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. 2023 Feb 3;18(2):e0279829. doi: 10.1371/journal.pone.0279829

The proportion of Thai postmenopausal women who would be eligible for anti-osteoporosis therapy

Piyachat Chanidkul 1, Dueanchonnee Sribenjalak 1, Nipith Charoenngam 2,3, Chatlert Pongchaiyakul 1,*
Editor: Inge Roggen4
PMCID: PMC9897565  PMID: 36735672

Abstract

Purpose

To determine the proportion of postmenopausal Thai women who would be classified as having high risk of fracture and eligible for anti-osteoporosis therapy according to the National Osteoporosis Foundation (NOF) criteria.

Methods

Postmenopausal Thai women aged 40–90 years who had been screened for osteoporosis during 2014–2019 were recruited. Demographic data and osteoporosis risk factors were collected based on the Fracture Risk Assessment Tool (FRAX) questionnaire. Bone mineral density (BMD) at the femoral neck and lumbar spine measured using dual energy X-ray absorptiometry. Ten-year probabilities of hip and major osteoporotic fracture (MOF) were calculated based on the Thai FRAX model with BMD. The study’s protocol was approved by the Institutional Ethical Committee (HE581241).

Results

A total of 3,280 postmenopausal women were included. The mean ± SD age was 63.6 ± 10.1 years. A total of 170 (5.2%) participants had a history of hip and/or vertebral fracture. After excluding these participants with fracture history, 699 (21.3%) had osteoporosis, 355 (10.8%) had osteopenia with high risk of fracture (FRAX 10-year probability of hip fracture ≥ 3% and/or MOF ≥ 20%), 1192 (36.3%) had osteopenia with low risk of fracture (FRAX 10-year probability of hip fracture < 3% and MOF < 20%) and 864 (26.3%) had normal BMD. Taken together, a total of 1,224 (37.3%) participants would be eligible for anti-osteoporosis therapy (prior fracture, osteoporosis or osteopenia with high risk of fracture).

Conclusion

The prevalence of Thai postmenopausal women who would be eligible for anti-osteoporosis therapy was 37.3%.

Introduction

Fragility fractures are fractures that result from low energy forces and are major clinical manifestations of osteoporosis. Fracture carries a significant public health burden because it is associated with patients’ quality of life, substantial pain and disability, increased risk of morbidity and mortality and health-care costs [1–4]. To illustrate the burden of this condition, it has been shown that individuals with a history of fracture have a two-fold increased risk of mortality [5]. In addition, presence of a fragility fracture results in an increased risk of development of subsequent fractures, particularly in the first two years after the initial fracture, also known as an imminent fracture risk [6, 7]. The burden of fragility fractures is expected to be more pronounced in many regions of the world given the predicted increased number of aging populations in many countries [8, 9].

Given the significant burden of fracture, attempts have been made to determine the risk of fracture based on clinical information and bone mineral density (BMD) with the aim to guide the decision to pursue interventions to prevent subsequent fragility fractures. The fracture risk assessment tool, also known as FRAX, is a model that incorporates 12 risk factors developed to determine 10-year risk of hip fracture and major osteoporotic fracture (MOF), which has been calibrated in several countries [10–13]. The US National Osteoporosis Foundation (NOF) [3] has defined recommended that individuals with high-risk fracture receive anti-osteoporosis therapy. These individuals include postmenopausal women and men aged 50 years and older who have a prior fracture, osteoporosis (T-score of ≤ -2.5 at the femoral neck and/or lumbar spine), or osteopenia (T-score -1 to -2.5) with a FRAX 10-year probability of at least 3% for hip fracture or at least 20% for major osteoporotic fracture [5].

The prevalence of individuals who met the NOF criteria for anti-osteoporosis therapy has been reported in a few studies in Western population [14, 15]; however, these data in the Southeast Asian populations are relatively limited [16]. Therefore, we aimed to determine the proportion of postmenopausal Thai women who would be classified as having a high risk of fracture and eligible for a pharmacological treatment according to the NOF criteria.

