Risk factors predicting the 'time to first fracture' and its association with imminent fractures: a substudy of the FRISBEE cohort.

Only previous glucocorticoid use and rheumatoid arthritis were predictors of an early fracture (< 2 years after inclusion). A shorter 'time to first fracture' was not an independent clinical risk factor for imminent fractures. PURPOSE: Risk factors for fragility fractures independent of BMD were assessed in several prediction models. However, predictors of a shorter 'time to first fracture' and its impact on imminent fractures are unknown. METHODS: We studied the concept of 'time to first fracture' in the FRISBEE ("Fracture RIsk Brussels Epidemiological Enquiry") cohort (3560 postmenopausal women). Validated fractures were divided into 3 groups: first fracture < 2 years, 2-5 years, and > 5 years after inclusion. Factors associated with first fracture risk were evaluated with uni- and multivariate analyses using Cox modeling. We examined 'time to first fracture' as a risk factor for imminent fractures in untreated subjects and in those receiving pharmacological treatment. RESULTS: Classical risk factors (age, prior fracture, fall history and low BMD) were associated with first fracture in all groups. Previous glucocorticoids and rheumatoid arthritis (RA) were predictors for fracture < 2 years. Imminent fractures were similar in subjects with or without osteoporosis treatment, despite a higher estimated 10-year risk of fragility fracture in those treated, suggesting that treatment is efficient. 'Time to first fracture' was not an independent risk factor for imminent fractures. CONCLUSION: Among the risk factors considered, previous glucocorticoid use and RA were predictors for early fracture, consistent with the concept of very high risk. The 'time to first validated fracture' was not an independent risk factor for imminent fractures. Patients with a first osteoporotic fracture should thus be considered at very high risk for re-fracture, independent of the 'time to first fracture'.

Congenital hyperinsulinism-A case of mild hypoglycemia in an adult, detected by family testing.

Symptoms of mild hypoglycemia are easily overlooked especially when there are no complaints from the patients, but it could be a warning sign of an underlying genetic disease. Genetic testing for the entire family is a key step in neonatal hypoglycemia workup.

External validation of FRISBEE 5-year fracture prediction models: a registry-based cohort study.

Five-year fracture risk prediction from the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) models was externally tested in 9716 Canadian women and demonstrated good discrimination but consistently overestimated risk. INTRODUCTION: Five-year risk prediction models for all fractures, major osteoporotic fractures (MOFs) and central fractures (proximal to forearm and ankle) from the FRISBEE cohort demonstrated good performance in the original derivation cohort. Our aim was to externally validate the FRISBEE-based 5-year prediction models in routine practice. METHODS: Using the population-based Manitoba Bone Mineral Density (BMD) registry, we identified women aged 60-85 years undergoing baseline BMD assessment from September 1, 2012 to March 31, 2018. Five-year probabilities of all fractures, MOFs and central fractures were calculated using the FRISBEE prediction models. We identified incident non-traumatic fractures up to 5 years from population-based healthcare data sources. Performance characteristics included area under the receiver operating characteristic curve (AUROC), gradient of risk (hazard ratio [HR] per SD increase and across risk tertiles) from Cox regression analysis, and calibration (ratio 5-year observed cumulative incidence to predicted fracture probability). RESULTS: We included 9716 women (mean age 70.7 + / - SD 5.3 years). During a mean observation time of 2.5 years, all fractures, MOFs and central fractures were identified in 377 (3.9%), 264 (2.7%) and 259 (2.7%) of the women. AUROC showed significant fracture risk stratification with the FRISBEE models (all fractures 0.69 [95%CI 0.67-0.72], MOFs 0.71 [95%CI 0.68-0.74], central fractures 0.72 [95%CI 0.69-0.75]). There was a strong gradient of risk for predicting fracture outcomes per SD increase (HRs from 1.98 to 2.26) and across risk tertiles (HRs for middle vs lowest from 2.25 to 2.41, HRs for highest vs lowest from 4.70 to 6.50). However, risk was overestimated for all fractures (calibration-in-the-large 0.63, calibration slope 0.63), MOF (calibration-in-the-large 0.51, calibration slope 0.57) and central fractures (calibration-in-the-large 0.55, calibration slope 0.60). CONCLUSIONS: FRISBEE 5-year prediction models were externally validated to stratify fracture risk similar to the derivation cohort, but would need recalibration for Canada as risk was overestimated.

