Presentation on theme: "NanoString’s Prosigna Breast Cancer Assay Bringing Genomic Testing Into Your Lab."— Presentation transcript:
NanoString’s Prosigna Breast Cancer Assay Bringing Genomic Testing Into Your Lab
Measuring Nucleic Acids in Clinical Samples Current clinical practice Formalin-fixed, paraffin-embedded (FFPE) samples pose challenges to accurate and reproducible estimation of biomolecules Challenges of expression-profiling FFPE samples FFPE processed samples provide low and variable yields of mRNA Formalin fixation modifies and degrades mRNA, making it difficult to measure by traditional techniques Analytical need A robust and validated methodology is required to accurately estimate RNA expression levels in tumor FFPE samples 2
nCounter: Designed for Translational Research Highly Multiplexed 800 targets per reaction No Amplification (for > 25ng RNA input) Tolerant of FFPE and no bias Precision Digital counting means unparalleled reproducibility over nearly 6 logs of dynamic range Simple and Fast Easier, faster, automated data production Capture Probe Reporter Probe Target Target-Probe Complex
nCounter Advantage for Quantitating Nucleic Acids in FFPE Samples Direct measurement minimizes error/bias from enzyme-based processes (reverse transcriptase and polymerase) Ability to detect short chain RNA templates Linearity of measurement over a wide dynamic range ensures accurate quantitation of both rare and abundant transcripts –Facilitated by solution phase hybridization –Digital counting design –Excess probes Allows for flexible range of sample input 4
nCounter Workflow: Hands-off Process Enables Decentralized Testing 5 Simple and fast workflow is well suited for qualified clinical laboratories 1 1 nCounter ® Prep StationnCounter ® Digital Analyzer Hybridize 2 2 Purify 3 3 Count Step 3 3 – 4.5 HOURS, AUTOMATED Step 3 3 – 4.5 HOURS, AUTOMATED Minimal HANDS-ON Minimal HANDS-ON Step 2 2.5 – 3.0 HOURS, AUTOMATED Step 2 2.5 – 3.0 HOURS, AUTOMATED Minimal HANDS-ON Minimal HANDS-ON Step 1 12 HOURS OR OVERNIGHT Step 1 12 HOURS OR OVERNIGHT Minimal HANDS-ON Minimal HANDS-ON
6 nCounter Dx Analysis System With Flex Configuration A single instrument system can be used to 1.Validate genomic discoveries from NGS or arrays 2.Translate validated discoveries into clinical use 3.Run clinical diagnostics
nCounter Elements: Enabling More Options for Dx Development 7 CodeSets Custom-built assays Standardized panels 300+ peer-reviewed papers Prosigna™ Prosigna Breast Cancer Assay CE Marked & launched in EU Expected Q1 2014 U.S. launch FDA-cleared: September 9, 2013 Since 2009 Advanced Disease Research Global Diagnostic Kits
nCounter Elements: Enabling More Options for Dx Development 8 CodeSets Custom-built assays Standardized panels 300+ peer-reviewed papers nCounter Elements™ Components to Develop Assays Registered with FDA Flexible Format Prosigna™ Prosigna Breast Cancer Assay CE Marked & launched in EU Expected Q1 2014 U.S. launch Commercial Release: February 11, 2014 FDA-cleared: September 9, 2013 Since 2009 Advanced Disease Research Enable Clinical Testing Global Diagnostic Kits
10 Develop algorithm Determine optimal gene set Hierarchical clustering of 1,906 “intrinsic” genes defined by previous studies Optimized gene set (qRT-PCR data from 122 breast cancers) to 161 genes that passed FFPE performance criteria Cross-validation (random 10% left out in each of 50 cycles) by “N” t-test method selected 50 genes Compared reproducibility of classification across 3 centroid-based prediction methods Selected Prediction Analysis of Microarray (PAM) Trained with a multivariable Cox model Risk of recurrence (ROR) score developed for test case using correlation to subtype alone: ROR-S = 0.05*basal + 0.12*HER2 – 0.34*LumA + 0.23* LumB or using subtype correlation plus tumor size: ROR-C= 0.05*basal + 0.11*HER2 – 0.23*LumA + 0.09*LumB + 0.17* T Origins of Prosigna—PAM50 Gene Signature Deriving the Gene Set and Prognostic Algorithm Parker JS, et al. J Clin Oncol. 2009;27(8):1160-1167. Luminal A Basal-like Luminal B HER2-enriched UBE2C PTTG1 MYBL2 CCNB1 BIRC5 HSPC150 TYMS MELK KNTC2 CEP55 CDC6 RRM2 ORC6L ANLN KIF2C EXO1 CENPF CDCA1 CDC20 MKI67 CCNE1 GRB7 TMEM45B ERBB2 BLVRA GPR160 FOXA1 MMP11 NAT1 CXXC5 ESR1 SLC39A6 PGR BAG1 ACTR3B MIA FOXC1 MYC KRT5 SFRP1 KRT17 KRT14 BCL2 PHGDH CDH3 EFGR FGFR4 MDM2 MLPH MAPT Normal
