Fracture Risk Assessment: State of the Art, Methodologically Unsound, or Poorly Reported?
Abstract
Osteoporotic fractures, including hip fractures, are a global health concern associated with significant morbidity and mortality as well as a major economic burden. Identifying individuals who are at an increased risk of osteoporotic fracture is an important challenge to be resolved. Recently, multivariable prediction tools have been developed to assist clinicians in the management of their patients by calculating their 10-year risk of fracture (FRAX, QFracture, Garvan) using a combination of known risk factors. These prediction models have revolutionized the way clinicians assess the risk of fracture. Studies evaluating the performance of prediction models in this and other areas of medicine have, however, been characterized by poor design, methodological conduct, and reporting. We examine recently developed fracture prediction models and critically discuss issues in their design, validation, and transparency.
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In the absence of detailed and transparent reporting of the key study details, it is difficult for the scientific and health care community to objectively judge the strengths and weaknesses of a prediction model study.
“In the absence of detailed and transparent reporting of the key study details, it is difficult for the scientific and health care community to objectively judge the strengths and weaknesses of a prediction model study [34,50,51].”
From Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement (2015) · cites this paper as [50]
In the absence of detailed and transparent reporting of the key study details, it is difficult for the scientific and health care community to objectively judge the strengths and weaknesses of a prediction model study.
“In the absence of detailed and transparent reporting of the key study details, it is difficult for the scientific and health care community to objectively judge the strengths and weaknesses of a prediction model study.34,50,51”
From Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement (2015) · cites this paper as [50]
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Steurer, J., Haller, C., Häuselmann, H., Brunner, F., & Bachmann, L. M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019994 · Cited by 21 · see citing works
Courvoisier, D. S., Combescure, C., Agoritsas, T., et al. (2011) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2011.06.013 · Cited by 6 · see citing works
Mayor, S. J. (2010) · BMJ · doi:10.1136/bmj.c7025 · Cited by 3 · see citing works
Comment on Compston: Pathophysiology of atypical femoral fractures and osteonecrosis of the jaw
Michaëlsson, K., Schilcher, J., & Aspenberg, P. (2012) · Osteoporosis International · doi:10.1007/s00198-012-1905-1 · Cited by 3 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147 · see citing works
Self-citationCollins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. M. (2015) · BMJ · doi:10.1136/bmj.g7594 · Cited by 4,388 · see citing works
Self-citationCollins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. M. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0697 · Cited by 3,267 · see citing works
Self-citationCollins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. (2015) · BMC Medicine · doi:10.1186/s12916-014-0241-z · Cited by 1,927 · see citing works
“In the absence of detailed and transparent reporting of the key study details, it is difficult for the scientific and health care community to objectively judge the strengths and weaknesses of a prediction model study [34,50,51].”
Self-citationCollins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. M. (2015) · Circulation · doi:10.1161/circulationaha.114.014508 · Cited by 793 · see citing works
Self-citationCollins, G. S., de Groot, J. A., Dutton, S., Omar, O., Shanyinde, M., Tajar, A., Voysey, M., Wharton, R., Yu, L.-M., Moons, K. G., et al. (2014) · BMC Medical Research Methodology · doi:10.1186/1471-2288-14-40 · Cited by 729 · see citing works
Riley, R. D., Ensor, J., Snell, K. I. E., Debray, T. P. A., Altman, D. G., Moons, K. G. M., & Collins, G. S. (2016) · BMJ · doi:10.1136/bmj.i3140 · Cited by 585 · see citing works
Self-citationCollins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. M. (2015) · European Urology · doi:10.1016/j.eururo.2014.11.025 · Cited by 439 · see citing works
Conflicts at the heart of the FRAX tool
Järvinen, T. L. N., Jokihaara, J., Guy, P., Alonso-Coello, P., Collins, G. S., Michaëlsson, K., & Sievänen, H. (2014) · Canadian Medical Association Journal · doi:10.1503/cmaj.121874 · Cited by 37 · see citing works
Self-citation
- Authors
- Collins, G. S., & Michaëlsson, K.
- Affiliations
- Uppsala University (SE)
- ORCID
- Michaëlsson, Karl
- Venue
- Current Osteoporosis Reports
- Published
- 2012-06-12
- Volume
- 10
- Issue
- 3
- Pages
- 199-207
- ISSN
- 1544-1873 (ISSN-L)
- 1544-2241
- OpenAlex
- W1990083361
- Cited by
- 51
- References
- 104
- Citations by year
- 2024: 2 · 2023: 1 · 2022: 2 · 2021: 2 · 2020: 4 · 2019: 3 · 2018: 2 · 2017: 2 · 2016: 2 · 2015: 16 · 2014: 7 · 2013: 8
- FWCI
- 10.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Current Osteoporosis Reports (publishedVersion)
- PubMed (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Topics
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Bone health and osteoporosis research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Surgery › Hip and Femur Fractures
- Keywords
- fracture risk assessment, osteoporotic fractures, hip fracture, FRAX, QFracture, fracture prediction model, model validation, risk factor selection, model transparency, reporting quality, methodological critique
- MeSH terms
- Hip Fractures, Humans, Prognosis, Review Literature as Topic, Risk Factors, Risk Assessment, Validation Studies as Topic, Osteoporotic Fractures
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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