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Criteria for Optimizing Prognostic Risk Groups in Pediatric Cancer: Analysis of Data From the Children's Oncology Group

Richard Sposto, Wendy B. London, Todd A. Alonzo

From the Children's Center for Cancer and Blood Diseases, Children's Hospital Los Angeles; Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA; Department of Epidemiology and Health Policy Research, University of Florida, Gainesville, FL; and the Children's Oncology Group, Bethesda, MD

Address reprint requests to Richard Sposto, PhD, Children's Center for Cancer and Blood Diseases, Children's Hospital Los Angeles, 4650 Sunset Blvd, Mail Stop #54, Los Angeles, CA 90027-6016; e-mail: rsposto{at}chla.usc.edu

Purpose: Physicians who treat cancer often attempt to identify patient subgroups that are homogeneous in their chance of recurrence or death as a way to target the more toxic and presumably more effective treatments to patients with the worst prognosis. However, to date, prognosis-based treatment assignment in pediatric cancer has not been based on a quantitative assessment of the risks and benefits of different treatment strategies or on morbidity and efficacy outcome measures that are relevant to children.

Methods: We performed a quantitative analysis of the risks and benefits of prognosis-based treatment assignment in two examples from the Children's Oncology Group using a mathematical model of cancer cure and permanent treatment morbidity and defined an optimality criterion for assigning treatments to specific risk groups.

Results: In stage 4 MYCN-unamplified neuroblastoma, age-based risk grouping distinguishes clearly between patients with high and low risk of recurrence. However, our analysis suggests that the optimal age cut point depends profoundly on the morbidity of the treatments being considered and agrees with current published recommendations only for treatments that add significant morbidity. In Hodgkin's lymphoma, under our model, no clearly optimal risk groupings exist, and a compelling quantitative rationale for defining risks group at all may not exist.

Conclusion: Our analysis illustrates the inadequacy of naïve application of statistical criteria for defining prognostic risk groups in pediatric cancer and highlights the importance of quantifying treatment morbidity when defining risk groups or when deciding whether risk grouping is warranted.

Supported by Children's Cancer Group (CCG) Grant No. CA 13539 and Children's Oncology Group (COG) Grant No. CA 98543. A complete listing of grant support for research conducted by the CCG and Pediatric Oncology Group before initiation of the COG grant in 2003 is available online at http://www.childrensoncologygroup.org/admin/grantinfo.htm.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.