Cross-cultural adaptation and validation of a self-reporting tool to assess health-related quality of life for Egyptians with extremity bone sarcomas in childhood or adolescence
Bibliographic record
Abstract
Validated self-reporting tools are required to evaluate the functional outcome and health-related quality of life (HRQOL) for those who had extremity bone sarcomas in their childhood or adolescence. Our study pursued cross-cultural adaptation and validation of the pediatric Toronto Extremity Salvage Score (pTESS) and Toronto Extremity Salvage Score (TESS) to assess the functional outcome for Egyptian children and adult survivors following surgeries of extremity bone sarcomas. In the modified versions of pTESS and TESS, mental domains were added to allow the evaluation of HRQOL using a specific instrument for childhood bone cancer.The internal consistency and test-retest reliability of the studied forms were assessed with Cronbach's alpha and Intra-class coefficients (ICC), respectively. For convergent validity, correlations between scores of the generic Pediatric Quality of Life Inventory (PedsQL 4.0) and pTESS /TESS scores were reported. Factor Analysis was feasible for pTESS-leg; due to the insufficient samples, only the average inter-item correlation coefficients were reported for the remaining versions.Out of 233 participants, 134 responded to pTESS-leg, 53 to TESS-leg, 36 to pTESS-arm, and only 10 to TESS-arm. All versions showed excellent internal consistency (Cronbach's alpha >0.9), good test-retest reliability (ICC >0.8), moderate to strong correlations with PedsQL, and acceptable average inter-item correlation coefficients (≥0.3). Three factors were extracted for the pTESS-leg, in which all mental items were loaded on one separate factor with factor loadings exceeding 0.4. Active chemotherapy, less than one year from primary surgery, or tibial tumors were associated with significantly inferior pTESS/TESS scores in the lower extremity group.The Egyptian pTESS and TESS are valid and reliable self-reporting tools for assessing the functional outcome following surgeries for extremity bone sarcomas. The modified pTESS and TESS versions, which include additional mental domains, enabled the assessment of the overall health status of our population. Future studies should include a larger sample size and evaluate the ability of pTESS/TESS to track progress over time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".