A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

for the CaMos Research Group

doi:10.1002/jbmr.4100

A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

for the CaMos Research Group

Epidemiology & Community Health

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research.

Original language	English (US)
Pages (from-to)	1923-1934
Number of pages	12
Journal	Journal of Bone and Mineral Research
Volume	35
Issue number	10
DOIs	https://doi.org/10.1002/jbmr.4100
State	Published - Oct 1 2020

Bibliographical note

Funding Information:
We thank Professor Chris Jackson (MRC Biostatistics Unit, Cambridge, UK), the author of the msm and fic R packages, for his valuable help for data analyses. This work was supported by the National Health Medical Research Council Australia Projects 1070187 (to TT, DA, JAE, TVN, and JRC), 1008219 (to JRC), and 1073430 (to DB). DB was supported by a fellowship from Australian and New Zealand Bone and Mineral Society. Other funding bodies were an Osteoporosis Australia-Amgen grant and the Mrs Gibson and Ernst Heine Family Foundation. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. The Canadian Multicentre Osteoporosis Study was funded by the Canadian Institutes of Health Research (CIHR); Merck Frosst Canada Ltd.; Eli Lilly Canada Inc.; Novartis Pharmaceuticals Inc.; The Alliance: sanofi-aventis & Procter and Gamble Pharmaceuticals Canada Inc.; Servier Canada Inc.; Amgen Canada Inc.; The Dairy Farmers of Canada; and The Arthritis Society. Authors? roles: Study design: TT, DB, HMP, TVN, and JRC. Data analysis: TT, HMP, TVN, and JRC. Data interpretation: all authors. Drafting the manuscript: TT, TVN, and JRC. Revising the manuscript contents and approving the final version of the manuscript: all authors.

Funding Information:
TT, DB, HMP, TvG, CB, DAH, RGJ, CSK, SMK, and JCP have no competing interests to declare. JDA has received research grants and/or personal fees from Amgen and Eli Lilly. JvdB has consulted for and/or received research funding from Amgen, MSD, and Eli Lilly. JAE has consulted for and/or received research funding from Amgen, Eli Lilly, Merck Sharp and Dohme, and Sanofi‐Aventis. PG was advisory member for Amgen, has received speaker fees and/or research grants from Amgen, Pfizer, MSD, UCB, Abbott, Eli Lilly, BMS, Novartis, Roche, and Will Pharma. DG has consulted for and received research funding from Amgen. LL has received research funding from Merck and Abbott Nutrition. TVN has received honoraria for consulting and symposia from Merck Sharp and Dohme, Roche, Servier, Sanofi‐Aventis, and Novartis. JRC has consulted for and/or given educational talks for Merck Sharp and Dohme, Amgen, Actavis, and Sanofi‐Aventis.

Funding Information:
We thank Professor Chris Jackson (MRC Biostatistics Unit, Cambridge, UK), the author of the and R packages, for his valuable help for data analyses. This work was supported by the National Health Medical Research Council Australia Projects 1070187 (to TT, DA, JAE, TVN, and JRC), 1008219 (to JRC), and 1073430 (to DB). DB was supported by a fellowship from Australian and New Zealand Bone and Mineral Society. Other funding bodies were an Osteoporosis Australia‐Amgen grant and the Mrs Gibson and Ernst Heine Family Foundation. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. The Canadian Multicentre Osteoporosis Study was funded by the Canadian Institutes of Health Research (CIHR); Merck Frosst Canada Ltd.; Eli Lilly Canada Inc.; Novartis Pharmaceuticals Inc.; The Alliance: sanofi‐aventis & Procter and Gamble Pharmaceuticals Canada Inc.; Servier Canada Inc.; Amgen Canada Inc.; The Dairy Farmers of Canada; and The Arthritis Society. msm fic

Publisher Copyright:
© 2020 American Society for Bone and Mineral Research

Keywords

FRAGILITY FRACTURE
MORTALITY
MULTISTATE PREDICTION MODEL
OSTEOPOROSIS
SUBSEQUENT FRACTURE

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/jbmr.4100

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@article{90594edad49d4b598a3a2597a1afb25a,

title = "A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly",

abstract = "Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. {\textcopyright} 2020 American Society for Bone and Mineral Research.",

