Tackling the radiotherapy (RT) shortage in Sub-Saharan Africa by gathering and using data from LMICs and HICs facilities for designing a future robust RT facility
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Notice bibliographique
Résumé
Purpose Historically, highly sophisticated medical linear accelerators (linacs) produced for high- (HIC) and upper-middle-income country (MIC) markets frequently experience significant additional operational failures in low- and lower-middle-income countries (LMICs). This study focuses on LMICs in Africa where there is a substantial equipment shortfall, projected to be a gap by 2040 of about 5000 linacs. The purpose of this study was to gain an insight into the poor performance of linac components, the unreliable infrastructure often encountered in LMICs and the consequent linac-related treatment downtime. Methods and Materials A questionnaire was sent to at least one cancer center in each of the 28 African countries that had experience treating cancer patients with linacs at the time of the survey (4 more countries have acquired linacs) since we completed this survey. For comparison questionnaires were sent to selected facilities in four high-income countries (Canada, Switzerland, UK, US) and to Jordan, a middle-income country. To investigate factors influencing linac downtime, we first utilised flow diagrams to illustrate the dependence of linac subsystem performance on infrastructural/environmental factors, the availability of spare parts and local repair capability. Secondly, a univariate analysis correlated linac downtime with factors such as method of linac fault diagnosis and staffing. Finally, a multivariate analysis investigated the relationship between GDP per capita and cancer mortality to incidence ratio statistics and compared these with the surveyed linac downtime across low-, middle- and high- income countries. Results Responses to the survey confirmed significant multi-factorial issues that influence the extent of linac downtime especially the performance of multi-leaf collimators, electron guns, vacuum systems, RF power and software. Other challenges include electrical power instability, inadequate national funding (GDP/capita), and workforce capability as well as a significant shortfall in formal education and training programmes for the radiation therapy (RT) workforce. Conclusion This survey identified numerous modes of radiotherapy (RT) equipment failure causing treatment downtime in LMICs that can be overcome by improvements in the design of RT technology but they need to be accompanied by increased RT staff training, improved broadband access and increased annual national funding for RT. The collaborative network of linac-based RT facilities in 28 1 * African countries that was developed to conduct this study is available for further investigations as RT capacity and capability improve in Africa.
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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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| 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 découle