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Updated: Aug 31, 2025

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
Published on: January 22, 2011
Development of an online cancer data collection and processing tool for population-based cancer registries in a
Susan Hasanpour-Heidari1, Ali Ahmadi2, SeyedMohsen Mansuri2
1Golestan Research Center of Gastroenterology and Hepatology, Golestan University of Medical Sciences, Gorgan, Iran.
Background:
Golestan Population-based Cancer Registry (GPCR) with more than 15-years experiences developed an in-house online software called Cancer Data Collection and Processing (CanDCap) to improve its data collection operations from the conventional offline method to new online method. We aimed to report the methods and framework that GPCR applied to design and implementation of the CanDCap.
Methods:
CanDCap was designed based on International Agency for Research on Cancer (IARC) protocols and standards and according to the GPCR workflow. CanDCap has two parts including a web-based online part for data collection and a windows-based part for data processing consisting of quality control and deduplication of repeated records. Questionnaire for User Interface Satisfaction (QUIS) was used in order to assess user interaction satisfaction.
Results:
CanDCap was implemented in 2018 and could improve the quality of the GPCR data during its first three years of activity (2018-2020), during which about 9,000 records were registered. The coverage for optional items including national ID, father name, address and telephone number were improved from 23 %, 32 %, 83 % and 82 % in conventional offline method (2015-2017) to 83 %, 81 %, 87 %, and 90 % after using the CanDCap (2018-2020), respectively. The timeliness was also improved from 4 years to 2 years. Overall, user interaction satisfaction was acceptable (7.8 out of 9).
Conclusion:
CanDCap could resulted in improvement in data quality and timeliness of the GPCR as a cancer registry unit with limited resources. It has the potential to be considered as a model for population-based cancer registries in lower-resource settings.
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