Preliminary validation of the Edmonton Symptom Assessment Scale – Acute Leukemia (ESAS-AL) in patients with acute leukemia (AL).
Bibliographic record
Abstract
210 Background: Patients with AL have numerous symptoms resulting from their disease and its treatment. Here we report on a preliminary evaluation of an ESAS version including AL-specific symptoms (ESAS-AL). Methods: Forty-two inpatients with newly-diagnosed AL (31 AML, 11 ALL), receiving induction chemotherapy, completed baseline assessments with the ESAS-AL and the Memorial Symptom Assessment Scale (MSAS) as part of a clinical trial. The ESAS-AL includes the nine usual ESAS symptoms (rated from 0-10), as well as five symptoms reported by patients with AL in a previous longitudinal study: trouble sleeping, mouth sores, diarrhea, constipation, and itching. Correlations between each ESAS symptom and the corresponding MSAS symptom (rated 1-4) were calculated using Spearman’s correlation. Results: The mean age was 52.86 (SD 15.84). Most correlations were moderate to large and were highly significant (Table). Correlations ranged from 0.86 (ESAS-AL/MSAS Itching) to 0.20 (ESAS-AL Anxiety/MSAS Worried). Correlations for 4 physical symptoms specific to ESAS-AL (itching, diarrhea, mouth sores, and constipation) were among the highest (rs>.70). Correlations between ESAS-AL trouble sleeping and MSAS difficulty sleeping and between ESAS-AL anxiety and MSAS worried were lowest (rs<.30). ESAS-anxiety correlated better with MSAS nervous (rs=.61). Conclusions: Well-defined ESAS-AL physical symptoms are highly correlated with equivalent MSAS symptoms, whereas less well-defined symptoms have weaker correlations. These findings provide preliminary support for the validity of the ESAS-AL. Further data collection for larger-scale validation is ongoing. [Table: see text]
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".