Literature Decoded

Living reprintoriginally published in Osteoporosis International 2023CC BY 4.0Read the version of record Opt out

Literature DecodedLiving reprint
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Previous fracture and subsequent fracture risk: A meta-analysis to update FRAX

Meta-analysis first published in Osteoporosis International (2023), reprinted in full under its CC BY 4.0 licence.

John A Kanis1*, Helena Johansson2, Eugene V McCloskey3, Enwu Liu4, Kristina E Åkesson5, Fred A Anderson6, Rafael Azagra7, Cecilie L Bager8, Charlotte Beaudart9, Heike A Bischoff-Ferrari10, Emmanuel Biver11, Olivier Bruyère12, Jane A Cauley13, Jacqueline R Center14, Roland Chapurlat15, Claus Christiansen8, Cyrus Cooper16, Carolyn J Crandall17, Steven R Cummings18, José AP da Silva19, Bess Dawson-Hughes20, Adolfo Diez-Perez21, Alyssa B Dufour22, John A Eisman14, Petra JM Elders23, Serge Ferrari11, Yuki Fujita24, Saeko Fujiwara25, Claus-Christian Glüer26, Inbal Goldshtein27, David Goltzman28, Vilmundur Gudnason29, Jill Hall30, Didier Hans31, Mari Hoff32, Rosemary J Hollick33, Martijn Huisman34, Masayuki Iki35, Sophia Ish-Shalom36, Graeme Jones37, Magnus K Karlsson38, Sundeep Khosla39, Douglas P Kiel40, Woon-Puay Koh41, Fjorda Koromani42, Mark A Kotowicz43, Heikki Kröger44, Timothy Kwok45, Olivier Lamy46, Arnulf Langhammer47, Bagher Larijani48, Kurt Lippuner49, Dan Mellström50, Thomas Merlijn51, Anna Nordström52, Peter Nordström53, Terence W O’Neill54, Barbara Obermayer-Pietsch55, Claes Ohlsson56, Eric S Orwoll57, Julie A Pasco58, Fernando Rivadeneira59, Anne Marie Schott60, Eric J Shiroma61, Kristin Siggeirsdottir62, Eleanor M Simonsick63, Elisabeth Sornay-Rendu64, Reijo Sund65, Karin MA Swart66, Pawel Szulc67, Junko Tamaki68, David J Torgerson69, Natasja M van Schoor70, Tjeerd P van Staa71, Joan Vila72, Nicholas J Wareham73, Nicole C Wright74, Noriko Yoshimura75, M Carola Zillikens59, Marta Zwart76, Liesbeth Vandenput77, Nicholas C Harvey78, Mattias Lorentzon79, William D Leslie80

1Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia; Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK2Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia; Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Sweden3Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK; MRC Versus Arthritis Centre for Integrated research in Musculoskeletal Ageing, Mellanby Centre for Musculoskeletal Research, University of Sheffield, Sheffield, UK4Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia5Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden; Department of Orthopedics, Skåne University Hospital, Malmö, Sweden6GLOW Coordinating Center, Center for Outcomes Research, University of Massachusetts Medical School, Worcester, MA, USA7Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain; Health Centre Badia del Valles, Catalan Institute of Health, Barcelona, Spain; GROIMAP (research group), Unitat de Suport a la Recerca Metropolitana Nord, Institut Universitari d’investigació en Atenció Primària Jordi Gol, Cerdanyola del Vallès, Barcelona, Spain; PRECIOSA-Fundación para la investigación, Barberà del Vallés, Barcelona, Spain8Nordic Bioscience A/S, Herlev, Denmark9WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium; Department of Health Services Research, University of Maastricht, Maastricht, the Netherlands10Department of Aging Medicine and Aging Research, University Hospital, Zurich, and University of Zurich, Zurich, Switzerland; Centre on Aging and Mobility, University of Zurich and City Hospital, Zurich, Switzerland11Division of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland12WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium13Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Philadelphia, United States.14Skeletal Diseases Program, Garvan Institute of Medical Research, Sydney, NSW, Australia; St Vincent’s Clinical School, School of Medicine and Health, University of New South Wales Sydney, Sydney, NSW, Australia; School of Medicine Sydney, University of Notre Dame Australia, Sydney, NSW, Australia15INSERM UMR 1033, Université Claude Bernard-Lyon1, Hôpital Edouard Herriot, Lyon, France16MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK; NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospitals Southampton NHS Foundation Trust, Southampton, UK; NIHR Oxford Biomedical Research Unit, University of Oxford, Oxford, UK17Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA, USA18San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA19Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine, University of Coimbra, Coimbra, Portugal; Rheumatology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal20Bone Metabolism Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA21Department of Internal Medicine, Hospital del Mar and CIBERFES, Autonomous University of Barcelona, Barcelona, Spain22Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA; Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA23Petra JM Elders Department of General Practice, Amsterdam UMC, location AMC, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands24Center for Medical Education and Clinical Training, Kindai University Faculty of Medicine, Osaka, Japan25Department of Pharmacy, Yasuda Women’s University, Hiroshima, Japan26Section Biomedical Imaging, Molecular Imaging North Competence Center, Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein Kiel, Kiel University, Kiel, Germany27Maccabitech Institute of Research and Innovation, Maccabi Healthcare Services, Tel Aviv, Israel; Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel28Department of Medicine, McGill University and McGill University Health Centre, Montreal, Canada29Icelandic Heart Association, Kopavogur, Iceland; University of Iceland, Reykjavik, Iceland30MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK31Interdisciplinary Centre of Bone Diseases, Bone and Joint Department, Lausanne University Hospital (CHUV) & University of Lausanne, Lausanne, Switzerland32Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway; Department of Rheumatology, St Olavs Hospital, Trondheim, Norway33Aberdeen Centre for Arthritis and Musculoskeletal Health, Epidemiology Group, University of Aberdeen, Aberdeen, UK34Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands; Department of Sociology, VU University, Amsterdam, The Netherlands35Department of Public Health, Kindai University Faculty of Medicine, Osaka, Japan36Endocrine Clinic, Elisha Hospital, Haifa, Israel37Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia38Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden; Department of Orthopaedics, Skåne University Hospital, Malmö, Sweden39Robert and Arlene Kogod Center on Aging and Division of Endocrinology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA40Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA; Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA41Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore; Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore42Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands43Deakin University, IMPACT (Institute for Mental and Physical Health and Clinical Translation), Geelong, Victoria, Australia; Barwon Health, Geelong, Victoria, Australia; Department of Medicine - Western Health, The University of Melbourne, St Albans, Victoria, Australia44Department of Orthopedics and Traumatology, Kuopio University Hospital, Kuopio, Finland; Kuopio Musculoskeletal Research Unit, University of Eastern Finland, Kuopio, Finland45Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong; Jockey Club Centre for Osteoporosis Care and Control, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong46Centre of Bone Diseases, Lausanne University Hospital, Lausanne, Switzerland; Service of Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland47HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian; University of Science and Technology, Trondheim, Norway48Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran49Department of Osteoporosis, Bern University Hospital, University of Bern, Bern, Switzerland50Geriatric Medicine, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Geriatric Medicine, Sahlgrenska University Hospital Mölndal, Mölndal, Sweden51Department of General Practice, Amsterdam UMC, location AMC, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands52School of Sport Sciences, UiT The Arctic University of Norway, Tromsø, Norway; Department of Health Sciences, Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden; Department of Medical Sciences, Uppsala University, Sweden53Department of public health and caring sciences, Uppsala University, Uppsala, Sweden54National Institute for Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK; Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester, UK55Department of Internal Medicine, Division of Endocrinology and Diabetology, Medical University Graz, Graz, Austria; Center for Biomarker Research in Medicine, Graz, Austria56Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Drug Treatment, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden57Department of Medicine, Oregon Health and Science University, Portland, Oregon, USA58Deakin University, Institute for Physical and Mental Health and Clinical Translation (IMPACT), Geelong, Australia; Department of Medicine-Western Health, The University of Melbourne, St Albans, Australia; Barwon Health, Geelong, Australia; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia59Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands60Université Claude Bernard Lyon 1, U INSERM 1290 RESHAPE, Lyon, France61Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, Maryland, USA62Icelandic Heart Association, Kopavogur, Iceland; Janus Rehabilitation, Reykjavik, Iceland63Translational Gerontology Branch, National Institute on Aging Intramural Research Program, Baltimore, Maryland64INSERM UMR 1033, University of Lyon, Hôpital Edouard Herriot, Lyon, FranceINSERM65Kuopio Musculoskeletal Research Unit, University of Eastern Finland, Kuopio, Finland66Department of General Practice, Amsterdam UMC, location VUmc, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands; PHARMO Institute for Drug Outcomes Research, Utrecht, The Netherlands67INSERM UMR 1033, University of Lyon, Hôpital Edouard Herriot, Lyon, France68Department of Hygiene and Public Health, Faculty of Medicine, Educational Foundation of Osaka Medical and Pharmaceutical University, Osaka, Japan69York Trials Unit, Department of Health Sciences, University of York, York, UK70Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands71Centre for Health Informatics, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK72Statistics Support Unit, Hospital del Mar Medical Research Institute, CIBER Epidemiology and Public Health (CIBERESP), Barcelona, Spain73MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom74Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA75Department of Preventive Medicine for Locomotive Organ Disorders, The University of Tokyo Hospital, Tokyo, Japan76Health Center Can Gibert del Plà, Catalan Institute of Health, Girona, Spain; Department of Medical Sciences, University of Girona, Girona, Spain; GROIMAP/GROICAP (research groups), Unitat de Suport a la Recerca Girona, Institut Universitari d’investigació en Atenció Primària Jordi Gol, Girona, Spain; PRECIOSA-Fundación para la investigación, Barberà del Vallés, Barcelona, Spain77Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia; Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden78MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK; NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK79Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia; Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Sweden; Region Västra Götaland, Geriatric Medicine, Sahlgrenska University Hospital, Mölndal, Sweden80Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada*Corresponding author

