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MEAN HOUNSFIELD UNITS ON UNENHANCED CT PREDICTS RESPONSE TO EVEROLIMUS IN TUBEROUS SCLEROSIS COMPLEX ASSOCIATED ANGIOMYOLIPOMAS

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Sources of Funding: Novartis Pharmaceuticals

Introduction

Everolimus, a mammalian target of rapamycin (mTOR) inhibitor, has been used for tuberous sclerosis complex associated angiomyolipoma (TSC-AML). However, we lack tools to accurately predict response in individual patients.

Methods

In this single-center phase 2 nonrandomized open label trial, eighteen patients with forty-three measurable AMLs associated tuberous sclerosis complex were treated with oral everolimus (10mg/d). AML volume and computed tomography (CT) parameters were measured at baseline, 12, 24, 48 and 96 weeks. Receiver operating characteristic curve (ROC) method was used to calculate the sensitivity, specificity and diagnostic accuracy. All analyses used a significance level of 0.05 and were generated in SPSS19.0 software.

Results

Target AML response, volume reductions over 50% relative to baseline defined by RECIST criteria, were 65.85%(27/41), 67.50%(27/40) and 68.42%(26/38) at weeks 12, 24 and 48, respectively. Mean HU on unenhanced CT and the longest diameter (DL) at baseline significantly correlated with percentage change of target AML at different indicated time. The AUC for mean hounsfield units (HU) on unenhanced CT were 0.99, 1.00 and 0.94 at weeks 12, 24 and 48, respectively, while the AUC for DL of 0.71, 0.78 and 0.91 at weeks 12, 24 and 48, respectively. Representative scans from two different status of mean HU target AML treated with everolimus are shown in Figure 1. A threshold of -24.50 HU for predicting AML response showed 92.86% sensitivity and 96.30% specificity at 12 weeks (likelihood ratio=25.07), 100.0% sensitivity and 96.30% specificity at 24 weeks (likelihood ratio=27.00), while 91.67% sensitivity and 96.15% specificity at 48 weeks (likelihood ratio=23.83), respectively (Figure 2).

Conclusions

Mean HU on unenhanced CT of target AML at baseline predicts response to everolimus and it may be useful to select treatment.

Funding

Novartis Pharmaceuticals

Authors
Yi Cai
Hanzhong Li
Yushi Zhang
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