Methods

The current study was designed as a descriptive study in Srinagarind Hospital, a tertiary setting in Northeast of Thailand between 2010 and 2019. Postmenopausal Thai women aged 40 to 90 years who had been screened for osteoporosis between Jan 2014 and February 2019 were recruited. Patients with medication-induced or surgical menopause were excluded from the study. After completing the informed consent, participants were interviewed by a well-trained nurse to ascertain their demographic data and osteoporosis risk factors for FRAX questionnaire. Prior fractures including hip and vertebral fractures using the ICD-10 diagnoses and self-report were reviewed and recorded. In this study only fragility fractures were included. A review of the ICD-10 diagnoses from the hospital database, as well as self-report and the medical record and film X-ray including hip and vertebral fracture. Body weight (including light indoor clothing) was measured using an electronic scale (accuracy of 0.1 kilogram) and standing height (without shoes) was measured using a stadiometer. Body mass index (BMI) was derived as the weight in kilograms divided by the square of the height in meters (kg/m2).

BMD at the FN and LS were measured using dual energy X-ray absorptiometry on a Lunar Prodigy bone densitometer (GE Healthcare, Madison, WI, USA). BMD T-scores were analyzed using Asian population reference databases, supplied by the manufacturer. The coefficient of variation for BMD for normal participants ranged from 1.3–1.5% and 1.5–2.0% for FN and LS, respectively. FRAX scores with femoral BMD were calculated using an online calculator for each individual in the study (https://www.sheffield.ac.uk/FRAX/tool.aspx?country=9) based on the Thai reference. Clinical data and femoral neck T-score data were input into the Thai FRAX model to obtain the 10-year risk of hip and major osteoporotic fractures [11]. The study’s protocol was approved by the Human Research Ethics Committee of Khon Kaen University (HE581241).

Statistical analysis

Data were mainly analyzed by descriptive statistical methods. Mean and standard deviation (SD), and proportions for continuous and categorical variables were presented, respectively. Based on the femoral neck and lumbar spine T-score data, the prevalence of osteoporosis (T-score ≤ -2.5) was calculated. Based on NOF’s recommendation for osteoporosis treatment, we determine the proportion of individuals who had prior fracture (fragility fracture, i.e., hip, vertebral fracture), osteoporosis at femoral neck and/or lumbar spine, and osteopenic individuals who had a 10-year probability of hip ≥ 3% and/or MOF ≥ 20%. In addition, we determined the proportion of individuals at high risk by using a 10-year probability of MOF ≥ 10% in this study [17]. Comparison of dependent variables between study groups were made using independent t-test or ANOVA as appropriate. The Chi-square analysis was used to compare categorical variables between groups. The odds ratio (OR) with 95% confidence interval (CI) were used to determine the association between osteoporosis at FN/LS and clinical characteristics (fractures and 10-yr probability of hip and MOF). The correlation among variables were analyzed using the Pearson’s correlation. Statistical significance was defined as p-value of <0.05. All statistical analyses were performed using SPSS version 19 (SPSS Inc, Chicago, IL, USA.).

Results

A total of 3,280 participants were recruited in the study. The mean ± SD age and BMI were ~63.6 ± 10.1 years and 23.9 ± 3.9 kg/m2, respectively. A total of 170, 1156, 1103 and 851 patients aged 40 –<50, 50 –<60, 60–70 and >70 years, respectively. The prevalence of osteoporosis is 23.0%, with 12.4% and 18.6% of the participants having osteoporosis (T-score BMD <-2.5) at FN and LS, respectively. Table 1 demonstrates characteristics of participants with and without osteoporosis. Compared with participants without osteoporosis, postmenopausal women with osteoporosis were older and had lower BMI, FN and LS BMD, and higher 10-year probability of hip fracture and major osteoporotic fracture with and without BMD (Table 1).

Table 1. Characteristics of participants with and without osteoporosis.