Reprinted 2026-10-01 14 min read Living reprint · journal article Version of record: Osteoporosis International 2023Licence: CC BY 4.0

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In plain languageMeta-analysis first published in Osteoporosis International (2023), reprinted in full under its CC BY 4.0 licence.

Meta-analysis first published in Osteoporosis International (2023), reprinted in full under its CC BY 4.0 licence.

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Educational summary of research findings; not medical advice. Discuss care decisions with a qualified clinician.

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No plain-language summary has been written for this reprint yet. The authors' abstract and full text follow, unchanged apart from layout.

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Educational summary of research findings; not medical advice. Discuss care decisions with a qualified clinician.

The paper

Full manuscript

Abstract

Summary

A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX.

Introduction

The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD).

Methods

We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD and duration of follow up. The results of the different studies were merged by using the weighted β-coefficients.

Results

A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (Hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06) or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination.

Conclusion

A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies.

Keywords: Prior fracture; Meta-analysis; Hip fracture; Osteoporotic fracture; Major osteoporotic fracture

Introduction

A history of a prior fracture at a site characteristic for osteoporosis is an important risk factor for further fracture1, 2, 3, 4, 5, 6. Fracture risk is approximately doubled in the presence of a prior fracture, including morphometric vertebral fractures. The risks are in part independent of BMD4. However, the increase in risk is not constant with age. For example, a large meta-analysis showed that a prior fracture history was a significant risk factor for hip fracture at all ages, but the population relative risk was highest at younger ages and decreased progressively with age4.

The identification of patients with a fracture history is a well-established goal in the clinical management of osteoporosis as outlined in most clinical guidelines worldwide7, 8, 9, 10, 11, 12. In many cases, individuals with a prior fracture are eligible for treatment irrespective of BMD. For example, the National Osteoporosis Guideline Group (NOGG) in the United Kingdom recommends treatment in all women with a prior fragility fracture10. A similar threshold is provided in the European guidance13. In the United States, a prior vertebral or hip fracture qualifies for a treatment recommendation irrespective of BMD14.

Because a prior fracture provides a fracture risk that is largely independent of BMD, it has been incorporated into assessment guidelines that integrate the risks associated with a number of risk variables15, 16, 17. FRAX®, currently available in 78 territories, is the most widely used fracture risk assessment tool and is incorporated into a large number of assessment guidelines7, recommended by the Committee for Medicinal Products for Human Use (CHMP)18, and approved by the National Institute for Health and Care Excellence (NICE)19. The incorporation of a prior fracture as an input variable for risk prediction was based on a meta-analysis, published in 2004, of 15,259 men and 44,902 women from 11 cohorts followed for a total of 250,000 person-years4. Since then, many more prospectively studied cohorts have become available that have the potential to improve the accuracy of FRAX20.

The aim of the present study was to quantify the risk for future fracture associated with a history of prior fracture in an international setting, and to explore the dependence of this risk on age, sex, time since baseline assessment and BMD.

Methods

The study population was derived from a systematic review that identified prospective cohort studies for the update of FRAX. The study was registered with the International prospective register of systematic reviews, PROSPERO (CRD42021227266), and followed the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. Studies were eligible if the cohort was prospective, included at least 200 participants, assessed an adequate number of clinical risk factors and reported an adequate number of incident fracture outcomes. We studied 2,104,506 men and women from 64 prospectively studied cohorts of whom 9.7% had a prior fracture history. 58 cohorts included women (n=1,438,535) and 40 cohorts included men (n=665,971). Details of the cohorts studied have been given previously20 and are summarized in Table 1.

