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Record W1970298748 · doi:10.1177/1049909109346307

Predictors of Symptom Severity and Response in Patients With Metastatic Cancer

2009· article· en· W1970298748 on OpenAlexaffabout
Camilla Zimmermann, Debika Burman, Matthew Follwell, Kristina Wakimoto, Dori Seccareccia, John Bryson, Lisa W. Le, Gary Rodin

Bibliographic record

VenueAmerican Journal of Hospice and Palliative Medicine® · 2009
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicinePalliative careDistressPsychological interventionMultivariate analysisPhysical therapyInternal medicinePerformance statusAnxietyCancerClinical psychologyPsychiatryNursing

Abstract

fetched live from OpenAlex

We examined determinants of symptom severity and response to treatment among 150 patients with cancer participating in a phase II trial of a palliative care team intervention. Patients completed a modified Edmonton Symptom Assessment Scale (ESAS) at baseline and 1 week. Women had a worse baseline ESAS Distress Score (EDS; P = .003) and Total Distress Score (TDS; P = .005); differences were particularly marked for anxiety and appetite. Performance status was inversely associated with EDS, TDS, well-being, appetite, and fatigue (Kruskal-Wallis, all P < .005). Multivariate analysis of covariance (ANCOVA) showed that symptom improvement was independently predicted by worse baseline EDS score and female gender. Performance status, gender, and baseline symptom severity should be accounted for in trials of palliative care interventions; inclusion criteria based on symptom severity should also be considered.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.009
GPT teacher head0.286
Teacher spread0.277 · 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

Citations44
Published2009
Admission routes2
Has abstractyes

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