PMID- 36222103
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20221108
IS  - 2633-1462 (Electronic)
IS  - 2633-1462 (Linking)
VI  - 3
IP  - 10
DP  - 2022 Oct
TI  - Computerized adaptive testing for the Oxford Hip, Knee, Shoulder, and Elbow 
      scores : accurate measurement from fewer, and more patient-focused, questions.
PG  - 786-794
LID - 10.1302/2633-1462.310.BJO-2022-0073.R1 [doi]
AB  - AIMS: The aim of this study was to develop and evaluate machine-learning-based 
      computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee 
      Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and 
      its subscales. METHODS: We developed CAT algorithms for the OHS, OKS, OSS, 
      overall OES, and each of the OES subscales, using responses to the full-length 
      questionnaires and a machine-learning technique called regression tree learning. 
      The algorithms were evaluated through a series of simulation studies, in which 
      they aimed to predict respondents' full-length questionnaire scores from only a 
      selection of their item responses. In each case, the total number of items used 
      by the CAT algorithm was recorded and CAT scores were compared to full-length 
      questionnaire scores by mean, SD, score distribution plots, Pearson's correlation 
      coefficient, intraclass correlation (ICC), and the Bland-Altman method. 
      Differences between CAT scores and full-length questionnaire scores were 
      contextualized through comparison to the instruments' minimal clinically 
      important difference (MCID). RESULTS: The CAT algorithms accurately estimated 
      12-item questionnaire scores from between four and nine items. Scores followed a 
      very similar distribution between CAT and full-length assessments, with the mean 
      score difference ranging from 0.03 to 0.26 out of 48 points. Pearson's 
      correlation coefficient and ICC were 0.98 for each 12-item scale and 0.95 or 
      higher for the OES subscales. In over 95% of cases, a patient's CAT score was 
      within five points of the full-length questionnaire score for each 12-item 
      questionnaire. CONCLUSION: Oxford Hip Score, Oxford Knee Score, Oxford Shoulder 
      Score, and Oxford Elbow Score (including separate subscale scores) CATs all 
      markedly reduce the burden of items to be completed without sacrificing score 
      accuracy.Cite this article: Bone Jt Open 2022;3(10):786-794.
FAU - Harrison, Conrad J
AU  - Harrison CJ
AUID- ORCID: 0000-0002-1428-5751
AD  - Methodology Oxford Limited, London, UK.
FAU - Plummer, Otho R
AU  - Plummer OR
AUID- ORCID: 0000-0002-6037-4069
AD  - Universal Research Solutions, Columbia, Missouri, USA.
FAU - Dawson, Jill
AU  - Dawson J
AUID- ORCID: 0000-0002-2358-1333
AD  - Nuffield Department of Population Health, University of Oxford, Oxford, UK.
FAU - Jenkinson, Crispin
AU  - Jenkinson C
AUID- ORCID: 0000-0002-3692-0779
AD  - Nuffield Department of Population Health, University of Oxford, Oxford, UK.
FAU - Hunt, Audrey
AU  - Hunt A
AUID- ORCID: 0000-0001-5197-9413
AD  - Universal Research Solutions, Columbia, Missouri, USA.
FAU - Rodrigues, Jeremy N
AU  - Rodrigues JN
AUID- ORCID: 0000-0002-9347-5026
AD  - Methodology Oxford Limited, London, UK.
LA  - eng
PT  - Journal Article
PL  - England
TA  - Bone Jt Open
JT  - Bone & joint open
JID - 101770336
PMC - PMC9626870
OTO - NOTNLM
OT  - Computerized adaptive testing
OT  - Hip
OT  - Knee
OT  - Machine-learning
OT  - Oxford Elbow Score
OT  - Oxford Hip Score
OT  - Oxford Hip Score (OHS)
OT  - Oxford Knee Score
OT  - Oxford Shoulder Score
OT  - Patient-reported outcome measures
OT  - Pearson's correlation coefficient
OT  - Shoulder
OT  - elbow
OT  - intraclass correlation
COIS- ICMJE COI statement: C. Harrison and J. N. Rodrigues are Directors of Methodology 
      Oxford Ltd, which was commissioned to assist with this work through Oxford 
      University Innovation consultancy services. J. N. Rodrigues also reports project 
      grants from NIHR (unrelated to this study), and is Chair of the British Society 
      for Surgery of the Hand UK Hand Registry and an unpaid BSSH Council member. J. 
      Dawson reports a grant from NIHR (Research for Patient Benefit ref 
      PB-PG-1217-20017 1/10/19-30/09/21) for development and validation of the GCA PRO 
      questionnaire, and royalties and consulting fees from Oxford University 
      Innovation, all of which are unrelated to this study. C. Harrison is also funded 
      by an NIHR Doctoral Research Fellowship (NIHR300684) for similar work, unrelated 
      to this study.
EDAT- 2022/10/13 06:00
MHDA- 2022/10/13 06:01
PMCR- 2022/10/10
CRDT- 2022/10/12 04:32
PHST- 2022/10/12 04:32 [entrez]
PHST- 2022/10/13 06:00 [pubmed]
PHST- 2022/10/13 06:01 [medline]
PHST- 2022/10/10 00:00 [pmc-release]
AID - BJO-3-786 [pii]
AID - 10.1302/2633-1462.310.BJO-2022-0073.R1 [doi]
PST - ppublish
SO  - Bone Jt Open. 2022 Oct;3(10):786-794. doi: 
      10.1302/2633-1462.310.BJO-2022-0073.R1.