Table 1. Characteristics of the cohorts studied
Quality gradeAge (years)Number of fractures
CohortnPerson yearsMeanRange% femalePrior fracture (%)HipAnyMOFMOF minus hipOsteoporotic
AGESA57064550877.066 -9857.642.2535161911347661395
AHSB26131010965.147-9569.625.932368281257281
APOSSA38403362948.544-5610013.14335142141176
AUSTRIOS BC2046237083.968-10384.146.676174---
BEHB24141008569.360-9651.912.942105---
BernB2310418135258.920-9585.043.92945033291327303891
CaMosA942212162762.125-10369.444.0340243511889351753
DO_HEALTHB2139591475.070-9561.922.510264118111190
DOESA21331888470.147-9460.715.0110561363294465
ECOSAPB51461685772.365-10010020.252311188136259
EPIC-NorfolkA2560049350059.239-7954.77.01356304023441205-
EPIDOSB75952119280.570-10010045.02261026568376837
EPIFROSB284282661.640-9654.64.6327161320
EVOS/EPOSB133664098363.841-9152.136.344538286245538
FORMENA18851625372.565-9307.91090584990
Framingham offspringA35395840261.533-9054.133.9105758316239533
Framingham originalA11661118479.972-10165.320.013627918768242
FRIDEXB815807756.840-8410020.415112412856
FROCATA19531940469.232-11155.717.133229160135183
GERICOC764276667.965-7279.546.3271262451
GLOWB5425821670368.255-1081003.14905690284824374285
GOSA1403936469.550-9510030.33114910580135
Gothenburg IA1736981885.570-9657.010.7304431361100408
Gothenburg IIA1137114982559.021-8410016.82591192739644856
HAIB2085330370.570-7251.114.1442262236
HCSA632559564.959-7150.316.3367353351
Health ABCA30623630973.668-8051.522.0235696518349594
HUNTA5020962202053.220-10054.623.4167410239473336017128
JPOSB19442581257.540-8210015.82926599--
LASAA1473757575.765-8951.627.938131--95
MaccabiA659266629732556.330-9152.04.81129354312519554275953907
ManitobaB9228183342463.420-10489.121.33085135069578718712655
MINOSB681615265.250-86012.8363252256
MiyamaA400370359.140- 7950.033.5761353047
MrOS Hong KongB20001974472.465-92013.76323114893201
MrOS SwedenA29993401974.969-81020.9339968728482874
MrOS USAA59937499873.764-100055.333013948144901082
MsOS Hong KongB20001752872.665-9810020.869338247189298
NHEFSA1220612162349.425-7459.66.7113----
OFELYA8671513658.840-8910010.340245180159207
OPRAA10441213375.275-7610045.8195524453-473
OPUSB19831216762.020-8010042.014236113102148
OsteoLausB1475672664.550-8210036.48307226221245
OSTPREB1120010946557.352-621009.08018519188481259
PERFB57603780264.244-8110017.362828544489550
REFORMC1003148377.965- 9960.56.543012817
RochesterA1001768656.821-9465.218.137326243229283
RotterdamA1461915808565.845-10658.822.98303317232217422892
SAOL_IPR_EPIPortoB9291128455.940- 8977.412.7121059--
SarcoPhAgeC22844075.968-9357.025.4113548
SCHSA5204246243661.648- 8457.48.11091----
SCOOPA123685882675.670-8610023.1378192712849751625
SEMOFB71302062475.270 -9110051.780683464384596
SheffieldB2148735480.074-10110045.466281186132227
SOFB961913547471.665-8910037.114044337279418333455
SOSB166266211974.261-9210030.026013839937021325
STOP/ITB424184071.165-8755.049.1250242232
STRAMBOA823758272.151-88011.717117422686
SUPERBB30191073677.875-8110036.870463341-421
TASOACB10981095563.051-8148.944.25146494688
THINA366104212576463.850-1161009.1694231633--23622
UK BiobankB502536576621256.537-7354.43.739432519012099833220075
WHIB6439986838065.855-7910017.419815259371219014213
YorkB4532904477.148-9910044.742393223189310
Total21045061953551520-1163935818679411055984614155825?
Mean61.568.39.7

MOF, major osteoporotic fracture; AGES, Age, Gene/Environment Susceptibility-Reykjavik Study; AHS, Adult Health Study; APOSS, Aberdeen Prospective Osteoporosis Screening Study; BEH, Bushehr Elderly Health; CaMos, Canadian Multicentre Osteoporosis Study; DOES, Dubbo Osteoporosis Epidemiology Study; DO-HEALTH, VitaminD3-Omega3-Home Exercise-Healthy Aging and Longevity Trial; ECOSAP, Ecografía Osea en Atención Primaria; EPIC-Norfolk, European Prospective Investigation of Cancer-Norfolk; EPIDOS, Epidémiologie de l’Ostéoporose; EPIFROS, EPIdemiology and Fracture Risk factors for Osteoporosis in Spain; EVOS/EPOS, European Vertebral Osteoporosis Study/European Prospective Osteoporosis Study; FORMEN, Fujiwara-kyo Osteoporosis Risk in Men; FRIDEX, Fracture RIsk factors and bone DEnsitometry type central dual X-ray; FROCAT, Fracture Risk factors for Osteoporosis in CATalonia; GERICO, Geneva Retirees Cohort; GLOW, Global Longitudinal Study of Osteoporosis in Women; GOS, Geelong Osteoporosis Study; HAI, Healthy Ageing Initiative; HCS, Hertfordshire Cohort Study; Health ABC, Health, Aging and Body Composition; HUNT, The Trøndelag Health Study; JPOS, Japanese Population-based Osteoporosis Study; LASA, Longitudinal Aging Study Amsterdam; MINOS, Montceau les MINes OSteoporosis; MrOS, Osteoporotic Fractures in Men; MsOS, Osteoporotic Fractures in Women; NHEFS, National Health and Nutrition Examination Survey (NHANES) I Epidemiologic Follow-up Study; OFELY, Os des Femmes de Lyon; OPRA, Osteoporosis Prospective Risk Assessment; OPUS, Osteoporosis and Ultrasound Study; OSTPRE, Kuopio OSTeoporosis risk factor and PREvention study; PERF, Prospective Epidemiologic Risk Factor; REFORM, REducing Falls with ORthoses and a Multifaceted podiatry intervention; SAOL-IPR-EPIPorto, Santo António dos Olivais, Instituto Português de Reumatologia and EPIPorto; SarcoPhAge, Sarcopenia and Physical Impairment with advancing Age; SCHS, Singapore Chinese Health Study; SCOOP, screening for prevention of fractures in older women; SEMOF, Swiss Evaluation of the Methods of Measurement of Osteoporotic Fracture risk; SOF, Study of Osteoporotic Fractures; SOS, SALT Osteoporosis Study; STRAMBO, Structure of the Aging Men’s Bone; SUPERB, Sahlgrenska University hospital Prospective Evaluation of Risk of Bone fractures; TASOAC, Tasmanian Older Adult Cohort; THIN, The Health Improvement Network; WHI, Women’s Health Initiative.

Baseline and outcome variables

The construct of the question to determine a prior fracture history differed between the cohorts studied, based on time of previous fracture, fracture site, energy, validity, and inclusion of morphometric vertebral fractures (Table 2).

