Quality of Data in Population-Based Cancer Registry and its Implications for Cancer Control: A Cross-Sectional Study in Northern Tanzania

Abstract

Background: Cancer remains a significant global health challenge, especially in low-resource settings where limited data obstructs effective control measures. Reliable cancer registries are essential tools for collecting, managing, and analyzing cancer-related data. In Tanzania, as in many other sub-Saharan African countries, the need for accurate and timely cancer data is critical for informed decision-making. This study assesses the data quality of a population-based cancer registry in Tanzania to improve cancer control efforts. Methodology: This study adopted a descriptive cross-sectional study design to analyze 9617 records of cancer patients in population-based cancer registry database (Canreg5) from 2018 to 2022. Data analysis is done using Stata 17.0 and IARC validity check software. The percentage of complete, valid, and timely records was computed and compared with the required target. Comparability analysis compared age-standardized rates (ASR) and percentages of morphologically verified (MV%) against the standards in sub-Saharan Africa. Results: In the defined period from 2018 to 2022, a total of 9,617 records were included in the final analysis. The study found high data quality indicators: completeness at 94% for mandatory variables, validity at 76%, timeliness at 93%, and a high comparability with cancer data in sub-Saharan Africa at 60%. However, variations were noticed in age-standardized rates (ASR) and morphologically verified cases (MV). For comparability findings, mouth and pharynx cancer had lower age-standardized rates (ASR) for males (5.7) and females (3.4) but high morphological verification rates. Esophageal cancer had significantly higher ASR for males (22.0) and females (6.1), with moderate morphological verification rates. Stomach cancer had lower ASR but higher verification rates. Colon, rectum, and anus cancer had comparable ASR and higher verification rates. Conclusion: The data quality in the population-based cancer registry at the study site was optimal, with a high proportion of completeness, timeliness, and comparability, but with suboptimal validity of data, particularly for date format, and unlike combinations that highlight continuous monitoring and quality checks. While data quality is vital, challenges like missing and invalid records persist, necessitating reinforced protocols and validation measures.