Abstract PO-213: Relationship between travel distance and radiotherapy waiting time in Zaria, Northwestern Nigeria
Notice bibliographique
Résumé
Abstract Background Travel distance to healthcare facility has been recognized as a factor associated with treatment outcomes, utilization and a measure of the accessibility of health care services. In Nigeria, radiotherapy facilities are limited and machine breakdown is frequent, patients travel miles to access radiotherapy services. Objectives The aim of this study is to examine the distance travelled for radiotherapy and the relationship between distance to radiotherapy facility and radiotherapy waiting time in Zaria, Nigeria Materials and Methods The radiotherapy & oncology centre, Ahmadu Bello University Teaching Hospital, Zaria is located in Kaduna state, the northwestern part of Nigeria. It is the first radiotherapy centre in northern Nigeria and patients are referred from all over the country for treatment. Records of patients treated for cervix, breast and nasopharyngeal cancer from 2010 to 2014 were reviewed, the nearest distance by road from capital cities of patient’s state of residence to Zaria was measured using the web-based Geographic Information System Google map The distance was categorized into those who are near (≤ 300km) and those who are far (>300km) We defined radiotherapy waiting time as the interval from the first consultation to radiotherapy measured in days and was categorized into those who commenced radiotherapy within 31 days and those who delayed. We used the Mann-Whitney test to compare between groups. Data were analyzed using IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, N.Y., USA) Results A total of 233 cases were reviewed, cervix (55%), breast (31%) and nasopharynx (14 %). The mean age is 46.7(SD±12.0), females account for 92% of cases. The mean distance to Zaria is 407 (SD±250.1)km, the median is 350(IQR 165- 584.5), minimum 98.5km, maximum 941km. Only 18% of cases lived within 100km of the Zaria radiotherapy centre, 25.4% lived within 101-300 km of the centre, 16.3% within 301-500km and 40% of cases >500km from the centre. The mean radiotherapy waiting time is162 (SD±192.7) days, median 145(IQR 18-217.5) days. Only 31% of cases started radiotherapy within 31 days after consultation and 69% commenced more than 31 days Radiotherapy waiting time is negatively correlated with travel distance. Although the correlation was weak (r = -0.183) it is statistically significant (p=0.005) Patients who travelled ≤ 300 km waited longer than those who travelled> 300km. (p=0.007), and those who commenced treatment within 31 days travelled longer than those who commenced after 31 days (p= 0.032) Conclusion This study shows that patients travel far to access radiotherapy services, however, there is an inverse relationship between travel distance and radiotherapy waiting time. longer travel is associated with a shorter wait for radiotherapy. More and equitable distribution of radiotherapy facilities are needed and further studies to understand the factors responsible for this relationship. Citation Format: Nuhu Tumba, Sunday Adeyemi Adewuyi, Kelechi Eguzo, Maurice Nandul Nimark, Jamperda Jabani Mamza. Relationship between travel distance and radiotherapy waiting time in Zaria, Northwestern Nigeria [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-213.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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) | 0,003 | 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 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 ».