14P Clinical outcomes of women who attend the Cameroon Baptist Convention Health Services (CBCHS) with cervical cancer
Notice bibliographique
Résumé
Cervical cancer ranks the fourth most frequently diagnosed cancer and the fourth leading cause of cancer-related deaths among women globally. In LMIC, most women with cervical cancer are diagnosed at an advanced stage because they have limited access to proper diagnosis. Treatment options are limited due to limited access to radiation therapy. Thus, survival outcomes are poor. There is no data on this issue in Cameroon so we undertook to determine the survival outcomes for women who present with cervical cancer to the CBCHS. Data was extracted Women’s Health Program (WHP) database. Outcomes were categorized as alive with disease, alive without disease, or dead. Kaplan-Meier (KM) curves for survival were plotted stratified by age, HIV status, and histologic subtype. Cox regression model for survival analysis was used to determine the impact of some variables on the mean time of patient survival after diagnosis. Between 2013 and 2018, 752 women were diagnosed with cervical cancer. The average age at cervical cancer diagnosis was 53.33 (+/-13.82) with a mean survival time of 2.34 years (+/-2.00). Within five years of diagnosis, the overall survival for women diagnosed with cervical cancer was 27.1%. 285 (37.5%) of cases diagnosed did not go in for treatment. 387 (51.5%) went in for treatment, including 205 who did not complete their treatment. Age at diagnosis (HR 1.007 (95% Cl (1.000-1.013)), p=0.035), a positive HIV status (HR 1.032 (95% Cl (0.930-1.145)), p = 0.558), and histologic subtype of adenocarcinoma (HR 1.026 (95% Cl (0.705-1.493)), p=0.894) were associated with lower survival (although these associations were not statistically significant). A diagnosis of cervical cancer is a serious threat to the health of women, especially in LMIC like Cameroon. Survival from the disease is extremely poor in this country, consistent with data from other LMICs. Most cases present late with symptoms, and the majority cannot afford treatment reflected by the very few who attend recommended forms of treatment or are unable to complete it. Education, and creating awareness around primary and secondary prevention and universal health care funding are necessary steps to strengthen cervical cancer control in Cameroon.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».