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Mapping EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS)

Kiadaliri, Ali LU orcid ; Alava, Monica Hernández ; Roos, Ewa M LU and Englund, Martin LU orcid (2020) In Quality of Life Research 29(1). p.265-274
Abstract

PURPOSE: To develop a mapping model to estimate EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS).

METHODS: The responses to EQ-5D-3L and KOOS questionnaires (n = 40,459 observations) were obtained from the Swedish National anterior cruciate ligament (ACL) Register for patients ≥ 18 years with the knee ACL injury. We used linear regression (LR) and beta-mixture (BM) for direct mapping and the generalized ordered probit model for response mapping (RM). We compared the distribution of the original data to the distributions of the data generated using the estimated models.

RESULTS: Models with individual KOOS subscales performed better than those with the average of KOOS subscale scores (KOOS5, KOOS4). LR... (More)

PURPOSE: To develop a mapping model to estimate EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS).

METHODS: The responses to EQ-5D-3L and KOOS questionnaires (n = 40,459 observations) were obtained from the Swedish National anterior cruciate ligament (ACL) Register for patients ≥ 18 years with the knee ACL injury. We used linear regression (LR) and beta-mixture (BM) for direct mapping and the generalized ordered probit model for response mapping (RM). We compared the distribution of the original data to the distributions of the data generated using the estimated models.

RESULTS: Models with individual KOOS subscales performed better than those with the average of KOOS subscale scores (KOOS5, KOOS4). LR had the poorest performance overall and across the range of disease severity particularly at the extremes of the distribution of severity. Compared with the RM, the BM performed better across the entire range of disease severity except the most severe range (KOOS5 < 25). Moving from the most to the least disease severity was associated with 0.785 gain in the observed EQ-5D-3L. The corresponding value was 0.743, 0.772 and 0.782 for LR, BM and RM, respectively. LR generated simulated EQ-5D-3L values outside the feasible range. The distribution of simulated data generated from the BM model was almost identical to the original data.

CONCLUSIONS: We developed mapping models to estimate EQ-5D-3L from KOOS facilitating application of KOOS in cost-utility analyses. The BM showed superior performance for estimating EQ-5D-3L from KOOS. Further validation of the estimated models in different independent samples is warranted.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Quality of Life Research
volume
29
issue
1
pages
10 pages
publisher
Springer
external identifiers
  • scopus:85074023890
  • pmid:31541386
ISSN
1573-2649
DOI
10.1007/s11136-019-02303-9
language
English
LU publication?
yes
id
1fd366db-8660-4671-b50d-87ce37b3bc7a
date added to LUP
2019-09-23 17:14:01
date last changed
2024-06-26 02:21:18
@article{1fd366db-8660-4671-b50d-87ce37b3bc7a,
  abstract     = {{<p>PURPOSE: To develop a mapping model to estimate EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS).</p><p>METHODS: The responses to EQ-5D-3L and KOOS questionnaires (n = 40,459 observations) were obtained from the Swedish National anterior cruciate ligament (ACL) Register for patients ≥ 18 years with the knee ACL injury. We used linear regression (LR) and beta-mixture (BM) for direct mapping and the generalized ordered probit model for response mapping (RM). We compared the distribution of the original data to the distributions of the data generated using the estimated models.</p><p>RESULTS: Models with individual KOOS subscales performed better than those with the average of KOOS subscale scores (KOOS5, KOOS4). LR had the poorest performance overall and across the range of disease severity particularly at the extremes of the distribution of severity. Compared with the RM, the BM performed better across the entire range of disease severity except the most severe range (KOOS5 &lt; 25). Moving from the most to the least disease severity was associated with 0.785 gain in the observed EQ-5D-3L. The corresponding value was 0.743, 0.772 and 0.782 for LR, BM and RM, respectively. LR generated simulated EQ-5D-3L values outside the feasible range. The distribution of simulated data generated from the BM model was almost identical to the original data.</p><p>CONCLUSIONS: We developed mapping models to estimate EQ-5D-3L from KOOS facilitating application of KOOS in cost-utility analyses. The BM showed superior performance for estimating EQ-5D-3L from KOOS. Further validation of the estimated models in different independent samples is warranted.</p>}},
  author       = {{Kiadaliri, Ali and Alava, Monica Hernández and Roos, Ewa M and Englund, Martin}},
  issn         = {{1573-2649}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{265--274}},
  publisher    = {{Springer}},
  series       = {{Quality of Life Research}},
  title        = {{Mapping EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS)}},
  url          = {{http://dx.doi.org/10.1007/s11136-019-02303-9}},
  doi          = {{10.1007/s11136-019-02303-9}},
  volume       = {{29}},
  year         = {{2020}},
}