  All participants Osteoporosis at FN and/or LS Non-Osteoporosis p-value
(N = 3280) (N = 753) (N = 2527)
Age (years) 63.6 ± 10.1 70.6 ± 9.7 61.5 ± 9.2 <0.001
Body Weight (kg) 56.0 ±9.9 49.6 ± 8.5 57.9 ± 9.5 <0.001
Height (cm) 152.9 ± 6.1 150.1 ± 6.4 153.7 ± 5.7 <0.001
Body mass index (kg/m2) 23.9 ± 3.9 22.0 ± 3.5 24.5 ± 3.8 <0.001
FN BMD (g/cm2) 0.769 ± 0.137 0.624 ± 0.094 0.812 ± 0.117 <0.001
LS BMD (g/cm2) 0.966 ± 0.182 0.755 ± 0.114 1.028 ± 0.148 <0.001
10-year probability of hip fracture with BMD 2.52 ± 3.59 6.04 ± 5.34 1.48 ± 1.85 <0.001
10-year probability of major osteoporotic fracture with BMD 7.09 ± 5.47 12.27 ± 7.08 5.54 ± 3.68 <0.001
10-year probability of hip fracture without BMD 2.60 ± 3.36 4.95 ± 0.16 1.90 ± 0.05 <0.001
10-year probability of major osteoporotic fracture without BMD 6.94 ± 5.04 10.24 ± 5.82 5.96 ± 4.33 <0.001
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Abbreviations: BMD: Bone mineral density; FN: Femoral neck; LS: Lumbar spine

Table 2 demonstrates FB and LS BMD and FRAX scores by age group (<60 years, 60–70 years vs >70 years). The prevalence of osteoporosis and hip fracture as well as 10-year probability of hip fracture and MOF with and without BMD increased significantly with age (p<0.001). However, the proportion of participants with a history of all fracture or vertebral fracture did not differ among age groups (Table 2). Correlation analysis revealed that increased age was positively associated with increased 10-year probability of hip fracture (r = 0.50 and 0.573, p<0.001) and MOF (r = 0.573, p<0.001) and was negatively associated with FB and LSBMD (r = -0.522 and -0.318, p<0.001 at FN and LS, respectively).

Table 2. Age-stratified bone mineral density and fracture risk assessment score status.

Age group p-value
<60 (N = 1326) 60–70 (N = 1103) >70 (N = 851) All ages (N = 3280)
FN BMD (g/cm2) 0.839 ± 0.13 0.757 ± 0.11 0.674 ± 0.12 0.769 ± 0.14 <0.001
LS BMD (g/cm2) 1.023 ± 0.16 0.955 ± 0.16 0.890 ± 0.19 0.965 ± 0.18 <0.001
10-year probability of hip fracture with BMD 0.82 ± 1.71 2.47 ± 3.49 5.25 ± 4.17 2.52 ± 3.59 <0.001
10-year probability of major osteoporotic fracture with BMD 3.76 ± 2.97 7.79 ± 5.22 11.36 ± 5.50 7.09 ± 5.47 <0.001
10-year probability of Hip Fracture with BMD ≥3% 61 (4.6%) 275 (24.9%) 579 (68.0%) 915 (27.9%) <0.001
10-year probability of major osteoporotic fracture with BMD ≥10% 44 (3.3%) 233 (21.1%) 446 (52.4%) 723(22%) <0.001
10-year probability of major osteoporotic fracture with BMD ≥20% 7 (0.5%) 33 (3%) 69 (8.1%) 109 (3.3%) <0.001
10-year probability of hip Fracture with BMD ≥3% and/or 10-year probability of major osteoporotic fracture with BMD ≥10% 68 (5.1%) 311 (28.2%) 588 (69.1%) 967 (29.5%) <0.001
10-year probability of hip Fracture with BMD ≥3% and/or 10-year probability of major osteoporotic fracture with BMD ≥20% 61 (4.6%) 275 (24.9%) 579(68.0%) 915 (27.9%) <0.001
Prior fractures (hip and vertebral) 66 (5.0%) 43 (3.9%) 61 (7.2%) 170 (5.2%) 0.005
    Hip fracture 2 (0.2%) 11 (1.1%) 32 (4.1%) 45 (1.6%) <0.001
    Vertebral fracture 64 (4.8%) 32 (2.9%) 29 (3.4%) 125 (3.8%) 0.037
Osteoporosis
    Femoral neck 34 (2.6%) 96 (8.7%) 277 (32.5%) 407 (12.4%) <0.001
    Lumbar spine 106 (8.0%) 206 (18.7%) 298 (35.0%) 610 (18.6%) <0.001
    Femoral neck and/or lumbar spine 122 (9.2%) 236 (21.4%) 395 (46.4%) 753 (23.0%) <0.001
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Abbreviations: BMD: Bone mineral density

