MétaCan
Menu
Back to cohort
Record W3035496249 · doi:10.4251/wjgo.v12.i6.604

Real-world evidence on adjuvant chemotherapy in older adults with stage II/III colon cancer

2020· review· en· W3035496249 on OpenAlexaff
Atul Batra, Rodrigo Rigo, Dropen Sheka, Winson Y. Cheung

Bibliographic record

VenueWorld Journal of Gastrointestinal Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineColorectal cancerStage (stratigraphy)Clinical trialOncologyCancerInternal medicineDiseasePopulationAdjuvant chemotherapyRandomized controlled trialChemotherapy

Abstract

fetched live from OpenAlex

Colon cancer represents one of the most common cancers diagnosed in older adults worldwide. The standard of care in resected stage II and stage III colon cancer continues to evolve. While there is unequivocal evidence to suggest both disease free and overall survival benefits with the use of combination chemotherapy in patients with stage III colon cancer, data regarding its use in patients with stage II colon cancer are less clear. Further, although colon cancer is a disease that affects older adults, there is considerable debate on the value of adjuvant chemotherapy in the aging population. In particular, many older patients are undertreated when compared to their younger counterparts. In this review, we will describe the clinical trials that contributed to the current adjuvant chemotherapy approach in colon cancer, discuss representation of older adults in trials and the specific challenges associated with the management of this sub-population, and highlight the role of comprehensive geriatric assessments. We will also review how real-world evidence complements the data gaps from clinical trials of early stage colon 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 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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.056
GPT teacher head0.397
Teacher spread0.341 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations17
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of Gastrointestinal OncologySame topicColorectal Cancer Surgical TreatmentsFrench-language works237,207