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Knee osteoarthritis and time-to all-cause mortality in six community based cohorts: an international meta-analysis of individual participant-level data

Knee osteoarthritis and time-to all-cause mortality in six community based cohorts: an international meta-analysis of individual participant-level data
Knee osteoarthritis and time-to all-cause mortality in six community based cohorts: an international meta-analysis of individual participant-level data
Background: Osteoarthritis (OA) is a chronic joint disease, with increasing global burden of disability and healthcare utilisation. Recent meta-analyses have shown a range of effects of OA on mortality, reflecting different OA definitions and study methods. We seek to overcome limitations introduced when using aggregate results by gathering individual participant-level data (IPD) from international observational studies and standardising methods to determine the association of knee OA with mortality in the general population.

Methods: Seven community-based cohorts were identified containing knee OA-related pain, radiographs, and time-to-mortality, six of which were available for analysis. A two-stage IPD meta-analysis framework was applied: (1) Cox proportional hazard models assessed time-to-mortality of participants with radiographic OA (ROA), OA-related pain (POA), and a combination of pain and ROA (PROA) against pain and ROA-free participants; (2) hazard ratios (HR) were then pooled using the Hartung-Knapp modification for random-effects meta-analysis.

Findings: 10,723 participants in six cohorts from four countries were included in the analyses. Multivariable models (adjusting for age, sex, race, BMI, smoking, alcohol consumption, cardiovascular disease, and diabetes) showed a pooled HR, compared to pain and ROA-free participants, of 1.03 (0.83, 1.28) for ROA, 1.35 (1.12, 1.63) for POA, and 1.37 (1.22, 1.54) for PROA.

Discussion: Participants with POA or PROA had a 35-37% increased association with reduced time-to-mortality, independent of confounders. ROA showed no association with mortality, suggesting that OA-related knee pain may be driving the association with time-to-mortality.
Knee, Meta-analysis, Mortality, Osteoarthritis
1594-0667
529-545
Leyland, Kirsten M.
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Gates, Lucy
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Sanchez-Santos, Maria T.
3287c8bd-6e98-45a5-9198-431de4e5f9c8
Nevitt, Michael
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Felson, David
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Jones, Graeme
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Jordan, Joanne M
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Judge, Andrew
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Alhambra, Dani Prieto
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Yoshimura, Noriko
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Newton, Julia
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Callahan, Leigh F.
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Cooper, Cyrus
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Batt, Mark
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Lin, Jianhao
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Liu, Qiang
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Cleveland, Rebecca
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Collins, Gary
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Arden, Nigel K.
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Leyland, Kirsten M.
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Gates, Lucy
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Sanchez-Santos, Maria T.
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Nevitt, Michael
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Felson, David
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Jones, Graeme
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Jordan, Joanne M
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Judge, Andrew
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Alhambra, Dani Prieto
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Yoshimura, Noriko
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Newton, Julia
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Callahan, Leigh F.
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Cooper, Cyrus
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Batt, Mark
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Lin, Jianhao
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Liu, Qiang
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Cleveland, Rebecca
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Collins, Gary
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Arden, Nigel K.
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Leyland, Kirsten M., Gates, Lucy, Sanchez-Santos, Maria T., Nevitt, Michael, Felson, David, Jones, Graeme, Jordan, Joanne M, Judge, Andrew, Alhambra, Dani Prieto, Yoshimura, Noriko, Newton, Julia, Callahan, Leigh F., Cooper, Cyrus, Batt, Mark, Lin, Jianhao, Liu, Qiang, Cleveland, Rebecca, Collins, Gary and Arden, Nigel K. (2021) Knee osteoarthritis and time-to all-cause mortality in six community based cohorts: an international meta-analysis of individual participant-level data. Aging Clinical and Experimental Research, 33 (3), 529-545. (doi:10.1007/s40520-020-01762-2).

Record type: Article

Abstract

Background: Osteoarthritis (OA) is a chronic joint disease, with increasing global burden of disability and healthcare utilisation. Recent meta-analyses have shown a range of effects of OA on mortality, reflecting different OA definitions and study methods. We seek to overcome limitations introduced when using aggregate results by gathering individual participant-level data (IPD) from international observational studies and standardising methods to determine the association of knee OA with mortality in the general population.

Methods: Seven community-based cohorts were identified containing knee OA-related pain, radiographs, and time-to-mortality, six of which were available for analysis. A two-stage IPD meta-analysis framework was applied: (1) Cox proportional hazard models assessed time-to-mortality of participants with radiographic OA (ROA), OA-related pain (POA), and a combination of pain and ROA (PROA) against pain and ROA-free participants; (2) hazard ratios (HR) were then pooled using the Hartung-Knapp modification for random-effects meta-analysis.

Findings: 10,723 participants in six cohorts from four countries were included in the analyses. Multivariable models (adjusting for age, sex, race, BMI, smoking, alcohol consumption, cardiovascular disease, and diabetes) showed a pooled HR, compared to pain and ROA-free participants, of 1.03 (0.83, 1.28) for ROA, 1.35 (1.12, 1.63) for POA, and 1.37 (1.22, 1.54) for PROA.

Discussion: Participants with POA or PROA had a 35-37% increased association with reduced time-to-mortality, independent of confounders. ROA showed no association with mortality, suggesting that OA-related knee pain may be driving the association with time-to-mortality.

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Knee osteoarthritis and time-to all-cause mortality in six community based cohorts - Accepted Manuscript
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Accepted/In Press date: 26 November 2020
e-pub ahead of print date: 15 February 2021
Keywords: Knee, Meta-analysis, Mortality, Osteoarthritis

Identifiers

Local EPrints ID: 445656
URI: http://eprints.soton.ac.uk/id/eprint/445656
ISSN: 1594-0667
PURE UUID: 1eb10efb-e8db-47de-97e2-ced104ca7153
ORCID for Lucy Gates: ORCID iD orcid.org/0000-0002-8627-3418
ORCID for Cyrus Cooper: ORCID iD orcid.org/0000-0003-3510-0709

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Date deposited: 05 Jan 2021 17:32
Last modified: 22 Nov 2021 08:17

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Contributors

Author: Kirsten M. Leyland
Author: Lucy Gates ORCID iD
Author: Maria T. Sanchez-Santos
Author: Michael Nevitt
Author: David Felson
Author: Graeme Jones
Author: Joanne M Jordan
Author: Andrew Judge
Author: Dani Prieto Alhambra
Author: Noriko Yoshimura
Author: Julia Newton
Author: Leigh F. Callahan
Author: Cyrus Cooper ORCID iD
Author: Mark Batt
Author: Jianhao Lin
Author: Qiang Liu
Author: Rebecca Cleveland
Author: Gary Collins
Author: Nigel K. Arden

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