亚洲骨质疏松筛查工具在健康体检中的筛查准确性评价及适宜切点研究

doi:10.19723/j.issn.1671-167X.2019.06.019

Abstract

Abstract:

Objective: To explore the screening value of osteoporosis self-assessment tool for Asians (OSTA) and the optimal cut-off value in Chinese healthy physical examination population.Methods: We selected a healthy physical examination population for bone mineral density screening at the Health Examination Center in Peking University Third Hospital from 2013 to 2016. Quantitative ultrasound (QUS) results were used as the gold standard, and T value ≤-2.5 was defined as osteoporosis patients. Diagnostic test methods were used to analyze the sensitivity, specificity, likelihood ratio and area under curve (AUC) of different cut points of OSTA. The screening accuracy of OSTA at different cut points was compared and the optimal cut-point value determined.Results: A total of 5 833 subjects were included in the study, with an average age of (48.3±17.5) years and 2 594 women (44.5%). The QUS test showed 403 patients with osteoporosis (6.9% of the total population), 343 female osteoporosis patients (13.22% of the female population). In the whole age group, AUC at the international routine cut-off value (OSTA ≤-1) screening for osteoporosis was 0.815 (95%CI: 0.804-0.825), and screening accuracy was higher in the women (AUC=0.837, 95%CI: 0.823-0.851) than that in the men (AUC=0.767, 95%CI: 0.752-0.781; P<0.05). In the whole age group, when the optimal cut-off value was 0, its AUC 0.842 (95%CI: 0.832-0.851) was significantly higher than that when the cut-off value was -1 (P<0.01), and net reclassification improvement (NRI) increased by 5.5%. In the 40 to 65-year-old group, when OSTA cut-off value ≤0, the screening accuracy was significantly higher (NRI=19.5%, P=0.003) than that when it was-1.Conclusion: The OSTA screening tool had good osteoporosis screening value in healthy people, and the screening accuracy in women is higher than that in men. Increasing the screening cut-off value of OSTA would be helpful to improve the screening accuracy in the whole and 40 to 65-year-old population. There may be different optimal cut-off values for different age group population.

Key words: Osteoporosis self-assessment tool for Asians, Bone density, Health surveys, Sensitivity and specificity

CLC Number:

R681

Peng WANG,Hua WU,Ying CHE,Dong-wei FAN,Jue LIU,Li-yuan TAO. Evaluation of screening accuracy on osteoporosis self-assessment tool for Asians and its cut-off value in healthy physical examination population[J].Journal of Peking University(Health Sciences), 2019, 51(6): 1085-1090.