keywords = "FRAGILITY FRACTURE, MORTALITY, MULTISTATE PREDICTION MODEL, OSTEOPOROSIS, SUBSEQUENT FRACTURE",

author = "{for the CaMos Research Group} and Thach Tran and Dana Bliuc and Pham, {Hanh M.} and {van Geel}, Tineke and Adachi, {Jonathan D.} and Claudie Berger and {van den Bergh}, Joop and Eisman, {John A.} and Piet Geusens and David Goltzman and Hanley, {David A.} and Josse, {Robert G.} and Kaiser, {Stephanie M.} and Kovacs, {Christopher S.} and Lisa Langsetmo and Prior, {Jerilynn C.} and Nguyen, {Tuan V.} and Center, {Jacqueline R.}",

note = "Funding Information: We thank Professor Chris Jackson (MRC Biostatistics Unit, Cambridge, UK), the author of the msm and fic R packages, for his valuable help for data analyses. This work was supported by the National Health Medical Research Council Australia Projects 1070187 (to TT, DA, JAE, TVN, and JRC), 1008219 (to JRC), and 1073430 (to DB). DB was supported by a fellowship from Australian and New Zealand Bone and Mineral Society. Other funding bodies were an Osteoporosis Australia-Amgen grant and the Mrs Gibson and Ernst Heine Family Foundation. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. The Canadian Multicentre Osteoporosis Study was funded by the Canadian Institutes of Health Research (CIHR); Merck Frosst Canada Ltd.; Eli Lilly Canada Inc.; Novartis Pharmaceuticals Inc.; The Alliance: sanofi-aventis & Procter and Gamble Pharmaceuticals Canada Inc.; Servier Canada Inc.; Amgen Canada Inc.; The Dairy Farmers of Canada; and The Arthritis Society. Authors? roles: Study design: TT, DB, HMP, TVN, and JRC. Data analysis: TT, HMP, TVN, and JRC. Data interpretation: all authors. Drafting the manuscript: TT, TVN, and JRC. Revising the manuscript contents and approving the final version of the manuscript: all authors. Funding Information: TT, DB, HMP, TvG, CB, DAH, RGJ, CSK, SMK, and JCP have no competing interests to declare. JDA has received research grants and/or personal fees from Amgen and Eli Lilly. JvdB has consulted for and/or received research funding from Amgen, MSD, and Eli Lilly. JAE has consulted for and/or received research funding from Amgen, Eli Lilly, Merck Sharp and Dohme, and Sanofi‐Aventis. PG was advisory member for Amgen, has received speaker fees and/or research grants from Amgen, Pfizer, MSD, UCB, Abbott, Eli Lilly, BMS, Novartis, Roche, and Will Pharma. DG has consulted for and received research funding from Amgen. LL has received research funding from Merck and Abbott Nutrition. TVN has received honoraria for consulting and symposia from Merck Sharp and Dohme, Roche, Servier, Sanofi‐Aventis, and Novartis. JRC has consulted for and/or given educational talks for Merck Sharp and Dohme, Amgen, Actavis, and Sanofi‐Aventis. Funding Information: We thank Professor Chris Jackson (MRC Biostatistics Unit, Cambridge, UK), the author of the and R packages, for his valuable help for data analyses. This work was supported by the National Health Medical Research Council Australia Projects 1070187 (to TT, DA, JAE, TVN, and JRC), 1008219 (to JRC), and 1073430 (to DB). DB was supported by a fellowship from Australian and New Zealand Bone and Mineral Society. Other funding bodies were an Osteoporosis Australia‐Amgen grant and the Mrs Gibson and Ernst Heine Family Foundation. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. The Canadian Multicentre Osteoporosis Study was funded by the Canadian Institutes of Health Research (CIHR); Merck Frosst Canada Ltd.; Eli Lilly Canada Inc.; Novartis Pharmaceuticals Inc.; The Alliance: sanofi‐aventis & Procter and Gamble Pharmaceuticals Canada Inc.; Servier Canada Inc.; Amgen Canada Inc.; The Dairy Farmers of Canada; and The Arthritis Society. msm fic Publisher Copyright: {\textcopyright} 2020 American Society for Bone and Mineral Research",

year = "2020",

month = oct,

day = "1",

doi = "10.1002/jbmr.4100",

language = "English (US)",

volume = "35",

pages = "1923--1934",

journal = "Journal of Bone and Mineral Research",

issn = "0884-0431",

publisher = "Wiley-Blackwell",

number = "10",

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TY - JOUR

T1 - A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

AU - for the CaMos Research Group

AU - Tran, Thach

AU - Bliuc, Dana

AU - Pham, Hanh M.

AU - van Geel, Tineke

AU - Adachi, Jonathan D.