Table 2. Details of the construct of the questionnaire on fracture type and history in the cohorts studied.
ElementConstruct
Time horizonEver in life, adult life, from age 18, 20, 35, 40, 45, 50, past 12 months, 5 years or10 years
Site of fractureAny fracture, osteoporotic fracture, MOF
EnergyAll trauma included, moderate trauma, low trauma
ValiditySelf-reported, verified, based on GP medical record, administrative healthcare data, has a doctor/nurse/physician assistant told you?
Vertebral deformityVertebral fractures assessed by semiquantitative criteria included, not included

For outcomes Information on all clinical fractures was used for this report ‘all fractures’. In addition, fractures considered to be associated with osteoporosis were examined21. According to this classification, fractures of the skull, face, hands, feet, ankle and patella were excluded as well as tibial and fibular fractures in men. Hip fracture and major osteoporotic fracture were also analysed separately. No distinction was made according to trauma since both high- and low-trauma fractures show similar relationships with low BMD and future fracture risk22. The risk of death as function of fracture history was also assessed.

Statistical methods

The risk of fracture was estimated by an extended Poisson model applied separately to each cohort (and also separately by sex for those cohorts with both men and women)23, 24. Because of an embargo on transfer of primary data from Manitoba, Cox regression was used on the Manitoba cohort on site and beta-coefficients, variances and covariances forwarded to the analysis team. Covariates included current time since start of follow up, current age (derived from age at since start of follow up and current time since start of follow up), prior history of fracture, and BMD at the femoral neck. Femoral neck BMD was adjusted for manufacturer and T-scores were calculated from the NHANES III White female reference values20. We additionally estimated a model that excluded BMD from the covariates. A further model included the interaction term ‘prior fracture · current time since baseline’ to determine whether the strength of the association of prior fracture and fracture risk changed with time. An additional model included the interaction term ‘prior fracture · current age’ to determine whether the strength of the association of prior fracture and fracture risk changed with age. Interactions with time and with age were also explored using piece-wise linear regression to check the adequacy of the Poisson model. The hazard ratio (HR) for previous fracture was determined for each age from 40 years from the Poisson model. Results of each cohort and the two sexes were weighted according to the variance and merged to determine the weighted means and standard deviations. The HR of those with a prior fracture history versus those without a prior fracture history was equal to eweighted mean of β. There was significant heterogeneity in risk between cohorts (index of heterogeneity I2 = 82-98% depending on fracture outcome), and a random effects model was used in the meta-analysis.

The component of the risk ratio explained by BMD was computed from a meta-analysis of BMD and fracture risk in men and women combined25. Based on the prior evidence, the risk of any clinical fracture was assumed to increase 1.45-fold for each SD decrease in BMD at the femoral neck. For hip fracture, the gradient of risk was assumed to be 2.07 per SD and 1.55 for any osteoporotic fracture4. These findings permitted comparison of the calculated expected difference in mean BMD between those with, versus those without, a prior fracture, with the actual difference ascertained from the baseline data. Thus, the proportion of risk attributed to a low BMD was computed as:

([logHRa/logGR]−[logHRb/logGR])/([logHRa/logGR])

where HRa is the unadjusted hazard ratio for prior fracture, HRb is the hazard ratio adjusted for BMD, and GR is the gradient of risk for femoral neck BMD4.

Individuals with missing data were excluded. No data were imputed.

Sensitivity analyses

As noted above, the effect of sex on the hazard ratio for fracture was examined in those cohorts that contributed both men and women. Similarly, differences in risk with and without BMD were additionally explored in those cohorts that contributed both scenarios. Assessment of the effects of race and ethnicity was confined to those cohorts recording more than one race or ethnic group (Asian, Black, Hispanic, White), comprising Health ABC, CAMOS, MROs USA, WHI, SOF, Manitoba and UK Biobank. Results were also computed according to study quality as previously defined20. Quality was based on a 0/1 score for four criteria: Population-based cohort (yes scores 1); Fracture ascertainment (self-report scores 0, others score 1); Duration of follow-up (> 2 years, scores 1); Average loss to follow-up/year (< 10%, scores 1). This gives a maximum score of 4 and a minimum of 0. A quality score of 0 or 1 was designated as poor quality (designated C), a score of 2 or 3 categorised as intermediate quality (B) and a score of 4 designated as high quality (A). Quality grades are given in Table1.

Results

Of 2,104,506 men and women studied in 32 countries, 45,059 men and 158,659 women had sustained a prior fracture. At follow up, 38,897 men and 147,897 women were identified as having a subsequent clinical fracture of any kind; 31,686 and 124,139 were characterized as osteoporotic in men and women, respectively; 26,744 men and 83,815 women sustained a MOF; 8182 and 31,176 were hip fractures. The total follow-up time was 6.8 million-person years in men and 12.7-million-person years in women. BMD measurements were available in 13.8% (289,841) of individuals. The probability of fracture history rose almost linearly with age from the age of 40 years but tended to decline in women after age 90 years (Table 3). The prevalence of recording a history of a prior fracture was higher in women than in men (OR = 1.34; 95% CI = 1.32–1.35 unadjusted).

Table 3. Prevalence of a prior fracture history in men and women by age. The Manitoba and Maccabi data are not included since primary data were not available.
Age (years)Fracture history (%)
MenWomenCombined
40-494.23.53.8
50-595.97.06.6
60-696.411.09.6
70-7914.120.619.3
80-8917.823.722.7
90+21.421.821.8

Risk of fracture by site and sex

Previous fracture was associated with a significantly increased risk of any subsequent fracture (Table 4). In men and women, the HR ranged from 1.71 to 1.99 depending upon category of the outcome fracture. There were no significant differences in hazard ratios by site of fracture. The risk ratio was marginally but not significantly higher in men than in women by approximately 7-11%. In a sensitivity analysis using only those cohorts that contributed both men and women, there was no sex difference in hazard ratio for all sites (Appendix, Table A)

Table 4. Hazard ratio (HR) and 95% confidence interval (CI) of fracture at the sites indicated associated with a history of prior fracture in men and women and both sexes combined. HRs are adjusted for age and time since baseline.
Outcome fractureNumber of cohortsI2(%)HR95% CI
Women
Any56941.841.72-1.97
Hip51811.711.57-1.86
MOF50941.771.63-1.93
MOF without hip fracture45911.801.65-1.95
Osteoporotic51941.821.70-1.96
Men
Any34971.921.56-2.34
Hip29911.991.53-2.59
MOF31961.901.51-2.39
MOF without hip fracture30941.791.43-2.25
Osteoporotic31971.921.55-2.38
Men and women
Any62981.851.69-2.02
Hip56921.771.59-1.98
MOF55971.801.61-2.01
MOF without hip fracture51961.801.62-2.01
Osteoporotic56981.841.68-2.03

The increase in risk among those who reported a prior clinical fracture was fairly heterogeneous as shown in the Forest plots in Figure 1 for MOF and hip fracture outcomes. Forest plots for any clinical fracture and osteoporotic fracture outcomes are given in the appendix. Heterogeneity was not related to the question construct since the question construct had little effect on the outcome. In the case of an osteoporotic fracture, for example, the question construct of any prior fracture was associated with a similar increase in fracture risk (HR=1.87; 95%CI=1.58-2.22) as that when the question referred to a prior major osteoporotic fracture (HR=1.77; 95%CI=1.51-2.07) or where the site of prior fracture was unspecified (HR=1.75; 95%CI=1.61-1.89). Similarly, there was no significant difference when low or moderate trauma was specified (HR=1.77; 95%CI=1.41-2.22) or unspecified (HR=1.84; 95%CI=1.67-2.03; p>0.3).

