Risk-Adjusted CUSUM Chart for Breast Cancer Treatment Monitoring

A 2026 study by Navid Rafiei introduces a novel log-logistic risk-adjusted CUSUM control chart for monitoring therapeutic processes in breast cancer patients. The chart incorporates an accelerated failure time model for patient risk adjustment and uses multi-objective optimization to balance detection speed and cost-efficiency.

Use Cases

• Validate the novel log-logistic RACUSUM chart's performance against traditional models using clinical breast cancer data.
• Apply the integrated AFT model for precise risk adjustment of individual patient survival times in therapeutic monitoring.
• Implement the multi-objective optimization framework, utilizing MOPSO, DEA, and WASPAS methods for optimal parameter selection in control chart design.
• Assess the chart's sensitivity and specificity in detecting deviations in breast cancer treatment effectiveness.

Strengths

• Method validated with a clinical case study at a breast cancer center.
• Integrated approach balances detection speed and cost-efficiency via multi-objective optimization.
• Chart design incorporates an AFT model for precise adjustment of individual patient risk factors.

Limitations

• Dataset size is 8.7 KB, indicating a very limited scope, likely containing methodological descriptions or summary results rather than raw patient data.
• No column or sample data is provided, limiting direct analytical utility for ML practitioners.
• The data represents a specific methodological case study, which may not be generalizable without adaptation.

Provenance

Source

figshare, author Navid Rafiei

Collection Method

Proposed methodological study validated with a clinical case study.

Time Range

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Freshness

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Geography

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