Witzel","suffix":""},{"id":344610465,"identity":"3c3d6348-306f-4974-a554-7bad953ff386","order_by":2,"name":"Christina Heppner","email":"","orcid":"","institution":"MVZ endokrinologikum Göttingen","correspondingAuthor":false,"prefix":"","firstName":"Christina","middleName":"","lastName":"Heppner","suffix":""},{"id":344610467,"identity":"6983c538-06f7-40fe-942a-10860cb0d230","order_by":3,"name":"Annette Lamersdorf","email":"","orcid":"","institution":"MVZ endokrinologikum Göttingen","correspondingAuthor":false,"prefix":"","firstName":"Annette","middleName":"","lastName":"Lamersdorf","suffix":""},{"id":344610471,"identity":"78a50ac3-9d25-4a0f-a74c-68b39c8634e4","order_by":4,"name":"Andreas Leha","email":"","orcid":"","institution":"University Medical Center Göttingen","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Leha","suffix":""},{"id":344610472,"identity":"cbf9d33d-8e17-4c1f-805d-ccfc10aa177e","order_by":5,"name":"Heide Siggelkow","email":"","orcid":"","institution":"MVZ endokrinologikum Göttingen","correspondingAuthor":false,"prefix":"","firstName":"Heide","middleName":"","lastName":"Siggelkow","suffix":""}],"badges":[],"createdAt":"2024-08-21 08:17:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4949818/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4949818/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66764238,"identity":"2a2696f9-945b-4f86-8753-2209380377ba","added_by":"auto","created_at":"2024-10-16 09:12:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":13297,"visible":true,"origin":"","legend":"\u003cp\u003e10-year fracture probabilities (vertical axis) for hip or vertebral fractures according to the DVO score, split into primary (black) and secondary (grey) causes of osteoporosis\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4949818/v1/a9d901b9c76d803d6250e296.png"},{"id":66764239,"identity":"ede2ad01-e52b-4b0b-aade-1483c2c36f30","added_by":"auto","created_at":"2024-10-16 09:12:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18257,"visible":true,"origin":"","legend":"\u003cp\u003eTherapy recommendations “yes” (black) and “no” (grey) based on DVO guidelines, FRAX score (grouped by therapy thresholds for MOF and HF). The figure displays a difference in the total number of therapy recommendations based on the score.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4949818/v1/fa205aeb31f048506addc6c5.png"},{"id":66766457,"identity":"c02fb292-19a5-44da-a78f-a911e00207c9","added_by":"auto","created_at":"2024-10-16 09:28:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":573968,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4949818/v1/a80117be-ad49-48ba-8433-7909abe82ac0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"German DVO risk score identified more patients requiring treatment compared to FRAX score in a retrospective analysis of women evaluated for osteoporosis","fulltext":[{"header":"Background","content":"\u003cp\u003eOsteoporosis is one of the four most common health problems. Worldwide, 6% of men and 21% of women between 50 and 84 years of age suffer from osteoporosis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor the assessment and timely treatment of osteoporosis, the determination of individual fracture risks is becoming more relevant. Lately, the availability of anabolic therapeutic agents has increased the necessity to improve the prediction of fragility fractures and thus target therapeutic interventions in postmenopausal women more effectively [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A number of different tools have been developed to assess fracture risk, taking into account that factors other than areal bone mineral density (BMD) also influence fracture risk [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The FRAX score is one such tool that was established in 2008 and updated several times to adapt to new developments, especially to include the recency of fractures [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The FRAX score calculates an individual 10-year fracture risk by considering defined clinical risk factors and (optionally) the bone mineral density at the femoral neck. The percentage calculated is a country-specific risk of suffering a major osteoporotic fracture (MOF), including spinal, hip, shoulder, and wrist fracture, or a hip fracture (HF), using an algorithm. FRAX does not propose any therapy thresholds, above which scores patients are recommended treatment. However, the internationally most commonly implemented therapy thresholds for FRAX are \u0026ge; 20% for MOF and \u0026ge; 3% for HF [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe score commonly used in German-speaking countries is based on the German guidelines for diagnostics and treatment of osteoporosis developed by the \u003cem\u003eDachverband Osteologie (German Confederation of Osteologists, DVO\u003c/em\u003e). Founded on these guidelines, the DVO score is a multistep approach (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to classify patients in groups of 10-year fracture-risk probabilities of suffering a hip or clinical vertebral fracture. Starting with a set of forty risk factors, patients are assessed whether their 10-year fracture risk is \u0026lt;\u0026thinsp;20% or \u0026gt;\u0026thinsp;20%. Patients with a 10-year fracture probability\u0026thinsp;\u0026gt;\u0026thinsp;20% are advised to undergo further diagnostics including bone mineral density measurement via dual-energy absorptiometry (DXA). Depending on the resulting BMD in combination with the risk factors, patients are then stratified further into groups with either a risk between 20% and 30% or \u0026gt;\u0026thinsp;30%. All patients with a 10-year fracture risk of \u0026gt;\u0026thinsp;30% are recommended specific treatment for osteoporosis [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The first edition of these guidelines was published in 2003 and was revised in 2006, 2009, 2014, and 2017, in accordance with the relevant literature. In 2023, a new DVO score was published, representing a major change in risk assessment by calculating the 3-year fracture risk for 10-year fracture-risk probabilities of suffering a hip or clinical vertebral fracture and adapting different risk categories [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of DVO and FRAX score\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDVO score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFRAX score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMany (version 2017\u0026thinsp;=\u0026thinsp;40) risk factors listed in the DVO guidelines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 risk factors, DXA value optional\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifferent fracture types\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrior fractures\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDXA at lumbar spine OR total femur OR femoral neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDXA at femoral neck only, optional\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStep-by-step evaluation of the 10-year fracture probability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOne step to the 10-year fracture probability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConsistent therapy threshold\u0026thinsp;\u0026gt;\u0026thinsp;30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo therapy threshold set by tool\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent variable: 10-year fracture incidence of hip and vertebral fracture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent variable: 10-year fracture probability of major osteoporotic fracture or hip fracture\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublished 10-year fracture risk calculation method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10-year fracture risk calculation algorithm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdditional risk factors with direct therapy recommendation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eAims:\u003c/h2\u003e \u003cp\u003ePrior to the development of the new DVO score, it was in discussion as to whether German-speaking countries would also apply FRAX score in the clinical care of patients with osteoporosis. We were therefore interested to answer the question of how the respective FRAX score would have characterized women treated according to the DVO score prior to 2023. In this retrospective study, we compared risk scores and treatment recommendations in Germany on the basis of DVO score with the internationally employed FRAX fracture-risk assessment tool effective at the time of clinical presentation in a cohort of women evaluated for osteoporosis in an endocrinology centre in Germany. Furthermore, we assessed therapy thresholds for FRAX frequently employed internationally (\u0026ge; 20% for MOF and \u0026ge; 3% for HF) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and adapted these to our study group to compare them to the therapy recommendations based on DVO score. Owing to the fact that our patients were treated according to DVO score during the subsequent years, it is not possible to conclude which score is more accurate regarding fracture risk prediction.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cstrong\u003ePatients\u003c/strong\u003e \u003cp\u003eThis seven-year retrospective study bases on data recorded between July 2007 and June 2014 at MVZ endokrinologikum G\u0026ouml;ttingen, which is an endocrinological centre specialising in the diagnosis and treatment of patients with osteoporosis. Patients were mainly referred from other clinics or practices for evaluation of secondary osteoporosis, fracture risk, and treatment consideration.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eOut of 710 female patients (age 40\u0026ndash;91 years) identified, 555 met the study criteria including a complete set of data on DVO score, clinical risk factors for the FRAX score, and a DXA measurement of the femoral neck on at least one side. Of these 555 patients, 500 also underwent DXA measurement of the lumbar spine. All data were documented and validated by a physician.\u003c/p\u003e \u003cp\u003eAll patients provided informed consent to use of their individual data in an anonymized form for research purposes. The local ethics review board in G\u0026ouml;ttingen approved this approach with their decision dated 18 February 2007 (Ref. 18-2-07).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData\u003c/strong\u003e \u003cp\u003eAvailable data on general patient information (age, height and loss of height, body mass), medical history (medication, illnesses, lifestyle factors, risk factors for osteoporosis), family and fracture history (previously experienced, pathological and/or traumatic, fracture side), as well as laboratory parameters and DXA measurements were collected from the patients\u0026rsquo; electronic medical records (Medistar) retrospectively.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eDXA was used to measure BMD and T-score at the femoral neck, the total femur, and the lumbar spine (L1-L4). Whereas 57.4% of the DXA procedures were performed at MVZ endokrinologikum G\u0026ouml;ttingen using a GE Lunar Prodigy densitometer (GE Healthcare GmbH), the other 42.6% were performed in other radiological centres. We used the minimum T-score (and not BMD) at the femoral neck to calculate the respective FRAX score.