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Integration of somatic molecular profiling for rare epithelial gynaecologic cancer patients.

2016· article· en· W2892215224 on OpenAlexaff
V. Rodriguez Freixinós, Stéphanie Lheureux, Victoria Mandilaras, Blaise Clarke, Neesha C. Dhani, Helen Mackay, Marcus O. Butler, Lisa Wang, Lillian L. Siu, Suzanne Kamel‐Reid, Tracy Stockley, Phillipe Bedard, Amit M. Oza

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineKRASSerous fluidInternal medicineOncologyNeuroblastoma RAS viral oncogene homologHRASGynecologyCancerPathology

Abstract

fetched live from OpenAlex

5509 Background: Rare gynaecologic cancers (R-GYN) represent over 50% of all gynaecologic malignancies. Conducting clinical trials in R-GYN is challenging due to the limited number of patients (pts) and differences in biologic behavior. Somatic molecular profiling (SMP) may increase biologic understanding of R-GYN and identify pts for target specific therapies. Methods: A cohort of epithelial R-GYN pts was analyzed for somatic variants (SV) through an institutional SMP screening (NCT01505400) using a customized Sequenom SNP genotyping panel or targeted sequencing (NGS) using the Illumina MiSeq TruSeq Amplicon Cancer Panel or the Ion Proton Ampliseq Cancer Hotspot Panel version 2, in a CLIA certified laboratory. Outcomes of genotype-matched (GM) versus genotype-unmatched (GUnM) trials were compared. Results: 721 GYN pts underwent SMP and 189 were classified as R-GYN (26%), with a median of 1.5 prior systemic treatments [0-4]. 52 low grade serous, 2 transitional and 1 squamous OC, 10 cervical adenosquamous/adenocarcinomas, 23 serous endometrial, 2 vaginal, 12 vulvar, 37 clear cell, 17 mucinous, 1 small cell and 32 carcinosarcomas. Pathology review confirmed diagnosis in 95%. A total of 134 pts (71%) had ≥ 1 SV (range 1-4), being the most common: 37% TP53; 39% KRAS; 37% PIK3CA. Upon SMP, 75 pts were not treated further, 64% due to progressive disease (PD). 91/189 pts were referred for clinical trials and 39/189 (21%) participated in 45 studies. 19/189 pts (10%), with a median of 0.5 prior systemic treatments [0-1], participated in GM trials (1 pt with vaginal cancer participated in two consecutive GM trials). Main reasons for non-enrollment were not fulfilling eligibility criteria (49%) and PD (29%). RECIST 1.1 response among evaluable pts showed: 3 PR (7%) (2 in GM trials) and 18 pts had SD ≥ 4 months(m) [9/18 pts (50%) in GM vs. 9/26 pts (35%) in GUnM]. Of 9/18 pts who had received prior systemic therapy for recurrent disease, the median time to progression of GM was 5.3 m (0.9-22) compared with 2.8 m (1.7-25.1) for the immediate prior line of therapy (p = 0.17). Conclusions: SMP screening of R-GYN identified actionable SV in 71% of pts, expanding the spectrum of therapeutic approaches in a population with limited standard options.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.108
GPT teacher head0.463
Teacher spread0.356 · 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 designObservational
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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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