Figures/Tables 4

Table 1

Table 2

Figure 1

Table 3

References 28

[1]	Kanis JA, McCloskey E, Branco J, et al. Goal-directed treatment of osteoporosis in Europe[J]. Osteoporos Int, 2014,25(11):2533-2543.
[2]	Lorenc R, Gluszko P, Franek E , et al. Guidelines for the diagnosis and management of osteoporosis in Poland: Update 2017[J]. Endokrynol Pol, 2017,68(5):604-609.
[3]	Si L, Winzenberg TM, Jiang Q , et al. Projection of osteoporosis-related fractures and costs in China: 2010—2050[J]. Osteoporos Int, 2015,26(7):1929-1937.
[4]	Koh LK, Sedrine WB, Torralba TP , et al. A simple tool to identify Asian women at increased risk of osteoporosis[J]. Osteoporos Int, 2001,12(8):699-705.
[5]	Lydick E, Cook K, Turpin J , et al. Development and validation of a simple questionnaire to facilitate identification of women likely to have low bone density[J]. Am J Manag Care, 1998,4(1):37-48.
[6]	Cadarette SM, Jaglal SB, Kreiger N , et al. Development and validation of the osteoporosis risk assessment instrument to facilitate selection of women for bone densitometry[J]. CMAJ, 2000,162(9):1289-1294.
[7]	Sedrine WB, Chevallier T, Zegels B , et al. Development and assessment of the osteoporosis index of risk (OSIRIS) to facilitate selection of women for bone densitometry[J]. Gynecol Endocrinol, 2002,16(3):245-250.
[8]	Salaffi F, Silveri F, Stancati A , et al. Development and validation of the osteoporosis prescreening risk assessment (OPERA) tool to facilitate identification of women likely to have low bone density[J]. Clin Rheumatol, 2005,24(3):203-211.
[9]	Crandall CJ . Risk assessment tools for osteoporosis screening in postmenopausal women: a systematic review[J]. Curr Osteoporos Rep, 2015,13(5):287-301.
[10]	中华医学会骨质疏松和骨矿盐疾病分会. 原发性骨质疏松症诊疗指南(2017)[J]. 中华骨质疏松和骨矿盐疾病杂志, 2017,10(5):413-443.
[11]	《中国老年骨质疏松症诊疗指南(2018)》工作组, 中国老年学和老年医学学会骨质疏松分会, 马远征 , 等. 中国老年骨质疏松症诊疗指南(2018)[J]. 中国骨质疏松杂志, 2018,24(12):1541-1567.
[12]	Chang SF, Yang RS . Determining the cut-off point of osteoporosis based on the osteoporosis self-assessment tool, body mass index and weight in Taiwanese young adult women[J]. J Clin Nurs, 2014,23(17-18):2628-2636.
[13]	Chang AJ, Ying Q, Chen XN , et al. Evaluation of three risk assessment tools in discriminating fracture status among Chinese patients undergoing hemodialysis[J]. Osteoporosis Int, 2016,27(12):3599-3606.
[14]	Oh SM, Nam B, Rhee Y , et al. Development and validation of osteoporosis risk-assessment model for Korean postmenopausal women[J]. J Bone Miner Metab, 2013,31(4):423-432.
[15]	Pencina MJ, D’Agostino RS, D’Agostino RJ, et al. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond[J]. Stat Med, 2008, 27(2): 157-172, 207-212.
[16]	Si L, Winzenberg TM, Chen M , et al. Screening for osteoporosis in Chinese post-menopausal women: a health economic modelling study[J]. Osteoporos Int, 2016,27(7):2259-2269.
[17]	Yang Y, Wang B, Fei Q , et al. Validation of an osteoporosis self-assessment tool to identify primary osteoporosis and new osteoporo-tic vertebral fractures in postmenopausal Chinese women in Beijing[J]. BMC Musculoskelet Disord, 2013,14:271.
[18]	Huang JY, Song WZ, Zeng HR , et al. Performance of the osteoporosis self-assessment tool for asians (OSTA) in screening osteoporosis among middle-aged and old women in the Chengdu region of China[J]. J Clin Densitom, 2015,18(4):539-545.
[19]	Li-Yu JT, Llamado LJ, Torralba TP . Validation of OSTA among Filipinos[J]. Osteoporos Int, 2005,16(12):1789-1793.
[20]	Muslim D, Mohd E, Sallehudin A , et al. Performance of osteoporosis self-assessment tool for asian (OSTA) for primary osteoporosis in post-menopausal Malay women[J]. Malays Orthop J, 2012,6(1):35-39.
[21]	Kung AW, Ho AY, Ross PD , et al. Development of a clinical assessment tool in identifying Asian men with low bone mineral density and comparison of its usefulness to quantitative bone ultrasound[J]. Osteoporos Int, 2005,16(7):849-855.
[22]	Oh SM, Song BM, Nam BH , et al. Development and validation of osteoporosis risk-assessment model for Korean men[J]. Yonsei Med J, 2016,57(1):187-196.
[23]	Liu M, Zhang Y, Cheng X , et al. The effect of age on the changes in bone mineral density and osteoporosis detection rates in Han Chinese men over the age of 50[J]. Aging Male, 2014,17(3):166-173.
[24]	Huang JY, Song WZ, Huang M . Effectiveness of osteoporosis self-assessment tool for Asians in screening for osteoporosis in healthy males over 40 years old in China[J]. J Clin Densitom, 2017,20(2):153-159.
[25]	Geater S, Leelawattana R, Geater A . Validation of the OSTA index for discriminating between high and low probability of femoral neck and lumbar spine osteoporosis among Thai postmenopausal women[J]. J Med Assoc Thai, 2004,87(11):1286-1292.
[26]	Chan SP, Teo CC, Ng SA , et al. Validation of various osteoporosis risk indices in elderly Chinese females in Singapore[J]. Osteoporos Int, 2006,17(8):1182-1188.
[27]	Moon JH, Kim LO, Kim HJ , et al. Evaluation of the predictive index for osteoporosis as a clinical tool to identify the risk of osteoporosis in Korean men by using the Korea National Health and Nutrition Examination Survey Data[J]. Korean J Fam Med, 2016,37(6):346-350.
[28]	Zha XY, Hu Y, Pang XN , et al. Diagnostic value of osteoporosis self-assessment tool for Asians (OSTA) and quantitative bone ultrasound (QUS) in detecting high-risk populations for osteoporosis among elderly Chinese men[J]. J Bone Miner Metab, 2015,33(2):230-238.