Subtype Predictions by PAM50 Shows Distinct Clinical Outcomes Intrinsic subtypes assigned using PAM50 show clear differences in RFS in node- negative patients who did not receive systemic adjuvant therapy Similar differences in RFS by subtype were seen in the subset of patients with ER + BC 11 RFS, relapse-free survival. Parker JS, et al. J Clin Oncol. 2009;27(8):1160-1167. Patients who did not receive systemic adjuvant therapy Subset of patients with ER + disease 1.0 0.8 0.6 0.4 0.2 0 246810 Time, years 1.0 0.8 0.6 0.4 0.2 0 246810 Time, years Basal-like HER2-enriched Luminal A Luminal B Log-rank P = 2.26e-12 Relapse-Free Survival (probability) Basal-like HER2-enriched Luminal A Luminal B Log-rank P = 1.89e-10
PAM50 ROR-Score Provides Increased Accuracy in Outcome Predictions Risk prediction based on the PAM50 gene set added significant information to pathologic staging, histologic grade, and standard clinical molecular markers 12 Kaplan-Meier estimates of risk groups show clear separation of RFS Parker JS, et al. J Clin Oncol. 2009;27(8):1160-1167. Relapse-Free Survival (probability) Time, years 1.0 0.8 0.6 0.4 2108640 High Low Medium Log-rank P = 9.52e-11
PAM50 Gene Signature Is Robust Validated by TCGA (Independent Dataset, Different Platform) Semi-supervised hierarchical cluster analysis showed consensus across breast cancer intrinsic subtypes defined in independent datasets using 5 different genomic/ proteomic platforms a These data are independent of nCounter technology 13. a Heat map display of subtypes defined independently by microRNAs, DNA methylation, copy number, PAM50 mRNA expression, and RPPA expression. The Cancer Genome Atlas Network. Nature. 2012;490(7418):61-70.
Transitioning qRT-PCR–Based PAM50 to nCounter Platform (NanoString) Objective Replace qRT-PCR protocol with an automated, multiplexed assay (nCounter) to assign risk score Endpoints Assess concordance between outputs: –Expression measurements of each gene –Assignment of intrinsic subtype –Proliferation and risk scores Approach Assess concordance with above endpoints Retrain algorithm using nCounter-based measurements 14
nCounter-Based Measurements Concordant With qRT-PCR 15 Liew M, et al, AMP National Meeting, 2010. ROR scores or proliferation scores obtained using estimates of gene expression of the nCounter-PAM50 gene signature gene panel by qRT-PCR or by the nCounter platform were very similar 80 60 40 20 0 qRT-PCR ROR ScoreProliferation Score –1.0 –05 0.0 0.5 qRT-PCR icc = 0.951icc = 0.947 020406080 NanoString –1.0–0.50.00.5 nCounter results versus qRT-PCR
Switching Analytic Platform to nCounter Retraining the Algorithm Data from Parker et al 1 were re-analyzed using the prototypical subtype centroids from nCounter training Subtypes showed a similar prognostic profile to the originally reported data 16 1.Parker JS, et al. J Clin Oncol. 2009;27(8):1160-1167. ER + 1.0 0.8 0.6 0.4 0.2 0.0 0246810 Probability of Event Log-rank P = 4.16e-07 LumA 62/243 LumB 72/157 Her2 42/81 Basal 32/82 ER – 1.0 0.8 0.6 0.4 0.2 0.0 0246810 Probability of Event LumA 7/51 LumB 19/42 Her2 5/11 Basal 9/28 Log-rank P =.00988 10 All 1.0 0.8 0.6 0.4 0.2 0.0 02468 Probability of Event Log-rank P = 1.14e-08 LumA 72/297 LumB 94/204 Her2 48/95 Basal 42/111
New Training as Robust as Published Classifier in the Intended Use Population The recurrence-free curves of the intrinsic subtype cohorts defined by qRT-PCR (left) and nCounter (right) are highly concordant 17 nCounter (NanoString) Subtype 2 qRT-PCR Subtype 1 1.0 0.8 0.6 0.4 0.2 0.0 051015 1.0 0.8 0.6 0.4 0.2 0.0 051015 Probability of Event Log-rank P =.155 Her2 4/14 LumA 10/54 LumB 22/58 Normal 0/3 Probability of Event Log-rank P =.0336 Her2-enriched 3/13 Luminal A 3/31 Luminal B 30/85 1. Nielsen et al. Clin Cancer Res. 2010;16(21):5222-32. 2. NanoString data on file.