Figure 1
Figure 1. Forest plot showing effect size on hip fracture risk (left panel) and major osteoporotic fracture (right panel) associated with a prior fracture in men and women combined adjusted for age and time since baseline

Dependence on BMD

The impact of BMD on the fracture risk in individuals with a prior fracture is quantified in Table 5. The HR was marginally decreased by approximately 8-16% when account was taken of BMD. In the case of any clinical fracture, if it is assumed that the risk of any clinicalfracture increases 1.45-fold for each standard deviation (SD) decrease in hip BMD (gradient of risk), then the difference in risk between those with and without a prior fracture is equal to an expected difference in BMD of 1.57SD [log 1.79/log1.45]. In reality, the difference in BMD at all ages in men and women combined was approximately 0.22 SD ([log (1.79)/log(1.45)]- [log(1.65)/log(1.45)]). Thus, low BMD accounted for the minority (14%; 0.22/1.57) of the difference in risk of any clinical fracture between those with or without a prior fracture. As would be expected, the proportion of risk accounted for by BMD was greater in the case of hip fractures (see Table 5) but remained less than 50% (see Table 5).

Table 5. Hazard ratio (HR) and 95% confidence interval (CI) of fracture at the sites indicated associated with a history of prior fracture in men and women combined. HRs are adjusted for age and time since baseline and additionally adjusted for BMD where indicated. The last column indicates the proportion of risk explained by BMD.
UnadjustedAdjusted for BMD
Outcome fractureNumber of cohortsHR95% CIHR(95% CI)Gradient of risk (HR/SD) for BMDProportion of risk (%) from BMD
Any521.791.67-1.921.651.53-1.781.4514
Hip451.701.58-1.841.431.30-1.562.0733
Osteoporotic481.781.65-1.921.611.48-1.751.5517

Interaction with age

A prior fracture history was a significant risk factor for fracture at all ages. The hazard ratio was highest at younger ages and decreased progressively with age (Table 6). The interaction term was significant for all fracture outcomes in men and women combined. The decrease with age was most marked for hip fracture which decreased by approximately 16% for each decade of age (Figure 2). An almost identical relationship was observed using piece-wise linear regression (data not shown).

Table 6. Hazard ratio (HR) and 95% confidence interval (CI) of fracture by age at baseline at the sites indicated associated with a history of prior fracture in men and women combined. HRs are adjusted for time since baseline and sex. n refers to the number of cohorts available. P values refer to the significance of the interaction term with age
Site of outcome fracture
Any (n=62)Hip (n=56)MOF (n=55)Osteoporotic (n=56)
Age (years)HR95% CIHR95% CIHR95% CIHR95% CI
402.471.96-3.133.572.42-5.272.321.77-3.032.401.87-3.08
452.381.93-2.943.272.30-4.672.221.74-2.842.311.84-2.89
502.291.90-2.763.002.18-4.132.131.71-2.662.221.82-2.72
552.201.87-2.592.762.08-3.662.051.68-2.492.141.79-2.55
602.111.84-2.432.531.98-3.241.971.66-2.332.061.76-2.40
652.031.81-2.282.321.88-2.861.891.63-2.191.981.73-2.25
701.961.78-2.152.131.78-2.541.811.60-2.051.901.71-2.12
751.881.75-2.021.951.70-2.251.741.57-1.921.831.68-1.99
801.811.72-1.901.791.61-1.991.671.55-1.801.761.65-1.88
851.741.68-1.801.641.52-1.771.601.52-1.691.691.62-1.77
901.671.63-1.721.511.43-1.591.541.49-1.591.631.58-1.68
P=0.0014P<0.001P=0.0011P=0.0013
Figure 2
Figure 2. Hazard ratio (HR) and 95% confidence interval of a major osteoporotic fracture (MOF) and hip fracture by age associated with a history of prior fracture in men and women combined. HRs are adjusted for time since baseline and sex.

Interaction with time

Fracture risk associated with a prior fracture decreased slowly with time since baseline by about 2-4% per year (Table 7). A similar relationship was observed using piece-wise linear regression (data not shown).

Table 7. Hazard ratio (HR) and 95% confidence interval (CI) of fracture by time since baseline at the sites indicated associated with a history of prior fracture in men and women combined. HRs are adjusted for age and sex. N refers to the number of cohorts available. P values refer to the significance of the interaction term with time since baseline.
Site of outcome fracture
Any (n=61)Hip (n=54)MOF (n=54)Osteoporotic (n=55)
Time (years)HR95% CIHR95% CIHR95% CIHR95% CI
02.121.78-2.522.121.73-2.692.061.65-2.572.131.76-2.58
12.061.76-2.412.041.70-2.552.001.63-2.442.071.74-2.45
22.001.73-2.301.971.68-2.421.931.61-2.322.001.71-2.33
31.941.71-2.201.911.65-2.301.871.59-2.201.941.69-2.23
41.881.68-2.111.841.63-2.191.811.56-2.101.881.66-2.13
51.831.65-2.021.781.59-2.081.751.54-2.001.821.62-2.03
61.771.61-1.951.721.56-1.991.701.50-1.921.761.58-1.95
71.721.58-1.881.661.52-1.911.641.46-1.841.701.54-1.89
81.671.53-1.831.601.48-1.841.591.41-1.781.651.49-1.83
91.621.48-1.781.551.42-1.781.541.37-1.731.601.43-1.78
101.581.43-1.741.491.37-1.731.491.31-1.691.551.38-1.74
P=0.0035P=0.0031P=0.0095P=0.0042

Race and Ethnicity

With one exception, there was no difference in the HR by race and ethnicity in those cohorts where race or ethnicity was documented (Table B of Appendix). The exception was for major osteoporotic fracture such that in Blacks, those with prior fracture history had a higher risk of subsequent fracture hazard ratio than Whites (Blacks: HR=2.43, 95% CI=1.37-3.78 vs. Whites: HR=1.57, 95% CI= 1.32-1.87). The effect was largely driven by a high HR in Blacks from Manitoba (HR=5.34, 95% CI= 1.79-15.94).

Quality scores

There was no significant difference in fracture outcomes when cohorts of high quality were compared with those of moderate quality (Appendix, Table C). For cohorts of low quality, there was a significant difference from high quality cohorts for MOF, based on a single low-quality cohort (GERICO).