Severe osteoporosis as atypical presentation of hereditary hemochromatosis.

Besides important metabolic repercussions, iron overload is reported to be associated with deleterious effects on articulations and bones. We present the case of a male patient diagnosed with severe osteoporosis and vertebral fracture, in whom the evaluation for secondary osteoporosis revealed hereditary hemochromatosis.

Antenatal insulin therapy in gestational diabetes mellitus: validation of the new Brugmann scores.

BACKGROUND: Following the adoption of the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria for gestational diabetes mellitus (GDM) diagnosis by the World Health Organization (WHO) in 2014, many investigators have tried to identify independent risk factors for antenatal insulin therapy (AIT). The purpose of the current study is to build and validate a score that stratifies patients according to their need for AIT. METHODS: All pregnant women diagnosed with GDM according to the IADPSG definition were included. Group 1 comprised patients of 2018, and group 2 comprised patients of 2019. Each group was divided into two subgroups: subgroup A comprised patients diagnosed according to the 75-g oral glucose tolerance test (OGTT), and subgroup B comprised patients diagnosed according to fasting plasma glucose (FPG). RESULTS: A total of 1298 patients were included; 19.3% of those diagnosed by OGTT and 40.9% by FPG required AIT. The risk for AIT was stratified as low, moderate, and high. Brugmann FPG score comprised six risk factors and Brugmann OGTT score 12. Higher scores were associated with higher risk for AIT. The use of these scores in the two subgroups of group 2 showed no statistical differences compared to group 1. CONCLUSIONS: Both Brugmann FPG and OGTT scores may be useful to stratify patients with GDM according to their need for AIT. Future studies should be conducted to prospectively validate these scores, and to examine whether or not using oral anti-hyperglycemic agents in a high-risk group may decrease the need for AIT.

Fragility Fractures in Postmenopausal Women: Development of 5-Year Prediction Models Using the FRISBEE Study.

CONTEXT: Individualized fracture risk may help to select patients requiring a pharmacological treatment for osteoporosis. FRAX and the Garvan fracture risk calculators are the most used tools, although their external validation has shown significant differences in their risk prediction ability. OBJECTIVE AND METHODS: Using data from the Fracture Risk Brussels Epidemiological Enquiry study, a cohort of 3560 postmenopausal women aged 60 to 85 years, we aimed to construct original 5-year fracture risk prediction models using validated clinical risk factors (CRFs). Three models of competing risk analysis were developed to predict major osteoporotic fractures (MOFs), all fractures, and central fractures (femoral neck, shoulder, clinical spine, pelvis, ribs, scapula, clavicle, sternum). RESULTS: Age, a history of fracture, and hip or spine BMD were predictors common to the 3 models. Excessive alcohol intake and the presence of comorbidities were specific additional CRFs for MOFs, a history of fall for all fractures, and rheumatoid arthritis for central fractures. Our models predicted the fracture probability at 5 years with an acceptable accuracy (Brier scores ≤ 0.1) and had a good discrimination power (area under the receiver operating curve of 0.73 for MOFs and 0.72 for central fractures) when internally validated by bootstrap. Three simple nomograms, integrating significant CRFs and the mortality risk, were constructed for different fracture sites. In conclusion, we derived 3 models predicting fractures with an acceptable accuracy, particularly for MOFs and central fractures. The models are based on a limited number of CRFs, and we constructed nomograms for use in clinical practice.

