Prevalence of Solid Neoplasms Diagnosed Between the Years of 2011 to 2016 and Oncologically Treated at the University Hospital of Santa Maria
Notice bibliographique
Résumé
BACKGROUND: Cancer is a public health problem, especially in developing countries. In order to establish effective measures for the cancer control, there is a need for quality information, thus enabling a better understanding of the disease and its determinants, formulation of causal hypotheses, evaluation of the technological advances applied to prevention and treatment as well as the effectiveness of health care. The objective of the study was to investigate the prevalence of solid neoplasms diagnosed between the years 2011 to 2016 and treated at the Oncology Department of the University Hospital of Santa Maria and the existing oncological context. METHODS: This is an observational cross-sectional study. The target population was comprised of adult patients (18 years of age or older) and elderly people (60 years of age or older) diagnosed with solid cancer by anatomico-pathological examination between 2011 and 2016, who started oncological treatment, according to high complexity procedure authorization (APAC)/Oncology. RESULTS: A total of 2,757 patients were selected, of which 1,493 patients were female (54.2%) and 1,264 male (45.8%). The mean age at the time of initiation of treatment was 59.94 years for both sexes, with the 95% confidence interval (59.44 - 60.44). The majority of patients were aged 61 - 70 years, totaling 747 patients, followed by 718 patients between 51 - 60 years. In all 31 primary sites identified the most prevalent one of neoplasms are breast, prostate, colorectal and lung; and most cases were stage IV (1,039 cases). A percentage of the number of cases of breast and esophageal cancer was higher than expected, and in contrast to a low percentage of hepatocarcinoma, kidney cancer and central nervous system tumors. The patients came from the entire area of the fourth Health Coordinating Area, where 100% of the municipalities referred to the institution, as well as other nine locations belonging to other coordinators. CONCLUSION: Most of the data obtained are consistent with the Brazilian reality, not identifying any peculiar characteristic of this region of the study worthy of note, except for the difference in the prevalence of some types of cancer, a fact that deserves further studies. There were also no discrepancies in a regional analysis. Along with this work, it was possible to demonstrate the cancer situation and the profile of oncology patients attended at a reference center for 41 municipalities, mainly in the central region of Rio Grande do Sul state, which may be useful in the elaboration of public policies to modify the profile identified, and serve as the basis for further studies in this region.
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 | 0,000 | 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 | 0,000 | 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) | 0,002 | 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 ».