Risk of death

A prior fracture was associated with a significant increase in the risk of death in both men (HR=1.11; 95%CI=1.02, 1.21) and women (HR=1.10; 95%CI=1.05-1.15). Hazard ratios remained unchanged when adjusted for femoral neck BMD.

Discussion

The present study represents the largest meta-analysis to date on the association between prior fracture and subsequent fracture risk. The effect is similar in men and women and is consistent with our previous meta-analyses4. It is of interest that the quantum of effect was not dependent the question construct. The size of the effect was also relatively immune to cohort quality and different race and ethnicities. Nonetheless, the true effect size relies on the accuracy of information provided which cannot be assessed in the construct of the present study. For the purposes of risk assessment, however, accuracy and causality of associations are of less concern than repeatability and that the risk identified shows reversibility of effect17, 28.

The extensive data resource permitted the elucidation of important interactions comprising an interaction with age, and time since baseline. For all fracture outcomes, the risk ratios decreased significantly with age, consistent with our previous meta-analysis4 and incorporated into FRAX17. Of Importance, we were able to examine the risk associated with prior fractures among the oldest -old. Additionally, the increased power of the present study revealed that hazard ratios also decreased significantly with time, a phenomenon not accounted for in the current FRAX model17. As with all risk variables used in FRAX, any interaction of effect over time is also important to incorporate in future probability models.

The present study also quantified the independent contributions of low BMD and prior fracture. For all outcomes studied, low BMD explained a minority of the total risk. The mechanism for the BMD-independent increase in risk could not be determined from this study but is likely due, in part, to coexisting morbidity that might increase the risk of falls or impair the protective responses to injury27, 28. In addition, changes in the structural or material properties of bone may weaken bone out of proportion to any effect on BMD29, 30, 31, 32, 33, 34.

A particular strength of the present study is that the estimate of risk is made in an international setting largely from population-based cohorts. Calculations were based on the primary data, decreasing the risk of publication biases. The consistency of the association between cohorts additionally indicates the international validity of this risk variable. The present study has several limitations that should be mentioned. As with nearly all population-based studies, nonresponse biases may have occurred, which we were unable to document for all cohorts. The effect is likely to exclude sicker members of society, including those in institutional care, and may underestimate the absolute risk of fracture. Thus, the probability of a prior fracture may be underestimated from a societal perspective, but this is unlikely to affect risk ratios. The greatest potential problem was the construct of the question concerning prior fractures and the methods of documenting and characterizing subsequent fracture events. These differed substantially between cohorts. The effect of this heterogeneity on fracture outcomes was, however, marginal. It should also be recognised that additional factors affect the risk associated with a prior fracture. The increase in risk is more marked the greater the number of prior fractures35, 36, 37, particularly prior vertebral fractures for a subsequent vertebral fracture35, 38, 39, 40, 41. Also, the risk of a subsequent osteoporotic fracture is particularly acute immediately after an index fracture and wanes progressively with time3, 42, 43, 44. For example, after a fracture, the risk of subsequent fracture is highest in the immediate post fracture interval with more than one-third of subsequent fractures occurring within 1 year45. The waning of risk with time is also age-dependent44. Also, the effect of recency is site dependent47 with higher risk ratios for hip and vertebral fracture than for humerus, forearm, or minor osteoporotic fracture. Finally, morphometric but subclinical fractures were not assessed though they do add to fracture probability independently of FRAX48. Data on these additional modulating factors were not available for this meta-analysis, thus residual confounding could be present in our findings. However, adjustments to FRAX probabilities for these factors is available through FRAXplus49. FRAXplus, which has recently been released in a beta version, brings together a number of adjustments that can illustrate the potential impact of modulating factors on FRAX fracture probabilities. These include trabecular bone score, recency of fracture (by site and time within the last two years), the number of self-reported falls in the previous year, glucocorticoid dose, and duration of type 2 diabetes mellitus. An additional limitation is that no account was taken of treatment effects.

In conclusion, this analysis has quantified the magnitude of the risk for future fractures conferred by a prior fracture in the largest meta-analysis conducted to date, and that this risk is largely independent of BMD. The effect is similar in men and women. The consistency of the association in an international setting provides the rationale for the use of these data in the next iteration of FRAX.

Supplementary Material

Supplementary Material — available with the version of record.

Figures and tables

Figure 3
Figure 3. Forest plot showing effect size on osteoporotic fracture risk (left panel) and any clinical fracture (right panel) associated with a prior fracture in men and women combined adjusted for age and time since baseline

Acknowledgements

We are grateful to Dr Östen Ljunggren for contributing the MrOS Sweden cohort. UK Biobank data are included under approved access agreement 3593. The authors acknowledge the Manitoba Centre for Health Policy for use of Manitoba data contained in the Population Health Research Data Repository (HIPC 2016/2017-29). The results and conclusions are those of the authors and no official endorsement by the Manitoba Centre for Health Policy, Manitoba Health, Seniors and Active Living, or other data providers is intended or should be inferred.

The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, 75N92021D00005.

Funding

No external funding

Declarations

Compliance with ethical standards

Conflict of interest

JA Kanis led the team that developed FRAX as director of the WHO Collaborating Centre for Metabolic Bone Diseases. EV McCloskey, WD Leslie, M Lorentzon, NC Harvey, E Liu, L Vandenput and H Johansson are members of the FRAX team. JA Kanis, NC Harvey, and EV McCloskey are members of the advisory body to the National Osteoporosis Guideline Group. JA Kanis reports no additional competing interests.

KE Åkesson has no financial interest related to FRAX; chaired the National SALAR Group for Person-Centered Care Pathway Osteoporosis.

FA Anderson led the team that developed GLOW, while director of the Center for Outcomes Research at the University of Massachusetts Medical School; he has no financial interest in FRAX.

R Azagra has received funding for research from Instituto Carlos III of Spanish Ministry of Health, IDIAP Jordi Gol of Catalan Government and from Scientific Societies SEMFYC and SEIOMM.

CL Bager is employed at Nordic Bioscience and owns stock in Nordic Bioscience. She declares no competing interests in relation to this work.

HA Bischoff-Ferrari has no financial interest in FRAX. For the DO-HEALTH trial cohort, Prof. Bischoff-Ferrari reports independent and investigator-initiated grants from European Commission Framework 7 Research Program, from the University of Zurich, from NESTEC, from Pfizer Consumer Healthcare, from Streuli Pharma, plus non-financial support from DNP. For the study cohort extension, she reports independent and investigator-initiated grants from Pfizer and from Vifor. Further, Prof. Bischoff-Ferrari reports non-financial support from Roche Diagnostics and personal fees from Wild, Sandoz, Pfizer, Vifor, Mylan, Roche, Meda Pharma, outside the submitted work with regard to speaker fees and travel fees.

JR Center has received honoraria for speaking at educational meetings and for advisory boards from Amgen and honoraria for an advisory board from Bayer.

