The role of health economic evidence in clinical practice guidelines for colorectal cancer: a comparative analysis across countries
Notice bibliographique
Résumé
Aim: Colorectal cancer (CRC) is among the most prevalent malignancies globally and causes massive resource consumption and economic burden. Health economic evidence (HEE) has been used in clinical practice guidelines (CPGs) for cancer to facilitate the rational allocation of health resources. However, in certain guideline development organizations, HEE is not yet utilized as a formal decision-making criterion. This study aimed to compare the discrepancies in the utilization of health economics as evidence in CRC CPGs across different countries and review specific features of economic evidence concerning the guidelines’ applicability. Materials & methods: A systematic review was conducted using databases including Medline, Embase, CNKI, WanFang, and other guidelines databases to identify CPGs for CRC published in English or Chinese from January 2017 to September 2023. Data on the incorporation and application of HEE were extracted, and the method and quality of cost–effectiveness analysis (CEA) studies were evaluated. Descriptive analyses were used to summarize the results. Results: Out of 53 CPGs from 14 countries, most originated from the USA (n = 17 of 53 [32%]) and Canada (n = 9 of 53 [17%]). Sixty-eight percent (36/53) considered cost justification, and 57% (30/53) incorporated health economics studies as evidence. The included HEE cited in CPGs ranged from 1990 to 2021 and were not aligned with the countries in which the guidelines were issued. Among these CEA studies, 52% (26/50) were related to screening strategies, and 32% (16/50) pertained to treatment measures. The Markov model was the most frequently used (n = 27 of 50 [54%]). Based on the CHEQUE tool, the methodological quality of these CEA studies was inadequate in areas such as multiple data sources, approaches to select data sources, assessing the quality of data, and relevant equity or distribution. Conclusion: In summary, 57% of guidelines incorporated health economics studies as evidence, with a variation between different countries. The included HEE still had deficiencies in methodology and reporting quality. In the future, it is suggested that health economics research should use a standardized methodology and reporting approach to assist in clinical decision making.
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 | 0,267 | 0,046 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,011 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».