Comparison of PSA-based
g
-rate and conventional PSA metrics in veterans with metastatic prostate cancer (mPC).
Authors: Leuva Harshraj , Zhou Mengxi , Teply Benjamin A. , Park Yeun-Hee Anna , Faiena Izak , Bates Susan Elaine , Fojo Antonio Tito 
Published: February 2025

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Background:
While PSA is routinely used for monitoring in clinics for pts with mPC, it is not a surrogate endpoint for survival or benefit in the majority of cases for specific interventions. However, a novel tumor growth rate (
g
-rate) method that can estimate tumor growth (
g
) and decay (
d
) rates using PSA values while on treatment, has the potential to serve as such. This has been validated to show a robust inverse correlation with overall survival (OS) using 13 clinical trials and real-world data from the US Veterans in mPC regardless of type of treatments. We now compare its prognostic utility to currently used PSA metrics.
Methods:
We have created a comprehensive database to assess drug efficacy in mPC by collecting data from the VA nationalized data warehouse using VA Informatics. Details such as age, race, serial PSA values, reason for treatment, castrate sensitive (mCSPC) or resistant (mCRPC) setting, line of therapy, and survival were collected.
g
and
d
rates are calculated using PSA values while on treatment via the TUMGr package for R.
Results:
We collected PSA values on 38,929 treatment records from 25,023 unique pts getting novel hormonal therapies (abiraterone, enzalutamide, darolutamide, apalutamide), chemotherapies (docetaxel, cabazitaxel) or olaparib. Of this, 17383 had achieved a nadir followed by an increase in PSA, 10738 had the last available result as their lowest, and 10808 had a PSA rise only while on treatment. Nadir-based PSA metrics, such as 50% decrease in PSA (PSA50), absolute PSA nadir, percent PSA nadir can be applied to 28,121 (72%) of records. PSA50 response rate was noted in 1780/2390 (84%) mCSPC and 16796/36539 (65%) mCRPC pts. Only 487 (20%) and 155 (6.5%) of mCSPC and 2038(5.6%) and 508 (1.4%) of mCRPC achieved PSA of 0.2 and 0.02 at 6 months(mo), respectively. For pts with PSA rise only, PSA doubling time(DT) of < 3 mo was noted in 5843 (54%). However,
g
-rate was calculated in 36124 (93%) of pts regardless of treatment type, treatment setting, and rise or fall in PSA while on treatment. 22,800 pts had at least 3 PSA values within the first 3 mo of starting treatment, and we could calculate either
g
or
d
values in 19,465 (85%) of pts. Linear regression testing of both log
g
and log percent PSA nadir revealed a robust inverse correlation with OS, with R
2
of 0.98 and 0.99, respectively.
Conclusions:
PSA decline with absolute 6 mo PSA < 0.2 or PSA increase with DT of < 3 mo was noted in only 26% and 54 % of pts, respectively, noting limitation of current validated PSA metrics. In contrast, we can calculate the
g
-rate in 93% of pts on treatments and
g
values can be calculated or imputed as early as 3 months. It has a robust inverse correlation with OS demonstrating its superiority over PSA kinetics alone. The
g
-rate method can potentially replace all current PSA-based metrics regardless of decline or increase in PSA for assessing treatment response in mPC in both research and clinical settings.