Real world challenges in defining oligometastatic disease in clinical practice.
Notice bibliographique
Résumé
e18873 Background: There is little data understanding the multi-disciplinary application of oligo-metastatic disease (OMD) treatment and decision-making. Through an anonymous survey, we sought to understand the knowledge gaps and challenges faced by physicians caring for cancer patients in deciphering and delivering treatments for patients with OMD. Methods: This was an IRB approved single institution quality improvement study conducted via an anonymous electronic survey. Three clinical cases of OMD that ranged from de-novo OMD to oligo-progressive disease, were presented to check participants’ comprehension of OMD. Descriptive statistics were used to summarize quantifiable information obtained from the survey. A qualitative approach was taken for the open-ended questions, in which the answers were reviewed by 2 independent readers and grouped together into common themes, and analyzed using sector and bar diagram, decision-tree method and sorted by prevalence. Results: The survey was answered by 70 clinicians (39 (56%) medical oncologists, 17 (24%) radiation oncologists, 5 (7%) surgeons, 9 (13%) from anatomical pathology/radiology/palliative care). The three clinical cases were correctly answered in 63%, 94% and 76%, respectively; of these, 76% to 84% would offer local treatment for each OMD scenario. Most (79%) perceived differences between local therapies (surgery, SBRT and RFA). Surgery was preferred to improve local control and overall survival, while SBRT was considered as being less invasive and more beneficial to patient quality of life. The definition of OMD was perceived by 94% as patients harboring 1-5 metastases. The main perceived challenges consist of lack of evidence in clinical and prospective trial data. Referrals are hindered as the goals and approach of OMD care are unclear. The most important determinant in deciding whether patients may benefit from OMD treatment is tumor histology and molecular profile. Conclusions: SBRT as a treatment of OMD emerged during an era of rapid expansion in systemic treatments and improvements in imaging techniques. Positive and negative trials in various histologies of cancer further added uncertainty on who would best benefit from OMD SBRT. As more radiation centres offer SBRT, the discordance in the outcome expectations from referring physicians, radiation oncologists and patients will need to be addressed to ensure that patients’ goals of care are met.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».