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Adiposity in resectable colorectal cancer.

2022· article· en· W4286295712 on OpenAlexafffundabout
J. Matthew Hopkins, David L. Bigam, Vickie E. Baracos, Dean T. Eurich, Rebecca Reif, Michael B. Sawyer

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of AlbertaUniversity of Calgary
FundersAlberta Health Services
KeywordsMedicineSarcopeniaCohortAdipose tissueInternal medicineColorectal cancerHazard ratioRetrospective cohort studyCancerProportional hazards modelQuartileObesityGastroenterologyOncology

Abstract

fetched live from OpenAlex

3614 Background: Sarcopenia and myosteatosis affect survival in colorectal cancer (CRC). The role of adiposity is not yet fully elucidated. This study explores visceral and subcutaneous adipose tissue (VAT/SAT) distributions, and how they affect overall (OS), disease-free (DFS) and cancer specific survival (CSS). Methods: This retrospective cohort study, included resected stage I-III CRC in Alberta from January 2007 to December 2009. We excluded recurrent/metastatic disease or no CT scan. This study was approved by the Health Research Ethics Board at the University of Alberta. Body composition parameters were measured from CT scans. Sarcopenia and myosteatosis were defined by cohort-specific cut-off values. Total and visceral fat areas were indexed by height, and cohort-specific cut-offs defined total and visceral obesity (VO). SAT (SC:TFR) and VAT (V:TFR) to total adipose ratios were compared by gender, as described by Fleming. SAT and VAT fat radiodensity (Hounsfield units, HU) was measured and divided into quartiles. Differences between groups were compared with student’s t-test and Fisher Exact test. Cox proportional hazard models were created, adjusting for important covariates, to assess adiposity effects on OS, DFS and CSS. Results: Our cohort included 968 patients with a median follow up of 63.5 months. The majority were stage II (38.6%) and III (51.0%). In total, 67.9% had total obesity and 51.0% had visceral obesity. In males, there was no difference in the incidence of myosteatosis or sarcopenia, regardless of V:TFR or SC:TFR. In women, those with a high V:TFR or SC:TFR had significantly higher incidence of myosteatosis, but not sarcopenia. Men and women with elevated V:TFR had significantly lower VAT and SAT HU (p<0.001, p=0.0113). Those with elevated SC:TFR had significantly higher VAT and SAT HU (p<0.001). VAT and SAT HU was lowest in those with myosteatosis alone (p<0.001; p=0.005). In survival analysis, VO and VAT HU quartiles predicted worse OS in uni-, but not multivariate analysis. SAT HU quartiles predicted worse survival in uni- and multivariate analysis, with the highest quartile of SAT HU predicting increased risk of death (HR 1.35, p=0.037). Adiposity was not predictive of CSS or DFS in uni- or multivariate analysis. Conclusions: This study demonstrated changes in VAT/SAT in relation to well described body composition parameters. SAT HU may have a more important role in OS than visceral adipose characteristics, despite known metabolic characteristics of VAT. True roles of adipose tissue in CRC outcomes remains unclear. VAT/SAT measurements using cross-sectional imaging allows for a detailed analysis and understanding of how adiposity may affect survival. [Table: see text]

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.254
GPT teacher head0.568
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2022
Admission routes3
Has abstractyes

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