A simple system to determine who needs osteoporosis screening

doi:10.1016/S0029-7844(98)00549-3

Obstetrics & Gynecology

Volume 93, Issue 5, Part 1, May 1999, Pages 757-760

https://doi.org/10.1016/S0029-7844(98)00549-3 Get rights and content

Abstract

Objective: To define factors that identify patients at highest risk for osteoporosis who should be screened.

Methods: We gave a questionnaire we developed for osteoporosis risk factors to 1346 menopausal women who were being screened by bone densitometry at the spine, hip, and femoral neck. Chi-square analysis using the one-tailed test was done on all categoric variables to determine differences or patterns in bone mineral density at specific sites. Multivariate logistic regression analysis was done on each of the three sites scanned to determine which combination of independent variables was a significant predictor of the presence or absence of osteoporosis.

Results: Factors identified that were significant for the presence of osteoporosis were age 61 years or older, weight 165 pounds or less, or lack of any use of estrogen, either oral contraceptives or estrogen replacement therapy.

Conclusion: We devised a simple system to identify which patients should be screened for osteoporosis.

Section snippets

Materials and methods

The study was performed by interviewing 1346 menopausal women consecutively during a 2 $12$ -year period with a questionnaire developed by the senior author. The women presented for osteoporosis evaluation and had a dual-energy x-ray absorptiometry scan of three sites. The questionnaire was administered in person before or during the scan, which was done with a Hologic QDR 1500 densitometer (Hologic Inc., Waltham, MA). The sites evaluated were lumbar spine (L1–4) in the anteroposterior position,

Results

The population studied consisted of 1346 menopausal women. They were all white and had been referred by their private physician for a scan for osteoporosis evaluation. All women were having their first scan. None were taking bisphosphonate or calcitonin. The mean age of the patients was 62.2 years (standard deviation [SD] 10.3 years), mean weight was 149.6 pounds (SD 32.2 pounds), and mean years from menopause was 16.2 (SD 11.0 years).

Osteoporosis was absent at all three sites in 873 women

Discussion

Our results suggest that the risk factors usually used to determine who might have osteoporosis and therefore benefit from screening might not be reliable. We demonstrated that the strongest associations with osteoporosis occur with increasing age, decreasing weight, and never having used oral estrogen therapy for 6 months or longer. The beneficial effects of estrogen in the form of oral contraceptives on bone mineral density have been reported previously.8, 9

