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The Predictive DCIS Test

DCISionRT® identifies which clinically low-risk patients have elevated biological risk, with a likelihood of benefiting from radiation therapy.

DCISionrt upstages diagram

Not every case of DCIS is the same.
Precision Therapy needs Precision Information.

DCISionRT® Predicts Which Patients Would Benefit from Radiation Therapy

  • In patients identified by DCISionRT as having Elevated IBC Risk, there was a 9% absolute benefit and 70% relative Risk reduction from radiation therapy (HR 0.24, p=0.012)2
  • In patients identified by DCISionRT as having Low IBC Risk, there was no significant benefit (1%) from radiation therapy (HR 0.84, p=NS)2

DCISionRT® enables Radiation Oncologists to be more confident that the right patients receive radiation therapy.

Developed specifically for DCIS and 10-year local recurrence1, 4

  • The most comprehensive assessment available of key drivers of progression and recurrence in DCIS
  • Non-linear algorithmic machine-learning integration of 7 biomarkers across 5 pathways with 4 clin/path factors (age, size, margin status, palpability)2

Provides biologic insight beyond clin/path factor

  •  Consistently reclassifies more than 50% of patients with clinical significance3
  • “Non-linear modeling integrates combinations of factors and accounts for complex interactions between them. This method explains why the Decision Score* mitigated the significance of traditional individual prognostic variables…”4

*Decision Score is a proprietary result of PreludeDx’s DCISionRT test.

Predicts RT benefit (supported by Level 1b evidence)

  • 70% relative RT benefit and 9% absolute RT benefit for patients with Elevated IBC Risk by DCISionRT
    (HR 0.24, p=0.012)4
  • No significant RT benefit (1%) for patients with Low IBC Risk by DCISionRT (HR 0.84). p=NS)2, 4

Published and presented in numerous clinical studies covering greater than 2,000 patients with consistent results

Clinical
Cancer Research

Validation of predictive biologic profile

2018

Cancer Research

Validation of predictive biologic profile

2017

MBCC

Comparison of biologic risk profile to MSKCC

2017

Cancer Research

Validation of biologic profile

2016

MBCC

Early Validation of biologic profile

2015

JNCI

Development of biologic profile

2010

Validated across a comprehensive patient population

  • Clinically indicated regardless of pathology, margin status, lesion size or patient age
    • +/- ER, PR, HER2
    • +/- 50 years old
    • +/- Margins
    • Size ≤ 5 mm and > 2.5 cm
  1. Whitworth PW et al. ASBS; Abstract: Interim Analysis of the DCISionRT PREDICT Study: Clinical Utility of a Biologic Signature Predictive of Radiation Therapy Benefit in Patients with DCIS
  2. Warnberg, F et al. A Validation of DCIS Biological Risk Profile in a Randomised Study for Radiation Therapy with 20 Year Follow-up (SweDCIS), SABCS 2017; Abstract: 851741
  3. Bremer, TM et al. MBCC 2017 Poster: Utility of the DCIS Biological Risk Profile for Predicting Recurrence Risk Compared to Standard Clinicopathologic Factors
  4. Bremer, TM et al. A Biological Signature for Breast Ductal Carcinoma In Situ to Predict Radiotherapy (RT) Benefit and Assess Recurrence Risk. Clinical Cancer Research 2018; published online 12/01/2018.

This test was developed and its performance characteristics determined by PreludeDx. It has not been cleared or approved by the FDA. This test is used for clinical purposes and should not be regarded as investigational or for research. The laboratory is certified under CLIA-88 as qualified to perform high complexity clinical testing.

To help a patient that could benefit from DCISionRT

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