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Record W2530776777 · doi:10.1080/17474124.2016.1244003

Decision-making in geriatric oncology: systemic treatment considerations for older adults with colon cancer

2016· review· en· W2530776777 on OpenAlexfundno aff
Erin Moth, Janette L. Vardy, Prunella Blinman

Bibliographic record

VenueExpert Review of Gastroenterology & Hepatology · 2016
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsnot available
FundersAGE-WELL
KeywordsMedicineGeriatric oncologyColorectal cancerOncologyInternal medicineCancerSystemic therapyIntensive care medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Colon cancer is common and can be considered a disease of older adults with more than half of cases diagnosed in patients aged over 70 years. Decision-making about treatment with chemotherapy for older adults may be complicated by age-related physiological changes, impaired functional status, limited social supports, concerns regarding the occurrence of and ability to tolerate treatment toxicity, and the presence of comorbidities. This is compounded by a lack of high quality evidence guiding cancer treatment decisions for older adults. Areas covered: This narrative review evaluates the evidence for adjuvant and palliative systemic therapy in older adults with colon cancer. The value of an adequate assessment prior to making a treatment decision is addressed, with emphasis on the geriatric assessment. Guidance in making a treatment decision is provided. Expert commentary: Treatment decisions should consider goals of care, a patient's treatment preferences, and weigh up relative benefits and harms.

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)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.028
GPT teacher head0.392
Teacher spread0.364 · 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 designNot applicable
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

Citations19
Published2016
Admission routes1
Has abstractyes

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