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A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT)

2018· article· en· 787 citations· W2888034354 on OpenAlex· 10.1093/annonc/mdy263

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Bench or experimentalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.434
Threshold uncertainty score
0.387
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.070
GPT teacher head0.464
Teacher spread
0.394 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Background: In order to facilitate implementation of precision medicine in clinical management of cancer, there is a need to harmonise and standardise the reporting and interpretation of clinically relevant genomics data. Methods: The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group (TR and PM WG) launched a collaborative project to propose a classification system for molecular aberrations based on the evidence available supporting their value as clinical targets. A group of experts from several institutions was assembled to review available evidence, reach a consensus on grading criteria and present a classification system. This was then reviewed, amended and finally approved by the ESMO TR and PM WG and the ESMO leadership. Results: This first version of the ESMO Scale of Clinical Actionability for molecular Targets (ESCAT) defines six levels of clinical evidence for molecular targets according to the implications for patient management: tier I, targets ready for implementation in routine clinical decisions; tier II, investigational targets that likely define a patient population that benefits from a targeted drug but additional data are needed; tier III, clinical benefit previously demonstrated in other tumour types or for similar molecular targets; tier IV, preclinical evidence of actionability; tier V, evidence supporting co-targeting approaches; and tier X, lack of evidence for actionability. Conclusions: The ESCAT defines clinical evidence-based criteria to prioritise genomic alterations as markers to select patients for targeted therapies. This classification system aims to offer a common language for all the relevant stakeholders in cancer medicine and drug development.

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.

The record

Venue
Annals of Oncology
Topic
Cancer Genomics and Diagnostics
Field
Biochemistry, Genetics and Molecular Biology
Canadian institutions
Princess Margaret Cancer Centre
Funders
Medical Research CouncilStand Up To CancerNational Cancer InstituteServierEuropean Society for Medical OncologyCRUK Lung Cancer Centre of ExcellenceRosetrees TrustNational Institute for Health and Care ResearchUniversity College LondonWellcome TrustCancer Research UKAstraZenecaInvitaeSyndax PharmaceuticalsBiomedical Research CouncilFrancis Crick InstituteGenentechSeattle GeneticsNational Institute on Handicapped ResearchPTC TherapeuticsNovartisCelgeneSanofiWellcomeRocheMerckGlaxoSmithKlineUniversity College London Hospitals NHS Foundation TrustProstate Cancer FoundationAssociazione Italiana per la Ricerca sul CancroEli Lilly and CompanyBristol-Myers SquibbPfizerBreast Cancer Research FoundationBoehringer Ingelheim
Keywords
MedicinePrecision medicineScale (ratio)CancerComputational biologyRank (graph theory)OncologyBioinformaticsMedical physicsInternal medicinePathologyCartographyBiology
Has abstract in OpenAlex
yes