Assessing fracture risk using gradient boosting machine (GBM) models

Journal of Bone and Mineral Research

Volumn 27, Issue 6, 2012, Pages 1397-1404

  Atkinson, Elizabeth J ^a   Therneau, Terry M ^a   Melton III, L Joseph ^a   Camp, Jon J ^a   Achenbach, Sara J ^a   Amin, Shreyasee ^a   Khosla, Sundeep ^a  

^a MAYO CLINIC   (United States)

Author keywords

BONE DENSITY; BONE QUALITY; DISTAL FOREARM FRACTURE; GRADIENT BOOSTING; QCT; VERTEBRAL FRACTURE

Indexed keywords

ADULT; ARTICLE; BONE DENSITY; BONE STRENGTH; BONE STRUCTURE; COHORT ANALYSIS; CONTROLLED STUDY; EXPERIMENTAL MODEL; FEMALE; FOREARM FRACTURE; GRADIENT BOOSTING MACHINE MODEL; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; PARAMETRIC TEST; POSTMENOPAUSE; PREDICTION; RECEIVER OPERATING CHARACTERISTIC; RISK; VERTEBRA FRACTURE; VERTEBRA MALFORMATION; AREA UNDER THE CURVE; DIAGNOSTIC IMAGING; FOREARM INJURY; FRACTURE; PATHOPHYSIOLOGY; PROBABILITY; RISK ASSESSMENT; SPINE FRACTURE; THEORETICAL MODEL; X-RAY COMPUTED TOMOGRAPHY;

AREA UNDER CURVE; BONE DENSITY; FEMALE; FOREARM INJURIES; FRACTURES, BONE; HUMANS; MACHINE LEARNING; MODELS, THEORETICAL; PROBABILITY; RISK ASSESSMENT; SPINAL FRACTURES; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84859440161     PISSN: 08840431     EISSN: 15234681     Source Type: Journal    
DOI: 10.1002/jbmr.1577     Document Type: Article

References (35)