R Chapurlat has no financial interest in FRAX. He has received grant funding from Amgen, UCB, Chugai, MSD, Mylan and Medac. He has received honoraria from Amgen, UCB, Chugai, Galapagos, Biocon, Abbvie, Haoma Medica, Pfizer, Amolyt, MSD, Lilly, BMS, Novartis, Arrow, PKMed, Kyowa-Kirin, and Sanofi.

C Christiansen owns stock in Nordic Bioscience. He declares no competing interests in relation to this work.

C Cooper reports personal fees from Alliance for Better Bone Health, Amgen, Eli Lilly, GSK, Medtronic, Merck, Novartis, Pfizer, Roche, Servier, Takeda and UCB.

A Diez-Perez reports personal fees from Amgen, Lilly, Theramex and grants from Instituto Carlos III and owns shares of Active Life Scientific, all outside the submitted work.

JA Eisman declares consulting and research support from Actavis, Amgen, Aspen, Lilly, Merck Sharp and Dohme, Novartis, Sanofi-Aventis, Servier and Theramex.

PJM Elders has no financial interest in FRAX. PJM Elders reports support for the SOS study by Stichting Achmea Gezondheidszorg, Achmea and VGZ zorgverzekeraar. Additional support was given by the stichting Artsenlaboratorium en Trombosedienst. Outside the submitted work, she did receive independent investigator driven grants by Zonmw, the Netherlands, de Hartstichting, the Netherlands, the European foundation for the study of Diabetes, Amgen the Netherlands, TEVA, the Netherlands and Takeda, the Netherlands.

Claus-C. Glüer reports honoraria and research support from AgNovos, Amgen, osteolabs and UCB unrelated to this work.

NC Harvey has received consultancy/lecture fees/honoraria/grant funding from Alliance for Better Bone Health, Amgen, MSD, Eli Lilly, Radius Health, Servier, Shire, UCB, Consilient Healthcare and Internis Pharma.

DP Kiel has no financial interest in FRAX but has received support for his work in the Framingham Study over the past 30 years by the National Institutes of Health, Astra Zeneca, Merck, Amgen, and Radius Health.

MA Kotowicz has received funding from the National Health and Medical Research Council (NHMRC) Australia, and the Medical Research Future Fund (MRFF) Australia. He has served on advisory boards for Amgen Australia, Novartic and Eli Lilly – all unrelated to this work and is the Director of the Geelong Bone Densitometry Service.

M Lorentzon has received lecture fees from Amgen, Lilly, Meda, Renapharma and UCB Pharma and consulting fees from Amgen, Radius Health, UCB Pharma, Renapharma and Consilient Health, all outside the presented work.

EV McCloskey has received consultancy/lecture fees/grant funding/honoraria from AgNovos, Amgen, AstraZeneca, Consilient Healthcare, Fresenius Kabi, Gilead, GSK, Hologic, Internis, Lilly, Merck, Novartis, Pfizer, Radius Health, Redx Oncology, Roche, Sanofi Aventis, UCB, ViiV, Warner Chilcott and I3 Innovus.

C Ohlsson is listed as a coinventor on two patent applications regarding probiotics in osteoporosis treatment.

ES Orwoll reports consulting fees from Amgen, Biocon, Radius, and Bayer, and research support from Mereo.

JA Pasco has received funding from the National Health and Medical Research Council (NHMRC) Australia, and the Medical Research Future Fund (MRFF) Australia, all unrelated to this work.

KMA Swart is an employee of the PHARMO Institute for Drug Outcomes Research. This independent research institute performs financially supported studies for government and related healthcare authorities and several pharmaceutical companies.

NC Wright sits on the Board of Trustee of the US Bone Health and Osteoporosis Foundation, and has received consulting fees from Radius and ArgenX

MC Zillikens has received honoraria in the past for lectures or advice from Alexion, Amgen, Eli Lilly, Kyowa Kirin, Shire and UCB, unrelated to the current work.

M Zwart has received research funding from national societies (SEMFYC and SEIOMM).

C Beaudart, E Biver, · Bruyère, JA Cauley, CJ Crandall, SR Cummings, JAP da Silva, B Dawson-Huges, AB Dufour, S Ferrari, Y Fujita, S Fujiwara, I Goldshtein, D Goltzman, V Gudnason, J Hall, D Hans, M Hoff, RJ Hollick, M Huisman, M Iki, S Ish-Shalom, H Johansson, G Jones, MK Karlsson, S Khosla, W-P Koh, F Koromani, H Kröger, T Kwok, · Lamy, A Langhammer, B Larijani, WD Leslie, K Lippuner, E Liu, D Mellström, T Merlijn, A Nordström, P Nordström, TW O’Neill, B Obermayer-Pietsch, F Rivadeneira, A-M Schott, EJ Shiroma, K Sigeirsdottir, EM Simonsick, E Sornay-Rendu, R Sund, KMA Swart, P Szulc, J Tamaki, DJ Torgerson, L Vandenput, NM van Schoor, TP van Staa, J Vila, NJ Wareham, N Yoshimura declare no competing interests in relation to this work.

Human and animal rights

This review does not contain any original studies with human participants or animals performed by any of the authors.

Ethics

All individual cohorts with candidate risk factors available have been approved by their local ethics committees and informed consent has been obtained from all study participants. General ethics approval for the use of these cohorts is also given by the University of Sheffield. Participant data will be stored in coded, de-identified form. Only summary statistics and aggregate data will be published, not allowing for identification of individual study participants.

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Version of record: Osteoporosis International 2023
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Osteoporosis International (2023) · doi:10.1007/s00198-023-06870-z
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2023-08-11
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  2. Living reprint on Literature Decoded2026-10-01
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Cite this article

