In the longitudinal, retrospective study, the ability of the FRAX, Garvan, and POL-RISK algorithms to predict osteoporotic fractures was compared in a group of 457 women. Using the rigid threshold of 10% showed a significant discrepancy in sensitivity and specificity of all tools. New thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds allow for improving the diagnostic accuracy of all three calculators.
BACKGROUND: The aim of the longitudinal, retrospective study was to compare three tools designed to assess fracture risk: FRAX, Garvan, and POL-RISK in their prediction of fracture incidence.
METHODS: The study group consisted of 457 postmenopausal women with a mean age of 64.21 ± 5.94 years from the Gliwice Osteoporosis (GO) Study. Comprehensive data on clinical factors related to fractures were collected for all participants. Bone densitometry was performed at the proximal femur using the Prodigy device (GE, USA). Fracture risk was established using the FRAX, Garvan, and POL-RISK algorithms. Data on the incidence of osteoporotic fractures were collected over the last 10 years.
RESULTS: During the period of observation 72, osteoporotic fractures occurred in 63 subjects. For a preliminary comparison of the predictive value of analyzed diagnostic tools, the fracture risk threshold of 10% was used. For FRAX, the fracture probability exceeding 10% was observed only in 11 subjects who experienced fractures; thus, the fracture was properly predicted only in 22.9% of women. For Garvan, the respective value was 90.5%, and for POL-RISK, it was 98.4%. That gave a very low true positive value for FRAX and a very high false positive value for Garvan and POL-RISK. Based on ROC curves, new thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds improve the diagnostic accuracy of all compared fracture prediction tools.
CONCLUSIONS: The current study showed that different fracture risk assessment tools, although having similar clinical purposes, require different cut-off thresholds for making therapeutic decisions. Better identification of patients requiring therapy based on such an approach may help reduce the number of new fractures.

Human body height loss of 3-4 cm or more may be considered a simple indicator of increasing fracture risk, where the information is very similar to the results from fracture risk assessments by available online calculators, all of them based on a multiple variable approaches.
BACKGROUND: The aim of the study was to assess the relationship between body height loss (HL) and fracture risk in postmenopausal women from the Gliwice Osteoporosis (GO) Study.
METHODS: The study sample included 1735 postmenopausal women, aged over 55 years and recruited at the Osteoporotic Outpatient Clinic. The mean age of the study participants was 68.15 ± 8.16 years. Fracture risk was established, using the fracture risk assessment tool (FRAX) (10-year probability of major and hip fractures), the Garvan calculator (any and hip fractures, 5 and 10 years) and the Polish (POL-RISK) algorithm, available at www. fracture - risk .pl (any fractures, 5 years). Bone densitometry at the femoral neck was performed, using a Prodigy device (Lunar, GE, USA). Body heights were measured before bone densitometry, using a wall stadiometer and compared with the maximum body heights, measured in early adulthood and reported by the study participants themselves.
RESULTS: In 199 women, the body heights, measured during the study, did not change in comparison to their corresponding values in early adulthood, while being decreased in the other 1536 women. The mean height loss (HL) in the whole study group was 3.95 ± 3.24 cm. That HL correlated significantly with the calculated fracture risk (the r range from 0.13 to 0.39, p < 0.0001). In general, regarding the patients with fracture risk close to the recommended therapeutic thresholds, HL was around 3-4 cm, except of the values from the FRAX calculator for major fractures, where the commonly used therapeutic threshold (20%) was related to HL of approximately 6.5 cm. In subjects with HL between 3.5 and 4 cm (n = 208), the FRAX value for major fractures was 6.83 ± 3.74.
CONCLUSIONS: Body height measurements, carried out to establish HL, provide an important information for clinical practice, where HL of 3-4 cm or more may be considered a simple indicator of increasing fracture risk.

The study project was designed to assess the concordance of clinical results in the assessment of 5-year fracture risk of any fracture, carried out by two methods: the Garvan algorithm and the POL-RISK model. The study group included 389 postmenopausal women of Caucasian race. The concordance of results, obtained by those two models, turned out to be moderate, and the threshold for high fracture risk group was 11% in the POL-RISK model.
The goal of the study was to evaluate the concordance of results in fracture risk assessments between the Garvan Fracture Risk Calculator and POL-RISK, a new Polish algorithm, and to define an optimal threshold for intervention.
The study was a part of the Silesia Osteo Active Study. A group of 389 postmenopausal women, aged 65.2±6.9 years (mean ± SD), was randomly selected from the general population of Zabrze, Poland. All the participants had bone densitometry examination to assess the bone mineral density of the femoral neck. The mean femoral neck T-score was (-0.99) ± 1.05 SD. 6.4% of the women revealed osteoporosis. Five-year risk of any fracture was assessed, using the Garvan and POL-RISK calculators. The performance of each model was evaluated by the area under the receiver operating characteristic curve (AUC).
The median 5-year risk of any fracture was 7% (range 1-54%) in the Garvan model and 8.8% (range 1.1-45.5%) in the POL-RISK algorithm. There was a significant correlation between the results obtained by both methods (r=0.6, p<0.005). For the thresholds, assumed at 8% and 13% (according to recommendation derived from Garvan tool), the rates of concordance of results between both calculators were 76% and 84%, respectively. In ROC analysis for the POL-RISK method, performed with reference to the Garvan method at two different cut-offs, assumed to be high fracture risk indicators (8% and 13%), the AUC values were 0.865 and 0.884, respectively. The optimal threshold for high fracture risk in the POL-RISK algorithm was ≥ 11%, which yielded a sensitivity of 0.94 and a specificity of 0.71.
The obtained data demonstrate a moderate concordance of results between the POL-RISK algorithm and the Garvan model, illustrated by low and high fracture risk cut-offs, established in ROC analysis. In addition, the threshold of 11% in the POL-RISK method was the optimal level for \"high risk\".