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Record W4403300728 · doi:10.1097/corr.0000000000003257

Does a Concise Patient-reported Outcome Measure Provide a Valid Measure of Physical Function for Cancer Patients After Lower Extremity Surgery?

2024· article· en· W4403300728 on OpenAlexaboutno aff
Theresa Nalty, Shalin S. Patel, Justin E. Bird, Valerae O. Lewis, Patrick P. Lin

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsnot available
FundersUniversity of California, Los Angeles
KeywordsMedicineMeasure (data warehouse)Physical therapySurgerySports medicinePatient-reported outcomeCancerOutcome (game theory)Quality of life (healthcare)Internal medicineData mining

Abstract

fetched live from OpenAlex

BACKGROUND: Current functional assessment tools for orthopaedic oncology are long surveys that contribute to patients' survey fatigue and yet lack the ability to discern meaningful differences in a patient population that is often mobile but unable to perform strenuous activities. We sought to determine whether a shorter, novel tool based on existing, validated surveys could better capture differences in a sample of orthopaedic oncology patients. QUESTIONS/PURPOSES: (1) Can a concise fixed-item functional tool derived from the 50 items in the Toronto Extremity Salvage Score for the lower extremity (TESS LE) and the Lower Extremity Functional Scale (LEFS) demonstrate similar responsiveness in terms of sensitivity and specificity? (2) What is the precision and accuracy of the concise tool compared with the TESS LE and LEFS? METHODS: Functional outcome data were collected and maintained in a longitudinally maintained database at a single institution. Patients were included in the study if (1) they had undergone a tumor excision or a nononcologic orthopaedic procedure (for example, arthroplasty for osteoarthritis) for a bone or soft tissue tumor affecting lower extremity function, and (2) they had completed the LEFS, TESS LE, and Patient-Reported Outcomes Measurement Information System (PROMIS) global health tool on at least two clinic visits. Between September 2014 and April 2022, we treated 14,234 patients for primary bone or soft tissue sarcoma, metastatic disease to bone, or orthopaedic sequelae of chronic cancer care. Approximately 6% (854 of 14,234) were excluded due to the need of a language translator. Approximately 2% (278 of 13,380) refused or were unable to participate. Seventy-two percent (9433 of 13,102) of the patients had an operation on a lower extremity. Of these, 4% (339 of 9433) of the patients completed the TESS LE, LEFS, and Item 3 of the PROMIS global health tool on ≥ 2 clinic visits. Of the patients in the current study, 49% (167 of 339) were women, and 27% (93 of 339) had metastatic carcinoma. Twelve percent (41 of 339) of the patients died before the end of the study period. Spearman rank-order correlation, principal component analysis (PCA), and item response theory (IRT) modeling identified 14 highly discriminating items from the TESS LE and LEFS. Multiple linear stepwise regression (MLSR) was performed with the dependent variable being the summary score of the 14 items derived from the TESS LE and LEFS and standardized to a percentage of 100. The beta coefficient from the MLSR was used to derive a weight for each of the 14 items. Evaluation of the model with 10 to 17 variables was performed to ensure that the model with the 14 items met the most criteria for fit with the PCA, the receiver operating characteristic (ROC) curve, and the IRT modeling criteria. The responsiveness (sensitivity and specificity) of the change scores in the shortened 14-item survey, the 30-item TESS LE, and the 20-item LEFS as compared with the dichotomized changes in Item 3 of the PROMIS global health tool was evaluated using ROCs. The concordance (accuracy and precision) of the 14 items derived from the LEFS and TESS LE was evaluated. RESULTS: The responsiveness (sensitivity and specificity) of the shortened 14-item survey, the TESS LE, and the LEFS to the criterion target of the PROMIS global health tool (Item 3) was similar, with areas under the curve (AUCs) ranging from 0.62 to 0.65 for the ROC curves. The responsiveness of the 14-item survey to the TESS LE showed sensitivity of 96% and specificity of 90%, with an AUC of 0.98 (p < 0.001). The responsiveness of the 14 items to the LEFS showed sensitivity of 95% and specificity of 86%, with an AUC of 0.96. The validity of the 14 items to the TESS LE was measured by concordance, with a precision of 0.98 and an accuracy of 0.97. Concordance of the 14 items to the LEFS showed a precision of 0.98 and accuracy of 0.83. CONCLUSION: The concise 14 items derived from patient-reported responses in the TESS LE and LEFS outcome measures showed similar responsiveness (sensitivity and specificity) as the original TESS LE and LEFS for cancer patients after lower extremity orthopaedic surgery performed for oncologic and nononcologic indications. The concise 14 items have a similar ability to the TESS LE and LEFS to tell the clinician or patient how they are functioning compared with other patients. These 14 items are shorter than the combined 50 items of the TESS LE and LEFS while retaining the capacity to describe a broad range of lower extremity function for orthopaedic oncology patients. We have named the 14-item survey the Lower Extremity Oncology Functional Assessment Tool (LEO).Level of Evidence Level II, diagnostic study.

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)0.011
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.060
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.122
GPT teacher head0.421
Teacher spread0.299 · 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 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".

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Citations6
Published2024
Admission routes1
Has abstractyes

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