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195 Identifying the Outliers Among Gene Expression Profiling (GEP)-Defined Low-Risk Myeloma Patients Treated with Total Therapy 2 and 3 (TT2, TT3)Clinically Relevant Abstract

Program: Oral and Poster Abstracts
Type: Oral
Session: 651. Myeloma - Biology and Pathophysiology, excluding Therapy: Genomic and Molecular Determinant of Outcome in Myeloma
Sunday, December 9, 2012: 5:00 PM
Thomas Murphy Ballroom 1, Level 5, Building B (Georgia World Congress Center)

Frits van Rhee, MD, PhD1, Sarah Waheed, MD1, Saad Z Usmani, MD FACP1, Joshua Epstein, DSc1, Adam Rosenthal2*, Christoph Heuck, MD1, Jameel Muzaffar, MD1*, Al-Ola Abdallah, MD1*, Nathan M Petty1*, Clyde Bailey1*, Antje Hoering2* and Bart Barlogie, MD, PhD1

1Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR
2Research and Biostatistics, Cancer Research and Biostatistics, Seattle, WA

GEP analysis is a robust method to distinguish low- and high-risk multiple myeloma (MM), pertaining to 85% and 15% of newly diagnosed patients, respectively (Shaughnessy et al., Blood, 2007; 109:2276-84). As developed in TT2 and validated in TT3A and TT3B, we are now examining, similar to previous work in high-risk MM, whether we can define outliers among low-risk MM, i.e., patients not living up to the low-risk prediction model. Toward this end, we scrutinized early relapses in TT3A and TT3B within three years of protocol entry. Using logistic regression analysis, we identified baseline parameters including GEP, en route for distinguishing this high-risk subset among low-risk MM. Also examined was whether a new model could be built within low-risk disease that allowed for the identification of   a high-risk subset. Our database was interrogated for patients known to have GEP-defined low-risk in the GEP-70 model. Table 1 summarizes the 3-year events among GEP-70 low-risk subjects per protocol. An optimal cut-point at +0.146 distinguished, among the combined TT2 and TT3 patients, inferior progression-free survival (PFS) and overall survival (OS) (Figure 1a). Next, we examined outcomes among all TT2 and TT3 patients with GEP data, including those with traditionally-defined high-risk (>=0.66).  Here, we  were able to distinguish three subgroups with distinctly different PFS and OS (Figure 1b). Utilizing  logistic regression analysis, limited to traditionally-defined GEP-70 low-risk MM (=<0.66), three-year progression events during the this period were adversely dominated  by the following: GEP-70 scores >0.146 (HR=2.61, p=0.0005),  the presence of cytogenetic abnormalities (CA) (HR=1.93, p=0.018), B2M >5.5mg/L (HR=1.95, p=0.04) and LDH >190U/L (HR=1.93, 0.02). These are all reported in Table 2. In conclusion, we have identified, within GEP-70 low-risk patients, a new cut-point.  This allows a better categorization of patients having truly low risk disease. Also, above which a prognosis intermediate to the traditional high-risk prognostic group (>=0.66) could be identified. GEP >0.146 dominated a multivariate logistic regression model. Further efforts will be presented on unique genes characterizing this intermediate risk group in relationship to low and high-risk subsets.

Table 1. Three-year Events Among GEP-70 Subjects Per Protocol

Protocol

Total with GEP

GEP-70

low-risk

GEP-70 low-risk, event within first 3 years

TT2 - thalidomide

176

156

55

TT2 + thalidomide

175

149

36

TT3A

275

235

39

TT3B

166

129

23

Table 2. Logistic Regression for 3-year Event Factors, TT2+3 GEP-70 Low-Risk (<0.66)

 

Event in first three years on protocol

 

Variable

N

With
Factor

Without
Factor

OR (95% CI)

P - value

Multivariate

B2M > 5.5 mg/L

666

24/69 (35%)

59/328 (18%)

1.95 (1.03, 3.69)

0.0401

 

LDH >= 190 U/L

668

33/99 (33%)

50/298 (17%)

1.93 (1.10, 3.40)

0.0229

 

Cytogenetic abnormalities

665

35/116 (30%)

48/281 (17%)

1.93 (1.12, 3.32)

0.0182

 

GEP-70 score > 0.146

669

37/104 (36%)

46/293 (16%)

2.61 (1.52, 4.47)

0.0005

OR - Odds Ratio, 95% CI - 95% Confidence Interval, P - value from Wald Chi - Square Test in Logistic Regression
NS2 - Multivariate results not statistically significant at 0.05 level. Univariate p - values reported regardless of significance.
Multivariate model uses stepwise selection with entry level 0.1 and variable remains if meets the 0.05 level.
A multivariate p - value greater than 0.05 indicates variable forced into model with significant variables chosen using stepwise selection.

Description: outliers figure 1.jpg

Disclosures: No relevant conflicts of interest to declare.

*signifies non-member of ASH