Development and validation of a one year predictive model for secondary fractures in osteoporosis.
The number of osteoporosis-related fractures in the United States is no longer declining. Existing risk-based assessment tools focus on long-term risk. Payers and prescribers need additional tools to identify patients at risk for imminent fracture. We developed and validated a predictive model for s...
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2021
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oai:doaj.org-article:9aba1236bef648df96814e34f46eb2ff2021-12-02T20:06:09ZDevelopment and validation of a one year predictive model for secondary fractures in osteoporosis.1932-620310.1371/journal.pone.0257246https://doaj.org/article/9aba1236bef648df96814e34f46eb2ff2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257246https://doaj.org/toc/1932-6203The number of osteoporosis-related fractures in the United States is no longer declining. Existing risk-based assessment tools focus on long-term risk. Payers and prescribers need additional tools to identify patients at risk for imminent fracture. We developed and validated a predictive model for secondary osteoporosis fractures in the year following an index fracture using administrative medical and pharmacy claims from the Optum Research Database and Symphony Health, PatientSource. Patients ≥50 years with a case-qualifying fracture identified using a validated claims-based algorithm were included. Logistic regression models were created with binary outcome of a second fracture versus no second fracture within a year of index fracture, with the goal of predicting second fracture occurrence. In the Optum Research Database, 197,104 patients were identified with a case-qualifying fracture (43% commercial, 57% Medicare Advantage). Using Symphony data, 1,852,818 met the inclusion/exclusion criteria. Average patient age was 70.09 (SD = 11.09) and 71.28 (SD = 14.24) years in the Optum Research Database and Symphony data, respectively. With the exception of history of falls (41.26% vs 18.74%) and opioid use (62.80% vs 46.78%), which were both higher in the Optum Research Database, the two populations were mostly comparable. A history of falls and steroid use, which were previously associated with increased fracture risk, continue to play an important role in secondary fractures. Conditions associated with bone health (liver disease), or those requiring medications that impact bone health (respiratory disease), and cardiovascular disease and stroke-which may share etiology or risk factors with osteoporosis fractures-were also predictors of imminent fractures. The model highlights the importance of assessment of patient characteristics beyond bone density, including patient comorbidities and concomitant medications associated with increased fall and fracture risk, in alignment with recently issued clinical guidelines for osteoporosis treatment.Setareh A WilliamsSusan L GreenspanTim BancroftBenjamin J ChastekYamei WangRichard J WeissNick PyrihHily NicholsJane A CauleyPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257246 (2021) |
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DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Setareh A Williams Susan L Greenspan Tim Bancroft Benjamin J Chastek Yamei Wang Richard J Weiss Nick Pyrih Hily Nichols Jane A Cauley Development and validation of a one year predictive model for secondary fractures in osteoporosis. |
| description |
The number of osteoporosis-related fractures in the United States is no longer declining. Existing risk-based assessment tools focus on long-term risk. Payers and prescribers need additional tools to identify patients at risk for imminent fracture. We developed and validated a predictive model for secondary osteoporosis fractures in the year following an index fracture using administrative medical and pharmacy claims from the Optum Research Database and Symphony Health, PatientSource. Patients ≥50 years with a case-qualifying fracture identified using a validated claims-based algorithm were included. Logistic regression models were created with binary outcome of a second fracture versus no second fracture within a year of index fracture, with the goal of predicting second fracture occurrence. In the Optum Research Database, 197,104 patients were identified with a case-qualifying fracture (43% commercial, 57% Medicare Advantage). Using Symphony data, 1,852,818 met the inclusion/exclusion criteria. Average patient age was 70.09 (SD = 11.09) and 71.28 (SD = 14.24) years in the Optum Research Database and Symphony data, respectively. With the exception of history of falls (41.26% vs 18.74%) and opioid use (62.80% vs 46.78%), which were both higher in the Optum Research Database, the two populations were mostly comparable. A history of falls and steroid use, which were previously associated with increased fracture risk, continue to play an important role in secondary fractures. Conditions associated with bone health (liver disease), or those requiring medications that impact bone health (respiratory disease), and cardiovascular disease and stroke-which may share etiology or risk factors with osteoporosis fractures-were also predictors of imminent fractures. The model highlights the importance of assessment of patient characteristics beyond bone density, including patient comorbidities and concomitant medications associated with increased fall and fracture risk, in alignment with recently issued clinical guidelines for osteoporosis treatment. |
| format |
article |
| author |
Setareh A Williams Susan L Greenspan Tim Bancroft Benjamin J Chastek Yamei Wang Richard J Weiss Nick Pyrih Hily Nichols Jane A Cauley |
| author_facet |
Setareh A Williams Susan L Greenspan Tim Bancroft Benjamin J Chastek Yamei Wang Richard J Weiss Nick Pyrih Hily Nichols Jane A Cauley |
| author_sort |
Setareh A Williams |
| title |
Development and validation of a one year predictive model for secondary fractures in osteoporosis. |
| title_short |
Development and validation of a one year predictive model for secondary fractures in osteoporosis. |
| title_full |
Development and validation of a one year predictive model for secondary fractures in osteoporosis. |
| title_fullStr |
Development and validation of a one year predictive model for secondary fractures in osteoporosis. |
| title_full_unstemmed |
Development and validation of a one year predictive model for secondary fractures in osteoporosis. |
| title_sort |
development and validation of a one year predictive model for secondary fractures in osteoporosis. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2021 |
| url |
https://doaj.org/article/9aba1236bef648df96814e34f46eb2ff |
| work_keys_str_mv |
AT setarehawilliams developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT susanlgreenspan developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT timbancroft developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT benjaminjchastek developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT yameiwang developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT richardjweiss developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT nickpyrih developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT hilynichols developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis AT janeacauley developmentandvalidationofaoneyearpredictivemodelforsecondaryfracturesinosteoporosis |
| _version_ |
1718375440190537728 |