Prosigna Assay Uses the expression profile of 50 classifier genes (and 8 housekeeping genes for normalization) to determine breast cancer subtype and probability of relapse Algorithm provides a continuous risk of recurrence (ROR) score; henceforth, referred to as the “Prosigna Score” –Incorporates intrinsic subtype, proliferation score, and tumor size –Uses different cut-points for probability of relapse in patients with node- negative and node-positive breast cancer Validated on the nCounter platform allowing decentralized and standardized breast cancer testing worldwide 18
Prosigna Algorithm Prosigna Score for Individual Patients ROR score integrates intrinsic subtype, proliferation index, and tumor size (in the context of nodal status) to provide an integer score proportional to the risk of recurrence 19 Determine intrinsic subtype through Pearson’s correlation to centroids aR LumA + bR LumB + cR Her2e + dR Basal + Pearson’s correlation to centroids Calculate ROR (Risk of Recurrence Score) Patient expression profile LumB LumA Basal-like HER2- enriched PAM50 centroids Proliferation score Gross tumor size Gnant M, et al. SABCS. 2012; poster P2-10-02. ROR = eP + fT
Prosigna Score Is a Continuous Risk Function The probability of distant recurrence within 10 years increases as a function of ROR and nodal status based on data in the tested patient population 20 Package Insert (US). http://www.prosigna.com/assets/templates/ProsignaTemplate/doc/Prosigna_Packet_Insert_US.pdfhttp://www.prosigna.com/assets/templates/ProsignaTemplate/doc/Prosigna_Packet_Insert_US.pdf Node-negative Node-positive (1-3 nodes) A change of 10 ROR units corresponds to an average change in 10-year distant recurrence free survival of 7% and 6% for node negative and node positive patients respectively
Prosigna Categorizes Risk Groups by Nodal Status Risk classification groups are provided based on cutoffs related to clinical outcome in the tested patient populations: –Low risk: 10-year probability of distant recurrence of < 10% –High risk: 10-year probability of distant recurrence of > 20% ROR score discriminates risk groups within patients with node-negative disease 21 Nodal StatusROR RangeRisk Categorization Node-negative 0 - 40Low 41 - 60Intermediate 61 - 100High Node-positive (1 - 3 nodes) 0 - 40Low 41 - 100High 1.Package Insert (US). http://www.prosigna.com/assets/templates/ProsignaTemplate/doc/Prosigna_Packet_Insert_US.pdfhttp://www.prosigna.com/assets/templates/ProsignaTemplate/doc/Prosigna_Packet_Insert_US.pdf 2.Gnant M, et al. Ann Oncol. 2014;25(2):339-345.
Prosigna Patient Report The nCounter-PAM50 Gene Signature Assay is intended for use as a prognostic indicator for distant recurrence-free survival at 10 years Indicated for postmenopausal women with Stage I/II lymph node- negative or Stage II lymph node-positive (1 to 3 positive nodes) hormone receptor-positive breast cancer who have undergone surgery in conjunction with locoregional treatment consistent with standard of care Risk of Recurrence (ROR Score) Zero to 100 Relates to recurrence rate at 10 years on 5 years of endocrine therapy alone Risk Groups Node Negative ― Low, Intermediate, or High risk ― Based on ROR Score and nodal status Node Positive ― Low or High risk ― Based on ROR Score and nodal status US Prosigna Patient Report; FDA 510K cleared. 22
Analytic Reproducibility of nCounter-PAM50 Gene Signature Assay Evaluated in Two Studies Study 1: Reproducibility from tissue Extract RNA from FFPE tumor sample Study 2: Precision from RNA nCounter- PAM50 ROR Score Run on the nCounter Dx Analysis System 24
Evaluating Variation in nCounter Gene Expression Estimate RNA Precision Study Assessed reproducibility of device, reagents, and operator-specific components using a common template RNA Measured variability between and within assay variables including –Testing site (n = 3) –Sample type (n = 5) –Operator (n = 6) –Reagent lot (n = 3) –Assay run (n = 18/site) 25 Site 1Site 2Site 3Operator 1Operator 2Reagent Lot 1Reagent Lot 2Reagent Lot 3Run 1Run 2Run 3 Basal-likeHER2-ELum ALum B1Lum B2 X 2 Nielsen T, et al. BMC Cancer. 2014;14(1):177.
