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Thread: Time to Move Beyond NCCN Risk Stratification? / Adding Genomics to Interm. Risk RT

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    Time to Move Beyond NCCN Risk Stratification? / Adding Genomics to Interm. Risk RT

    Although genomic testing is making its way into decision-making, it hasn't been incorporated into the commonly used risk-groups. Both of these issues are addressed in this recent editorial and study. The editorial is in reference to the study (below), which is in the same journal issue. The Decipher test was the genomics test used in this study.

    Precision Medicine for Localized Prostate Cancer: Time to Move Beyond NCCN Risk Stratification? [2019, Editorial, Full Text]

    Prostate cancer is the leading cause of cancer treatment–related years lived with disability for men worldwide.1 This has driven a disruptive change in management of favorable-risk prostate cancer such that nearly all National Comprehensive Cancer Network (NCCN) very low-risk patients are recommended conservative management rather than radical therapy.2 Simultaneously, at the other end of the risk spectrum, treatment intensification with more potent systemic therapies has been the subject of recent trials for men with higher-risk disease (eg, NCT02772588 ). Given this tremendous heterogeneity, how does one decide how best to personalize treatment for men who harbor disease outside of the extreme ends of this spectrum?

    What clinicians have always used, and what we still use today to guide nearly all treatment decisions in all cancer types, are prognostic biomarkers. In prostate cancer, the classic examples are prostate-specific antigen (PSA), TNM stage, and Gleason grade (eg, International Society of Urological Pathology grade groups). Usually these variables are combined into multivariable models, such as NCCN risk groups, that have improved performance over single-variable models to identify which patients will ultimately experience recurrence or die from prostate cancer. Patients in general with a high PSA, Gleason score, and T-stage have a worse prognosis than a typical patient with a low PSA, Gleason score, and T-stage, regardless of whether they are treated with surgery, radiation therapy, or observation. However, although these biomarkers help determine who is more likely to have recurrence, they do not indicate which patients will intrinsically derive greater relative benefit from a given therapy, and thus they are prognostic and not predictive biomarkers.

    Although predictive biomarkers are ideal biomarkers for clinical decision making, “ultra-prognostic” biomarkers can effectively serve as biomarkers to drive therapeutic decisions. An ultra-prognostic biomarker is one that can accurately predict which patients have such a favorable outcome of interest that treatment intensification would be futile and improbable to show any benefit. For example, if low-risk patients have a 1% risk of distance metastasis and very high-risk patients have a 30% risk, even if androgen deprivation therapy (ADT) has the same relative effect in both groups, the absolute benefit would be clinically meaningful only in the higher risk group because the risk of metastasis is so small in low-risk patients that the harms of the treatment would outweigh any possible benefit.

    How well do NCCN risk groupings, on which we base nearly all treatment decisions, perform in accurately discriminating which patients will experience recurrence, develop metastatic disease, or die from prostate cancer? To many people's surprise, the classic 3-tiered NCCN risk groups commonly have an area under the curve (AUC) (a test of discriminatory ability) of only 0.50 to 0.65 (by comparison, a random coin flip would have an AUC of 0.5).3

    The expanded Zumsteg (or MSKCC) 4-tier system improved the original NCCN system by stratifying the heterogeneous intermediate-risk subgroup into favorable and unfavorable groups based on primary Gleason pattern, percentage of positive biopsy cores, and number of intermediate risk factors.4 This stratification of intermediate-risk prostate cancer has been validated in over 7500 intermediate-risk patients across multiple independent datasets and various treatment modalities and is now codified in NCCN guidelines.2, 4, 5, 6, 7 One of the most important elements of the favorable/unfavorable intermediate risk classification, in terms of clinical decision making, was the realization that favorable intermediate-risk patients have a very small risk of metastasis and prostate cancer–specific mortality, similar to low-risk prostate cancer in fact, and therefore seem to derive relatively little absolute benefit from the addition of ADT to radiation.4, 7 Nevertheless, substantial heterogeneity remains, particularly for those with unfavorable intermediate-risk disease, and better ways to discriminate pretreatment indolent and aggressive disease in these patients are still needed.
    ...
    See Full Text

    Genomic Classifier for Guiding Treatment of Intermediate-Risk Prostate Cancers to Dose-Escalated Image Guided Radiation Therapy Without Hormone Therapy [2019, Full Text]

    Abstract

    Purpose
    The National Comprehensive Cancer Network (NCCN) has recently endorsed the stratification of intermediate-risk prostate cancer (IR-PCa) into favorable and unfavorable subgroups and recommend the addition of androgen deprivation therapy (ADT) to radiation therapy (RT) for unfavorable IR-PCa. Recently, more accurate prognostication was demonstrated by integrating a 22-feature genomic classifier (GC) to the NCCN stratification system. Here, we test the utility of the GC to better identify patients with IR-PCa who are sufficiently treated by RT alone.

    Methods and Materials
    We identified a novel cohort comprising 121 patients with IR-PCa treated with dose-escalated image guided RT (78 Gy in 39 fractions) without ADT. GC scores were derived from tumors sampled in diagnostic biopsies. Multivariable analyses, including both NCCN subclassification and GC scores, were performed for biochemical failure (prostate-specific antigen nadir + 2 ng/mL) and metastasis occurrence.

    Results
    By NCCN subclassification, 33 (27.3%) and 87 (71.9%) of men were classified as having favorable and unfavorable IR-PCa, respectively (1 case unclassifiable). GC scores were high in 3 favorable IR-PCa and low in 60 unfavorable IR-PCa. Higher GC scores, but not NCCN risk subgroups, were associated with biochemical relapse (hazard ratio, 1.36; 95% confidence interval [CI], 1.09-1.71] per 10% increase; P = .007) and metastasis (hazard ratio, 2.05; 95% CI, 1.24-4.24; P = .004). GC predicted biochemical failure at 5 years (area under the curve, 0.78; 95% CI, 0.59-0.91), and the combinatorial NCCN + GC model significantly outperformed the NCCN alone model for predicting early-onset metastasis (area under the curve for 5-year metastasis of 0.89 vs 0.86 [GC alone] vs 0.54 [NCCN alone]).

    Conclusions
    We demonstrated the accuracy of the GC for predicting disease recurrence in IR-PCa treated with dose-escalated image guided RT alone. Our findings highlight the need to evaluate this GC in a prospective clinical trial investigating the role of ADT-RT in clinicogenomic-defined IR-PCa subgroups.
    See Full Text.

    [All emphasis mine.]

    Genomic classifiers are showing their mettle across risk groups for treatment decisions. IMO it just makes sense to get one. It might tell you something new or might confirm what you thought. In either case, it's information about your cancer, unlike something like a nonomgram, which lumps together and averages out several factors except genomics.
    Last edited by DjinTonic; 07-18-2019 at 04:35 PM.

 

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