First accounting of comprehensive radiotherapy life cycle assessment components in Africa.
Notice bibliographique
Résumé
e23213 Background: Climate change is a pressing issue on the global stage. Recently a comprehensive lifecycle assessment (LCA) of external beam radiotherapy (EBRT) for cancer delineated the environmental and secondary health impacts of radiotherapy in the United States (US) (PMID 38821084). The continent of Africa is warming faster than any other in the world, leaving Africa to face the most disproportionate burden worldwide arising from climate change. Thus far, an LCA of EBRT has yet to be performed in Africa. We report initial pilot data on breast cancer patients treated in Africa with EBRT as a first step towards LCA analysis. As breast cancer is the most common indication for EBRT (and the most common cancer worldwide in women), it represents an optimal disease site to initiate LCA analysis. These findings represent the first assessment of the complete components of an LCA in Africa, using our experience from a Ghanaian hospital. Methods: Data collection was performed using the ISO 14040 and 14044 standards as a guide in accordance with PMID 38821084. The scope of the study was defined as one round of curative intent EBRT from initial consultation through delivery of the last fraction. LCA data components were comprised from breast cancer patients receiving adjuvant EBRT at Korle-Bu Teaching Hospital (KBTH), Ghana from 2021-2024. Data for a complete life cycle of adjuvant EBRT for breast cancer consisted of medical supplies, equipment, patient and staff travel, and building energy usage. Results: Ten breast cancer patients were assessed for data collection, of which six received 50 Gray (Gy) in 25 fractions; the remaining four received 40.05 Gy/15 fractions. Patients received EBRT via a cobalt machine (n = 9) or linear accelerator (n = 1). Medical supplies were grouped into reusable and single use items. For initial consultation, patients traveled median 13.9 km (8.6 mi), and median distance traveled by staff was 10.5 km (6.5 mi). CT simulation was used for planning; peer review and weekly on-treatment visits were performed by a Radiation Oncologist while pre-treatment quality assurance was completed by a medical physicist. During treatment, patients traveled median 15.3 km (9.5 mi), and radiation therapists traveled a median of 11.8 km (7.3 mi). Most associated with the radiation delivery process used public transit for travel. Clinic energy usage was in accordance with previously reported data (PMID: 37552912). Conclusions: Given the importance of radiotherapy in the treatment of cancer (involved in half of all cancers treated), an accurate LCA analysis of EBRT is essential for combating climate change worldwide. This study represents the first comprehensive accumulation of LCA data for the continent of Africa. Further analysis will involve assessment of these parameters to create an LCA which will have far reaching impact not only in breast cancer but in other disease sites both in Africa and worldwide.
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 | 0,006 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».