Metrics

Viewed

Full text

271

HTML			PDF

Just accepted	Online first	Issue	Just accepted	Online first	Issue
0	0	10	0	0	261

From	Others	local

Times	64	207
Rate	24%	76%

Abstract

1058

Just accepted	Online first	Issue

0	0	1058

From	Others	local

Times	1053	5
Rate	100%	0%

Cited

Web of Science	Crossref	ScienceDirect	Search for Citations in Google Scholar >>


This page requires you have already subscribed to WoS.

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

Items	All	Non-osteoporosis	Osteoporosis	t/χ²	P value
Participants, n (%)	5 833	5 430 (93.09)	403 (6.91)
Age/years, $x ?$ ±s	48.32±17.53	46.42±16.40	74.02±10.70	33.26	<0.001
Age group, n (%)				1 111.43	<0.001
<40 years	2 398 (41.11)	2 390 (44.01)	8 (1.99)
40-65 years	2 274 (38.99)	2 216 (40.81)	58 (14.39)
≥65 years	1 161 (19.90)	824 (15.18)	337 (83.62)
Gender, n (%)				289.55	<0.001
Female	2 594 (44.47)	2 251 (41.45)	343 (85.11)
Male	3 239 (55.53)	3 179 (58.55)	60 (14.89)
Height/cm, $x ?$ ±s	166.44±8.26	167.11±7.99	157.39±6.32	23.89	<0.001
Weight/kg, $x ?$ ±s	67.34±13.20	67.86±13.23	60.26±10.40	11.28	<0.001
BMI/(kg/m²), $x ?$ ±s	24.17±3.60	24.17±3.62	24.26±3.45	0.47	0.638

Items	Osteoporosis,n (%)	Sensitivity/%	Specificity/%	+LR	-LR	AUC (95%CI)
All age group
All	403 (6.9)	73.95	88.99	6.71	0.29	0.815 (0.804-0.825)
Male	60 (1.9)	66.67	86.66	5.00	0.38	0.767 (0.752-0.781)
Female	343 (13.2)	75.22	92.27	9.73	0.27	0.837 (0.823-0.851)
More than 40-year-old
All	395 (11.5)	75.44	80.33	3.84	0.31	0.779 (0.753-0.805)
Male	58 (3.1)	68.96	77.12	3.01	0.40	0.730 (0.661-0.800)
Female	337 (22.11)	76.56	85.35	5.23	0.27	0.809 (0.781-0.838)