Citation
Kanis JA, Johansson H, McCloskey EV, Liu E, Åkesson KE, Anderson FA, et al. Previous fracture and subsequent fracture risk: A meta-analysis to update FRAX. Osteoporos Int. 2023;34(12):2027–2045. doi:10.1007/s00198-023-06870-z
BibTeX
@article{Kanis2023Previous,
  title   = {Previous fracture and subsequent fracture risk: A meta-analysis to update FRAX},
  author  = {John A Kanis and Helena Johansson and Eugene V McCloskey and Enwu Liu and Kristina E Åkesson and Fred A Anderson and Rafael Azagra and Cecilie L Bager and Charlotte Beaudart and Heike A Bischoff-Ferrari and Emmanuel Biver and Olivier Bruyère and Jane A Cauley and Jacqueline R Center and Roland Chapurlat and Claus Christiansen and Cyrus Cooper and Carolyn J Crandall and Steven R Cummings and José AP da Silva and Bess Dawson-Hughes and Adolfo Diez-Perez and Alyssa B Dufour and John A Eisman and Petra JM Elders and Serge Ferrari and Yuki Fujita and Saeko Fujiwara and Claus-Christian Glüer and Inbal Goldshtein and David Goltzman and Vilmundur Gudnason and Jill Hall and Didier Hans and Mari Hoff and Rosemary J Hollick and Martijn Huisman and Masayuki Iki and Sophia Ish-Shalom and Graeme Jones and Magnus K Karlsson and Sundeep Khosla and Douglas P Kiel and Woon-Puay Koh and Fjorda Koromani and Mark A Kotowicz and Heikki Kröger and Timothy Kwok and Olivier Lamy and Arnulf Langhammer and Bagher Larijani and Kurt Lippuner and Dan Mellström and Thomas Merlijn and Anna Nordström and Peter Nordström and Terence W O’Neill and Barbara Obermayer-Pietsch and Claes Ohlsson and Eric S Orwoll and Julie A Pasco and Fernando Rivadeneira and Anne Marie Schott and Eric J Shiroma and Kristin Siggeirsdottir and Eleanor M Simonsick and Elisabeth Sornay-Rendu and Reijo Sund and Karin MA Swart and Pawel Szulc and Junko Tamaki and David J Torgerson and Natasja M van Schoor and Tjeerd P van Staa and Joan Vila and Nicholas J Wareham and Nicole C Wright and Noriko Yoshimura and M Carola Zillikens and Marta Zwart and Liesbeth Vandenput and Nicholas C Harvey and Mattias Lorentzon and William D Leslie},
  journal = {Osteoporosis International},
  year    = {2023},
  volume  = {34},
  number  = {12},
  pages   = {2027–2045},
  doi     = {10.1007/s00198-023-06870-z},
  pmid    = {37566158}
}
RIS
TY  - JOUR
TI  - Previous fracture and subsequent fracture risk: A meta-analysis to update FRAX
AU  - John A Kanis
AU  - Helena Johansson
AU  - Eugene V McCloskey
AU  - Enwu Liu
AU  - Kristina E Åkesson
AU  - Fred A Anderson
AU  - Rafael Azagra
AU  - Cecilie L Bager
AU  - Charlotte Beaudart
AU  - Heike A Bischoff-Ferrari
AU  - Emmanuel Biver
AU  - Olivier Bruyère
AU  - Jane A Cauley
AU  - Jacqueline R Center
AU  - Roland Chapurlat
AU  - Claus Christiansen
AU  - Cyrus Cooper
AU  - Carolyn J Crandall
AU  - Steven R Cummings
AU  - José AP da Silva
AU  - Bess Dawson-Hughes
AU  - Adolfo Diez-Perez
AU  - Alyssa B Dufour
AU  - John A Eisman
AU  - Petra JM Elders
AU  - Serge Ferrari
AU  - Yuki Fujita
AU  - Saeko Fujiwara
AU  - Claus-Christian Glüer
AU  - Inbal Goldshtein
AU  - David Goltzman
AU  - Vilmundur Gudnason
AU  - Jill Hall
AU  - Didier Hans
AU  - Mari Hoff
AU  - Rosemary J Hollick
AU  - Martijn Huisman
AU  - Masayuki Iki
AU  - Sophia Ish-Shalom
AU  - Graeme Jones
AU  - Magnus K Karlsson
AU  - Sundeep Khosla
AU  - Douglas P Kiel
AU  - Woon-Puay Koh
AU  - Fjorda Koromani
AU  - Mark A Kotowicz
AU  - Heikki Kröger
AU  - Timothy Kwok
AU  - Olivier Lamy
AU  - Arnulf Langhammer
AU  - Bagher Larijani
AU  - Kurt Lippuner
AU  - Dan Mellström
AU  - Thomas Merlijn
AU  - Anna Nordström
AU  - Peter Nordström
AU  - Terence W O’Neill
AU  - Barbara Obermayer-Pietsch
AU  - Claes Ohlsson
AU  - Eric S Orwoll
AU  - Julie A Pasco
AU  - Fernando Rivadeneira
AU  - Anne Marie Schott
AU  - Eric J Shiroma
AU  - Kristin Siggeirsdottir
AU  - Eleanor M Simonsick
AU  - Elisabeth Sornay-Rendu
AU  - Reijo Sund
AU  - Karin MA Swart
AU  - Pawel Szulc
AU  - Junko Tamaki
AU  - David J Torgerson
AU  - Natasja M van Schoor
AU  - Tjeerd P van Staa
AU  - Joan Vila
AU  - Nicholas J Wareham
AU  - Nicole C Wright
AU  - Noriko Yoshimura
AU  - M Carola Zillikens
AU  - Marta Zwart
AU  - Liesbeth Vandenput
AU  - Nicholas C Harvey
AU  - Mattias Lorentzon
AU  - William D Leslie
JO  - Osteoporosis International
PY  - 2023
VL  - 34
IS  - 12
SP  - 2027
EP  - 2045
DO  - 10.1007/s00198-023-06870-z
SN  - 0937-941X
UR  - https://doi.org/10.1007/s00198-023-06870-z
ER  -

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This page reproduces Previous fracture and subsequent fracture risk: A meta-analysis to update FRAX by John A Kanis, Helena Johansson, Eugene V McCloskey, Enwu Liu, Kristina E Åkesson, Fred A Anderson, Rafael Azagra, Cecilie L Bager, Charlotte Beaudart, Heike A Bischoff-Ferrari, Emmanuel Biver, Olivier Bruyère, Jane A Cauley, Jacqueline R Center, Roland Chapurlat, Claus Christiansen, Cyrus Cooper, Carolyn J Crandall, Steven R Cummings, José AP da Silva, Bess Dawson-Hughes, Adolfo Diez-Perez, Alyssa B Dufour, John A Eisman, Petra JM Elders, Serge Ferrari, Yuki Fujita, Saeko Fujiwara, Claus-Christian Glüer, Inbal Goldshtein, David Goltzman, Vilmundur Gudnason, Jill Hall, Didier Hans, Mari Hoff, Rosemary J Hollick, Martijn Huisman, Masayuki Iki, Sophia Ish-Shalom, Graeme Jones, Magnus K Karlsson, Sundeep Khosla, Douglas P Kiel, Woon-Puay Koh, Fjorda Koromani, Mark A Kotowicz, Heikki Kröger, Timothy Kwok, Olivier Lamy, Arnulf Langhammer, Bagher Larijani, Kurt Lippuner, Dan Mellström, Thomas Merlijn, Anna Nordström, Peter Nordström, Terence W O’Neill, Barbara Obermayer-Pietsch, Claes Ohlsson, Eric S Orwoll, Julie A Pasco, Fernando Rivadeneira, Anne Marie Schott, Eric J Shiroma, Kristin Siggeirsdottir, Eleanor M Simonsick, Elisabeth Sornay-Rendu, Reijo Sund, Karin MA Swart, Pawel Szulc, Junko Tamaki, David J Torgerson, Natasja M van Schoor, Tjeerd P van Staa, Joan Vila, Nicholas J Wareham, Nicole C Wright, Noriko Yoshimura, M Carola Zillikens, Marta Zwart, Liesbeth Vandenput, Nicholas C Harvey, Mattias Lorentzon, William D Leslie, first published in Osteoporosis International 2023;34(12):2027–2045, doi:10.1007/s00198-023-06870-z, PMID 37566158, PMC7615305. It is used under the CC BY 4.0 licence.

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