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Record W2008684860 · doi:10.1002/cncr.22055

Validation of the functional assessment of cancer therapy esophageal cancer subscale

2006· article· en· W2008684860 on OpenAlexaff
Gail Darling, David T. Eton, Joanne Sulman, Alan G. Casson, David Cella

Bibliographic record

VenueCancer · 2006
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsDalhousie UniversityMount Sinai HospitalToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineEsophageal cancerQuality of life (healthcare)CancerChemoradiotherapyOncologyProspective cohort studyInternal consistencyNeoadjuvant therapyInternal medicineEsophagectomyClinical trialPhysical therapyPsychometricsClinical psychologyBreast cancerNursing

Abstract

fetched live from OpenAlex

BACKGROUND: To develop and validate a quality of life subscale for patients with esophageal cancer to be used with the Functional Assessment of Cancer Therapy-General (FACT-G). METHODS: Prospective cohort study of patients with esophageal cancer treated with surgery alone or neoadjuvant chemoradiotherapy and surgery evaluating the validity, internal consistency, and responsiveness to change of the FACT-Esophageal (FACT-E) when comparing it with the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ 30) and esophageal (OES 24) as well as clinical factors. RESULTS: The FACT-E demonstrated very good convergent and divergent validity when compared with the EORTC QLQ30 and OES 24 and clinical variables. Internal consistency was also good with coefficient alpha > 0.70 for all subscales and individual items. Stability coefficients were > 0.80. Changes in clinical status were reflected in changes in FACT-E scores demonstrating responsiveness to change, particularly in patients receiving neoadjuvant chemoradiotherapy before surgery. CONCLUSIONS: The FACT-E met or exceeded all standards for validity, providing an option to measure health-related quality of life for different treatment strategies for esophageal cancer.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.373
Teacher spread0.339 · 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.

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

Citations116
Published2006
Admission routes1
Has abstractyes

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