MSKCC Nomogram Update: Metastatic Progression Prediction in the Italian TPCP Cohort

The Turin Prostate Cancer Prognostication cohort includes data from 891 unselected prostate cancer patients diagnosed between 2008 and 2013 in Turin, Italy. Nicolas Destefanis authored this research, which updates and compares the D’Amico, CAPRA, and MSKCC prognostic models for predicting metastatic disease within five years of diagnosis. The dataset was last updated on 2026-05-13.

Use Cases

• Compare the performance of prognostic models (MSKCC, CAPRA, D’Amico) for predicting metastatic progression based on clinical cohort data.
• Assess the utility of nomogram-based risk thresholds for active surveillance eligibility based on predicted probabilities.
• Analyze the impact of competing risks on model performance for metastatic disease and overall mortality.
• Investigate the trade-off between increasing active surveillance uptake and minimizing metastatic risk using model-derived thresholds.

Strengths

• Dataset includes 891 patient records from a defined clinical cohort.
• Analysis provides optimism-corrected discrimination metrics (AUC) and scaled Brier scores for model comparison.
• Research explores a specific five-year timeframe for metastatic progression prediction.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying data is unknown, which may limit suitability assessment.
• Data may reflect geographic and temporal bias inherent to a single Italian cohort from 2008-2013.

Provenance

Source

Turin Prostate Cancer Prognostication (TPCP) cohort.

Collection Method

Clinical cohort analysis of unselected prostate cancer patients.

Time Range

Patients diagnosed between 2008 and 2013.

Freshness

Last updated 2026-05-13 04:41:17; freshness should be verified.

Geography

Turin, Italy.