Discriminative Ability of Heel Quantitative Ultrasound in Postmenopausal Women With Prevalent Low-Trauma Fractures: Application of Optimal Threshold Cutoff Values Using CART Models

Navarro, Marlene Isabel Hernández; Saavedra, Pedro; Gómez-de-Tejada, María Jesús; Suárez, Mercedes López; Hernández, Daniel; Sosa, Manuel

doi:10.1016/j.jocd.2011.06.008

Cited by 6 publications

(4 citation statements)

References 26 publications

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“…The sensitivity, specificity and AUC of salivary calcium in this study were similar to those of the QUS test (sensitivity 68, specificity 70 and AUC 0.72%). Nevertheless, sensitivity, specificity and AUC of digital X‐ray radiogrammetry (DXR) and radiographic absorptiometry (RA) were higher than the corresponding values for salivary calcium …”

Section: Discussionmentioning

confidence: 99%

Salivary calcium concentration as a screening tool for postmenopausal osteoporosis

et al. 2012

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Section: Discussionmentioning

confidence: 99%

Salivary calcium concentration as a screening tool for postmenopausal osteoporosis

et al. 2012

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“…Integrated information obtained by QUS can represent a reasonable alternative because bone structural quality may conflict with measurement of BMD which only detects bone density. 16 , 37…”

Section: Discussionmentioning

confidence: 99%

“… 13 , 14 Taken together, these findings suggest that QUS, unlike BMD, could possibly evaluate bone quality, especially microarchitecture, and therefore be useful for assessing fracture risk. 15 Most studies aimed to evaluate the role of the heel QUS in osteoporosis diagnosis were performed in elderly osteoporotic woman 16 ; other studies have considered populations characterized mainly by poor bone quality. 17 , 18 …”

Section: Introductionmentioning

confidence: 99%

Comparison between the gold standard DXA with calcaneal quantitative ultrasound based-strategy (QUS) to detect osteoporosis in an HIV infected cohort

Quiros-Roldan

Brianese

Raffetti

et al. 2017

The Brazilian Journal of Infectious Diseases

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We observed that patients with osteoporosis determined by calcaneal quantitative ultrasound and/or dual-energy X-ray absorptiometry have higher probability to undergo vertebral fracture, but neither of them can be used for predicting vertebral fracture. Use of calcaneal quantitative ultrasound for screening is a reasonable alternative of dual-energy X-ray absorptiometry since our study confirm that none strategy is clearly superior, but both screen tools must be always completed with X-ray.

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“…Particularly, in this study, CAR as a composite indicator has a multicollinearity relationship with CRP and albumin, which may lead to the wrong identification of relevant predictors in regression analysis 14 Classification and regression tree (CART), as a data mining technique, is ideally suitable for the generation of clinical rules, which often enables the detection of complex interactions between predictors (including predictors with multicollinearity), which may be difficult or impossible to uncover using traditional statistical techniques 15 CART has been shown to perform as well or better than other traditional statistical techniques, such as logistic regression analysis, and is increasingly being applied to diagnose disease and predict outcomes or complications in patients, including diabetes, trauma, and cancer. [16][17][18][19] To the best of our knowledge, CART analysis has not previously been used to assess the predictors of AL in patients after esophagectomy.…”

Section: Introductionmentioning

confidence: 99%

C‐reactive protein to albumin ratio is a key indicator in a predictive model for anastomosis leakage after esophagectomy: Application of classification and regression tree analysis

Shao

Liu

et al. 2019

Thoracic Cancer

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Background Anastomotic leakage (AL), a serious complication after esophagectomy, might impair patient quality of life, prolong hospital stay, and even lead to surgery‐related death. The aim of this study was to show a novel decision model based on classification and regression tree (CART) analysis for the prediction of postoperative AL among patients who have undergone esophagectomy. Methods A total of 450 patients (training set: 356; test set: 94) with perioperative information were included. A decision tree model was established to identify the predictors of AL in the training set, which was validated in the test set. A receiver operating characteristic curve was also created to illustrate the diagnostic ability of the decision model. Results A total of 12.2% (55/450) of the 450 patients suffered AL, which was diagnosed at median postoperative day 7 (range: 6–16). The decision tree model, containing surgical duration, postoperative lymphocyte count, and postoperative C‐reactive protein to albumin ratio, was established by CART analysis. Among the three variables, the postoperative C‐reactive protein to albumin ratio was identified as the most important indicator in the CART model with normalized importance of 100%. According to the results validated in the test set, the sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy of the prediction model were 80%, 98.8%, 88.9%, 97.6%, and 96.8%, respectively. Moreover, the area under the receiver operating characteristic curve was 0.95. Conclusion The decision model based on CART analysis presented good performance for predicting AL, and might allow the early identification of patients at high risk.

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Discriminative Ability of Heel Quantitative Ultrasound in Postmenopausal Women With Prevalent Low-Trauma Fractures: Application of Optimal Threshold Cutoff Values Using CART Models

Cited by 6 publications

References 26 publications

Salivary calcium concentration as a screening tool for postmenopausal osteoporosis

Salivary calcium concentration as a screening tool for postmenopausal osteoporosis

Comparison between the gold standard DXA with calcaneal quantitative ultrasound based-strategy (QUS) to detect osteoporosis in an HIV infected cohort

C‐reactive protein to albumin ratio is a key indicator in a predictive model for anastomosis leakage after esophagectomy: Application of classification and regression tree analysis

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