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAnalysis\u003c/b\u003e: To calculate the FRAX 10-year fracture risks for a MOF and HF, respectively, we utilised the web-based data interface of the country-specific version of the risk calculator for Germany, which is available on the University of Sheffield website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.sheffield.a.uk/FRAX/tool.aspx?lang=de\u003c/span\u003e\u003cspan address=\"https://www.sheffield.a.uk/FRAX/tool.aspx?lang=de\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The required data include age, body mass, previous fracture, parental history of hip fracture, current smoking, long-term use of oral glucocorticoids, rheumatoid arthritis, daily alcohol consumption, other causes of secondary osteoporosis, and optionally the minimum T-score of the left and right femoral neck.\u003c/p\u003e \u003cp\u003eWe implemented therapy thresholds for FRAX scores of \u0026ge; 20% for a MOF and \u0026ge; 3% for a HF [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Subsequently, we compared the calculated FRAX scores with the recommendations based on the DVO guidelines. All patients\u0026rsquo; data were used to determine the 10-year fracture probability for hip or vertebral fractures, referring to the edition of the DVO guidelines available during the year of first presentation to the MVZ endokrinologikum for osteoporosis evaluation. The DVO guidelines suggest a step-by-step procedure to estimate 10-year fracture probabilities. By taking into account the presence of various risk factors and their different impact on fracture risk, the fracture risk is initially determined as lying below or above 20%. All patients with 10-year fracture risk\u0026thinsp;\u0026gt;\u0026thinsp;20% are recommended to undergo DXA measurement at all three sites. The DVO guidelines provide a therapy-indication table based on gender, age, a number of BMD-independent risk factors, and DXA T-score that can be used to determine whether the 10-year fracture risk exceeds 30%. All patients with a 10-year probability\u0026thinsp;\u0026gt;\u0026thinsp;30% are recommended specific anti-osteoporotic treatment.\u003c/p\u003e \u003cp\u003eStatistical analysis was performed with the software packages IBM SPSS Statistics Version 25 and Microsoft Excel 365, using descriptive statistics as well as Wilcoxon signed-ranked and McNemar tests. The McNemar test was specifically used to test the agreement of therapy recommendations. The significance level was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Furthermore, we used a confusion matrix to analyse and visualize the sensitivities and specificities of the DVO and FRAX scores based on therapy recommendations and the prevalence of spinal fractures. Owing to the fact that women were treated according to their fracture risk, we cannot evaluate the true incidence of new fractures. Therefore, we cannot conclude which score predicts the actual fracture incidence more accurately from our data.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn total, 555 female patients with a complete set of data were analysed. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarises the baseline characteristics of the included patients. The two scores approach risk factors differently. Smoking, glucocorticoid intake, rheumatoid arthritis, and alcohol consumption are treated as causes of secondary osteoporosis in DVO, whereas these risk factors have to be entered separately into the FRAX interface. Focussing on the secondary osteoporosis causes according to FRAX, the onset of menopause prior to the age of forty-five was the most common (95.23%). The most common secondary cause in DVO was vitamin-D deficiency in 28 of 116 patients (24.13%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline characteristics of patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMVZ endokrinologikum G\u0026ouml;ttingen\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge in years \u0026plusmn; SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.21 (\u0026plusmn; 10.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI in kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e\u0026plusmn; SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.94 (\u0026plusmn; 4.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior fracture\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.61%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParental hip fractures\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.87%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOral glucocorticoids (current intake\u0026thinsp;\u0026gt;\u0026thinsp;5mg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.76%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRheumatoid arthritis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.03%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol three or more units a day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.65%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemoral neck T-score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.86 (\u0026plusmn; 0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecondary osteoporosis (as described in FRAX)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecondary osteoporosis (as described in DVO)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll 555 patients had at least one documented T-score at the femoral neck. The average T-score at the femoral neck was \u0026minus;\u0026thinsp;1.86 \u003cb\u003e\u0026plusmn;\u003c/b\u003e 0.98 and thus higher than the average T-score at the lumbar spine of -2.21 \u003cb\u003e\u0026plusmn;\u003c/b\u003e 1.23. Taking into account the lowest T-score of all the three measurement sites, the mean value of -2.51 \u003cb\u003e\u0026plusmn;\u003c/b\u003e 0.99 was even lower than at the lumbar spine. When only patients with any prior fracture were analysed, the minimum T-score at the femoral neck was significantly lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Wilcoxon test) than in those without any fracture (femoral T-score \u0026minus;\u0026thinsp;1.99 \u0026plusmn; 0.93 versus \u0026minus;\u0026thinsp;1.72 \u0026plusmn; 1.01).