Table 3 demonstrates proportion of participants with prior history of fracture and FRAX score status among participants with and without osteoporosis. Compared with participants without osteoporosis, postmenopausal women with osteoporosis had higher likelihood of history of fracture (OR 1.61, 95%CI 1.15–2.24, p<0.05), hip fracture (OR 5.55, 95%CI 3.02–10.20, p<0.001) as well as FRAX scores of hip fracture (≥ 3%) (OR 14.27, 95%CI 11.77–17.30) and/or MOF (≥ 10% or 20%) (OR 13.98, 95%CI 11.53–16.95 for MOF ≥ 10% and OR 14.27, 95%CI 11.77–17.30 for MOF ≥ 20%) (Table 3). However, the likelihood of vertebral fracture was not significantly difference between participants with and without osteoporosis (OR 0.88, 95%CI 0.56–1.36, p = 0.66).

Table 3. History of fracture and 10-year probability of fractures with bone mineral density among participants with and without osteoporosis.

Osteoporosis at FN/LS (N = 753) Non-Osteoporosis (N = 2527) OR (95%CI)
Prior fractures (hip and vertebral) 54 (7.2%) 116 (4.6%) 1.61 (1.15–2.24)**
    Hip fracture 28 (4.2%) 17 (0.8%) 5.55 (3.02–10.20)*
    Vertebral fracture 26 (3.5%) 99 (3.9%) 0.88 (0.56–1.36)
10-yr probability of fractures with BMD
    Hip fracture ≥ 3% 583 (71.4%) 377 (14.9%) 14.27 (11.77–17.30)*
    MOF ≥ 10% 444 (59.0%) 279 (11.0%) 11.58 (9.56–14.02)*
    MOF ≥ 20% 89 (11.8%) 20 (0.8%) 16.80 (10.27–27.49)*
    Hip ≥ 3% and/or MOF ≥ 10% 552 (73.3%) 415 (16.4%) 13.98 (11.53–16.95)*
    Hip ≥ 3% and/or MOF ≥ 20% 538 (71.4%) 377 (14.9%) 14.27 (11.77–17.30)*
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*p <0.001

**p <0.05

Abbreviations: BMD: Bone mineral density; FN: Femoral neck; MOF: Major osteoporotic fracture; LS: Lumbar spine

The proportion of participants with different risks of fractures stratified by age group is shown in Fig 1. A total of 170 (5.2%) participants among all participants had a history of hip and/or vertebral fracture. After excluding these participants with fracture history, 699 (21.3%) had osteoporosis, 355 (10.8%) had osteopenia with high risk of fracture (FRAX score of hip fracture ≥ 3% and/or MOF ≥ 20%), 1192 (36.3%) had osteopenia with low risk of fracture (FRAX score of hip fracture < 3% and MOF < 20%) and 864 (26.3%) had normal BMD. Taken together, a total of 1,224 (37.3%, 95%CI 35.7–39.0%) participants would be eligible for anti-osteoporosis therapy. The proportion of participants who would be eligible for anti-osteoporosis therapy increased significantly with age (15.5% versus 35.5% versus 73.6% for participants aged <60, 60–70 and >70 years, respectively, p <0.001). If the cut-off value of FRAX score for MOF ≥ 10% was used to determine high-risk individuals, 1,253 (38.2%) participants (15.7%, 37.5% and 74.1% for participants aged <60, 60–70 and >70 years, respectively) would be eligible for anti-osteoporosis therapy.

Fig 1. Proportion of participants with different fracture risks by age group.

Fig 1

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Osteoporosis and osteopenia were defined as T-score <-2.5 and T-score -1 –-2.5 for LS or FN. BMD, respectively. Osteopenia with high risk of fracture was defined as participants with osteopenia and 10-year probability of hip fractures with BMD ≥ 3% and/or MOF with BMD ≥ 20%. Osteopenia with low risk of fracture was defined as participants with osteopenia and 10-year probability of hip fractures with BMD < 3% and MOF with BMD < 20%. Participants who would be eligible for anti-osteoporosis therapy included those with hip/vertebral fracture, osteoporosis and osteopenia with high risk of fracture. (37.3% for all participants; 15.5% for participants aged <60; 35.5% for participants aged 60–70 years; and 73. 6% for participants aged >70 years). Note that proportions of participants with osteoporosis, osteopenia with high risk of fracture, osteopenia with low risk of fracture and normal bone mineral density were calculated after excluding participants with hip/vertebral fracture. Abbreviations: BMD: Bone mineral density; FN: Femoral neck; LS: Lumbar spine; MOF: Major osteoporotic fracture.

