Exploring the Potential of Electronic Patient-Reported Outcome Measures to Inform and Assess Care in Sarcoma Centers
Bibliographic record
Abstract
BACKGROUND: Electronic patient-reported outcome measures (ePROMs) are useful tools to assess care needs of patients diagnosed with cancer and to monitor their symptoms along the illness trajectory. Studies regarding the application of ePROMs by advanced practice nurses (APNs) specialized in sarcoma care and the use of such electronic measures for care planning and assessing quality of care are lacking. OBJECTIVE: To explore the potential of ePROMs in clinical practice for assessing the patient's quality of life, physical functionality, needs, and fear of progression, as well as distress and the quality of care in sarcoma centers. METHODS: A multicenter longitudinal pilot study design was chosen. Three sarcoma centers with and without APN service located in Switzerland were included. The instruments EQ-5D-5L, Pearman Mayo Survey of Needs, the National Comprehensive Cancer Network Distress Thermometer, PA-F12, and Toronto Extremity Salvage Score were used as ePROMs. Data were analyzed descriptively. RESULTS: Overall, 55 patients participated in the pilot study; 33 (60%) received an intervention by an APN, and 22 (40%) did not. Patients in sarcoma centers with APN service reported overall higher scores in quality of life and functional outcome. The number of needs and distress level were lower in sarcoma centers with APN service. No differences were found with respect to patients' fear of progression. CONCLUSIONS: Most of the ePROMs proved to be reasonable in clinical practice. PA-F12 has shown low clinical relevance. IMPLICATIONS FOR PRACTICE: Using ePROMs appears to be reasonable to obtain clinically relevant patient information and to evaluate the quality of care in sarcoma centers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".