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates fracture risk probabilities (vertical axis) according to the DVO score in our study population. The DVO score identified 52.8% (293 out of 555) as having a 10-year fracture risk of suffering a hip or vertebral fracture\u0026thinsp;\u0026gt;\u0026thinsp;30%. We identified a secondary cause of osteoporosis in 22.9% (67 out of 293) of these patients (12.1% of the total 555 patients).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe mean 10-year fracture probabilities according to FRAX were significantly higher when including BMD, both for MOF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and HF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). We additionally calculated the mean individual FRAX 10-year fracture probability within the subgroups of \u0026lt;\u0026thinsp;20%, 20\u0026ndash;30%, and \u0026gt;\u0026thinsp;30% fracture risk according to the DVO score. The mean FRAX score fracture probabilities with and without BMD proved to be lower than those determined for the DVO scores in all groups. Hence, the FRAX score identified fewer patients at risk. The mean FRAX score fracture probabilities for patients with a DVO score\u0026thinsp;\u0026gt;\u0026thinsp;30% without BMD proved to be 18.2 \u003cb\u003e\u0026plusmn;\u003c/b\u003e 11.4 for FRAX MOF and 8.9 \u003cb\u003e\u0026plusmn;\u003c/b\u003e 9.5 for FRAX HF. Including BMD they were 17.4 \u003cb\u003e\u0026plusmn;\u003c/b\u003e 10.8 for FRAX MOF and 8.1 \u003cb\u003e\u0026plusmn;\u003c/b\u003e 9.1 for FRAX HF.\u003c/p\u003e \u003cp\u003eConsidering the fact that the DVO score identified 52.8% of patients in need of therapy, we calculated FRAX score thresholds that would identify the same percentage of patients. We found the adapted therapy thresholds for MOF to be markedly lower (without BMD 11.0%, with BMD 10.0%) in value in our female study population than internationally employed thresholds of \u0026ge; 20%. Looking at the internationally common therapy threshold of \u0026ge; 3% for HF, our adapted therapy threshold without BMD was higher (3.4%), whereas the value with BMD (2.6%) was below the internationally implemented threshold.\u003c/p\u003e \u003cp\u003eWe again applied the commonly used therapy thresholds for FRAX to compare the therapy indications for both the DVO and FRAX scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and statistically determined whether the respective differences were significant or not. The most patients were identified by the FRAX score as requiring treatment adopting a threshold of 3% for HF without BMD followed by the DVO score, with the small difference being statistically insignificant (p\u0026thinsp;=\u0026thinsp;0.705). The fewest patients were recommended treatment by the FRAX score based on a therapy threshold of\u0026ge; 20% for MOF with or without BMD. All FRAX scores, except FRAX for HF without BMD showed a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) difference regarding their therapy recommendations in respect to the DVO score.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAiming to determine the overlap of patients identified by each score, the greatest percentage concordance of 39.3% for women with therapy recommended was found between FRAX HF \u0026ge; 3% without BMD and DVO. However, both scores identified different individual women in need of therapy. The FRAX score classified 16.8% of patients as requiring therapy not identified by DVO score. In comparison, 13.5% were identified by DVO but not by FRAX. Furthermore, FRAX HF \u0026ge; 3% with BMD identified 72.4% of the patients recommended treatment according to the DVO score. The FRAX score for MOF \u0026ge; 20% with BMD identified the fewest individual patients also identified by DVO score as requiring treatment.\u003c/p\u003e \u003cp\u003eTable 4 depicts the patient-specific differences in the two scores with the greatest overlap (38.2% of the total population) but also with women unidentified by each score. We compared the parameters of patients identified by both DVO and FRAX HF with BMD with those of each single score to describe the difference in the risk profile of each score.\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e \u003cem\u003eComparison of risk factors in patient groups identified as in need of therapy by DVO and FRAX HF with BMD, only by DVO score and only by FRAX HF with BMD.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factors of patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDVO and FRAX HF with BMD overlap (n\u0026thinsp;=\u0026thinsp;212)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDVO only\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFRAX HF with BMD only\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior fracture\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; \u003cb\u003eSpinal fracture\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; \u003cb\u003ePeripheral fractures at the age of 50 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParent hip fractures\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOral glucocorticoids (current intake\u0026thinsp;\u0026gt;\u0026thinsp;5 mg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRheumatoid arthritis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol three units or more\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecondary osteoporosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemoral neck T-score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.5 \u0026plusmn; 0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.4 \u0026plusmn; 0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.3 \u0026plusmn; 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal femur T-score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.4 \u0026plusmn; 0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.5 \u0026plusmn; 0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.0 \u0026plusmn; 0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLumbar spine T-score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.7 \u0026plusmn; 1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.4 \u0026plusmn; 1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.1 \u0026plusmn; 1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eWe conclude from our results that a number of risk factors have differing influence on the scores, resulting in different treatment recommendations to patients. Those only identified by the DVO score presented double the number of prior spinal fractures (38.3% vs. 18.6%) and a higher percentage of parental hip fractures (13.6% vs. 8.5%), whereas the prevalence of peripheral fractures was around 11 percentage points higher in those identified only by the FRAX score (40.7% vs. 29.6%).\u003c/p\u003e \u003cp\u003eLooking at risk factors other than fracture history, those patients only identified by FRAX HF with BMD were found to have a higher percentage prevalence of the risk factor \u0026ldquo;current smoking\u0026rdquo; (22% vs. 16.6%). In addition, the risk factor \u0026ldquo;rheumatoid arthritis\u0026rdquo; was 5.1% vs. 2.5% in DVO-score. On the other hand, patients identified by the DVO score presented secondary osteoporosis more often (28.4% vs. 15.3%).\u003c/p\u003e \u003cp\u003eTo analyse the respective sensitivities and specificities of the DVO and FRAX scores with respect to the predictive value of prevalent spinal fractures, we used a confusion matrix. In comparison, the DVO score proved to have a greater and significant sensitivity (0.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), precision (0.41, p\u0026thinsp;=\u0026thinsp;0.002), negative predictive value (0.86, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and accuracy (0.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than the FRAX score for HF with BMD (sensitivity (0.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), precision (0.37, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), negative predictive value (0.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), accuracy (0.60, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)). Specificity was nearly identical between FRAX (0.58, p\u0026thinsp;=\u0026thinsp;0.002) and DVO score 0.57 (p\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this single-centre retrospective study, we compared the respective fracture risks calculated by the DVO and FRAX scores with and without bone mineral density measurements in 555 female patients evaluated for osteoporosis in an endocrinological healthcare centre between 2007 and 2014. The study population was not a representative sample of the female population, presenting a higher risk of suffering from osteoporosis compared to the general population. The FRAX and DVO scores applied for these women differ in the number of risk factors assessed and their algorithms of 10-year fracture-risk calculation. The FRAX score uses an algorithm to calculate the 10-year fracture probability of a MOF or HF. The score may be used without DXA measurements, or with BMD or T-score values (using a female reference population applied to men and women alike). In contrast, the DVO score used during the investigated period presents a step-by-step, replicable 10-year fracture assessment of the risk of suffering a hip or vertebral fracture and is based on the T-score (also using a female reference population). The DVO therapy threshold is set at a fixed fracture-risk level and the guidelines recommend specific anti-osteoporotic therapy for patients when their 10-year fracture probability of suffering a hip or vertebral fracture\u0026thinsp;\u0026gt;\u0026thinsp;30%. The FRAX therapy thresholds employed vary across countries. A systematic review revealed that the most common therapy threshold for MOF is \u0026ge;\u0026thinsp;20% and for HF\u0026thinsp;\u0026ge;\u0026thinsp;3% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are nearly no data published with the German DVO score in comparison with the FRAX score [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. To better analyse the similarities and differences of the scores, we compared both scores with respect to their indication for anti-osteoporotic treatment. As already stated above, we were not able to determine which score predicted the 10 -year fracture risk more accurately with this approach.\u003c/p\u003e \u003cp\u003e In accordance with the version of the DVO guidelines applied, patients were recommended further treatment when the estimated 10-year fracture risk is \u0026ge;\u0026thinsp;30%. Comparing the 10-year fracture risks that FRAX calculated to those determined by the DVO guidelines, only the FRAX score for HF without BMD was similar. The FRAX score for MOF both with and without BMD indicated a lower risk than the DVO score. This may have a number of different reasons: Firstly, the estimated fracture outcomes are not the same. The DVO score estimates fracture risks based on prevalent hip and vertebral fractures, whereas FRAX only estimates the risk dependent on clinical fractures including those of the shoulder and forearm in the MOF category and not including spinal fractures. Furthermore, our study population represented females suffering from severe forms of osteoporosis, with a high number (52.6%) of prior fractures including those of the spine.