pro-gram

pro-gram predicts the likelihood of metastasis on Ga-68 PSMA PET/CT in prostate cancer patients with biochemical recurrence (BCR) using clinical variables to inform imaging referral decisions.

Key Features:

• Nomogram development: A nomogram was developed using multivariable logistic regression to identify independent predictors of metastasis.
• Predictor variables: Independent predictors include International Society of Urological Pathology (ISUP) grade group, prostate-specific antigen (PSA) levels before PET scanning, and PSA doubling time.
• Discrimination performance: Receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.866 (95% confidence interval: 0.788–0.944).
• Internal validation: Internal validation was performed using 50 bootstrap resamples, producing a bootstrap-corrected accuracy of 78.8%.
• Clinical benefit assessment: Decision curve analysis was used to assess the clinical utility of the nomogram.
• Optimal cutoff: An optimal cutoff value of 60% likelihood of metastasis was identified for referring patients to Ga-68 PSMA PET/CT.

Scientific Applications:

• Imaging triage: Predicts which prostate cancer patients with BCR are most likely to have metastasis on Ga-68 PSMA PET/CT to guide referral for imaging.
• Clinical decision support: Provides a data-driven probability estimate to inform management decisions for patients with biochemical recurrence.
• Potential standardization: If validated in larger cohorts, can contribute to standardizing and improving management strategies for prostate cancer recurrence.

Methodology:

Multivariable logistic regression to build the nomogram; receiver operating characteristic (ROC) analysis to report AUC 0.866 (95% CI 0.788–0.944); internal validation with 50 bootstrap resamples yielding bootstrap-corrected accuracy 78.8%; decision curve analysis; identification of a 60% cutoff.