Table 2 Summary of selected articles from systematic review

[Benedetto et al., 2019] [37]

Design and validate SWInCaRe, a web-based application for cancer registry management

Manual vs. automated data processing; record linkage algorithms; usability evaluation

Cancer case coding, incidence, mortality, patient demographics

Automated procedures improved time and cost-efficiency. The system enhanced usability for cancer registries.

Highlights the efficiency and challenges in automation for cancer data collection, relevant for integration into cancer surveillance systems.

[Yang et al., 2021] [38]

Develop a web-based system to explore cancer risks with long-term drug use

Logistic regression on population-based datasets

Drug exposure, cancer risk factors, demographic characteristics

Identified associations between drug usage and cancer risk; provided predictive tools.

Demonstrates integration of predictive analytics in cancer surveillance, offering lessons for advanced functionality.

[Krejčí et al., 2021] [39]

Development of the Czech Childhood Cancer Information System (CCCIS)

Combined data from national cancer registries, death certificates, and clinical databases

Incidence,

survival,

mortality

Interactive platform enabled comprehensive epidemiological reporting for childhood cancers.

Example of integrating diverse data sources for a specialized cancer registry system.

[Henton et al., 2017] [40]

Implement SEER Cancer Survival Calculator (SEER*CSC)

Population datasets; usability testing

Survival rates, patient demographics, treatment data

Highlighted barriers in integrating tools into clinical workflows; improved communication with patients.

Useful for identifying challenges in tool adoption and integration with existing systems.

[Lundin et al., 2003] [41]

Evaluate an internet-based method for breast cancer survival estimation

Kaplan-Meier survival curves based on Finnish nationwide data

Survival probability, tumor characteristics, treatment outcomes

Demonstrated accuracy of survival estimates using web-based tools.

Validates survival prediction methodologies and underscores their utility in cancer care.

[Liang et al., 2023] [42]

Develop a visualized nomogram for small-cell lung cancer (SCLC)

Multivariable Cox regression; SEER database

Prognostic factors, survival probabilities

Visualized nomograms achieved high accuracy and usability.

Emphasizes the role of user-friendly tools in stratifying cancer risks and improving clinical decisions.

[Bianconi et al., 2012] [43]

Use IT tools for cancer registry and network integration

Web-based systems; GIS for data visualization

Incidence, mortality, survival, geographic analysis

Enabled geospatial mapping of cancer data, improving regional surveillance.

Exemplifies integration of GIS for enhancing data utility in cancer monitoring.

[Nasseh et al., 2020] [44]

Optimize oncology-related data analytics via Munich Online Comprehensive Cancer Analysis (MOCCA)

In-memory database analysis

Tumor descriptors, treatment data, demographic data

Improved data transparency and analytical capabilities for large datasets.

Highlights advanced analytics and visualization for multi-faceted oncology data.

[Mason et al., 2021] [45]

Develop a web-based calculator for metastatic progression in bladder cancer

Longitudinal dataset analysis; Markov modeling

Metastatic patterns, survival statistics, treatment pathways

Offered spatiotemporal insights into metastatic progression.

Demonstrates the importance of dynamic, real-time prediction in cancer systems.

[Jones et al., 2021] [46]

Pursue cancer data modernization with cloud-based systems

Pilot cloud computing platforms; automation analysis

Incidence, case tracking, real-time data

Automation reduced manual labor; improved timeliness and accuracy in cancer data reporting.

Supports the need for modernization and real-time data capabilities in cancer surveillance.

[Conderino et al., 2022] [10]

Assess the potential of electronic health records (EHRs) for public health surveillance of cancer prevention and control.

A scoping review of studies on EHRs for cancer surveillance, followed by a test of proposed indicators using common data models.

Indicators related to cancer prevention, early detection, treatment outcomes, and survivorship care extracted from EHRs; tested indicators for their feasibility and accuracy in public health surveillance systems.

EHR data can be a valuable resource for cancer surveillance, with indicators providing insights into prevention, early detection, and control. Challenges include data standardization, integration with existing CSS, and ensuring data quality and completeness.

Highlights the utility of advanced technological integration (EHRs) in cancer surveillance systems, aligning with this study’s emphasis on technological adaptability and standardization to improve CSS effectiveness.

[Ben Ramadan et al., 2017] [47]

Usability assessment of Missouri Cancer Registry’s Interactive Mapping Reports (Round 1)

Mixed-methodology usability testing; System Usability Scale (SUS)

GIS tools usability, mapping effectiveness, satisfaction metrics

Identified issues with user satisfaction and usability; recommendations for improvement.

Highlights the importance of user-centered design in GIS-based cancer surveillance tools.

[Ben Ramadan et al., 2019] [48]

Usability assessment of Missouri Cancer Registry’s Interactive Mapping Reports (Round 2)

Updated usability testing; comparison to previous round

GIS tools usability, task success rates, user satisfaction

Improved task completion rates; highlighted usability barriers specific to cancer professionals.

Reinforces the role of iterative refinement in designing effective cancer registry systems.