Prediction of an Imminent Fracture After an Index Fracture - Models Derived From the Frisbee Cohort.

Patients who sustain a fracture are at greatest risk of recurrent fracture during the next 2 years. We propose three models to identify subjects most at risk of an imminent fracture, according to fracture site (any fracture, major osteoporotic fracture [MOF] or central). They were constructed using data of the prospective Frisbee cohort, which includes 3560 postmenopausal women aged 60 to 85 years who were followed for at least 5 years. A total of 881 subjects had a first incident validated fragility fracture before December 2018. Among these, we validated 130 imminent fractures occurring within the next 2 years; 79 were MOFs, and 88 were central fractures. Clinical risk factors were re-evaluated at the time of the index fracture. Fine and Gray proportional hazard models were derived separately for each group of fractures. The following risk factors were significantly associated with the risk of any imminent fracture: total hip bone mineral density (BMD) (p < 0.001), a fall history (p < 0.001), and comorbidities (p = 0.03). Age (p = 0.05 and p = 0.03, respectively) and a central fracture as the index fracture (p = 0.04 and p = 0.005, respectively) were additional predictors of MOFs and central fractures. The three prediction models are presented as nomograms. The calibration curves and the Brier scores based on bootstrap resampling showed calibration scores of 0.089 for MOF, 0.094 for central fractures, and 0.132 for any fractures. The predictive accuracy of the models expressed as area under the receiver operating characteristic (AUROC) curve (AUC) were 0.74 for central fractures, 0.72 for MOFs, and 0.66 for all fractures, respectively. These AUCs compare well with those of FRAX and Garvan to predict the 5- or 10-year fracture probability. In summary, five predictors (BMD, age, comorbidities, falls, and central fracture as the incident fracture) allow the calculation with a reasonable accuracy of the imminent risk of fracture at different sites (MOF, central fracture, and any fracture) after a recent sentinel fracture. © 2021 American Society for Bone and Mineral Research (ASBMR).

Independent External Validation of FRAX and Garvan Fracture Risk Calculators: A Sub-Study of the FRISBEE Cohort.

Probabilistic models including clinical risk factors with or without bone mineral density (BMD) have been developed to estimate the 5- or 10-year absolute fracture risk. We investigated the performance of the FRAX and Garvan tools in a well-characterized population-based cohort of 3560 postmenopausal, volunteer women, aged 60 to 85 years at baseline, included in the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) cohort, during 5 years of follow-up. Baseline data were used to calculate the estimated 10-year risk of hip and major osteoporotic fractures (MOFs) for each participant using FRAX (Belgium). We computed the 5-year risk according to the Garvan model with BMD. For calibration, the predicted risk of fracture was compared with fracture incidence across a large range of estimated fracture risks. The accuracy of the calculators to predict fractures was assessed using the area under the receiver operating characteristic curves (AUC). The FRAX tool was well calibrated for hip fractures (slope 1.09, p < 0.001; intercept -0.001, p = 0.46), but it consistently underestimated the incidence of major osteoporotic fractures (MOFs) (slope 2.12, p < 0.001; intercept -0.02, p = 0.06). The Garvan tool was well calibrated for "any Garvan" fractures (slope 1.05, p < 0.001; intercept 0.01, p = 0.37) but largely overestimated the observed hip fracture rate (slope 0.32, p < 0.001; intercept 0.006, p = 0.05). The predictive value for hip fractures was better for FRAX (AUC: 0.841, 95% confidence interval [CI] 0.795-0.887) than for Garvan (AUC: 0.769, 95% CI 0.702-0.836, p = 0.01). The Garvan AUC for "any Garvan" fractures was 0.721 (95% CI 0.693-0.749) and FRAX AUC for MOFs was 0.708 (95% CI 0.675-0.741). In conclusion, in our Belgian cohort, FRAX estimated quite well hip fractures but underestimated MOFs, while Garvan overestimated hip fracture risk but showed a good estimation of "any Garvan" fractures. Both models had a good discriminatory value for hip fractures but only a moderate discriminatory ability for MOFs or "any Garvan" fractures. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

A rare cause of persistent hyperparathyroidism.

