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Record W4284960689 · doi:10.2106/jbjs.21.01539

Defining Minimally Important Differences in Functional Outcomes in Musculoskeletal Oncology

2022· article· en· W4284960689 on OpenAlexaffabout
Aaron Gazendam, Patricia Schneider, Mohit Bhandari, Jason W. Busse, Michelle Ghert

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineReceiver operating characteristicOrthopedic surgeryStandard deviationSurgeryPhysical therapyInternal medicineMathematicsStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Functional outcomes are commonly reported in studies of patients undergoing limb-salvage surgery for the treatment of musculoskeletal tumors; however, interpretation requires knowledge of the smallest amount of improvement that is important to patients: the minimally important difference (MID). We established the MIDs for the Musculoskeletal Tumor Society Rating Scale-93 (MSTS-93) and Toronto Extremity Salvage Score (TESS) for patients with bone tumors undergoing lower-extremity endoprosthetic reconstruction. METHODS: This study was a secondary analysis of the recently completed PARITY (Prophylactic Antibiotic Regimens in Tumor Surgery) study. We used MSTS-93 and TESS data from this trial to calculate (1) the anchor-based MIDs with use of an overall function scale and a receiver operating characteristic curve analysis and (2) the distribution-based MIDs based on one-half of the standard deviation of the change scores from baseline to the 12-month follow-up and one-half the standard deviation of baseline scores. RESULTS: Five hundred and ninety-one patients were available for analysis. The Pearson correlation coefficients for the association between changes in MSTS-93 and TESS scores and changes in the external anchor scores were 0.71 and 0.57, indicating high and moderate correlations. The anchor-based MID was 12 points for the MSTS-93 and 11 points for the TESS. Distribution-based MIDs were larger: 16 to 17 points for the MSTS-93 and 14 points for the TESS. CONCLUSIONS: Two methods for determining MIDs for the MSTS-93 and TESS for patients undergoing lower-extremity endoprosthetic reconstruction for musculoskeletal tumors yielded quantitatively different results. We suggest the use of anchor-based MIDs, which are grounded in changes in functional status that are meaningful to patients. These thresholds can facilitate responder analyses and indicate whether significant differences following interventions are clinically important to patients. LEVEL OF EVIDENCE: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.062
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.281
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations22
Published2022
Admission routes2
Has abstractyes

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