AU - Berger, Claudie

AU - van den Bergh, Joop

AU - Eisman, John A.

AU - Geusens, Piet

AU - Goltzman, David

AU - Hanley, David A.

AU - Josse, Robert G.

AU - Kaiser, Stephanie M.

AU - Kovacs, Christopher S.

AU - Langsetmo, Lisa

AU - Prior, Jerilynn C.

AU - Nguyen, Tuan V.

AU - Center, Jacqueline R.

N1 - Funding Information: We thank Professor Chris Jackson (MRC Biostatistics Unit, Cambridge, UK), the author of the msm and fic R packages, for his valuable help for data analyses. This work was supported by the National Health Medical Research Council Australia Projects 1070187 (to TT, DA, JAE, TVN, and JRC), 1008219 (to JRC), and 1073430 (to DB). DB was supported by a fellowship from Australian and New Zealand Bone and Mineral Society. Other funding bodies were an Osteoporosis Australia-Amgen grant and the Mrs Gibson and Ernst Heine Family Foundation. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. The Canadian Multicentre Osteoporosis Study was funded by the Canadian Institutes of Health Research (CIHR); Merck Frosst Canada Ltd.; Eli Lilly Canada Inc.; Novartis Pharmaceuticals Inc.; The Alliance: sanofi-aventis & Procter and Gamble Pharmaceuticals Canada Inc.; Servier Canada Inc.; Amgen Canada Inc.; The Dairy Farmers of Canada; and The Arthritis Society. Authors? roles: Study design: TT, DB, HMP, TVN, and JRC. Data analysis: TT, HMP, TVN, and JRC. Data interpretation: all authors. Drafting the manuscript: TT, TVN, and JRC. Revising the manuscript contents and approving the final version of the manuscript: all authors. Funding Information: TT, DB, HMP, TvG, CB, DAH, RGJ, CSK, SMK, and JCP have no competing interests to declare. JDA has received research grants and/or personal fees from Amgen and Eli Lilly. JvdB has consulted for and/or received research funding from Amgen, MSD, and Eli Lilly. JAE has consulted for and/or received research funding from Amgen, Eli Lilly, Merck Sharp and Dohme, and Sanofi‐Aventis. PG was advisory member for Amgen, has received speaker fees and/or research grants from Amgen, Pfizer, MSD, UCB, Abbott, Eli Lilly, BMS, Novartis, Roche, and Will Pharma. DG has consulted for and received research funding from Amgen. LL has received research funding from Merck and Abbott Nutrition. TVN has received honoraria for consulting and symposia from Merck Sharp and Dohme, Roche, Servier, Sanofi‐Aventis, and Novartis. JRC has consulted for and/or given educational talks for Merck Sharp and Dohme, Amgen, Actavis, and Sanofi‐Aventis. Funding Information: We thank Professor Chris Jackson (MRC Biostatistics Unit, Cambridge, UK), the author of the and R packages, for his valuable help for data analyses. This work was supported by the National Health Medical Research Council Australia Projects 1070187 (to TT, DA, JAE, TVN, and JRC), 1008219 (to JRC), and 1073430 (to DB). DB was supported by a fellowship from Australian and New Zealand Bone and Mineral Society. Other funding bodies were an Osteoporosis Australia‐Amgen grant and the Mrs Gibson and Ernst Heine Family Foundation. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. The Canadian Multicentre Osteoporosis Study was funded by the Canadian Institutes of Health Research (CIHR); Merck Frosst Canada Ltd.; Eli Lilly Canada Inc.; Novartis Pharmaceuticals Inc.; The Alliance: sanofi‐aventis & Procter and Gamble Pharmaceuticals Canada Inc.; Servier Canada Inc.; Amgen Canada Inc.; The Dairy Farmers of Canada; and The Arthritis Society. msm fic Publisher Copyright: © 2020 American Society for Bone and Mineral Research

PY - 2020/10/1

Y1 - 2020/10/1

N2 - Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research.

AB - Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research.

KW - FRAGILITY FRACTURE

KW - MORTALITY

KW - MULTISTATE PREDICTION MODEL

KW - OSTEOPOROSIS

KW - SUBSEQUENT FRACTURE

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DO - 10.1002/jbmr.4100

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VL - 35

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EP - 1934

JO - Journal of Bone and Mineral Research

JF - Journal of Bone and Mineral Research

IS - 10

ER -

A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

Abstract

Bibliographical note

Keywords

UN SDGs

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