Abstract
Summary
This systematic review and meta-analysis were conducted on all eligible cohort studies to evaluate the association between high-sensitivity C-reactive protein (hs-CRP) and osteoporotic fracture risk. Both frequentist and Bayesian approaches were employed for the meta-analysis. We found that high tertiles of hs-CRP were significantly associated with increased fracture risk.
Introduction
The association between the inflammatory marker CRP and osteoporotic fracture has remained uncertain. In this study, we conducted a systematic review and meta-analysis to examine the association of serum hs-CRP and fracture risk.
Methods
We performed a systematic literature search of relevant databases, including PubMed, Embase, and MEDLINE publications from January 1950 through April 2020. Three reviewers independently performed the study selection, quality assessment, and data abstraction. Frequentist and Bayesian hierarchical random-effects models were used separately for the analysis. Statistical heterogeneity was assessed using Higgin’s I2 and Cochran’s Q statistic, and publication bias was examined using funnel plots and rank correlation tests.
Results
Fourteen cohort studies that reported t fracture outcomes were eligible for the systematic review. Only ten studies (n = 29,741) qualified for meta-analysis. In the frequentist approach, the RR for fracture in a comparison of the top tertile group to the bottom tertile group of hs-CRP was 1.54 (1.18, 2.01). The estimated risk of fracture remained significant in all sensitivity and subgroup analyses. Higgin’s I2 (30.52%) and Cochran’s Q statistic (p < 0.01) suggested there was moderate heterogeneity for the meta-analysis. In the Bayesian approach, the pooled RR was 1.60 (95% CI (1.07–2.49)), and the probabilities that the high level of hs-CRP increased fracture risk by more than 0%, 10%, and 20% were 99%, 98%, and 93%, respectively.
Conclusion
A high level of hs-CRP is associated with a significantly increased risk of osteoporotic fracture.
This is a preview of subscription content, access via your institution.


Abbreviations
- BMD:
-
Bone mineral density
- CI:
-
Confidence interval
- CRP:
-
C-reactive protein
- HR:
-
Hazard ratio
- MOOSE:
-
Meta-analysis of observational studies in epidemiology
- OR:
-
Odds ratio
- PRISMA:
-
Preferred Reporting Items for Systematic Review and Meta-analyses
- RR:
-
Relative risk
- REDCap:
-
Research Electronic Data Capture
References
Dong Y, Zhao R, Wang C, Guo T (2018) Tuina for osteoporosis. Medicine (Baltimore) 97. https://doi.org/10.1097/MD.0000000000009974
Johnell O, Kanis JA (2006) An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 17:1726–1733. https://doi.org/10.1007/s00198-006-0172-4
Sözen T, Özışık L, Başaran NÇ (2017) An overview and management of osteoporosis. Eur J Rheumatol 4:46–56. https://doi.org/10.5152/eurjrheum.2016.048
Clarke B (2008) Normal Bone anatomy and physiology. Clin J Am Soc Nephrol 3:S131–S139. https://doi.org/10.2215/CJN.04151206
Harmer D, Falank C, Reagan MR (2019) Interleukin-6 interweaves the bone marrow microenvironment, bone loss, and multiple myeloma. Front Endocrinol 9. https://doi.org/10.3389/fendo.2018.00788
Hs L, Yh P, Sk K (2016) Relationship between serum inflammatory marker and bone mineral density in healthy adults. J Bone Metab 23:27–33. https://doi.org/10.11005/jbm.2016.23.1.27
Stojanović D, Bůžková P, Mukamal KJ et al (2018) Soluble inflammatory markers and risk of incident fractures in older adults: the Cardiovascular Health Study. J Bone Miner Res 33:221–228. https://doi.org/10.1002/jbmr.3301
Cauley JA, Barbour KE, Harrison SL et al (2016) Inflammatory markers and the risk of hip and vertebral fractures in men: the osteoporotic fractures in men (MrOS). J Bone Miner Res Off J Am Soc Bone Miner Res 31:2129–2138. https://doi.org/10.1002/jbmr.2905
Cauley JA, Danielson ME, Boudreau RM et al (2007) Inflammatory markers and incident fracture risk in older men and women: the Health Aging and Body Composition Study. J Bone Miner Res Off J Am Soc Bone Miner Res 22:1088–1095. https://doi.org/10.1359/jbmr.070409
