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Clinical Trial
. 2017 Apr 15;23(8):1967-1973.
doi: 10.1158/1078-0432.CCR-16-1224. Epub 2016 Sep 27.

The Added Value of Circulating Tumor Cell Enumeration to Standard Markers in Assessing Prognosis in a Metastatic Castration-Resistant Prostate Cancer Population

Glenn Heller  1 , Karim Fizazi  2   3 , Robert McCormack  4 , Arturo Molina  5 , David MacLean  6 , Iain J Webb  6 , Fred Saad  7 , Johann S de Bono  8 , Howard I Scher  9   10
Affiliations
Clinical Trial

The Added Value of Circulating Tumor Cell Enumeration to Standard Markers in Assessing Prognosis in a Metastatic Castration-Resistant Prostate Cancer Population

Glenn Heller et al. Clin Cancer Res. .

Abstract

Purpose: Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease for which better prognostic models for survival are needed. We examined the added value of circulating tumor cell (CTC) enumeration relative to common prognostic laboratory measures from patients with CRPC.Methods: Utility of CTC enumeration as a baseline and postbaseline prognostic biomarker was examined using data from two prospective randomized registration-directed trials (COU-AA-301 and ELM-PC4) within statistical models used to estimate risk for survival. Discrimination and calibration were used to measure model predictive accuracy and the added value for CTC enumeration in the context of a Cox model containing albumin, lactate dehydrogenase (LDH), PSA, hemoglobin, and alkaline phosphatase (ALK). Discrimination quantifies how accurately a risk model predicts short-term versus long-term survivors. Calibration measures the closeness of actual survival time to the predicted survival time.Results: Adding CTC enumeration to a model containing albumin, LDH, PSA, hemoglobin, and ALK ("ALPHA") improved its discriminatory power. The weighted c-index for ALPHA without CTCs was 0.72 (SE, 0.02) versus 0.75 (SE, 0.02) for ALPHA + CTCs. The increase in discrimination was restricted to the lower-risk cohort. In terms of calibration, adding CTCs produced a more accurate model-based prediction of patient survival. The absolute prediction error for ALPHA was 3.95 months (SE, 0.28) versus 3.75 months (SE, 0.22) for ALPHA + CTCs.Conclusions: Addition of CTC enumeration to standard measures provides more accurate assessment of patient risk in terms of baseline and postbaseline prognosis in the mCRPC population. Clin Cancer Res; 23(8); 1967-73. ©2016 AACR.

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Conflict of interest statement

Disclosure of Potential Conflicts of Interest: G. Heller reports research funding to Memorial Sloan Kettering Cancer Center from Janssen Research & Development, and he has served as an uncompensated consultant to Takeda Millennium. K. Fizazi has nothing to disclose. R. McCormack is an employee of Janssen Oncology Research & Development, LLC. A. Molina was an employee of Janssen Research & Development at the time of the analysis, and owns stock in Johnson & Johnson. D. MacLean and I.J. Webb are employees of Takeda Pharmaceuticals, which sponsored the C21004 and C21005 studies in men with metastatic CRPC. F. Saad been involved in advisory boards, received honoraria and served as an investigator for research funded by Astellas, Janssen, Takeda Millennium. J.S. de Bono has nothing to disclose. H.I. Scher reports research funding to Memorial Sloan Kettering Cancer Center from Janssen Research & Development, BIND Therapeutics, Medivation, Innocrin Pharma, and Exelixis; has served as an uncompensated consultant to AstraZeneca, BIND Pharmaceuticals, Blue Earth Diagnostics, Bristol Myers Squibb, Celegene, Genentech, Medivation, Novartis, Pfizer, Takeda Millennium, and Endocyte; has served as a paid consultant to Astellas, Elseiver's Practice Up-date, Ferring Pharmaceuticals, MED IQ, Merck, Oncology STAT, Roche, Sanofi Aventis, WCG Oncology, and Chugai Academy for Advanced Oncology; has received honoraria from BIND Pharmaceuticals and Blue Earth Diagnostics.

Figures

Figure 1
Figure 1
Consort diagrams for the COU-AA-301 (A) and ELM-PC4 (B) studies.
Figure 2
Figure 2
COU-AA-301 negative (A) and positive (B) predictive value and calibration (C) curves. Note: Negative predictive value includes patients in the lowest quartile and positive predictive value those in the highest of risk scores within each model. An improvement in the negative predictive value among these low-risk patients would be shown by an increase in the Kaplan-Meier estimate. An improvement in the positive predictive value among these high-risk patients would be demonstrated by an increase in the one minus Kaplan-Meier estimate. Calibration represents the relationship between observed survival time and the median predicted survival time. A model with good calibration would closely approximate the 45° line through the origin.
Figure 3
Figure 3
ELM-PC4 negative (A) and positive (B) predictive value and calibration (c) curves. Note: Negative predictive value includes patients in the lowest quartile of risk scores within each model; positive predictive value includes patients in the highest quartile of risk scores within each model; calibration represents the relationship between observed survival time and the median predicted survival time.
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References

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