MétaCan
Menu
Back to cohort
Record W2124216802 · doi:10.1089/jpm.2007.0007

Clinically Important Improvement in the Intensity of Fatigue in Patients with Advanced Cancer

2007· article· en· W2124216802 on OpenAlexaboutno aff
Shantan Reddy, Éduardo Bruera, Ellen Pace, Karen Zhang, Cielito C. Reyes‐Gibby

Bibliographic record

VenueJournal of Palliative Medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancerIntensity (physics)OncologyInternal medicine

Abstract

fetched live from OpenAlex

Cancer-related fatigue (CRF) is the most common symptom experienced by patients with cancer. Clinically important improvement in the intensity of fatigue in palliative care patients has not been well established. We reviewed the data from 3 clinical trials of fatigue in 194 patients receiving palliative care treatment. Patients completed the Functional Assessment for Chronic Illness Therapy Fatigue (FACIT-F) and Edmonton Symptom Assessment System (ESAS) at baseline and day 8 and their global perception of fatigue improvement (Global benefit score [GBS]: 1 = not beneficial, 7 = greatly important] during day 8. A GBS of 4 or more (moderate improvement, consistently beneficial) was considered a clinically significant improvement. Change scores in the ESAS and FACIT-F from baseline to day 8 were compared to the GBS greater than 4. Receiver-operating characteristic curves were also derived for ESAS and FACIT-F change scores for a GBS greater than 4, greater than 5, and greater than 6. Results showed the mean patient age was 56 (+/-12) years, and 37% were men. A reduction of approximately 10 points in FACIT-F (sensitivity = 73%, specificity = 78%, area under the curve = 0.82) and 4 points in ESAS fatigue (sensitivity = 66%, specificity = 72%, area under the curve = 0.78) score was best able to predict a clinically important improvement (GBS >/= 4). We were able to characterize the relationship between FACIT-F and ESAS scores and patients' global perception of improvement but further studies are needed to validate our findings.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.295

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.365
Teacher spread0.332 · 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 teacher head, 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".

Quick stats

Citations58
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Palliative MedicineSame topicCancer survivorship and careFrench-language works237,207