Ganesan K, Teklehaimanot S, Tran T-H et al (2005) Relationship of C-reactive protein and bone mineral density in community-dwelling elderly females. J Natl Med Assoc 97:329–333
de Pablo P, Cooper MS, Buckley CD (2012) Association between bone mineral density and C-reactive protein in a large population-based sample. Arthritis Rheum 64:2624–2631. https://doi.org/10.1002/art.34474
Apalset EM, Gjesdal CG, Ueland PM et al (2014) Interferon gamma (IFN-γ)-mediated inflammation and the kynurenine pathway in relation to risk of hip fractures: the Hordaland Health Study. Osteoporos Int 25:2067–2075. https://doi.org/10.1007/s00198-014-2720-7
Berglundh S, Malmgren L, Luthman H et al (2015) C-reactive protein, bone loss, fracture, and mortality in elderly women: a longitudinal study in the OPRA cohort. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 26:727–735. https://doi.org/10.1007/s00198-014-2951-7
Wu Z-J, He J-L, Wei R-Q et al (2015) C-reactive protein and risk of fracture: a systematic review and dose-response meta-analysis of prospective cohort studies. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 26:49–57. https://doi.org/10.1007/s00198-014-2826-y
Hind K, Pearce M, Birrell F (2017) Total and visceral adiposity are associated with prevalent vertebral fracture in women but not men at age 62 years: the Newcastle Thousand Families Study. J Bone Miner Res Off J Am Soc Bone Miner Res 32:1109–1115. https://doi.org/10.1002/jbmr.3085
Dahl K, Ahmed LA, Joakimsen RM et al (2015) High-sensitivity C-reactive protein is an independent risk factor for non-vertebral fractures in women and men: the Tromsø Study. Bone 72:65–70. https://doi.org/10.1016/j.bone.2014.11.012
Stroup DF, Berlin JA, Morton SC et al (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 283:2008–2012. https://doi.org/10.1001/jama.283.15.2008
Moher D, Liberati A, Tetzlaff J et al (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 151(264–269):W64. https://doi.org/10.7326/0003-4819-151-4-200908180-00135
Fleiss JL (1971) Measuring nominal scale agreement among many raters. Psychol Bull 76:378–382. https://doi.org/10.1037/h0031619
Pasco JA, Kotowicz MA, Henry MJ et al (2006) High-sensitivity C-reactive protein and fracture risk in elderly women. JAMA 296:1349–1355. https://doi.org/10.1001/jama.296.11.1353
Schett G, Kiechl S, Weger S et al (2006) High-sensitivity C-reactive protein and risk of nontraumatic fractures in the Bruneck study. Arch Intern Med 166:2495–2501. https://doi.org/10.1001/archinte.166.22.2495
Nakamura K, Saito T, Kobayashi R et al (2011) C-reactive protein predicts incident fracture in community-dwelling elderly Japanese women: the Muramatsu study. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 22:2145–2150. https://doi.org/10.1007/s00198-010-1425-9
Ahmadi-Abhari S, Luben RN, Wareham NJ, Khaw K-T (2013) C-reactive protein and fracture risk: European prospective investigation into Cancer Norfolk Study. Bone 56:67–72. https://doi.org/10.1016/j.bone.2013.05.009
Eriksson AL, Movérare-Skrtic S, Ljunggren Ö et al (2014) High-sensitivity CRP Is an independent risk factor for all fractures and vertebral fractures in elderly men: the MrOS Sweden Study. J Bone Miner Res 29:418–423. https://doi.org/10.1002/jbmr.2037
Ishii S, Cauley JA, Greendale GA et al (2013) C-Reactive protein, bone strength, and nine-year fracture risk: data from the Study of Women’s Health Across the Nation (SWAN). J Bone Miner Res Off J Am Soc Bone Miner Res 28. https://doi.org/10.1002/jbmr.1915
Oei L, Campos-Obando N, Dehghan A et al (2014) Dissecting the relationship between high-sensitivity serum C-reactive protein and increased fracture risk: the Rotterdam Study. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 25:1247–1254. https://doi.org/10.1007/s00198-013-2578-0
