Methods/Statistics
Parametric Regression Model Using Weibull Distribution in Patients with Ovarian Carcinoma in the State of Paraíba Tiago Almeida de Oliveira* Tiago Almeida de Oliveira Vitoria Soares de Souza Débora de Sousa Cordeiro Cleanderson Romualdo Fidelis Roberta Moreira Wichmann Ana Patricia Bastos Peixoto Tiago Almeida de Oliveira
This study investigates the survival time of ovarian cancer patients in the state of Paraíba, considering factors such as age, race/ethnicity, diagnostic methods, and disease extent. The sample comprised 146 patients, 72% of whom died from cancer, while 28% were censored cases. The median age was 57.5 years, with women aged 50 and older at higher risk. The mean overall survival time, including failures and censored cases, was 516 days, with a median of 340 days, indicating short survival for many patients. Approximately 48.6% of patients were aged between 31 and 60 years, and 63.7% self-identified as Black or Brown, suggesting disparities in access to diagnosis and treatment. The most common tumor type was adenocarcinoma, with 93.8% of diagnoses made via histological examination. Kaplan-Meier survival curves indicated that younger and White women had better survival rates. Although statistical analysis showed no significant impact of age, race/ethnicity emerged as a relevant factor, with pronounced differences due to disparities in access to diagnosis and treatment among groups. Based on the Akaike Information Criterion (AIC), the Weibull model was identified as the most suitable parametric regression model. The presence of metastasis was the main factor contributing to a poorer prognosis, increasing the risk of death by approximately eightfold during treatment. Additionally, the lack of information on cancer extent further elevated the risk, likely due to late diagnoses or inadequate treatment. Interestingly, patients over 60 years of age showed a 16% reduction in failure risk, suggesting a more favorable response to treatment. These findings underscore the importance of early diagnosis and highlight the impact of socioeconomic and cultural factors on survival disparities in ovarian cancer in Paraíba.
Keywords: ovarian cancer; survival; risk factors; Health disparities.
