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Immunoscore clinical utility to identify good prognostic colon cancer stage II patients with high-risk clinico-pathological features for whom adjuvant treatment may be avoided.

2019· article· en· W2914793375 on OpenAlex
Jérôme Galon, Fabienne Hermitte, Bernhard Mlecnik, Florence Marliot, Carlo Bifulco, Alessandro Lugli, Irıs D. Nagtegaal, Arndt Hartmann, Marc Van den Eynde, Michael H. A. Roehrl, Pamela S. Ohashi, Eva Závadová, Toshihiko Torigoe, Prabhudas S. Patel, Yili Wang, Yutaka Kawakami, Francesco M. Marincola, Paolo A. Ascierto, Bernard A. Fox, Franck Pagès

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

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicColorectal and Anal Carcinomas
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineInternal medicineStage (stratigraphy)OncologyColorectal cancerPathologicalSingle CenterProportional hazards modelCancer

Abstract

fetched live from OpenAlex

487 Background: Immunoscore Colon is an IVD test predicting the risk of relapse in early-stage colon cancer (CC) patients, by measuring the host immune response at the tumor site. It is a risk-assessment tool providing independent and superior prognostic value than the usual tumor risk parameters and is intended to be used as an adjunct to the TNM classification. Risk assessment is particularly important to decide when to propose an adjuvant (adj.) treatment for stage (St) II CC patients. High-risk stage II patients defined as those with poor prognostic features including T4, lymph nodes < 12, poor differentiation, VELIPI, bowel obstruction/perforation can be considered for adj. chemotherapy (CT). However, additional risk factors are needed to guide treatment decisions. Methods: A subgroup analysis was performed on the St II untreated patients (n = 1130) from the Immunoscore international validation study (Pagès The Lancet 2018). The high-risk patients (with at least 1 clinico-pathological high-risk feature) were classified in 2 categories using pre-defined cutoffs: Low Immunoscore versus High Immunoscore and their five-year time to recurrence (5Y TTR) was compared to the TTR of the low-risk patients (without any clinico-pathological high-risk feature). Results: Among the patients with high-risk features (n = 630), 438 (69.5%) had a High Immunoscore with a corresponding 5Y TTR of 87.4 (95% CI 83.9-91.0), statistically similar (logrank pv not stratified p > 0.42, wald pv stratified by center p > 0.20) to the TTR 89.1 (95% CI 86.1-92.1) observed for the 500 low-risk patients (with no clinico-pathological feature). Furthermore, 5Y TTR for these patients were statistically similar to those of St II patients with high-risk features and a High Immunoscore (n = 438), who received adj. CT (n = 162) (5Y TTR of 83.4 (95% CI 77.6-89.9). Conclusions: These data show that despite the presence of high-risk features that usually trigger adj. treatment, when not treated with CT, a significant part of these patients (69.5%) have a recurrence risk similar to the low risk patients. Therefore, the Immunoscore test could be a good tool for adj. treatment decision in St II patients.

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.159
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
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 integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.470
Teacher spread0.361 · 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