In a case of patient with persistent hypercalcemia after parathyroidectomy, different imaging techniques and particularly 18F-fluorocholine PET/CT are important to localize the adenoma even in a very unusual location.

Multiple Endocrine Neoplasia or Accidental Association?

Pheochromocytoma, papillary thyroid carcinoma and hyperparathyroidism have rarely been reported together. Whether this association is coincidental or results from an unknown genetic predisposition is difficult to ascertain. We present the case of a patient who was diagnosed with pheochromocytoma, bilateral papillary thyroid carcinoma and parathyroid hyperplasia with primary hyperparathyroidism. A genetic mutation was hypothesized as the connection between these lesions. Previously described mutations were explored. LEARNING POINTS: Parathyroid hyperplasia, primary hyperparathyroidism and papillary thyroid carcinoma individually are common conditions, but association with each other, although possibly incidental, should trigger genetic testing.Further research is needed to reliably explain the relationship between primary hyperparathyroidism and non-medullary thyroid cancer.

Can we safely reduce the administration of 131-iodine in patients with differentiated thyroid cancer? - experience of the Brugmann hospital in Brussels.

BACKGROUND: 131-iodine (131I) administration after surgery remains a standard practice in differentiated thyroid cancer (DTC). In 2014, the American Thyroid Association presented new guidelines for the staging and management of DTC, including no systematic 131I in patients at low-risk of recurrence and a reduced 131I activity in intermediate risk.The present study aims at evaluating the rate of response to treatment following this new therapeutic management compared to our previous treatment strategy in patients with DTC of different risks of recurrence. METHODS: Patients treated and followed up for DTC according to the 2014-ATA guidelines (Group 2) were compared to those treated between 2007 and 2014 (Group 1) in terms of general characteristics, risk of recurrence (based on the 2015-ATA recommendations), preparation to 131I administration, cumulative administered 131I activity and response to treatment. RESULTS: In total, 136 patients were included: 78 in Group 1 and 58 in Group 2. The two groups were not statistically different in terms of clinical characteristics nor risk stratification: 42.3% in Group 1 and 31% in Group 2 were classified as low risk, 38.5 and 48.3% as intermediate risk and 19.2 and 20.7% as high risk (P = 0.38). Two patients (one in each group) with distant metastases were excluded from the analysis.Preparation to 131I administration consisted in rhTSH stimulation in 23.4% of the patients in Group 1 and 100% in Group 2 (p < 0.001).131I was administered to 46/77 patients (59.7%) in Group 1 (5 at low risk of recurrence) and 38/57 patients (66.7%) in Group 2 (0 with a low risk). Among the patients treated by 131I, median cumulative activity was significantly higher in Group 1 (3.70GBq [100 mCi] range 1.11-11.1 GBq [30-300 mCi]) than in Group 2 (1.11 GBq [30 mCi], range 1.11-7.4 GBq [30-200 mCi], P < 0.001). Complete response was found in 90.9% in Group 1 vs. 96.5% in Group 2 (P = 0.20). CONCLUSIONS: Using the 2015-ATA evidence-based guidelines for the management of DTC, meaning no 131I administration in low-risk patients, a low activity in intermediate and even high risk patients, and a systematic use of rhTSH stimulation before 131I therapy allowed us to reduce significantly the median administered 131I activity, with a similar rate of complete therapeutic response.

Underevaluation of fractures by self-report: an analysis from the FRISBEE cohort.

