Bone Radiomics Score Derived From DXA Hip Images Enhances Hip Fracture Prediction in Older Women

Hong, Namki; Park, Heajeong; Kim, Chang Oh; Kim, Hyeon Chang; Choi, Jin Young; Kim, Hwiyoung; Rhee, Yumie

doi:10.1002/jbmr.4342

Cited by 27 publications

(16 citation statements)

References 34 publications

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“… 35–37 Bone radiomic score has been used as a predictor of hip fracture in older women. 38 This might provide backing for our results.…”

Section: Discussionsupporting

confidence: 61%

Prediction Models for Prognosis of Femoral Neck–Fracture Patients 6 Months after Total Hip Arthroplasty

Zheng¹,

Xiao²,

Xie³

et al. 2022

IJGM

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Purpose To establish prediction models for 6-month prognosis in femoral neck–fracture patients receiving total hip arthroplasty (THA). Patients and Methods In total, 182 computed tomography image pairs from 85 patients were collected and divided into a training set (n=127) and testing set (n=55). Least absolute shrinkage–selection operator regression was used for selecting optimal predictors. A random-forest algorithm was used to establish the prediction models, which were evaluated for accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC). Results The best model in this study was constructed based on demographic data, preoperative laboratory indicators, and three preoperative radiomic features. In the random-forest model, activated partial thromboplastin time, a preoperative radiomic feature (maximum diameter), and fibrinogen were important variables correlating with patient outcomes. The AUC, sensitivity, specificity, PPV, NPV, and accuracy in the training set were 0.986 (95% CI 0.971–1), 0.925 (95% CI 0.862–0.988), 0.983 (95% CI 0.951–1.016), 0.984 (95% CI 0.953–1.014), 0.922 (95% CI 0.856–0.988), and 0.953 (95% CI 0.916–0.990), respectively. The AUC, sensitivity, specificity, PPV, NPV, and accuracy in the testing set were 0.949 (95% CI 0.885–1), 0.767 (95% CI 0.615–0.918), 1 (95% CI 1–1), 1 (95% CI 1–1), 0.781 (95% CI 0.638–0.924), and 0.873 (95% CI 0.785–0.961), respectively. Conclusion The model based on demographic, preoperative clinical, and preoperative radiomic data showed the best predictive ability for 6-month prognosis in the femoral neck–fracture patients receiving THA.

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“… 35–37 Bone radiomic score has been used as a predictor of hip fracture in older women. 38 This might provide backing for our results.…”

Section: Discussionsupporting

confidence: 61%

Prediction Models for Prognosis of Femoral Neck–Fracture Patients 6 Months after Total Hip Arthroplasty

Zheng¹,

Xiao²,

Xie³

et al. 2022

IJGM

View full text Add to dashboard Cite

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“…As a standard method for diagnosing OP ( 6 ), dual-energy X-ray absorptiometry (DXA) cannot detect the pathological process of OP; these changes can only be displayed on DXA for many years. Some bone turnovers are now also used in the diagnosis and drug efficacy evaluation of patients with OP.…”

Section: Introductionmentioning

confidence: 99%

Discovery of Potential Biomarkers for Postmenopausal Osteoporosis Based on Untargeted GC/LC-MS

Kou

He²,

Chen³

et al. 2022

Front. Endocrinol.

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PurposeAs an important public health problem, osteoporosis (OP) in China is also in an upward trend year by year. As a standard method for diagnosing OP, dual-energy X-ray absorptiometry (DXA) cannot analyze the pathological process but only see the results. It is difficult to evaluate the early diagnosis of OP. Our study was carried out through a serum metabolomic study of OP in Chinese postmenopausal women on untargeted gas chromatography (GC)/liquid chromatography (LC)–mass spectrometry (MS) to find possible diagnostic markers.Materials and Methods50 Chinese postmenopausal women with osteoporosis and 50 age-matched women were selected as normal controls. We first used untargeted GC/LC-MS to analyze the serum of these participants and then combined it with a large number of multivariate statistical analyses to analyze the data. Finally, based on a multidimensional analysis of the metabolites, the most critical metabolites were considered to be biomarkers of OP in postmenopausal women. Further, biomarkers identified relevant metabolic pathways, followed by a map of metabolic pathways found in the database.ResultsWe found that there may be metabolic pathway disorders like glucose metabolism, lipid metabolism, and amino acid metabolism in postmenopausal women with OP. 18 differential metabolites are considered to be potential biomarkers of OP in postmenopausal women which are a major factor in metabolism and bone physiological function.ConclusionThese findings can be applied to clinical work through further validation studies. It also shows that metabonomic analysis has great potential in the application of early diagnosis and recurrence monitoring in postmenopausal OP women.

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“…The clinical prediction of osteoporosis risk mainly relies on bone mineral density detection and bone transformation markers [ 4 , 5 ], but there is still a lack of relatively effective serological indicators that can predict the risk of OVCFs. In this regard, it is worth mention that the circumstances and organization of the existing health care system may limit us to focus on the value of the serum calcium and phosphorus level variables in the prediction of OVCFs.…”

Section: Introductionmentioning

confidence: 99%

Serum calcium–phosphorus product for predicting the risk of osteoporotic vertebral compression fractures in elderly patients: a retrospective observational study

Ying

Jiang

et al. 2022

J Orthop Surg Res

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Background This study retrospectively analyzed and evaluated the potential correlations of serum calcium, serum phosphorus, and calcium-phosphorus product (Ca–P product) with the incidence of osteoporotic vertebral compression fractures (OVCFs), with the aim of exploring whether the Ca–P product can be used as a serological indicator to predict the risk of OVCFs. Methods This study randomly enrolled 400 elderly patients in our hospital with OVCFs and 400 patients with hip and knee arthroplasty due to femoral head necrosis or osteoarthritis from August 2013 to April 2021. Age, sex, past medical history, and admission biochemical indicators, including albumin, blood urea nitrogen, serum creatinine, serum calcium and serum phosphorus, were collected for statistical analysis. Results Albumin, serum calcium, serum phosphorus, Ca–P product, corrected serum calcium and corrected Ca–P product were lower in the OVCF group than in the non-OVCF group (P < 0.05). Multivariate logistic regression analysis showed that low values of serum calcium, serum phosphorus, Ca–P product, corrected blood calcium, and corrected Ca–P product can all be risk factors for OVCF. The ROC curve showed that the Ca–P product and corrected Ca–P product were effective in predicting the risk of OVCFs. The predictive value of the Ca–P product was the best; the cutoff point was 29.88, the sensitivity was 0.72 and the specificity was 0.62. The cutoff point of the corrected Ca–P product was 30.50, the sensitivity was 0.74, and the specificity was 0.62. Conclusion The Ca–P product and corrected Ca–P product can be used as serological indicators to predict the risk of OVCFs in elderly individuals. Early clinical interventions targeting this risk factor can further reduce the risk of OVCFs. Also, timely and regular testing of the serum calcium and phosphorus level is recommended and encouraged for this group of people.

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Bone Radiomics Score Derived From DXA Hip Images Enhances Hip Fracture Prediction in Older Women

Cited by 27 publications

References 34 publications

Prediction Models for Prognosis of Femoral Neck–Fracture Patients 6 Months after Total Hip Arthroplasty

Prediction Models for Prognosis of Femoral Neck–Fracture Patients 6 Months after Total Hip Arthroplasty

Discovery of Potential Biomarkers for Postmenopausal Osteoporosis Based on Untargeted GC/LC-MS

Serum calcium–phosphorus product for predicting the risk of osteoporotic vertebral compression fractures in elderly patients: a retrospective observational study

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