Reproducibility of nCounter-PAM50 Gene Signature Assay Concordance in Risk Group Reproducibility Study For each tissue sample, macrodissection, RNA extraction, and processing with the assay were performed by a single operator at each site per standard operating procedures 43 tissues across all sites represent a wide range (94 units) of ROR scores and all risk categories 26 Site 1Site 2Site 3 Operator 1 Operator 2 RNA Isolation Kit 1 Duplicate Run with Reagent Lot 1 Operator 3 Pathologist 1 Pathologist 2 Pathologist 3 Duplicate Run with Reagent Lot 1 Samples 1 - 43 Nielsen T, et al. BMC Cancer. 2014;14(1):177. The definition of “high reproducibility” was pre-specified to be a total SD<4.3
Prosigna Analytically Validated for Decentralized Testing Reproducibility from 43 FFPE Tissue Samples 1 Precision from 5 Pooled RNA Samples 1 Average of 90% risk group concordance between sites Site-to-site or operator-to-operator <1% of variance Prosigna Score Standard Deviation = 2.9 100% concordance between risk groups Site-to-site or operator-to-operator <1% of variance Prosigna Score Standard Deviation = 0.67 1 Analytical Reproducibility of the Breast Cancer Intrinsic Subtyping Test and nCounter ® Analysis System Using Formalin-Fixed Paraffin-Embedded (FFPE) Breast Tumor Specimens. T Nielsen, S McDonald, S Kulkarni, J Storhoff, C Schaper, B Wallden, S Ferree, S Liu, V Hucthagowder, K Deschryver, V Holtschlag, G Barry, M Evenson, N Dowidar, M Maysuria, D Gao. CAP 2013 2Output of the U.S. version of Prosigna submitted for 510(k) does not report intrinsic subtype. Reporting intrinsic subtype in the U.S. will require a future PMA supported by additional clinical studies Prosigna Score 27
Heterogeneity of Breast Cancer The Benefit: Risk Equation
Heterogeneity of Breast Cancer Clinicopathologic covariates and receptor status inform treatment decisions –However, disease course and treatment outcomes in patients with similar baseline disease covariates vary considerably –Advances in molecular understanding suggest underlying heterogeneity 29
Defining Heterogeneity in Breast Cancer Predictive Value of Intrinsic Subtypes 31 1. Wirapati P, et al. Breast Cancer Res. 2008;10(4):R65. 2. Figure from Sorlie T, et al. Proc Nat Acad Sci (USA). 2003;100(14):8418-8423. Clinical evidence suggests that intrinsic subtype is predictive of clinical outcomes 1,2 1 0.8 0.6 0.4 0.2 0 024487296120144168192 Probability Time to distant metastasis, months Luminal A Luminal B Basal ERBB2+ P <.01
Tumor Size, Grade, Lymph Node Status, ER, PR, Her2 Tumor Boards-Good actor vs bad actor
Breast cancer prognostic classification in the molecular era: the role of histological grade Histologic grade (NGS) is a robust, prognostic, with good to excellent reproducibility. The scrutiny applied to histologic grading has only recently been applied to molecular tests. 36% intermediate Histologic Grade; 40% of oncotype dx tests are Intermediate RS. Rare: Grade 1-Grade3. *Rakha EA, Reis-Filho JS, Baehner F, Dabbs DJ, Decker T, Eusebi V, Fox SB, Ichihara S, Jacquemier J, Lakhani SR, Palacios J, Richardson AL, Schnitt SJ, Schmitt FC, Tan PH, Tse GM, Badve S, Ellis IO. Breast Cancer Res. 2010;12(4):207. doi: 10.1186/bcr2607. Epub 2010 Jul 30. Review. PMID: 20804570
What your Pathologists Know – histological surrogates for the intrinsic subtypes Luminal A: – ER +, very high (HS 200-300) – PR + Very High (HS 200-300) – Ki67: Low 3-14% – Grade: 1, few percent grade 2. Luminal B: – ER + intermediate-low (HS 1-200) – PR: negative or low (HS <100) – Grade 2 or 3 – Ki67 >15%, often much higher
Significant Clinical Impact of Oncotype-MammaPrint Discordance Molecular Subtype (MP) PatientsOncotype Dx LUM A63 25% Major Discordance 47 Low, 12 Int, 4 High LUM B51 35% Major discordance 18 Low, 17 Int, 16 High Molecular Subtypes of Cases Discordant Between Risk Classification Assays in ER+ N0-N1 Patients: Shivers et al Miami Breast Conference March, 2014
