Global Consultation on Cancer Staging: To Promote Consistent Understanding and Use of Cancer Stage Terminology
Notice bibliographique
Résumé
Background and context: Although the TNM stage schema has been the traditional means to classify anatomic extent of disease, in recent years confusion and uncertainty have emerged which underpinned by lack of familiarity concerning underlying rules of staging and their application. In turn such lack of clarity has led increased risk of miscommunication regarding patient care, research, cancer surveillance, epidemiology and cancer control. The UICC TNM Committee has confirmed a lack of uniformity in the application of cancer stage and its rules. In addition to stage, numerous other factors influence the outcome of patients as relate to tumor characteristics, patient descriptors, and the environment where any treatment is administered. A particularly a frequent problem is mixing disease extent and biology which has promoted additional misunderstanding about the importance and relevance of different individual prognostic elements and to what degree biology vs disease burden contribute to outcome. Aim: To ensure uniformity of staging systems, rules and classifications, the TNM Committee developed a global consensus on cancer staging. Strategy/Tactics: A selected literature review of twelve high impact oncology journals was performed and results will be summarized. There was inconsistent understanding and use of cancer stage classification terminology evident in up to 20% of the literature. A survey was developed and found that only 12.5% of those surveyed thought that the application of the TNM staging terminology was consistent and uniform in the literature. Respondents believed that complete T, N and M data should be recorded in cancer registries, 71% considered that other predictive and prognostic factors should also be collected by central cancer registries but that anatomic disease extent should be collected as a separate variable (85%). The Global Consultation on Cancer Staging was held under the auspices of the Union for International Cancer Control (UICC) and Lancet Oncology with support from the United States (US) National Cancer Institute (NCI) and the US Centers for Disease Control and Prevention (CDC). Experts from these organizations and FIGO (Fédération Internationale de Gynécologie et d´Obstétrique), IACR (International Association of Cancer Registries), IARC (International Agency for Research in Cancer), and the ICCR (International Collaboration on Cancer Reporting) attended. Program/Policy process: The purpose of the staging classification was reaffirmed. Important issues about staging processes were annunciated, and inconsistencies in terminology and use were acknowledged. Definitions of frequently misused staging terms were clarified. What was learned: It was determined that methodologies need to be explored to identify and include necessary data elements relevant to personalized treatment. Selection of factors should particularly include attention to their inclusion in cancer registries where appropriate.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,104 | 0,137 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,014 | 0,012 |
| Études des sciences et des technologies | 0,003 | 0,007 |
| Communication savante | 0,007 | 0,012 |
| Science ouverte | 0,004 | 0,011 |
| Intégrité de la recherche | 0,007 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».