\u003c/p\u003e \u003cp\u003eInterestingly, below the age of 65 years, the fracture risk calculated by FRAX was higher in terms of percentage when including BMD compared to FRAX without BMD (data not shown). This relationship reversed for women above the age of 65 years, with higher percentages for FRAX without BMD. This perhaps reflects the changing influence of BMD in FRAX score calculation, possibly caused by the increasing importance of the different risk factors during aging. There was no further increase in FRAX scores after the age of 80 years perhaps owing to the inclusion of mortality risk in the FRAX score calculation.\u003c/p\u003e \u003cp\u003eTaking the internationally common therapy thresholds of 10-year fracture risk\u0026thinsp;\u0026ge;\u0026thinsp;20% for MOF and \u0026ge;\u0026thinsp;3% for HF into account, there was no significant difference between the therapy recommendations resulting from the DVO and FRAX HF\u0026thinsp;\u0026ge;\u0026thinsp;3% with BMD scores. However, the individual patients identified were not the same and there were patients only identified either by FRAX or by DVO as requiring treatment.\u003c/p\u003e \u003cp\u003eIf exactly those 52.8% of patients identified by the DVO score as in need of therapy were to be treated according to the FRAX scores, the therapy thresholds would need to be \u0026ge;\u0026thinsp;2.6% with BMD and \u0026ge;\u0026thinsp;3.4% without BMD for HF. The adapted therapy thresholds nearly match or even exceed the internationally recommended therapy threshold of \u0026ge;\u0026thinsp;3% for HF. For the FRAX MOF scores, the adapted therapy thresholds for the 52.8% of patients identified by the DVO score as in need of therapy strongly differ (\u0026ge;\u0026thinsp;10% without BMD; \u0026ge; 11% with BMD) from the internationally recommended therapy threshold of \u0026ge;\u0026thinsp;20%. This implies that female patients in Germany are treated at an earlier time point and at lower fracture risk compared to other European countries implementing FRAX. As demonstrated in previous studies, the FRAX score appears to discriminate better for HF than for MOF [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere might be several reasons for the difference between the FRAX and DVO scores and the differing therapy recommendations for the patients in our study population. One explanation might be that the DVO implements the lowest T-score of all measurement sites, and specifically including the spine. DXA measurement of the total femur or femoral neck have the best predictive value for hip fractures, whereas the measurement of the lumbar spine has a better predictive value for vertebral fractures [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Several epidemiological studies failed to demonstrate the improvement of fracture risk stratification by using the lowest T-score of several measurement sites including the spine versus taking T-score of the hip alone [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. An epidemiological study from Canada even revealed an overestimation of the fracture risk by taking the lumbar spine instead of femoral neck as an BMD parameter for FRAX. One might discuss whether the DVO score overestimates 10-year fracture risks by using the lowest T-score of all measurement sites. However, not all studies report the number of spinal fractures, because not all patients were admitted to a hospital or underwent an X-ray of the spine.\u003c/p\u003e \u003cp\u003eTo clarify this assumption, we analysed differences between patients identified by the different scores by comparing patient-specific risk factors. Women identified only by the DVO score as in need of therapy presented more than double the number of spinal fractures than the patients identified only by the FRAX score. This might lead to the assumption that the DVO score is more sensitive when detecting vertebral fractures in female patients by considering the lowest T-scores. Women identified as in need for treatment by the DVO score only also were positive for more secondary osteoporosis risk factors. In contrast, those only identified by the FRAX HF score as in need of treatment had more peripheral fractures at the age of fifty, were more likely to be smokers, took more glucocorticoids, and the T-score at the femoral neck was nearly one point lower compared to those only identified by the DVO score (-2.3 versus \u0026minus;\u0026thinsp;1.4, respectively). We applied a confusion matrix to analyse the respective sensitivities and specificities of the DVO and FRAX scores with respect to the predictive value using prevalent spinal fractures. There are no valid data on fracture incidence in these women because patients included in this study were treated based on their individual risk after being evaluated. Therefore, we cannot conclude which score predicts the actual fracture incidence more accurately.\u003c/p\u003e \u003cp\u003eWhereas the DVO score was more sensitive (0.8 versus 0.67) for patients with prevalent spinal fractures, both scores demonstrated similar specificities (0.57 versus 0.58).\u003c/p\u003e \u003cp\u003eIn summary, our study demonstrates that the DVO score and FRAX score identified different individual female patients at risk of fracture. In this retrospective study population of females with a higher risk of suffering from osteoporosis compared to the general population, when implementing the most common therapy thresholds for FRAX scores, only the FRAX score for HF without BMD identified a similar percentage of patients compared to the DVO criteria. Female patients in Germany identified by the DVO score as in need of treatment corresponded to a FRAX with BMD hip-fracture risk threshold of \u0026ge;\u0026thinsp;2.6%, slightly lower than the internationally common therapy threshold of \u0026ge;\u0026thinsp;3%. However, using the FRAX score for MOF with and without BMD for our study population, the results demonstrate that the German therapy threshold corresponds to \u0026ge;\u0026thinsp;11% (MOF with BMD) or \u0026ge;\u0026thinsp;10% (MOF without BMD). Hence, therapy was clearly recommended at a lower risk compared to the internationally common therapy threshold.