Several impediments to screening

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Osteoporosis Risk Calculators
2017, Journal of Clinical Densitometry
Citation Excerpt :
Study variables included past or current use of steroids, thyroid replacement, heparin, oral contraceptives, estrogen replacement therapy, alcohol (none, 5.0; mild, 5.1; moderate, 5.2; and excessive, 5.3), caffeine intake (0–3), exercise (0–3), dietary calcium intake (500 mg, 5.0; 500–1000 mg, 5.1; 1000–1500 mg, 5.2; and 1500 mg, 5.3), calcium supplementation (0–3), past or present smoking, presence or absence of the uterus or ovaries, and family history of osteoporosis. Smoking history, oral contraceptive use, and estrogen replacement therapy were considered positive if usage was 6 mo or longer (25). Multivariate logistic regression, performed to determine which independent variables were significant predictors, revealed age and years of menopause to be positive predictors and weight to be a negative predictor for osteoporosis at any of the 3 sites (all p < 0.001).
Osteoporosis is a silent disease until fractures occur, patient recognition is the greatest clinical challenge. Although more than 20 million women in the US are estimated to have established osteoporosis the majority are not appropriately identified. Bone densitometry is the current gold standard for diagnosis of osteoporosis; but may not be feasible or cost-effective to recommend for all postmenopausal women. Therefore, questionnaires incorporating risk factors have been developed to aid the clinician in identifying women with osteoporosis. We will review Qfracture, CAnadian Risk for Osteoporosis Calculator (CAROC), the Simple Calculated Osteoporosis Risk Index (SCORE), the Osteoporosis Risk Assessment Index (ORAI), the Osteoporotic Self-assessment Tool (OST), ABONE, and the United States Preventive Services Task Force recommendations.
Sensitivity, specificity, positive and negative predictive values of the criteria for indicating a bone densitometry in the evaluation of medical techniques and research in cataluña
2011, Reumatologia Clinica
La Agencia de Evaluación de Tecnologías e Investigación Médicas (AETIM) de Cataluña propuso en 2001 unos criterios de indicación de densitometría ósea (DO) para su uso en la consultas del sistema sanitario público. El objetivo fue conocer la sensibilidad, la especificidad, el valor predictivo positivo (VPP) y valor predictivo negativo (VPN) de los criterios de indicación de DO de la AETIM.
Cinco grupos de voluntarios (mujeres premenopáusicas de 46 a 65 años, posmenopáusicas de 46 a 65 años y posmenopáusicas de > 65 años, y varones de 46 a 65 años y de > 65 años) a los que se realizó DO y una encuesta sobre factores de riesgo. Se calcularon la sensibilidad, la especificidad, el VPP y el VPN de los criterios de la AETIM, y los resultados se compararon con los criterios de indicación de DO propuestos por la Organización Mundial de la Salud (en 1999 y 2003), la National Osteoporosis Foundation (en 1998 y 2010) y el Comité Internacional de Guías Clínicas en Osteoporosis.
Los criterios de la AETIM tienen una baja sensibilidad tanto para detectar baja masa ósea (índice T < −1) como osteoporosis (índice T < −2,5); la especificidad varía según el grupo. El VPP es bajo, pero el VPN para osteoporosis es alto en todos los grupos (excepto el de mujeres posmenopáusicas > 65 años). El resto de los criterios tienen un VPN alto y, en mujeres, buena sensibilidad y muy baja especificidad, especialmente para identificar pacientes con osteoporosis.
Los criterios de la AETIM son útiles para seleccionar pacientes a los que no sería necesario realizar una DO, pero carecen de sensibilidad suficiente para identificar individuos con baja masa ósea. El resto de criterios tienen también un VPN alto para osteoporosis y una sensibilidad algo mejor.
The Catalan Agency for Health Technology Assessment and Research (AETIM) proposed, in 2001, criteria for performing a bone densitometry (BD) for use in the consultations of the public health system.
To determine the sensitivity, specificity, positive predictive value and negative predictive value of the criteria to indicate BD.
Five groups of volunteers (premenopausal women aged 46 to 65 years, postmenopausal women aged 46 to 65 years, postmenopausal women aged> 65 years and men 46 to 65 years and> 65 years) underwent BD and a questionnaire on risk factors. The results obtained with the AETIM criteria are related to criteria for indication of BD proposed by the World Health Organization (1999 and 2003 criteria), the National Osteoporosis Foundation (1998 amd 2010 criteria) and the International Committee of Clinical Guidelines on Osteoporosis.
Criteria from the Catalan Agency have low sensitivity to detect both low bone mass (T index < −1) and osteoporosis (T index < −2.5), specificity varied according to the group. The positive predictive value is low, but the negative predictive value for osteoporosis is high in all groups (except for postmenopausal women aged> 65 years). The remaining criteria have a high negative predictive value and, in women, good sensitivity and low specificity, especially for identifying patients with osteoporosis.
Catalan Agency criteria are useful for selecting patients who would not need BD, but lack sufficient sensitivity to identify individuals with low bone mass. The other criteria also have a high negative predictive value for osteoporosis, and a better sensitivity.
The knowledge of osteoporosis risk factors in a Greek female population
2008, Maturitas
The social and economic burden of osteoporosis is important since it concerns a continuously aging population, while the disease is silent until the emergence of fractures. Aim of the study was to assess female population knowledge about osteoporosis risk factors and to identify the risk factors of the studied population.
A sample of 99 (aged: 61.59 ± 9.61 years) women under treatment for osteoporosis or osteopenia answered the questionnaire provided by their pharmacists and were included in the study's analysis. Various parameters on osteoporosis awareness and risk factor knowledge of the population sample studied were analyzed.
