Osteodensitometry, Bone Biomechanics and Fracture Risk João Costa, Rui Miranda, Rui Pinto “Normal” Bone Introduction The bone formation takes place in 3 steps:  production of extracellular matrix,  matrix mineralization  bone remodelling (resorption followed by bone formation) Bone remodelling is a dynamic process developed by the action of osteoclasts (bone resorption) and osteoblasts (bone formation). Osteoblasts produce osteoid, which is composed mainly of type I collagen. Osteoblasts are also responsible for mineralization of the osteoid matrix. After the resorption, osteoclasts are replaced by osteoblasts which, in young people, completely restore the bone. In the elderly, osteoblasts don’t repair all the removed bone mass. In each moment, the bone mass depends on the balance between the peak bone mass (which occurs on a mature skeleton, between 20 and 30 years, and depends up to 80% on genetic factors) and the later bone loss (depends not only on genetic factors but also on hormonal and environmental factors). After the peak bone mass, the bone resorption starts steadily to exceed the formation rate, leading to a decreased bone mass and bone quality, which increases the fracture risk. Osteoporosis is a bone tissue disorder. It results from the decrease of bone mass and from changes of its microstructure, leading to an increase in fracture risk. Postmenopausal women and elder people are at higher risk. Bearing in mind the current aging evolution pattern of the world’s population, there is a tendency for the increase of the number of affected individuals. As a result of osteoporosis, patients often suffer low energy fractures (when falling from their standing height), which are responsible for high incapacity and mortality rates. In order to diagnose high risk persons, dual-energy x-ray absorptiometry (DXA) is often used. This method measures the bone mineral density (BMD) of an individual.  If the obtained BMD value is between –2.5 and –1 standard deviations (SD) relatively to the estimated value for the peak bone mass, then the patient has osteopenia.  However, if the BMD is -2.5 SD or less, osteoporosis is diagnosed. BMD value is today’s most influent clinical argument for starting osteoporosis treatment, however it doesn’t fully express the real fracture risk as there is only a correlation of 0.4 between BMD and the biomechanical behaviour of the bone. Beside DXA, there may be other important factors to consider, such as:  Age  Previous occurrence of fragility fractures  Patient’s eating and drinking habits Osteoporosis Osteoporotic Bone It is also important to discuss the assessment tools designed to identify patients that are likely to have low bone density, like OPERA. This kind of algorithms have similar sensitivity and specificity, and differ on the number of factors used to calculate the score. OPERA, NOF, ABONE and ORAI use a simple calculation method. We believe that any of these methods have the capacity to identify someone which may have low bone mass and should make a DXA scan. Discussion Conclusion The main goal for this project was to describe and analyse the available fracture risk assessment tools, as osteoporosis tends to be a common disease on the contemporary society. Bone Mineral Density is often used in clinical practice as the main criteria to diagnose osteoporosis. However, this exam represents costs to the health systems, and must be only applied to patients that are likely to have low BMD. Algorithms like OSIRIS, OPERA and SCORE are able to easily select these patients for further evaluation and treatment. Advantages High risk situations are easily identified The first study that we have analysed was “Fracture Risk (FRISK) Score: Geelong Osteoporosis Study”. In two different groups of women, the bone mineral density (BMD) at femoral neck and spine column was measured, the weight, the number of falls on the year before this study as well as the number of fractures during adult age were assessed. The researchers congregated the above-mentioned factors and created a mathematical formula to predict the risk of osteoporotic fracture, expressed through a scale which varies from 0 to 10. The higher the score, the bigger the risk. Normally, when the score is equal or superior to 5.4, bone fracture is highly expected. When applied to a sample of 600 women, the FRISK score effectively predicted 75% of the fractures that occurred two years after the measurements. The latest published studies include “Development of a nomogram for individualizing hip fracture risk in men and women”. The nomogram built by the authors is capable of individualizing 5-year and 10-year risk of hip fracture for both sexes. The core set is made up of the following parameters:  Age;  The bone mineral density (BMD), T-score.  Prior fracture;  Fall in the last 12 months. It is noted that among those with low BMD (T-scores less than or equal to −2.5) and aged more than 70 years, the risk of hip fracture in men was almost equivalent or even higher than in women. Prior fracture and fall, as they are independent from BMD and age, contributed for an additional increase of fracture risk. The current algorithm developped by the World Health Organization for the calculation of the fractures risk focuses on the most important factors that contribute to fracture risk prediction. All these factors (such as age, z-score on certain bones or some habits like smoking or alcohol intake), are balanced, and put on a simple mathematical formula, giving a percentage as a result. Disadvantages This nomogram has not been validated in an independent population The accuracy of the nomogram is limited by the precision of the markings that need to be drawn and analysed Advantages Individualizes the absolute risk of hip fracture The parameters of the nomogram are reliable and easy to acquire. Reveals high accuracy in the identification of the individuals that have a high risk of fracture Development of a nomogram for individualizing hip fracture risk in men and women Fracture Risk (FRISK) Score: Geelong Osteoporosis Study Disadvantages Does not include the sex and the age of the patient Needs t-score measurements on different sites Requires a few calculations We applied each of the analysed algorithms to several combinations of factors (sex, age, previous fractures, recent falls, body mass index, t-score and z-score, etc…), obtaining a fracture risk. Our conclusions about each of them are the following: Current understanding of osteoporosis according to the position of the World Health Organization Advantages Takes into account all the factors referred by most of the studies as relevant for the prediction of fractures Gives to diagnostis the objectivity of a mathematical formula Disadvantages Absence of some factors (e.g. low physical activity and malnutrition) This algorithm has numerous factors, which make it difficult to use  After judging the three algorithms we are able to state that the Nomogram is probably the most functional fracture risk assessment tool. It is easy to use and employs the most important risk factors, which is reflected by the reliable sensitivity and specificity values. The truth is that the correlation between DXA values and biomechanical behaviour of the bone is low, which makes it unable to effectively predict the fracture risk. Thus, the present definition of osteoporosis must be reviewed, as there is the need to integrate other factors beside BMD. While this does not change, there are many methods that have been developed and adapted to the needs of current diagnosis. We have concluded that the assessment tool included in “Development of a nomogram for individualizing hip fracture risk in men and women” was the easiest and most reliable to use in practice. Looking at the evolution that these assessment tools suffered, we can foresee that, as time goes by, more studies and ideas will emerge, which will decrease mortality and incapacity rates related to this disease. Bone Formation and Resorption Methods and Results Objectives:  Analysis of different fracture risk algorithms in order to identify the most reliable and easy to use To obtain the most recent informations about this subject, we used the Pubmed search engine, and focused on the following expressions:  “Osteoporosis and fracture risk”, obtaining 5762 results  “Fracture Risk and Assessment tool”, obtaining 116 results. From the first search we managed to analyse 2 results, and 5 from the second. Unfortunately, some articles were written only in Japanese, so we were not able to explore them. Besides, some papers were impossible to obtain.