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Record W4413774689 · doi:10.1200/go-25-00276

Geriatric Assessment: ASCO Global Guideline

2025· article· en· W4413774689 on OpenAlexaff
Cristiane Decat Bergerot, Sarah Temin, Haydeé Cristina Verduzco-Aguirre, Matti Aapro, Shabbir M.H. Alibhai, Zeba Aziz, María de la Concepción Pérez de Celis Herrero, Trinanjan Basu, Martine Extermann, Ravindran Kanesvaran, Bogda Koczwara, Kah Poh Loh, Elene Mariamidze, Alex Mutombo, Vanita Noronha, Grant R. Williams, Enrique Soto‐Pérez‐de‐Celis

Bibliographic record

VenueJCO Global Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer InstituteEuropean Society for Medical OncologyAstraZenecaCardinal HealthMovember FoundationServierPfizerAmgen
KeywordsGuidelineMedicineMedical physicsPathology

Abstract

fetched live from OpenAlex

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the ASCO Guidelines Methodology Manual , ASCO Guidelines follow the ASCO Conflict of Interest Policy for Clinical Practice Guidelines . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by clinicians and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases or stages of diseases. Guidance is based on review and analysis of relevant literature, and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 for more. PURPOSE To guide clinicians and policymakers in global resource-constrained settings to assess the geriatric needs of patients older than 65 years with cancer when Maximal-setting guideline–recommended resources are unavailable. METHODS A multidisciplinary, multinational Expert Panel reviewed existing ASCO guidelines and conducted modified ADAPTE and formal consensus processes. RESULTS An ASCO resource-neutral guideline was adapted for resource-constrained settings, informing one round of formal consensus; recommendations received ≥75% agreement. RECOMMENDATIONS The Expert Panel endorses the Maximal-setting guideline's overarching recommendation that end users utilize geriatric assessment (GA), including essential domains, to identify “vulnerabilities or impairments not routinely captured in oncology assessment for all older patients over 65 years old with cancer.” All care plans for patients with cancer over 65 years old receiving systemic therapy with GA-identified deficits should include GA-guided management. A geriatric evaluation should at a minimum include the use of a brief geriatric screening tool. Tools in the Practical Geriatric Assessment (PGA) are validated in multiple languages, but users may use more appropriate tools in some settings and languages, if they include the relevant guideline-specified domains. Maximal-resource settings of high-income countries have traditionally developed cutoffs for GA-identified deficits, but locally validated research and practice may inform differing cutoffs. If validated all-cause mortality prognosis tools do not adequately represent the setting, clinicians may use actuarial life-expectancy tables with quartiles of overall health status. Additional information can be found at www.asco.org/global-guidelines . It is the view of ASCO that health care clinicians and health care system decision makers should be guided by the recommendations for the highest stratum of resources available. The guideline is intended to complement but not replace local guidelines.

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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.407
Teacher spread0.393 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

Quick stats

Citations12
Published2025
Admission routes1
Has abstractyes

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