Dabbs et al. ASCO-June, 2014 Molecular Subtype (MP) PatientsOncotype Dx LUM A287 34% Major Discordance 188 Low, 95 Int, 4 High LUM B90 18% Major Discordance 16 Low, 47 Int, 27 High
Breast Cancer Gene Expression Profiling Risk assessment profiles are not uniform. Platforms are not uniform. Information is often driven by marketing. Patient results show greater discordance for treatment purposes than the variation that is seen with pathologist grading of tumors. The need for FDA to regulate…..July 31, 2014.
Take Home Message..Why Magee is Offering Prosigna New generation Nanostring platform. Prosigna (PAM50) has superior prognostic information compared to Oncotype.* Intrinsic subtype adds more information to differentiate risk assessment, decreasing intermediate scores by 25%. Low Risk for node negative and positive. 10 year DR prognostic information is unique. A transparent, FDA cleared platform for patient safety. Value-added pathology. *Sestak I et al. Factors Predicting Late Recurrence for ER+ breast Cancer JNCI 2013; 105(19):1504-11. *Dowsett M et al. Comparison of PAM50 ROR with Oncotype Dx and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 2013; 31(22):2783-90.
Tumor Biomarker Tests The Burden of Proof 1 Analytical validation Robustness of hypothesis and algorithm Reproducibility of sampling and assay Clinical validation Prospective/retrospective study in the target population 2,a Clinical utility Significant association of biomarker-defined patient subset with treatment outcome Value in guiding treatment decision Economic utility The economic impact of consequent effects on treatment decisions is within accepted regional norms 39 a Prospective analysis plan sufficient for Level 1 evidence. 1.Hayes DF, et al. Breast. 2013;22(suppl 2):S22-S26. 2.Simon RM, et al. J Natl Cancer Inst 2009;101(12):1446-1452.
Clinical Validation in HR+ Breast Cancer TransATAC, ABCSG-8
nCounter-PAM50 Gene Signature Assay Clinically Validated in Two Studies Representative of the ‘Intended Use Population’ ● N = 1,007 patients ● Presented at San Antonio Breast Cancer Symposium in December 2011 ● Published in Journal of Clinical Oncology 1 TransATAC Study (n=1017)ABCSG-8 Study (n=1478) ● Presented at San Antonio Breast Cancer Symposium in December 2012 ● Published in Annals of Oncology 2 ● Prospectively defined analysis of two registration-quality databases with ≥10-yr median follow-up in postmenopausal women with HR+ early stage breast cancer treated with endocrine therapy alone ● Primary Objective: Validate published observations that the nCounter-PAM50 gene signature score provides additional prognostic information over and above standard clinical variables for DRFS at 10 years ● Primary Analysis: All patients ● Secondary Analysis: Node-negative, node-positive, and HER2-negative patients ● Secondary Objective: Validate observations that Luminal A and Luminal B patients have statistically significantly different DRFS at 10 years a a Output of the U.S. version of the nCounter-PAM50 gene signature assay FDA cleared for 510(k) does not report intrinsic subtype. 1. Dowsett M, et al. J Clin Oncol. 2013;31(22):2783-2790. 2. Gnant M, et al. Ann Oncol. 2014;25(2):339-345. 41
42 TransATAC and ABCSG8 Studies: Met Primary and Secondary Objectives Prosigna adds statistically significant prognostic information in addition to standard clinical-pathological variables 1,2. AnalysesPopulationTransATAC Number of Patients P-valueABCSG8 Number of Patients P-value Primary All Evaluable1,007<0.00011,478<0.0001 Seconda ry Node- negative 739<0.00011,047<0.0001 Node- positive (1-3 nodes) 2680.002382<0.0001 HER2 Negative 888<0.00011,397<0.0001 1. Dowsett et al. JCO 2013 2. Gnant et al. Annals of Oncology 2014.