Items	AUC	SE	95%CI	Z	P₁	NRI	P₂
All age group
OSTA ≤-1	0.815	0.011	0.804-0.825	Ref.	Ref.
OSTA ≤ 0	0.842	0.010	0.832-0.851	3.692	<0.001	0.055	<0.001
OSTA ≤ 0.62	0.850	0.009	0.841-0.859	4.048	<0.001	0.071	<0.001
40 to 65-year-old
OSTA ≤-1	0.572	0.025	0.551-0.592	Ref.	Ref.
OSTA ≤ 0	0.669	0.033	0.649-0.689	3.428	<0.001	0.195	0.003
OSTA ≤ 0.62	0.724	0.033	0.706-0.743	4.693	<0.001	0.305	<0.001
More than 40-year-old
OSTA ≤-1	0.779	0.011	0.765-0.793	Ref.	Ref.
OSTA ≤ 0	0.792	0.010	0.778-0.805	1.637	0.102	0.025	0.126
OSTA ≤ 0.62	0.790	0.009	0.776-0.803	1.153	0.249	0.021	0.293

Evaluation of screening accuracy on osteoporosis self-assessment tool for Asians and its cut-off value in healthy physical examination population

RICH HTML

PDF (PC)

Abstract

Cite this article

share this article

Figures/Tables 4

References 28

Related Articles 8

Metrics

Comments

Recommended 0

[1]	Rui-jie CAO,Zhong-qiang YAO,Peng-qing JIAO,Li-gang CUI. Comparison of diagnostic efficacy of different classification criteria for Takayasu arteritis in Chinese patients [J]. Journal of Peking University (Health Sciences), 2022, 54(6): 1128-1133.
[2]	Hai-hong YAO,Su-mei TANG,Zhi-min WANG,Xia ZHANG,Xu-yong CHEN,Li GAO,Jing LIU,Yi-jun DAI,Zhao-heng HU,Xue-wu ZHANG,Zhan-guo LI. Study of bone mineral density and serum bone turnover markers in newly diagnosed systemic lupus erythematosus patients [J]. Journal of Peking University(Health Sciences), 2018, 50(6): 998-1003.
[3]	CAO Jie, MENG Huan-xin. Evaluation of using cone beam computed tomography as a regular test before and after periodontal regenerative surgery#br# [J]. Journal of Peking University(Health Sciences), 2018, 50(1): 110-116.
[4]	XU Xiao， XU Li, JIANG Jiu-hui, WU Jia-qi, LI Xiao-tong, JING Wu-di. Accuracy analysis of alveolar dehiscence and fenestration of maxillary anterior teeth of Angle class Ⅲ by cone-beam CT [J]. Journal of Peking University(Health Sciences), 2018, 50(1): 104-109.
[5]	WANG Yu, HAO Yan-jie, DENG Xue-rong, LI Guang-tao, GENG Yan, ZHAO Juan, ZHOU Wei, ZHANG Zhuo-li. Risk factors for bone mineral density changes in patients with rheumatoid arthritis and fracture risk assessment [J]. Journal of Peking University(Health Sciences), 2015, 47(5): 781-786.
[6]	WANG Yu, GENG Yan, DENG Xue-rong, ZHANG Zhuo-li. Relationship between wrist bone mineral density and synovitis, erosion by ultrasonography in female rheumatoid arthritis patients [J]. Journal of Peking University(Health Sciences), 2015, 47(5): 774-780.
[7]	WEI Pan, LU Song-He, FU Jing-Ya, YAN Zhi-Min, HUA Hong. Validation of the American College of Rheumatology Classification Criteria for primary Sjögren’s syndrome in Chinese patients [J]. Journal of Peking University(Health Sciences), 2014, 46(2): 306-310.
[8]	YU Yang, SHENG Qin-Hui, ZHANG Bao-Wei, DING Wen-Hui. Left atrial size predicts adverse cardiac events in patients with non-obstruction hypertrophic cardiomyopathy [J]. Journal of Peking University(Health Sciences), 2014, 46(2): 207-210.