Oral cancer analysis in a Brazilian city: interval between diagnosis and treatment

Chiliti, Beatriz Afonso; Campos, Wladimir Gushiken de; Gallo, Camila de Barros; Lemos, Celso Augusto

doi:10.1590/1807-3107bor-2022.vol36.0073

Cited by 1 publication

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, due to the complexity of cancer treatment, it is crucial for municipalities to have well-established care flows to ensure timely OOC treatment in a high-demand patient [12,16,20,42]. Lack of supply or coverage of services, professionals and infrastructure that make it difficult for patients with OOC to access this care network can lead to delays in treatment [12,[15][16][17]. In addition, the arrangement of chemotherapy and radiotherapy services should consider epidemiological and social factors, the number of qualified professionals, and the capacity of each unit.…”

Section: Discussionmentioning

confidence: 99%

“…Studies have already reported the influence of unequal population coverage of primary and secondary health services in Brazilian cities on elevated number of hospitalizations and deaths due to OOC, especially when public oral health services are absent [ 15 , 16 ]. Therefore, the SUS-dependent population may have a time interval between diagnosis and treatment almost twice as long as private service patients [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Can predictive factors determine the time to treatment initiation for oral and oropharyngeal cancer? A classification and regression tree analysis

Montagnoli,

Leite,

Godoy

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

This ecological study aimed to identify the factors with the greatest power to discriminate the proportion of oral and oropharyngeal cancer (OOC) records with time to treatment initiation (TTI) within 30 days of diagnosis in Brazilian municipalities. A descriptive analysis was performed on the variables grouped into five dimensions related to patient characteristics, access to health services, support for cancer diagnosis, human resources, and socioeconomic characteristics of 3,218 Brazilian municipalities that registered at least one case of OOC in 2019. The Classification and Regression Trees (CART) technique was adopted to identify the explanatory variables with greater discriminatory power for the TTI response variable. There was a higher median percentage of records in the age group of 60 years or older. The median percentage of records with stage III and IV of the disease was 46.97%, and of records with chemotherapy, radiation, or both as the first treatment was 50%. The median percentage of people with private dental and health insurance was low. Up to 75% had no cancer diagnostic support services, and up to 50% of the municipalities had no specialist dentists. Most municipalities (49.4%) started treatment after more than 30 days. In the CART analysis, treatment with chemotherapy, radiotherapy, or both explained the highest TTI in all municipalities, and it was the most relevant for predicting TTI. The final model also included anatomical sites in the oral cavity and oropharynx and the number of computed tomography services per 100,000. There is a need to expand the availability of oncology services and human resources specialized in diagnosing and treating OOC in Brazilian municipalities for a timely TTI of OOC.

show abstract