Wells G, Shea B, O’Connell D, et al (2000) The Newcastle–Ottawa Scale (NOS) for Assessing the Quality of Non-Randomized Studies in Meta-Analysis
McCormack JP, Allan GM (2010) Measuring hsCRP—an important part of a comprehensive risk profile or a clinically redundant practice? PLoS Med 7:e1000196. https://doi.org/10.1371/journal.pmed.1000196
Ressing M, Blettner M, Klug SJ (2010) Data analysis of epidemiological studies. Dtsch Arztebl Int 107:187–192. https://doi.org/10.3238/arztebl.2010.0187
Nurminen M (1995) To use or not to use the odds ratio in epidemiologic analyses? Eur J Epidemiol 11:365–371. https://doi.org/10.1007/BF01721219
Petrie A, Bulman JS, Osborn JF (2003) Further statistics in dentistry Part 8: Systematic reviews and meta-analyses. Br Dent J 194:73–78. https://doi.org/10.1038/sj.bdj.4809877
Hemingway H, Henriksson M, Chen R et al (2010) The effectiveness and cost-effectiveness of biomarkers for the prioritisation of patients awaiting coronary revascularisation: a systematic review and decision model. Health Technol Assess Winch Engl 14(1–151):iii–iv. https://doi.org/10.3310/hta14090
Danesh J, Collins R, Appleby P, Peto R (1998) Association of fibrinogen, C-reactive protein, albumin, or leukocyte count with coronary heart disease: meta-analyses of prospective studies. JAMA 279:1477–1482. https://doi.org/10.1001/jama.279.18.1477
Higgins JPT, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21:1539–1558. https://doi.org/10.1002/sim.1186
Furukawa TA, Guyatt GH, Griffith LE (2002) Can we individualize the “number needed to treat”? An empirical study of summary effect measures in meta-analyses. Int J Epidemiol 31:72–76. https://doi.org/10.1093/ije/31.1.72
Sproston NR, Ashworth JJ (2018) Role of C-reactive protein at sites of inflammation and infection. Front Immunol 9:754. https://doi.org/10.3389/fimmu.2018.00754
Colón-Emeric CS, Saag KG (2006) Osteoporotic fractures in older adults. Best Pract Res Clin Rheumatol 20:695–706. https://doi.org/10.1016/j.berh.2006.04.004
Slaats J, ten Oever J, van de Veerdonk FL, Netea MG (2016) IL-1β/IL-6/CRP and IL-18/ferritin: Distinct inflammatory programs in infections. PLoS Pathog 12. https://doi.org/10.1371/journal.ppat.1005973
Kohli SS, Kohli VS (2011) Role of RANKL–RANK/osteoprotegerin molecular complex in bone remodeling and its immunopathologic implications. Indian J Endocrinol Metab 15:175–181. https://doi.org/10.4103/2230-8210.83401
Boyce BF, Xing L (2008) Functions of RANKL/RANK/OPG in bone modeling and remodeling. Arch Biochem Biophys 473:139–146. https://doi.org/10.1016/j.abb.2008.03.018
Moschen AR, Kaser A, Enrich B et al (2005) The RANKL/OPG system is activated in inflammatory bowel disease and relates to the state of bone loss. Gut 54:479–487. https://doi.org/10.1136/gut.2004.044370
Gowen M (1950) Mundy GR (1986) Actions of recombinant interleukin 1, interleukin 2, and interferon-gamma on bone resorption in vitro. J Immunol Baltim Md 136:2478–2482
Ansar W, Ghosh S (2013) C-reactive protein and the biology of disease. Immunol Res 56:131–142. https://doi.org/10.1007/s12026-013-8384-0
Mortensen JH, Manon-Jensen T, Jensen MD et al (2017) Ulcerative colitis, Crohn’s disease, and irritable bowel syndrome have different profiles of extracellular matrix turnover, which also reflects disease activity in Crohn’s disease. PLoS One 12:e0185855. https://doi.org/10.1371/journal.pone.0185855
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflicts of interest
None.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 40 kb)
Rights and permissions
About this article
Cite this article
Mun, H., Liu, B., Pham, T.H.A. et al. C-reactive protein and fracture risk: an updated systematic review and meta-analysis of cohort studies through the use of both frequentist and Bayesian approaches. Osteoporos Int 32, 425–435 (2021). https://doi.org/10.1007/s00198-020-05623-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00198-020-05623-6
Keywords
- Bayesian meta-analysis
- C-reactive protein
- Fracture
- Meta-analysis
- Osteoporosis
- Systematic review