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An international study of multitrial data investigating quality of life and symptoms as prognostic factors for survival in different cancer sites.

2012· article· en· W2608082715 on OpenAlex
Chantal Quinten, Efstathios Zikos, Miriam Sprangers, Eva Greimel, Francesca Martinelli, Bryce B. Reeve, Jolie Ringash, Carolyn Gotay, John Maringwa, Corneel Coens, Divine Ediebah, Madeleine King, David Osoba, Charles S. Cleeland, Hans‐Henning Flechtner, Jospeh Schmucker-Von Koch, Martin Taphoorn, Joachim Weis, Kristin Bjordal, Andrew Bottomley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicMultiple and Secondary Primary Cancers
Canadian institutionsUniversity of British ColumbiaPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineInternal medicineCancerLung cancerOncologyHazard ratioColorectal cancerProportional hazards modelQuality of life (healthcare)NauseaBreast cancerConfidence interval

Abstract

fetched live from OpenAlex

6002 Background: The prognostic value for survival of HRQOL data derived from self-report questionnaires, has been well documented in cancer research. The objective of this study was to examine the prognostic value of HRQOL parameters for different cancer sites using one standardized and validated patient self-assessment tool. Methods: A total of 11 different cancer sites, pooled from 30 European Organisation for Research and Treatment of Cancer (EORTC) Randomized Controlled Trials (RCTs), were selected for this study. For each cancer site, univariate and multivariate Cox proportional hazard modeling was used to assess the prognostic value (p<0.05) of 15 HRQOL parameters, assessed with the EORTC QLQ-C30 at baseline before randomization, for overall survival. Models were adjusted for the parameters age, gender, distant metastasis, World Health Organization performance status and stratified by clinical study. Results: A total of 7,417 patients completed the EORTC QLQ-C30 before randomization. For brain cancer cognitive functioning (CF) (hazard ratio (HR) =0.95; p<.0001) was prognostic. For breast cancer nausea and vomiting (NV) (HR=1.17; p=0.0011) was a prognostic indicator. For colorectal cancer physical functioning (PF) (HR=0.93; p<.0001), NV (HR=1.07; p<.0001), and appetite loss (AP) (HR=1.07; p<.0001) predicted survival. For esophageal cancer PF (HR=0.88; p=0.0072) and for head and neck cancer NV (HR=1.14; p=0.0097) were prognostic. For lung cancer PF (HR=0.94; p=0.0006) and pain (HR=1.08; p<0.0001), for melanoma dyspnea (HR=1.06; p<.0001), for ovarian cancer NV (HR=1.2; p<.0001), for pancreatic cancer global QOL (HR=0.83; p=0.0073), for prostate cancer role functioning (RF) (HR=0.96; p=0.006) and AP (HR=1.07; p<.0001), and for testis cancer RF (HR=0.81; p=0.0144) were predictors of survival. Conclusions: Our findings show that different HRQOL parameters provide prognostic information for survival for patients with different tumor sites and that no single HRQOL scale can predict survival in all cancer patients. Thus, each cancer site needs careful examination and no single QOL paramenter can predict survival in all cancer diseases.

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.

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)0.004
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.019
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 head0.506
GPT teacher head0.579
Teacher spread0.072 · 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