Nomogram for overall survival of patients with progressive metastatic prostate cancer after castration.

Publication/Presentation Date

10-1-2002

Abstract

PURPOSE: To develop a pretreatment prognostic model for survival of patients with progressive metastatic prostate cancer after castration using parameters that are measured during routine clinical management.

PATIENTS AND METHODS: Pretreatment clinical and biochemical determinants from 409 patients enrolled onto 19 consecutive therapeutic protocols from June 1989 through January 2000 were evaluated. The factors selected were age, Karnofsky performance status (KPS), hemoglobin (HGB), prostate-specific antigen (PSA), lactate dehydrogenase (LDH), alkaline phosphatase (ALK), and albumin. These factors were combined in an accelerated failure time regression model to produce a nomogram to predict median, 1-year, and 2-year survival. The nomogram was validated internally and externally using data from a multicenter randomized trial of suramin plus hydrocortisone versus hydrocortisone alone.

RESULTS: The median survival of the entire group was 15.8 months (range, 0.9 to 77.8 months); 87% have died. In multivariable analysis, KPS, HGB, ALK, albumin, and LDH were significantly associated with survival (P < .05), whereas age and PSA were not. All seven factors were included in the nomogram. When applied to the external validation data set, the nomogram achieved a concordance index of 0.67. Calibration plots suggested that the nomogram was well calibrated for all predictions.

CONCLUSION: A nomogram derived from pretreatment parameters that are measured on a routine basis was constructed. It can be used to predict the median, 1-year, and 2-year survival of patients with progressive castrate metastatic disease with reasonable accuracy. The information is useful to assess prognosis, guide treatment selection, and design clinical trials.

Volume

20

Issue

19

First Page

3972

Last Page

3982

ISSN

0732-183X

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

12351594

Department(s)

Administration and Leadership

Document Type

Article

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