Abstract
Many physicians in clinical practice have not had formal training in statistics. A basic knowledge of certain aspects of statistics is essential for the physician densitometrist. Quality control procedures for the various machines require some statistical analyses. The computer-generated reports of bone density data include statistical devices such as T- and z-scores and confidence intervals. To interpret serial studies, the physician must understand the concept of precision and be able to calculate the precision of repeat measurements in his or her facility. These concepts and others are discussed in this chapter.
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Notes
- 1.
The normal or Gaussian distribution is discussed later in this chapter.
- 2.
The Gaussian distribution is named after Johann Carl Friedrich Gauss (1777–1855), a German mathematician, astronomer, and physicist.
- 3.
Normal in this context simply means that the values follow the distribution described by Gauss. It should not be interpreted to mean that values that do not follow this distribution are abnormal.
- 4.
The actual value by which the standard error is multiplied depends upon the sample size. For samples with an n of greater than 20, the value is very close to 2. For smaller samples, the value will be slightly larger. The formula shown here is a practical characterization of the calculation of the 95% confidence interval.
- 5.
See Chapter 9 for a discussion of the World Health Organization (WHO) criteria for the dia- gnosis of osteoporosis.
- 6.
Sir Francis Galton (1822–1911) was a physician as well as a statistician, geographer, meteorologist, and explorer. He is a considered a pioneer in statistical correlation and regression as well as in the science of fingerprint identification.
References
Phillips JL. Interpreting individual measures. In: Statistical Thinking. New York: W.H. Freeman and Company, 1982:62–78.
Writing Group for the ISCD Position Development Conference. Nomenclature and decimal places in bone density. J Clin Densitom 2004;7:45–50.
Baim S, Leonard MB, Bianchi ML, Hans DB, Kalkwarf HJ, Langman CB et al. Official positions of the International Society for Clinical Densitometry and executive summary of the 2007 ISCD Pediatric Position Development Conference. J Clin Densitom 2008;11:6–21.
Melton LJ, Chrischilles EA, Cooper C, Lane AW, Riggs BL. How many women have osteoporosis? J Bone Miner Res 1992;7:1005–1010.
Cooper C, Atkinson EJ, O’Fallon WM, Melton LJ. Incidence of clinically diagnosed vertebral fractures: a population-based study in Rochester, Minnesota, 1985–1989. J Bone Miner Res 1992;7:221–227.
Melton LJ, Atkinson EJ, O’Fallon WM, Wahner HW, Riggs BL. Long-term fracture prediction by bone mineral assessed at difference skeletal sites. J Bone Miner Res 1993;8:1227–1233.
Cummings SR, Black DM, Rubin SM. Lifetime risks of hip, Colles’, or vertebral fracture, and coronary heart disease among white postmenopausal women. Arch Intern Med 1989;149:2445–2448.
International Organization of Standardization. Accuracy (trueness and precision) of measurement methods and results – Part 1: General principles and definition. 1st ISO 5725-1, Switzerland, ISO. International Standard. International Organization of Standardization, 1994: 1–17.
Glüer CC, Blake G, Lu Y, Blunt BA, Jergas M, Genant HK. Accurate assessment of precision errors: how to measure the reproducibility of bone densitometry techniques. Osteoporos Int 1995;5(4):262–270.
Takada M, Engelke K, Hagiwara S, Grampp S, Jergas M, Glüer CC, Genant HK. Assessment of osteoporosis: comparison of radiographic absorptiometry of the phalanges and dual X-ray absorptiometry of the radius and lumbar spine. Radiology 1997;202:759–763.
Hansen MA. Assessment of age and risk factors on bone density and bone turnover in healthy premenopausal women. Osteoporos Int 1994;4:123–128.
Mazess RB, Barden HS. Bone density in premenopausal women: effects of age, dietary intake, physical activity, smoking, and birth-control pills. Am J Clin Nutr 1991;53:132–142.
Campbell MJ. Statistics at Square Two. London: BMJ Books, 2001:3.
Hirsch RP, Riegelman RK. Statistical operations. Analysis of health research data. Cambridge: Blackwell Science, Inc., 1996:9–39.
Hanley JA, NcNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982;143:29–36.
Swets JA. Measuring the accuracy of diagnosis systems. Science 1988;240:1285–1293.
Lydick E, Cook D, Turpin J, Melton M, Stine R, Byrnes C. Development and validation of a simple questionnaire to facilitate identification of women likely to have low bone density. Am J Man Care 1998;4:37–48.
Galton F. Regression towards mediocrity in hereditary stature. J Anthropol Inst 1886;15:246–263.
Bourke CJ, Daly LE, McGilvray J. Interpretation and uses of medical statistics. Oxford: Blackwell Scientific Publications;1985:147–148.
Bonnick SL. Monitoring osteoporosis therapy with bone densitometry: a vital tool or regression toward mediocrity? J Clin Endocrinol Metab 2000;85:3493–3495.
Cummings SR, Palermo L, Browner W, et al. Monitoring osteoporosis therapy with bone densitometry. Misleading changes and regression to the mean. JAMA 2000;283:1318–1321.
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Bonnick, S.L. (2010). A Statistical Overview for the Non-statistician Densitometrist. In: Bone Densitometry in Clinical Practice. Current Clinical Practice. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60327-499-9_3
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