Discussion

The current study is the largest study in Thailand aiming to determine the proportion of individuals who were eligible for osteoporotic therapy among 3,280 postmenopausal women aged 40–90 years old who were eligible for BMD measurement for osteoporosis screening. We found that 1224 (37.3%) of the 3280 participants (95%CI 35.7–39.0%) would be eligible for anti-osteoporosis therapy based on the NOF criteria. Among them, 170 were eligible based on the presence of history of fracture, 699 participants without fracture were eligible as they had osteoporosis and the rest 355 participants with osteopenia were eligible because they had 10-year probability of hip fracture >3% or MOF >20%. As expected, the proportion of participants who would be eligible for anti-osteoporosis therapy increased significantly with age from 15.5% among participants aged <60 years to 73.6% among participants aged >70 years.

This study may have clinical and public health implications as it provides age-stratified estimation of proportion of individuals who would be eligible for anti-osteoporotic therapy. The result will be a reference to help inform care gap in identification and treatment of individuals with high risk of fragility fracture in general population. In fact, the prevalence of individuals who met treatment threshold based on FRAX score has been reported in the US population. However, such data in the Asian populations are relatively limited. Based on the US population-based Framingham study in 1,946 women, the proportion of women who met treatment criteria based on the 2008 NOF guideline was 41.1%. Concurrent with our observation, the proportion was much less among women aged <65 years (8.3%) compared with women aged >75 years (86.0%) [14]. An analysis of the National Health and Nutrition Examination Survey III of 1,754 women aged >50 years revealed that 37.4% met the 2008 NOF treatment threshold, and the proportion increased with age from 17.0% among those aged 50–59 years to 87.5% among those aged >80 years [15]. In Southeast Asia, a Vietnamese study in 1,421 women and 652 men aged 50 years or older, using the Thai version of FRAX, revealed that 49% of women and 35% of men would be eligible for osteoporotic therapy based on the NOF criteria [16].

While the NOF guideline has determined treatment threshold among patients with osteopenia as having a FRAX 10-year risk of at least 3% for hip fracture or at least 20% for MOF [3], the treatment threshold differs among different national guidelines given varying optimal cut-off values of FRAX based on local data [17]. In Thailand, a retrospective study conducted between 2008 and 2010 revealed that the original FRAX model with thresholds of ≥20% and ≥3% for MOF and hip fracture had moderate and low accuracy in predicting 10-year risk of MOF (73% sensitivity, 63% specificity) and hip fracture (62% sensitivity, 60% specificity), respectively [18, 19]. A subsequent study in 2,872 postmenopausal Thai women used the receiver operating characteristic curve revealed the optimal FRAX thresholds for hip fracture with BMD was 4% (82.2% sensitivity, 78.6% specificity), and the optimal FRAX thresholds for MOF with BMD was 8.9% (87% sensitivity, 71% specificity) [20]. Given such data, we performed additional analysis in our cohort by lowering the FRAX cut-off value for MOF to 10%, which identified additional 29 patients (0.9%) who met treatment threshold.

It is of particular interest that there was no difference in the likelihood of vertebral fracture between participants with and without osteoporosis based on BMD criteria. One of the potential explanations is that presence of vertebral fracture can result in false elevation of measured LS BMD, which may have occurred in participants with vertebral fractures who were classified as not having osteoporosis.

The major strength of our study is the large sample size of 3,280 participants. This is also the first study to determine the prevalence of osteoporosis in postmenopausal women using both BMD T-score and Thai FRAX score criteria that represents the real-world practice. However, there are some limitations that should be acknowledged. First, data on vertebral fracture were obtained by self-report, which may have jeopardized the accuracy of ascertainment of history of fragility fracture. Secondly, most of participants in this study are from Northeastern region of Thailand, which may not represent the whole Thai population. Finally, we also lack the data on the proportion of treated patients and treatment outcome, which requires further studies.

