Demographic, tumour, and treatment characteristics of female patients with breast cancer in Sri Lanka; results from a hospital-based cancer registry
Notice bibliographique
Résumé
BACKGROUND: Although breast cancer is the most common cancer among Sri Lankan women, there is little published data on patient characteristics and treatment in the local context. We aimed to describe disease characteristics and management in a large contemporary cohort of women with breast cancer at the National Cancer Institute of Sri Lanka (NCISL). METHODS: All women with invasive primary breast cancers diagnosed during 2016-2020 were identified from the NCISL breast cancer registry. The NCISL sees approximately 40% of all cancer patients in Sri Lanka. Cancer stage at diagnosis was defined according to the Tumour, Node, and Metastasis (TNM) staging system and the Estrogen (ER) and progesterone (PR) receptor status was determined based on the results of immunohistochemistry tests. Descriptive statistics were used to describe the study cohort and treatment patterns. RESULTS: Over 5100 patients were diagnosed with breast cancer during the study period at the NCISL. The mean age of the women was 56 (SD 12) years. Common co-morbidities were hypertension (n = 1566, 30%) and diabetes mellitus (n = 1196, 23%). Two thirds (66%) of the cancers were early stage (stage I & II) at diagnosis. ER/PR positivity rate was 72% and HER-2 positivity rate was 22%. Two thirds of the women had undergone mastectomy while 68% had undergone axillary clearance. The rate of chemotherapy delivery was 91% for women with node positive disease while 77% of eligible women (i.e., after wide local excision or with > 3 positive lymph nodes) had received adjuvant radiotherapy. Endocrine therapy was initiated in 88% of eligible women with hormone receptor positive disease while rate of trastuzumab use was 59% among women with HER2 positive breast cancer. CONCLUSIONS: High percentage of advanced breast cancer at diagnosis and high prevalence of comorbidities are some of the major challenges faced in the management of breast cancer in Sri Lanka. Given that stage at diagnosis is the most important prognostic factor determining survival, greater efforts are needed to promote early diagnosis of breast cancer. Considerable lapses in the concordance between guideline recommendations and the delivery of cancer care warrants closer assessment and intervention.
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 | 0,000 | 0,000 |
| 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 | 0,000 |
| 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) | 0,000 | 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; 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 ».