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Record W2920850891 · doi:10.1016/j.jot.2019.02.004

Patient-Reported Outcomes Measurement Information System physical function correlates with Toronto Extremity Salvage Score in an orthopaedic oncology population

2019· article· en· W2920850891 on OpenAlexaboutno aff
Kristen L. Ploetze, Jay F. Dalton, Ryan P. Calfee, Douglas J. McDonald, Regis J. O’Keefe, Cara A. Cipriano

Bibliographic record

VenueJournal of Orthopaedic Translation · 2019
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePatient-Reported Outcomes Measurement Information SystemConfidence intervalComputerized adaptive testingCeiling effectPhysical therapyPopulationDepression (economics)CorrelationInternal medicinePsychometricsClinical psychology

Abstract

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BACKGROUND: The National Institute of Health's Patient-Reported Outcomes Measurement Information System (PROMIS) uses computerised-adaptive testing to reduce survey burden and improve sensitivity. PROMIS is being used across medical and surgical disciplines but has not been studied in orthopaedic oncology. QUESTIONS/PURPOSES: The aim of the study was to compare PROMIS measures with upper extremity (UE) and lower extremity (LE) Toronto Extremity Salvage Score (TESS) by assessing the following: (1) responder burden, (2) correlation between scores and (3) floor/ceiling effects. PATIENTS AND METHODS: This cross-sectional trial analysed all 97 adult patients treated surgically for a bone or soft tissue tumour at a tertiary institution between November 2015 and March 2016. TESS (UE or LE) and PROMIS (Physical Function, Pain Interference and Depression) surveys were administered preoperatively. Pearson correlations between each PROMIS domain and TESS were calculated, as were floor/ceiling effects of each outcome measure. RESULTS: (1) Completion of three PROMIS questionnaires required a mean total of 16.8 (+/- 5.8 standard deviation) questions, compared with 31 and 32 questions for the LE and UE TESS questionnaires, respectively. (2) The PROMIS Physical Function scores demonstrated a strong positive correlation with the LE TESS (r = 0.84; 95% confidence interval [CI], 0.72-0.91; p < 0.001) and moderate positive correlation with the UE TESS (r = 0.64; 95% CI, 0.34-0.83; p = 0.055). The PROMIS Depression scores demonstrated a weak negative correlation with both the LE TESS (r = -0.38; 95% CI, -0.61 to -0.10; p = 0.010) and with UE TESS (r = -0.38; 95% CI, -0.67 to -0.01; p = 0.055). The PROMIS Pain Interference scores demonstrated a strong negative correlation with the LE TESS (r = -0.71; 95% CI, -0.83 to -0.52; p < 0.001) and a moderate negative correlation with the UE TESS (r = -0.62; 95% CI, -0.81 to -0.30; p = 0.001). (3) The UE TESS had a range of scores from 16 to 100 with a 27% ceiling effect and no floor effect, and the LE TESS had a range from 10 to 98 with no floor or ceiling effect. There was no floor or ceiling effect for any PROMIS measures. CONCLUSIONS: In an orthopaedic oncology population, the PROMIS Physical Function and Pain Interference scores correlate with the TESS and have the benefit of reduced survey burden and ceiling effect. The PROMIS Depression scores may provide additional information regarding patient outcomes not captured by the TESS. LEVEL OF EVIDENCE: Level III. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: Patient reported outcome measures asses patients' symptoms, function and health-related quality of life and are designed to capture more clinical information than can be gathered by objective medial testing alone. As reimbursements and the understanding of patient outcomes are becoming tied to performance on PROMIS measures, it is an important step to establish how PROMIS measures correlate and compare to traditional legacy measures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.270
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2019
Admission routes1
Has abstractyes

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