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Prostate cancer

Genomic information improves risk prediction

Nature Reviews Clinical Oncology volume 15, pages 66–67 (2018)Cite this article

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The US National Comprehensive Cancer Network (NCCN) classification system, commonly used to determine the prognosis of patients with localized prostate cancer, incorporates data on PSA levels, grade group and T stage. This system was developed to predict the chance of biochemical recurrence, an end point subsequently shown to be a poor surrogate of overall survival outcomes. To overcome this limitation, Dan Spratt and colleagues have developed a method that incorporates genomic information, now described in the Journal of Clinical Oncology.

Nearly 7,000 patients were involved in this multicentre study, which included two prospective cohorts (n = 5,937) and two retrospective cohorts (n = 991) with long-term outcomes data (median follow-up duration of 8 years). Data from the two retrospective cohorts were used for training and validation of the new risk-grouping system. “Earlier this year, we demonstrated the robustness of the Decipher genomic classifier for risk prediction across nearly all patient subgroups. We have now used modelling methods to generate a combination of clinical and genomic information. We found that a simple summation of the NCCN and Decipher scores results in an optimal model that is very easy to use,” Spratt describes.

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References

  1. Spratt, D. E. et al. Development and validation of a novel integrated clinical-genomic risk group classification for localized prostate cancer. J. Clin. Oncol. http://dx.doi.org/10.1200/JCO.2017.74.2940 (2017)

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  1. Diana Romero
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Romero, D. Genomic information improves risk prediction. Nat Rev Clin Oncol 15, 66–67 (2018). https://doi.org/10.1038/nrclinonc.2017.205

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