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Critical analysis of prostate-specific antigen doubling time calculation methodology†
Article first published online: 2 FEB 2006
Copyright © 2006 American Cancer Society
Volume 106, Issue 5, pages 1047–1053, 1 March 2006
How to Cite
Svatek, R. S., Shulman, M., Choudhary, P. K. and Benaim, E. (2006), Critical analysis of prostate-specific antigen doubling time calculation methodology. Cancer, 106: 1047–1053. doi: 10.1002/cncr.21696
Presented at a podium session at the American Urologic Association Meeting, San Antonio, Texas, May 25, 2005.
- Issue published online: 17 FEB 2006
- Article first published online: 2 FEB 2006
- Manuscript Accepted: 30 SEP 2005
- Manuscript Revised: 19 AUG 2005
- Manuscript Received: 4 JUN 2005
- prostate-specific antigen;
- doubling time;
- random coefficient model;
- prostate carcinoma
Prostate-specific antigen (PSA) doubling time (PSADT) has emerged as an important surrogate marker of disease progression and survival in men with prostate carcinoma. The literature is replete with different methods for calculating PSADT. The objective of the current study was to identify the method that best described PSA growth over time and predicted disease-specific survival in men with androgen-independent prostate carcinoma.
PSADT was calculated for 122 patients with androgen-independent prostate carcinoma using 2 commonly used methods: best-line fit (BLF) and first and last observations (FLO). Then, PSADT was calculated by using both a random coefficient linear (RCL) model and a random coefficient quadratic (RCQ) model. Statistical analysis was used to compare the ability of the methods to fit the patients' PSA profiles and to predict disease-specific survival.
The RCQ model provided the best fit of the patients' PSA profiles, as determined according to the significance of the added parameters for the RCQ equation (P ≤ 0.002). The PSADT estimates from the FLO method, the RCL model, and the RCQ model were highly significant predictors (P < 0.001) of disease-specific survival, whereas estimates from the BLF method were not found to be significant predictors (P = 0.66). PSADT estimates from the RCQ and RCL models provided an improved correlation of disease-specific survival (both R2 = 0.55) compared to the FLO (R2 = 0.11) and BFL (R2 = 0.003) methods.
Random coefficient methods provided a more reliable fit of PSA profiles than other models and were superior to other available models for predicting disease-specific survival in patients with androgen-independent prostate carcinoma. The authors concluded that consideration should be given to applying the RCL or RCQ models in future assessments of PSADT as a predictive parameter. Cancer 2006. © 2006 American Cancer Society.