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe comparison of the international FRAX score and the German DVO score valid prior to 2023 in a preselected female study population with a higher risk of suffering from osteoporosis compared to the general population revealed clear differences in risk assessment and therapy thresholds. It would therefore be highly recommendable to consider both scores when assessing individual female patients at risk of fracture for treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors whose names appear on the submission-made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; or the creation of new software used in the work;-drafted the work or revised it critically for important intellectual content;-approved the version to be published; and-agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eShariati-Sarabi Z, Rezaie HE, Milani N et al (2018) Evaluation of Bone Mineral Density in Perimenopausal Period. archives bone joint Surg 6:57\u0026ndash;62\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHernlund E, Svedbom A, Ivergard M et al (2013) Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 8:136. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11657-013-0136-1\u003c/span\u003e\u003cspan address=\"10.1007/s11657-013-0136-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, Harvey NC, McCloskey E et al (2020) Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures. Osteoporos Int 31:1\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00198-019-05176-3\u003c/span\u003e\u003cspan address=\"10.1007/s00198-019-05176-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, Melton LJ, Christiansen C et al (1994) The diagnosis of osteoporosis. J Bone Miner Res 9:1137\u0026ndash;1141. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jbmr.5650090802\u003c/span\u003e\u003cspan address=\"10.1002/jbmr.5650090802\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCruz AS, Lins HC, Medeiros RVA et al (2018) Artificial intelligence on the identification of risk groups for osteoporosis, a general review. Biomed Eng Online 17:12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12938-018-0436-1\u003c/span\u003e\u003cspan address=\"10.1186/s12938-018-0436-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCloskey EV, Harvey NC, Johansson H et al (2022) Fracture risk assessment by the FRAX model. Climacteric: J Int Menopause Soc 25:22\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13697137.2021.1945027\u003c/span\u003e\u003cspan address=\"10.1080/13697137.2021.1945027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, Johnell O, Oden A et al (2002) Ten-year risk of osteoporotic fracture and the effect of risk factors on screening strategies. Bone 30:251\u0026ndash;258. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s8756-3282(01)00653-6\u003c/span\u003e\u003cspan address=\"10.1016/s8756-3282(01)00653-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, Oden A, Johnell O et al (2007) 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 18:1033\u0026ndash;1046. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00198-007-0343-y\u003c/span\u003e\u003cspan address=\"10.1007/s00198-007-0343-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, McCloskey EV, Johansson H et al (2010) Development and use of FRAX\u0026reg; in osteoporosis. Osteoporos Int 21:407\u0026ndash;413. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00198-010-1253-y\u003c/span\u003e\u003cspan address=\"10.1007/s00198-010-1253-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFa\u0026szlig;bender WJ, Scheidt-Nave C, Pfeilschifter J (2003) Die neuen Leitlinien zur Osteoporose. Dtsch med Wochenschr 128:1615\u0026ndash;1617. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/s-2003-40930\u003c/span\u003e\u003cspan address=\"10.1055/s-2003-40930\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeuerburg C, Schmidmaier R, Schilling S et al (2015) [Identification, diagnostics and guideline conform therapy of osteoporosis (DVO) in trauma patients: a treatment algorithm]. Der Unfallchirurg 118:913\u0026ndash;924. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00113-015-0071-2\u003c/span\u003e\u003cspan address=\"10.1007/s00113-015-0071-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, Harvey NC, Cooper C et al (2016) A systematic review of intervention thresholds based on FRAX: A report prepared for the National Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos 11:25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11657-016-0278-z\u003c/span\u003e\u003cspan address=\"10.1007/s11657-016-0278-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiggelkow H, Thomasius F (2024) [Osteoporosis - implications of the new guidelines in practice]. Dtsch Med Wochenschr 149:684\u0026ndash;689. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/a-2127-2927\u003c/span\u003e\u003cspan address=\"10.1055/a-2127-2927\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidmaier R, Hadji P, Kern P et al (2023) Recommendations for the Pharmacological Treatment of Osteoporosis \u0026ndash; Update 2023 of the German Osteoporosis Guideline. Osteologie 32:115\u0026ndash;122. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/a-2034-6086\u003c/span\u003e\u003cspan address=\"10.1055/a-2034-6086\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, Compston J, Cooper C et al (2016) SIGN Guidelines for Scotland: BMD Versus FRAX Versus QFracture. Calcif Tissue Int 98:417\u0026ndash;425. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00223-015-0092-4\u003c/span\u003e\u003cspan address=\"10.1007/s00223-015-0092-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHadji P, Klein S, Gothe H et al (2013) The epidemiology of osteoporosis\u0026ndash;Bone Evaluation Study (BEST): an analysis of routine health insurance data. Dtsch Arztebl Int 110:52\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3238/arztebl.2013.0052\u003c/span\u003e\u003cspan address=\"10.3238/arztebl.2013.0052\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWitzel JC, Giessel A, Heppner C et al (2023) Discrepancies Between Osteoporotic Fracture Evaluations in Men Based on German (DVO) Osteoporosis Guidelines or the FRAX Score. Experimental and clinical endocrinology \u0026amp; diabetes: official journal. German Soc Endocrinol [and] German Diabetes Association 131:114\u0026ndash;122. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/a-1977-4413\u003c/span\u003e\u003cspan address=\"10.1055/a-1977-4413\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolland MJ, Siu AT, Mason BH et al (2011) Evaluation of the FRAX and Garvan fracture risk calculators in older women. J Bone Min Res 26:420\u0026ndash;427. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jbmr.215\u003c/span\u003e\u003cspan address=\"10.1002/jbmr.215\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSandhu SK, Nguyen ND, Center JR et al (2010) Prognosis of fracture: evaluation of predictive accuracy of the FRAX algorithm and Garvan nomogram. Osteoporos Int 21:863\u0026ndash;871. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00198-009-1026-7\u003c/span\u003e\u003cspan address=\"10.1007/s00198-009-1026-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Maghraoui A, Roux C (2008) DXA scanning in clinical practice. QJM 101:605\u0026ndash;617. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/qjmed/hcn022\u003c/span\u003e\u003cspan address=\"10.1093/qjmed/hcn022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA, Johnell O, Oden A et al (2006) The use of multiple sites for the diagnosis of osteoporosis. Osteoporos Int 17:527\u0026ndash;534. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00198-005-0014-9\u003c/span\u003e\u003cspan address=\"10.1007/s00198-005-0014-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeslie WD, Lix LM, Tsang JF et al (2007) Single-site vs multisite bone density measurement for fracture prediction. Arch Intern Med 167:1641\u0026ndash;1647. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archinte.167.15.1641\u003c/span\u003e\u003cspan address=\"10.1001/archinte.167.15.1641\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"bone mineral density, osteoporosis risk factors, therapy threshold, 10-year fracture risk, fracture risk assessment, DVO-score","lastPublishedDoi":"10.21203/rs.3.rs-4949818/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4949818/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn a retrospective study of 555 female\u003cstrong\u003e \u003c/strong\u003epatients, we compared osteoporosis-specific fracture risk probabilities and treatment recommendations according to the German DVO guidelines with those resulting from the internationally implemented FRAX score. We present the differences between both scores, which also identified different individual patients as in need of therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFracture risk determination is essential when recommending treatment in osteoporosis management. This study compares and contrasts the risk probabilities of major osteoporotic and hip fractures calculated by the DVO score established in German-speaking countries with those of the FRAX tool.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe retrospectively analysed data from 555 female patients (mean age 64.2 ± 10.3 years) evaluated for osteoporosis. For the DVO score, we set the therapy threshold of \u0026gt; 30% for vertebral and hip fractures as suggested by DVO guidelines before 2023. Major osteoporotic fracture (MOF) and hip fracture risk (HF) were calculated based on corresponding FRAX scores. We applied the internationally most common therapy threshold of ≥ 20% for MOF and ≥ 3% for HF and subsequently determined the “DVO-equivalent risk levels” for FRAX-based assessment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on DVO score, 52.8% of women had a 10-year risk of hip and vertebral fractures \u0026gt; 30%. Most patients were identified by HF ≥ 3% without BMD (56%). The 14.6% of patients identified for treatment only by DVO score presented a higher percentage of spinal fractures (38.3% vs. 18.6%), whereas the 10.6% of patients only identified by FRAX including BMD presented a higher percentage of peripheral fractures (40.7% vs. 29.6%). The thresholds for this “DVO-equivalent risk level” for ‘FRAX with BMD’ would be ≥ 10% for MOF and ≥ 2.6% for HF.\u003c/p\u003e\n\u003cp\u003eGiven the differences in the DVO and FRAX scores, it would be highly recommendable to consider both scores when assessing individual women for treatment.\u003c/p\u003e","manuscriptTitle":"German DVO risk score identified more patients requiring treatment compared to FRAX score in a retrospective analysis of women evaluated for osteoporosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-16 09:12:03","doi":"10.21203/rs.3.rs-4949818/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ddb3765d-b38a-40b5-bb52-5a0ce957c66f","owner":[],"postedDate":"October 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-16T09:12:06+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-16 09:12:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4949818","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4949818","identity":"rs-4949818","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}