In conclusion, the prevalence of osteoporosis in Thai postmenopausal women was 23.0%. A total of 37.3% would be eligible for anti-osteoporosis therapy based on the NOF criteria. The proportion increased significantly with age from 15.5% among participants aged <60 years to 73.6% among participants aged >70 years.

Supporting information

S1 Dataset

(XLSX)

Click here for additional data file. (646.5KB, xlsx)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Kanis JA, Oden A, Johnell O, Jonsson B, de Laet C, Dawson A. The Burden of Osteoporotic Fractures: A Method for Setting Intervention Thresholds. Osteoporosis International. 2001;12(5):417–27. doi: 10.1007/s001980170112 [DOI] [PubMed] [Google Scholar]
  • 2.Cooper C, Atkinson EJ, Jacobsen SJ, O’Fallon WM, Melton LJ, III. Population-Based Study of Survival after Osteoporotic Fractures. American Journal of Epidemiology. 1993;137(9):1001–5. [DOI] [PubMed] [Google Scholar]
  • 3.Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S, et al. Clinician’s Guide to Prevention and Treatment of Osteoporosis. Osteoporos Int. 2014;25(10):2359–81. doi: 10.1007/s00198-014-2794-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Harvey N, Dennison E, Cooper C. Osteoporosis: impact on health and economics. Nature Reviews Rheumatology. 2010;6(2):99–105. doi: 10.1038/nrrheum.2009.260 [DOI] [PubMed] [Google Scholar]
  • 5.Schnell S, Friedman SM, Mendelson DA, Bingham KW, Kates SL. The 1-year mortality of patients treated in a hip fracture program for elders. Geriatr Orthop Surg Rehabil. 2010;1(1):6–14. doi: 10.1177/2151458510378105 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Eastell R, Rosen CJ, Black DM, Cheung AM, Murad MH, Shoback D. Pharmacological Management of Osteoporosis in Postmenopausal Women: An Endocrine Society* Clinical Practice Guideline. The Journal of Clinical Endocrinology & Metabolism. 2019;104(5):1595–622. [DOI] [PubMed] [Google Scholar]
  • 7.Johansson H, Siggeirsdóttir K, Harvey NC, Odén A, Gudnason V, McCloskey E, et al. Imminent risk of fracture after fracture. Osteoporos Int. 2017;28(3):775–80. doi: 10.1007/s00198-016-3868-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Salari N, Darvishi N, Bartina Y, Larti M, Kiaei A, Hemmati M, et al. Global prevalence of osteoporosis among the world older adults: a comprehensive systematic review and meta-analysis. Journal of Orthopaedic Surgery and Research. 2021;16(1):669. doi: 10.1186/s13018-021-02821-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Christensen K, Doblhammer G, Rau R, Vaupel JW. Ageing populations: the challenges ahead. Lancet. 2009;374(9696):1196–208. doi: 10.1016/S0140-6736(09)61460-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Kanis JA, Johnell O, Oden A, Johansson H, McCloskey E. FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int. 2008;19(4):385–97. doi: 10.1007/s00198-007-0543-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Chotiyarnwong P, Harvey NC, Johansson H, Liu E, Lorentzen M, Kanis JA, et al. Temporal changes in access to FRAX® in Thailand between 2010 and 2018. Arch Osteoporos. 2019;14(1):66–. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Lesnyak O, Zakroyeva A, Babalyan V, Cazac V, Gabdulina G, Ismailov S, et al. FRAX-based intervention thresholds in eight Eurasian countries: Armenia, Belarus, Georgia, Kazakhstan, the Kyrgyz Republic, Moldova, the Russian Federation, and Uzbekistan. Arch Osteoporos. 2021;16(1):87. doi: 10.1007/s11657-021-00962-1 [DOI] [PubMed] [Google Scholar]
  • 13.Lekamwasam S. The diversity of Fracture Risk Assessment Tool (FRAX)-based intervention thresholds in Asia. Osteoporos Sarcopenia. 2019;5(4):104–8. doi: 10.1016/j.afos.2019.12.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Berry SD, Kiel DP, Donaldson MG, Cummings SR, Kanis JA, Johansson H, et al. Application of the National Osteoporosis Foundation Guidelines to postmenopausal women and men: the Framingham Osteoporosis Study. Osteoporos Int. 2010;21(1):53–60. doi: 10.1007/s00198-009-1127-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Dawson-Hughes B, Looker AC, Tosteson ANA, Johansson H, Kanis JA, Melton LJ. The potential impact of new National Osteoporosis Foundation guidance on treatment patterns. Osteoporosis International. 2010;21(1):41–52. doi: 10.1007/s00198-009-1034-7 [DOI] [PubMed] [Google Scholar]
  • 16.Hoang DK, Doan MC, Mai LD, Ho-Le TP, Ho-Pham LT. Burden of osteoporosis in Vietnam: An analysis of population risk. PLOS ONE. 2021;16(6):e0252592. doi: 10.1371/journal.pone.0252592 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Kanis JA, Harvey NC, Cooper C, Johansson H, Odén A, McCloskey EV, et al. A systematic review of intervention thresholds based on FRAX: A report prepared for the National Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos. 2016;11(1):25–. doi: 10.1007/s11657-016-0278-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Sangkomkamhang T, Sangkomkamhang US. Accuracy of application of who fracture risk assessment (FRAX™) for prediction hio fracture in Khon Kaen hospital Thailand. Osteoporosis International. 2012;23:S332. [Google Scholar]
  • 19.Sangkomkamhang US, Sangkomkamhang T. Prediction of fragility fracture with the FRAX tool in postmenopausal woman in Thailand. Osteoporosis International. 2012;23:S333–S4. [Google Scholar]
  • 20.Sribenjalak D, Charoensri S, Pongchaiyakul C. An optimal intervention threshold of FRAX in postmenopausal Thai women. Arch Osteoporos. 2022;17(1):21. doi: 10.1007/s11657-022-01058-0 [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Maria Elisabeth Johanna Zalm

