Evidence-based clinical practice parameter guidelines for the treatment of patients with metastatic brain tumors: introduction
Notice bibliographique
Résumé
Properly understood and employed, evidence-based medicine (EBM) is a tool of considerable value for medicine and neuro-oncology [1]. It provides a secure, scientificallydefensible base for clinical practice and practice improvement. However, pursued on an individual case-by-case basis, in purest form, it can be inefficient and time consuming, particularly for health providers with extremely busy clinical practices. Clinical guidelines based on the best evidence available, developed and regularly updated by subject matter experts, focusing on common and important clinical scenarios and questions, have the potential to be very desirable, useful, and efficient EBM tools for optimizing patient care. Clinical practice parameter guidelines are defined as ‘systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific individual circumstances’ [2]. An advantage of utilizing guidelines in clinical decision-making over sole reliance on randomized controlled trial (RCT) results, is that they take professional experience into account in an aggregate and more systematic manner, rather than on an individual or ad hoc basis [3]. Not only are more ‘‘experts’’ involved in the consensus process (diluting out outliers in opinion), but, in an evidence-based guidelines development process, the opinions solicited are the experts’ opinions about the collected evidence in the literature, rather than simply their own personal opinions regarding the subject. Multidisciplinary, evidence-linked clinical practice parameter guidelines, based on the most rigorous evidencebased methodology, offer the potential of reducing unexplainable variation in clinical practice while elevating the quality of patient care to the highest levels supported by the best available, and most up-to-date, evidence. They also have the potential to clearly point out where critical evidence ‘‘gaps’’ exist in areas important to clinical care that can then subsequently be filled by directed research planning and investment [4]. The goal of this guideline initiative is to optimize the care and outcome of our patients with brain metastases, by providing the most methodologically valid, evidence-linked treatment recommendations in a user-friendly and comprehensive manner, for real-world clinical scenarios encountered by clinicians and patients every day. The healthcare policy implications of clinical practice parameter guidelines are very real and deserve the careful attention of both individual practitioners and our national medical professional organizations. Legislation efforts currently active in Washington include language focusing on development and inclusion of ‘‘appropriateness criteria’’ as a means of restricting medical care and reducing medical costs. They also include language focusing on the development and funding of comparative effectiveness research analyzing clinical effectiveness, and not just cost effectiveness. Each of these efforts will likely lead to a search for the best available clinical practice guidelines in key public health impact areas for the purpose of improving value for every healthcare dollar spent, as well as reducing cost through practice restriction. It is in our patients’ interest, as well as our own as patient advocates, to ensure the availability of the highest quality guidelines S. N. Kalkanis (&) Department of Neurosurgery, Henry Ford Health System, 2799 West Grand Blvd, K-11, Detroit, MI 48202, USA e-mail: kalkanis@neuro.hfh.edu; skalkan1@hfhs.org
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 | 0,001 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| 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 ».