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<p>There is an unmet need for a tool that could predict early favorable prostate-specific antigen (PSA) response in metastatic hormone sensitive prostate cancer (mHSPC) patients receiving androgen receptor pathway inhibitor (ARPI). Here, we train and validate a multivariable logistic regression model to predict early favorable PSA response (≤0.2 ng/mL by 6 months) in these patients. Patients randomly allocated to the ARPI arms of the LATITUDE (abiraterone), TITAN (apalutamide), and ARASENS (darolutamide) trials, are split 60:40 into training (<i>n</i> = 1030) and internal validation (<i>n</i> = 688) cohorts. The locked model is validated in an independent external validation cohort - the enzalutamide arm of the ENZAMET trial (<i>n</i> = 540). The area under curve and Brier score for the locked model in the external validation cohort are 0.82 (95% confidence interval [CI] = 0.78–0.85) and 0.16, respectively. Stratification by predicted probability tertiles show PSA response rates of 92% (95% CI = 88–96), 74% (95% CI = 68–81), and 39% (95% CI = 32–47), respectively. Pending prospective validation, our model predicts early favorable PSA response supporting its potential role in guiding treatment decisions.</p>

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Early favorable prostate-specific antigen response prediction in metastatic hormone sensitive prostate cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月17日

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  • Soumyajit Roy,
  • Yilun Sun,
  • Maha Hussain,
  • Kim N. Chi,
  • Karim Fizazi,
  • Ian D. Davis,
  • Susan Halabi,
  • Neeraj Agarwal,
  • Simon Chowdhury,
  • Bertrand Tombal,
  • Scott C. Morgan,
  • Shawn Malone,
  • Pedro C. Barata,
  • Michael Ong,
  • Christopher J. D. Wallis,
  • Alejandro Berlin,
  • Umang Swami,
  • Amar U. Kishan,
  • Angela Y. Jia,
  • Nicholas G. Zaorsky,
  • Jorge A. Garcia,
  • Prateek Mendiratta,
  • Jason R. Brown,
  • Vinod V. Subhash,
  • Martin R. Stockler,
  • Hayley Thomas,
  • Rana R. McKay,
  • Eric J. Small,
  • Neal D. Shore,
  • Fred Saad,
  • Christopher J. Sweeney,
  • Daniel E. Spratt

摘要

There is an unmet need for a tool that could predict early favorable prostate-specific antigen (PSA) response in metastatic hormone sensitive prostate cancer (mHSPC) patients receiving androgen receptor pathway inhibitor (ARPI). Here, we train and validate a multivariable logistic regression model to predict early favorable PSA response (≤0.2 ng/mL by 6 months) in these patients. Patients randomly allocated to the ARPI arms of the LATITUDE (abiraterone), TITAN (apalutamide), and ARASENS (darolutamide) trials, are split 60:40 into training (n = 1030) and internal validation (n = 688) cohorts. The locked model is validated in an independent external validation cohort - the enzalutamide arm of the ENZAMET trial (n = 540). The area under curve and Brier score for the locked model in the external validation cohort are 0.82 (95% confidence interval [CI] = 0.78–0.85) and 0.16, respectively. Stratification by predicted probability tertiles show PSA response rates of 92% (95% CI = 88–96), 74% (95% CI = 68–81), and 39% (95% CI = 32–47), respectively. Pending prospective validation, our model predicts early favorable PSA response supporting its potential role in guiding treatment decisions.