1. Genant HK, Jiang Y., Advanced imaging assessment of bone quality. Ann N Y Acad Sci. 2006; 1068: 410-28.
2. van Lenthe GH, Müller R., CT-based visualization and quantification of bone microstructure in vivo. IBMS BoneKEy. 2006; 5: 410-25.
3. Boutroy S, Bouxsein ML, Munoz F, Delmas PD., In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab. 2005; 90 (12): 6508-15.
4. Melton LJ 3rd, Riggs BL, van Lenthe GH, Achenbach SJ, Müller R, Bouxsein ML, Amin S, Atkinson EJ, Khosla S., Contribution of in vivo structural measurements and load/strength ratios to the determination of forearm fracture risk in postmenopausal women. J Bone Miner Res. 2007; 22 (9): 1442-8.
5. Melton LJ 3rd, Riggs BL, Keaveny TM, Achenbach SJ, Hoffmann PF, Camp JJ, Rouleau PA, Bouxsein ML, Amin S, Atkinson EJ, Robb RA, Khosla S., Structural determinants of vertebral fracture risk. J Bone Miner Res. 2007; 22 (12): 1885-92.
6. Sornay-Rendu E, Boutroy S, Munoz F, Delmas P., Alterations of cortical and trabecular architecture are associated with fractures in postmenopausal women, partially independent of decreased BMD measured by DXA: the OFELY Study. J Bone Miner Res. 2007; 22 (3): 425-33.
7. Boutroy S, Van Rietbergen B, Sornay-Rendu E, Munoz F, Bouxsein ML, Delmas PD., Finite element analysis based on in vivo HR-pQCT images of the distal radius is associated with wrist fracture in postmenopausal women. J Bone Miner Res. 2008; 23 (3): 392-9.
8. Vico L, Zouch M, Amirouche A, Frere D, Laroche N, Koller B, Laib A, Thomas T, Alexandre C., High-resolution pQCT analysis at the distal radius and tibia discriminates patients with recent wrist and femoral neck fractures. J Bone Miner Res. 2008; 23 (11): 1741-50.
9. Radspieler H, Frieling I, Dambacher MA, Neff M., In vivo assessment of 3-dimensional bone micro architecture with HR-pQCT in patients with and without fractures. J Bone Miner Res. 2008; 23: S310.
10. Ladinsky GA, Vasilic B, Popescu AM, Wald M, Zemel BS, Snyder PJ, Loh L, Song HK, Saha PK, Wright AC, Wehrli FW., Trabecular structure quantified with the MRI-based virtual bone biopsy in postmenopausal women contributes to vertebral deformity burden independent of areal vertebral BMD. J Bone Miner Res. 2008; 23 (1): 64-74.
11. Sornay-Rendu E, Cabrera-Bravo J-L, Boutroy S, Munoz F, Delmas PD., Severity of vertebral fractures is associated with alterations of cortical architecture in postmenopausal women. J Bone Miner Res. 2009; 24: 737-43.
12. Hastie T, Tibshirani R, Friedman J., The elements of statistical learning, data mining, inference, and prediction springer series in statistics. 2nd ed. New York: Springer; 2009.
13. Melton LJ 3rd, Christen D, Riggs BL, Achenbach SJ, Muller R, van Lenthe GH, Amin S, Atkinson EJ, Khosla S., Assessing forearm fracture risk in postmenopausal women. Osteoporos Int. 2010; 21 (7): 1161-9.
14. Melton LJ 3rd, Riggs BL, Keaveny TM, Achenbach SJ, Kopperdahl D, Camp JJ, Rouleau PA, Amin S, Atkinson EJ, Robb RA, Therneau TM, Khosla S., Relation of vertebral fractures to bone density, structure and strength. J Bone Miner Res. 2010; 25: 1922-30.
15. Genant HK, Jergas M., Assessment of prevalent and incident vertebral fractures in osteoporosis research. Osteoporosis Int. 2003; 14 (Suppl 3): S43-55.
16. Seeman E, Delmas PD., Bone quality-the material and structural basis of bone strength and fragility. N Engl J Med. 2006; 354 (21): 2250-61.
17. ISCD. Official Positions of the International Society for Clinical Densitometry, updated 2007. Available from
18. Kanis JA, Melton LJ III, Christiansen C, Johnston CC, Khaltaev N., The diagnosis of osteoporosis. J Bone Miner Res. 1994; 9 (8): 1137-41.
19. Silva MJ, Wang C, Keaveny TM, Hayes WC., Direct and computed tomography thickness measurements of the human, lumbar vertebral shell and endplate. Bone. 1994; 15 (4): 409-14.
20. Prevrhal S, Fox JC, Shepherd JA, Genant HK., Accuracy of CT-based thickness measurement of thin structures: modeling of limited spatial resolution in all three dimensions. Med Phys. 2003; 30 (1): 1-8.
21. Kirmani S, Christen D, van Lenthe GH, Fischer PR, Bouxsein ML, McCready LK, Melton LJ 3rd, Riggs BL, Amin S, Müller R, Khosla S., Bone structure at the distal radius during adolescent growth. J Bone Miner Res. 2009; 24 (6): 1033-42.
22. Laib A, Hauselmann HJ, Ruegsegger P., In vivo high resolution 3D-QCT of the human forearm. Technol Health Care. 1998; 6 (5-6): 329-37.
23. Parfitt AM, Drezner MK, Glorieux FH, Kanis JA, Malluche H, Meunier PJ, Ott SM, Recker RR., Bone histomorphometry: standardization of nomenclature, symbols, and units. Report of the ASBMR Histomorphometry Nomenclature Committee. J Bone Miner Res. 1987; 2 (6): 595-610.
24. Laib A, Newitt DC, Lu Y, Majumdar S., New model-independent measures of trabecular bone structure applied to in vivo high-resolution MR images. Osteoporos Int. 2002; 13 (2): 130-6.
25. Laib A, Ruegsegger P., Calibration of trabecular bone structure measurements of in vivo three-dimensional peripheral quantitative computed tomography with 28-mm-resolution microcomputed tomography. Bone. 1999; 24 (1): 35-9.
26. MacNeil JA, Boyd SK., Accuracy of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys. 2007; 29 (10): 1096-105.
27. Ridgeway G., Generalized Boosted Regression Models. CRAN; 2007.
28. DeLong ER, DeLong DM, Clarke-Pearson DL., Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988; 44 (3): 837-45.
29. Schapire RE., The strength of weak learnability. Machine Learn. 1990; 5 (2): 197-227.
30. Friedman JH., Greedy function approximation: a gradient boosting machines. IMS. 1999 Reitz Lecture.
31. Friedman JH., Stochastic gradient boosting. Comput Stat Data Anal. 2002; 38 (4): 367-78.
32. Friedman JH, Meulman JJ., Multiple additive regression trees with application in epidemiology. Stat Med. 2003; 22 (9): 1365-81.
33. Elith J, Leathwick JR, Hastie T., A working guide to boosted regression trees. J Anim Ecol. 2008; 77: 802-13.
34. Hjort J, Marmion M., Periglacial distribution modelling with a boosting method. Permafrost Periglacial Process. 2008; 20 (1): 15-25.
35. Jalabert SSM, Martin MP, Renaud JP, Boulonne L, Jolivet C, Montanarella L, Arrouays D., Estimating forest soil bulk density using boosted regression modelling. Soil Use Manage. 2010; 26 (4): 516-28.