It was revealed that 96% of the participants knew osteoporosis definition and sources of this knowledge were one or more of the following: doctors (86.3%), mass media (20%) and friends or relatives (13.7%). It was found that the older age was associated with less knowledge (OR = 0.93, CI: 0.88–0.97, p = 0.004), and higher education with increased knowledge (OR = 1.68, CI: 1.10–2.55, p = 0.014) about osteoporosis. 56.4% of the participants were aware of at least one osteoporosis risk factor. In multivariate analysis, it was revealed that the participants who referred increased milk products consumption in childhood (OR = 3.72, CI: 1.34–10.36, p = 0.012) and current performance of physical activity (OR = 13.06, CI: 3.22–53.05, p < 0.001) were more likely to be informed about osteoporosis risk factors; age >61 years was associated with decreased knowledge of risk factors (OR = 0.27, CI: 0.09–0.82, p = 0.018).
This study implies that a higher degree of participant's health education may result in the avoidance of osteoporosis risk factors. Increasing knowledge of osteoporosis should be a priority for future intervention programs in order to promote specific behavioural strategies for osteoporosis prevention.
Construction of two instruments for the presumptive detection of post-menopausal women with low spinal bone mass by means of clinical risk factors
2005, Maturitas
The objective of this investigation was the design of two instruments based on clinical risk factors for the presumptive detection of post-menopausal women with spinal BMD < 2.5 S.D. below average (LBMD). We investigated the association of 20 risk factors (RF) with LBMD in a series of 131 women. According to current densitometric criteria, subjects were classified as normals (N = 33); osteopenics (N = 53) and osteoporotics (N = 45). Normals and osteopenics were taken as a single group because only ‘nulliparity’ and ‘personal fractures’ exhibited significant differences between these groups. A logistic regression attempting to identify which factors were associated with osteopenia showed a poor fit (pseudo R² = 0.289).
Univariate unconditional logistic regression analysis was used to calculate odd ratios (ORs) and their 95% CI for all RF. Those with associated P-values <0.100 were included in a multivariate logistic regression analysis to obtain the odds ratios (OR) adjusted by the effects of the others. The variables with not significant β coefficients were eliminated, producing a reduced model. BMI (<25 kg/m²), calcium intake (<1.2 g/day), menopause (>10 years), and the simultaneous occurrence of kyphosis and personal fractures showed significant association with low bone mass at the lumbar spine and their effect was additive. Fitting of the data to the model was assessed with the Hosmer–Lemeshow test (P = 0.926) The area under the ROC curve is 0.833 (95% CI = 0.757–0.909). The following equation calculates the probability of having low spinal bone mass:
The sensitivity, specificity and area under the ROC curve were defined. The point of maximum specificity and sensitivity derived from the ROC curve, has a probability of 0.409. With such a cut-off point, the equation has a sensitivity of 73%, specificity 79%, positive predictive value 65% and negative predictive value 85%.
The second instrument associates very low lumbar bone mass with the number of risk factors accumulated per patient. At baseline, all subjects had four RFs: they were, women, white, post-menopausal, and with no previous exposure to estrogens. With six additional RFs the presumptive diagnosis of LBMD has a specificity of 99%, positive predicting value 94% and false positives 6.5%. The area under the curve in a ROC graph was 0.826 (95% CI = 0.747–0.914).
Comparing present instruments with others in the literature, it is concluded that each population require its own algorithm for the presumptive detection of subjects with low bone mass. The algorithm should be reassessed periodically if the characteristics of the population or its social-economic conditions change.
Risk indices and osteoporosis screening: Scope and limits
2002, Mayo Clinic Proceedings
Evaluation of the simple calculated osteoporosis risk estimation (SCORE) in a sample of white women from Belgium
2001, Bone
Identifying patients at risk of developing an osteoporosis-related fracture will continue to be a challenge. The “gold standard” for osteoporosis diagnosis is bone densitometry. However, economic issues or availability of the technology may prevent its use under a mass screening scenario. A risk assessment instrument, the “simple calculated osteoporosis risk estimation” (SCORE), has been reported to appropriately identify women likely to have low (t score ≤−2 SD) bone mineral density (BMD) and who should be referred for bone densitometry. The aim of our study is to evaluate the discriminatory performance of SCORE in a random sample of postmenopausal white women from Belgium. For this purpose, we gathered medical data on 4035 consecutive patients aged ≥45 years, either consulting spontaneously or referred for a BMD measurement to an outpatient osteoporosis center located at the University of Liège, Belgium. BMD measurements, using dual-energy X-ray absorptiometry (DXA) technology, were taken at the hip (total and neck) and lumbar spine (L2–4). At the recommended cutoff point of 6, SCORE had a sensitivity of 91.5% to detect low BMD at any of the measured sites, a specificity of 26.5%, a positive predictive value of 52.8%, and a negative predictive value of 77.7%. According to SCORE, 18% of the patients would not be recommended for densitometry. Among these, 10.9% were misclassified as they had osteoporosis (t score ≤−2.5 SD) at one or more of the sites investigated. The negative predictive errors of SCORE, when failing to detect osteoporosis, were only 1% for the total hip, 3.2% for the femoral neck, and 8.8% for the lumbar spine. We conclude that, notwithstanding the high values of sensitivity, SCORE specificity is too low to be useful as a diagnostic tool for screening patients at high risk to later develop osteoporosis. Nevertheless, from a resource allocation perspective, this instrument can be used with relative confidence to exclude patients who do not need a BMD measurement, and would therefore provide an opportunity to realize substantial cost savings in comparison to a mass screening strategy.

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Original ArticlesA simple system to determine who needs osteoporosis screening

Abstract

Section snippets

Materials and methods

Results

Discussion

Am J Med

Contraception

Lifetime risks of hip, Colles’, or vertebral fracture and coronary heart disease among white postmenopausal women

Arch Intern Med

Involutional osteoporosis

N Engl J Med

Boneing up on osteoporosis. A guide to prevention and treatment

Rate of mortality for elderly patients after fracture of hip in the 1980s

J Bone Joint Surg

Original Articles
A simple system to determine who needs osteoporosis screening