Incompleteness trends of epidemiological variables in a Brazilian high complexity cancer registry: An ecological time...

Hospital Cancer Registries serve as a vital source of information for clinical and epidemiological research, allowing the evaluation of patient care outcomes through therapeutic protocol analysis and patient survival assessment. This study aims to assess the trend of incompleteness in the epidemiological variables within the Hospital Cancer Registry of a renowned oncology center in a Brazilian state. An ecological time-series study was conducted using secondary data from the Hospital Santa Rita de Cássia Cancer Registry in Espírito Santo between 2000 and 2016. Data completeness was categorized as follows: excellent (<5%), good (5%-10%), fair (10%-20%), poor (20%-50%), and very poor (>50%), based on the percentage of missing information. Descriptive and bivariate statistical analyses were performed using the free software RStudio (version 2022.07.2) and R (version 4.1.0). The Mann-Kendall test was used to assess temporal trends between the evaluated years, and the Friedman test was employed to evaluate quality scores across the years. Among the variables assessed, birthplace, race/color, education, occupation, origin, marital status, history of alcohol and tobacco consumption, previous diagnosis and treatment, the most important basis for tumor diagnosis, tumor-node-metastasis staging (TNM) staging, and clinical tumor staging by group (TNM) showed the highest levels of incompleteness. Conversely, other epidemiological variables demonstrated excellent completeness, reaching 100% throughout the study period. Significant trends were observed over the years for history of alcohol consumption (P < .001), history of tobacco consumption (P < .001), TNM staging (P = .016), clinical tumor staging by group (TNM) (P = .002), first treatment received at the hospital (P = .012), disease status at the end of the first treatment at the hospital (P < .001), and family history of cancer (P < .001), and tumor laterality (P = .032). While most epidemiological variables within the Hospital Santa Rita de Cássia Cancer Registry exhibited excellent completeness, some important variables, such as TNM staging and clinical staging, showed high levels of incompleteness. Ensuring high-quality data within Cancer Registries is crucial for a comprehensive understanding of the health-disease process.