We assessed the rate of non-reported fractures in the FRISBEE cohort. Over a median follow-up period of 9.2 years, we registered 992 fractures. The global percentage of non-reported fractures was 21.3%. Underreporting of fracture event might influence any model of fracture risk prediction. INTRODUCTION: Most fracture cohort studies rely on participant self-report of fracture event. This approach may lead to fracture underreporting. The purpose of the study was to assess the rate of non-reported fractures in a well-characterized population-based cohort of 3560 postmenopausal women, aged 60-85 years, included in the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) study. METHODS: Incident low-traumatic or non-traumatic fractures were registered annually during phone calls. In 2018, we reviewed the medical files of 67.9% of our study participants and identified non-reported fractures ("false negatives fractures (FN)"). We also evaluated whether the rate of FN was influenced by baseline patients' characteristics and fracture risk factors. Generalized estimating equation (GEE) was used to calculate odds ratio (OR) and 95% CI. RESULTS: Over a median follow-up period of 9.2 years, we registered 992 fractures (781 by self-report, confirmed by a radiological report and 211 unreported). The global false negative rate for all fractures was 21.3%, including 22% for MOFs (major osteoporotic fractures), 13.1% for other major fractures, and 25.8% for minor fractures. The rate of non-reported fractures varied by fracture site: for MOFs, it was 2.7% (n = 2/73) at the hip, 5.3% at the proximal humerus (n = 5/94), 7.1% at the wrist (n = 11/154), and 46.5% at the spine (n = 100/215). For "other major" fractures, the highest rate of false negatives fractures was found at the pelvic bone (21%, n = 13/62), followed by the elbow (17.9%, n = 5/28), long bones (10.5%, n = 2/19), ankle (6.2%, n = 4/65), and knee (5.9%, n = 1/17). Older subjects (OR 1.7; 95% CI, 1.2-2.4; P = 0.003), subjects with early non-substituted menopause (OR 1.8; 95% CI, 1.0-3.3; P = 0.04), with a lower education level (OR 1.5; 95%CI, 1.1-2.2; P = 0.01), and those under drug therapy for osteoporosis (OR 1.5; 95% CI, 1.0-2.2; P = 0.05) were associated with a higher rate of FN. CONCLUSIONS: In conclusion, underreporting of a substantial proportion of fracture events will influence any model of fracture risk prediction and induce bias when estimating the associations between candidate risk factors and incident fractures.

Assessment of bone quality with trabecular bone score in type 2 diabetes mellitus: A study from the FRISBEE cohort.

OBJECTIVE: The purpose of our study was to compare bone mineral density (BMD) and trabecular bone score (TBS) values between patients with type 2 diabetes (T2D) and control subjects with similar FRAX scores in order to evaluate TBS as an additional tool for assessing fracture risk in diabetic subjects. METHODS: A cross-sectional analysis was performed using BMD results from 260 subjects participating in the FRISBEE study (Fracture RISk Brussels Epidemiological Enquiry), an ongoing prospective epidemiological study in a population-based cohort (Brussels, Belgium) of 3560 postmenopausal women aged 60-85 years. TBS measurement was possible in 1108 subjects from the FRISBEE cohort. Among these 1108 subjects, 65 had known T2D at inclusion. For each diabetic case we selected 3 controls from our database. (n = 195). Diabetic subjects and controls were matched for age and baseline FRAX score for major osteoporotic fractures. RESULTS: BMD (g/cm2 ) tended to be higher in T2D than in control subjects, significantly so at the total hip 0.90 ± 0.13 versus 0.87 ± 0.12 (P = 0.015). On the contrary, TBS was significantly lower in the T2D group (mean = 1.19 ± 0.17) compared with the control group (mean = 1.27 ± 0.13) (P = 0.005). Mean TBS remained significantly lower in T2D (1.22 ± 0.17) compared with the control group (1.27 ± 0.13) (P = 0.02) after adjustment for body mass index. CONCLUSION: Our data suggest that TBS complements BMD at the total hip, in demonstrating the "diabetes-associated bone disease".