43 ABCSG-8: Prosigna Score Discriminates Recurrence Risk Within Nodal Subgroups Node-negative Patients Node-positive Patients (1-3 nodes) Risk GroupN (%)Events % without recurrence at 10 yr Low487 (47%)1597% [94% - 98%] Intermediate335 (32%)2890% [86% - 93%] High225 (21%)3284% [78% - 89%] Total1,047 Risk GroupN (%)Events % without recurrence at 10 yr Low158 (41%)794% [88% - 97%] High224 (59%)4676% [69% – 81%] Total382 Source: Gnant et al. Annals of Oncology 2014.
44 TransATAC: Prosigna v RS: Fewer Intermediate Risk Node-Negative Patients Risk groups prospectively defined based on predicted probability of 10-year distant recurrence (low 20%) Clinical and pathologic variables excluded from analysis Dowsett M, et al. J Clin Oncol. 2013;31(22):2783-2790. * Risk groups prospectively defined based on predicted probability of 10-yr distant recurrence (Low 20%) 100 90 80 70 60 0 Follow-Up Time (Years) 0 5 10 Percent Without Distance Recurrence ROR, low RS, low ROR, intermediate RS, intermediate ROR, high RS, high
45 3,901 enrolled in ABCSG-8 3,714 eligible for ABCSG-8 1,620 re-consented or deceased 25 insufficient cancer in specimen 73 insufficient RNA isolated 44 failed QC specs for device 25 insufficient cancer in specimen 73 insufficient RNA isolated 44 failed QC specs for device 1,478 evaluable tissue specimens 9,366 enrolled in ATAC 5,880 eligible for TransATAC 2,006 tissue specimen received 1,017 sufficient residual RNA 10 failed QC specs for device 1,007 evaluable RNA specimens 2,485 evaluable specimens Combined Analysis Clinical Validation in More Than 2,400 Patients Gnant M, et al. ASCO 2013; Poster 506.
Update--Late Recurrence Prosigna provides for additional information on the observed risk of distant recurrence in years 5-10 for node negative (1.3% Distant Recurrence) and node positive (3.7% Distant Recurrence). Patients in years 5-10 may avoid further endocrine therapy. FDA-cleared 46
47 5 years after endocrine therapy Node-negative Prosigna identifies Low Risk node-negative patients that remain Low Risk in all time periods --Low Risk node-negative patients had a total 10-year risk of recurrence of 3.4%
48 5 years after endocrine therapy Node-positive (1-3 nodes) Prosigna identifies Low Risk node-positive (1-3 nodes) patients that remain Low Risk in all time periods --Low Risk node-negative patients had a total 10-year risk of recurrence of 5.8%
Conclusions Across Clinical Studies Support the clinical validity of Prosigna Score for the risk of late recurrence in postmenopausal women with HR + ESBC Prosigna Score discriminates risk groups within subsets of patients defined by –Nodal status (negative versus positive) Prosigna Score score provides clinically actionable information –Identifies node negative and node-positive patients at sufficiently low risk to be spared chemotherapy –Identifies patients at sufficiently low risk of late-recurrence to be spared extended endocrine therapy The results of the TransATAC and ABCSG8 studies provide Level 1 evidence for the clinical validity of the PAM50 test 49
GEICAM Spanish Breast Cancer Group Decision Impact Study 50 Prosigna changed the treatment decision in 20% of cases --94% of physicians were confident with the prognosis --93% of physicians were confident with the intended treatment
Conclusions Prosigna has successfully undergone rigorous analytic validation –Highly reproducible and suited for decentralized testing Prosigna has been clinically validated in 2 large trials of adjuvant endocrine therapy (TransATAC and ABCSG-8) The results of the TransATAC and ABCSG8 studies provide Level 1 evidence for the clinical validity of the PAM50 test. Prosigna Score provides more prognostic information in endocrine treated patients than RS, with better differentiation of intermediate and high risk groups. Prosigna Score has strong prognostic information in years 5-10, which may help select patients who could benefit most from hormonal therapy beyond 5 years of treatment. 51