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Record W3203532227 · doi:10.1016/s2666-7568(21)00179-3

Is cancer biology different in older patients?

2021· review· en· W3203532227 on OpenAlex

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

VenueThe Lancet Healthy Longevity · 2021
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversity of TorontoUniversity Health NetworkPrincess Margaret Cancer Centre
FundersVlaamse regeringFonds Wetenschappelijk OnderzoekASCRS Research Foundation
KeywordsCancerProstate cancerMalignancyBreast cancerImmunosenescenceNarrative reviewAffect (linguistics)Colorectal cancerMedicineLung cancerOncologyImmune systemGerontologyInternal medicineImmunologyPsychologyIntensive care medicine

Abstract

fetched live from OpenAlex

Roughly 50% of cancer cases occur in people aged 65 years or older. Older people are often diagnosed at a later stage and might receive less (intensive) treatment, which might affect the outcome. In addition, an older age might be associated with biological differences in tumour and microenvironment behaviour, a domain that has been poorly studied so far. In this narrative Review of published literature, we explored the reported differences in tumour biology according to age in five major cancer types: breast, colorectal, prostate, lung, and melanoma. Our literature search uncovered clear differences in tumour histology and subtype distribution in older people compared with younger patients, as well as age-specific patterns of tumour mutations and other molecular alterations. Several studies also indicate notable changes in tumour-infiltrating immune cells in tumours of older versus younger people, although this research is still in its infancy. More research is needed and might lead to a better understanding of the biology of ageing in relation to malignancy. This knowledge could provide new perspectives for more personalised cancer treatments, eventually improving the global outcomes of older patients with 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.123
GPT teacher head0.437
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