5 Sep 2022

PONE-D-22-14831The proportion of Thai postmenopausal women who would be eligible for anti-osteoporosis therapyPLOS ONE

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The strength of study is large sample size. The manuscript is overall well written and informative. The study was properly designed and executed. The finding can help inform treatment guidelines in Thailand. However, there are some issues that I would like to invite the authors to comment on.

1. Please clarify the define of postmenopausal in this study? How many women aged 40-50 were there? Did all of them have natural or premature/induced menopause?

2. In the methods, please describe more details about prior fractures (trauma or non-trauma)?

3. The point estimate of the proportion of Thai menopausal women who would be eligible for treatment was given (37.3%). Please provide the related confidence intervals, quantifying the potential uncertainty of the finding which would make the interpretation stronger and more convincingly.

4. The authors defined “high-risk osteopenia” (as participants with osteopenia and 10-year probability of hip fractures with BMD ≥ 3% and/or MOF with BMD ≥ 20%.), but I think the term “high risk of fracture” is more appropriate.

5. Please discuss more about the likelihood of vertebral fracture was not significantly difference between participants with and without osteoporosis

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Reviewer #1: Yes: Lan T. Ho-Pham

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Decision Letter 1

Inge Roggen

15 Dec 2022

The proportion of Thai postmenopausal women who would be eligible for anti-osteoporosis therapy

PONE-D-22-14831R1

Dear Dr. Charoenngam,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Inge Roggen, M.D., Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have addressed all the issues raised. I do not have any more questions. The manuscript now is suitable to PLOS ONE.

Reviewer #2: Piyachat Chanidkul et al have done a study looking at the proportion of postmenopausal Thai women eligible for treatment for osteoporosis.

Strengths: it is a large study of 3280 women and the study is well described.

Weaknesses:

1 Using Pubmed and Scholar I found many papers about ostoporosis in Asian women and as such this paper does not contain new information.

2 The authors have just used the NOF criteria to identify women eligible for therapy. There are many studies already published with similar outcomes.

3 The authors should have used multi-regression analysis to analyze the relationship between variables.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Lan T. Ho-Pham

Reviewer #2: No

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Acceptance letter

Inge Roggen

25 Jan 2023

PONE-D-22-14831R1

The proportion of Thai postmenopausal women who would be eligible for anti-osteoporosis therapy

Dear Dr. Charoenngam:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Inge Roggen

Academic Editor

PLOS ONE

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