Survey on synoptic reporting of pathology within the Center of Integrative Oncology Aachen-Cologne-Bonn-Düsseldorf (CIOABCD) and documentation of national and international chances for further optimization
Notice bibliographique
Résumé
In 2008, the governmental organisation Palga Foundation started to introduce a system for pathology reports called "Synoptic Reporting". It aims to standardise pathology reports for, ideally, all types of pathology laboratories or institutes in a given geographical region. By introducing this system, Palga has significantly changed the field of pathology reporting in the Netherlands. Palga as an organisation is now at the centre of the data flow between pathology laboratories, cancer registries and research projects. By implementing a common software tool for the creation and processing of pathology reports, a huge database has been developed in the Netherlands, managed by Palga. This enables fast and selective data transfer, data analysis and the basis for research projects for Palga, cancer registries and researchers. In the study "The effects of implementing synoptic pathology reporting in cancer diagnosis: a systematic review" by Sluijter, Caro E. (1), it was shown that the introduction of SR has brought enormous benefits to pathology on a large scale. The effectiveness and progress of SR is based on a classification called the "Ontario classification" (see chapter 3.3). The purpose of this study was to compare the structures of the Netherlands with those of the recently established German CIOABCD structure in order to develop meaningful proposals to enable and facilitate progress towards standardisation and interoperability in Germany. In contrast to the Netherlands, SR reporting has not yet been implemented in the CIOABCD NRW. This was determined through structured interviews with representatives of the sites, including those of the NRW Cancer Registry. It was found that all representatives of the CIOABCD rely on NR-based structures. Individual institutes have made their own progress in the area of NR, so that structures ranging from free text to table format can be found. (see chapter 4.1). There was no evidence of measures to introduce common templates or infrastructures. Future-oriented projects were reported, e.g. a software tool called "Meldeportal", which aims to create a common interface for data transmission to the LKR-NRW. Another example is the plan to set up a database managed by the CIOABCD in which all members are to store data (see Chapter 6). A direct comparison between the two geographical regions with similar populations (Netherlands and NRW) is not directly feasible for a variety of reasons. Nevertheless, the comparison helps to suggest steps for changes towards SR. In line with this objective, several suggestions and recommendations were made to support the transition from NR to higher quality reporting in a step-by-step process.
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 | 0,166 | 0,303 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,019 | 0,037 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,005 | 0,008 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».