Oral cancer patient’s profile and time to treatment initiation in the public health system in Rio de Janeiro, Brazil

Conceição, Manoela Garcia Dias da; Emmerick, Isabel Cristina Martins; Figueiró, Ana Cláudia; Luiza, Vera Lúcia

doi:10.1186/s12913-021-06131-x

Cited by 6 publications

(3 citation statements)

References 12 publications

(5 reference statements)

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“…29 In 2012, a Brazilian federal law 30 established that for patients with a main clinical suspicion of malignant neoplasia, confirmatory exams must be performed within 30 days after medical request and treatment must be started within 60 days after conclusive and histopathologically proven cancer diagnosis. 31 The results of the current study seem to be in accordance with the deadlines established by the law; however, it is noticeable that the patient journey before cancer treatment initiation has not evolved since 2007, 19 evidencing the need to prevent OOC late diagnosis and delayed treatment.…”

Section: Discussionsupporting

confidence: 78%

Oral and oropharyngeal cancer: time from first symptoms to treatment initiation and associated factors

et al. 2023

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The aim of this study was to evaluate the time elapsed from first symptoms to the treatment of oral and oropharyngeal cancer (OOC) and to identify variables associated with treatment delay. This is an observational study with retrospective and prospective data collection. Patients with a diagnosis of OOC seen at the Head and Neck Surgery outpatient clinic of a Brazilian public hospital were included and followed up to treatment initiation. Participants answered a questionnaire for the collection of socioeconomic, demographic, cultural, and clinical information, as well as information about the time elapsed from first symptoms to the first appointment with a head and neck surgeon. Time to treatment was classified into four intervals: 1-first symptoms to first medical appointment; 2-first medical appointment to specialized medical care; 3-specialized medical care to preparation for treatment; and 4-preparation for treatment to treatment initiation. Bivariate statistics were computed. Out of 100 participants, nine died before treatment. Mean time to treatment was 217 days. Highest mean time was observed for interval 2 (94 days), followed by interval 1 (63 days), interval 4 (39 days), and interval 3 (21 days). At interval 1, a longer time was associated with severe alcohol consumption, severe smoking, and family history of cancer. At interval 2, the delay was associated with appointment with a general practitioner, clinical diagnosis of disease other than cancer, and antibiotic prescription. At interval 4, delay in treatment was associated with surgical treatment. Patients with OOC experience delays from symptom onset to treatment initiation. The longest interval was associated with professional delay, followed by patient delay in help-seeking.

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Section: Discussionsupporting

confidence: 78%

Oral and oropharyngeal cancer: time from first symptoms to treatment initiation and associated factors

et al. 2023

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“…RJ is one of the national metropolises, located in this specific region, and has a population of over 6 million. The state also has an extensive network of local government health units, and the headquarters of the National Cancer Institute (INCA) is located in RJ, which is the main reference center for cancer care and research in the country [ 26 ]. Another study has already analyzed the temporal trend in OC mortality rates in RJ and showed a reduction of 1.54% per year in the OC mortality rate from 1999 to 2018.…”

Section: Discussionmentioning

confidence: 99%

Association of Socioeconomic Status and Oral Cancer Mortality in Brazil: Temporal Trends and Spatial Distribution

Tavares¹,

Santos²,

Santos³

et al. 2023

Med Princ Pract

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The objective of this observational study was to evaluate the relationship between the oral cancer mortality rate and socioeconomic indicators throughout the Brazilian territory, between 2010 and 2019. The variables used in this study were oral cancer mortality rate from the Mortality Information System (SIM), population data from the Brazilian Institute of Geography and Statistics (IBGE), to calculate oral cancer mortality rates, along with the Human Development Index (HDI) and Social Vulnerability Index (SVI). The analysis was performed in tertile stratifications (Microsoft Excel 16.0), while temporal trends were examined by segmented linear regression (JoinPoint 4.9.0). High mortality rates were observed in more developed regions (South and Southeast), whereas temporal analysis showed significant increasing trends in the North (APC=+3.9%; p<0.05) and Northeast (APC=+2.4%; p<0.05) regions. The greater HDI (APC=+1.7%; p<0.05) and SVI (APC=+2.2%; p<0.05) tertiles had the lowest annual percentage increase, showing an inverse relationship between the temporal trend of mortality and socioeconomic indicators. Despite the higher number of oral cancer deaths located in regions with higher social indices, increasing temporal trends are more accentuated in regions with lower socioeconomic levels.

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“…Concerning the health system, the adult population’s difficult access to dental care and the lack of coordinated actions at the different care levels (primary, secondary, and tertiary) [ 11 , 12 ] can influence the late onset of treatment. The coordination of cancer care involves everything from health policies, organizational aspects of services, appropriate infrastructure, and prepared human resources to socioeconomic issues in the health system context [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

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

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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.

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Oral cancer patient’s profile and time to treatment initiation in the public health system in Rio de Janeiro, Brazil

Cited by 6 publications

References 12 publications

Oral and oropharyngeal cancer: time from first symptoms to treatment initiation and associated factors

Oral and oropharyngeal cancer: time from first symptoms to treatment initiation and associated factors

Association of Socioeconomic Status and Oral Cancer Mortality in Brazil: Temporal Trends and Spatial Distribution

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

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