Purpose
Targeted therapy can lead to considerable tumor reduction and may result initially in altered tissue at constant tumor size. In this setting, Response Evaluation Criteria in Solid Tumors (RECIST) can be inadequate for assessing early treatment response. Choi-criteria combine both size and density measurements. Our purpose was to evaluate computed tomography (CT) images of melanoma patients under BRAF-inhibitor therapy according to Choi-criteria which were adapted to our study (aChoi).
Material and Methods
Twelve patients (four male, eight female, mean age 49) with stage IV melanoma treated with a BRAF inhibitor were included. Response was assessed according to RECIST for 39 lesions in contrast-enhanced CT. Target volumes are semiautomatically segmented to calculate mean density for aChoi-criteria, thus using a two-dimensional nonstandardized region of interest could be prevented.
Results
Eight patients are RECIST responders. aChoi-criteria indicate therapy response earlier compared to RECIST in five of eight patients. In seven cases, tumor density in CT had decreased 8 weeks after therapy start, whereas in some cases tumor size diminished less or even increased. Response according to aChoi was diagnosed in seven patients who showed in RECIST-evaluation stable disease in five and partial response in two cases. Fifteen weeks after therapy start almost all patients within the aChoi responders were RECIST responders, too. Only one aChoi responder showed still stable disease in RECIST.
Conclusion
Our initial data indicate that aChoi-criteria can reflect response to vemurafenib earlier compared to RECIST. This is of clinical significance as BRAF-inhibitors are cost-intensive targeted therapies and can cause severe side effects, so criteria for early therapy response have to be evaluated.
Incidence of melanoma is dramatically increasing , faster than any other cancer. The number of new diagnoses per year has doubling times up to 10–20 years . Unfortunately effects of chemotherapy in stage IV melanoma patients remain poor, showing less than a year median survival time . Looking for treatments improving prognosis of these patients, research focuses besides immunotherapies such as CTLA-4/PD-1 inhibitors on development of targeted therapies against mutated kinases such as BRAF and c-kit . An accurate assessment of tumor response to these targeted therapies is a major challenge, and it is unlikely that a single response evaluation criterion will be sufficient .
In 2011 a promising targeted therapy for patients with unresectable or metastatic melanoma has been approved by US Food and Drug Administration: vemurafenib (Zelboraf, Roche Pharma, Grenzach-Wyhlen) . The European Commission authorized this BRAF inhibitor in February 2012. BRAF is a cytoplasmic serine/threonine kinase in cellular signaling pathways . About 40%–60% of all melanoma patients show a V600E mutation in the BRAF kinase, in most cases leading to a substitution of glutamic acid by valine . Patients with this mutation can be successfully treated with vemurafenib, a small-molecule BRAF inhibitor . Oncogenic BRAF kinase is an important stimulator of metabolic activity , so inhibiting this enzyme results in modification of metabolism, as long as melanoma cells do not develop resistance . In a clinical phase I study of vemurafenib, the authors were able to relate this altered metabolism to decreased signal intensities in fluorodeoxyglucose–positron emission tomography (FDG-PET). In 81% of patients, significant reduction in FDG uptake was observed 2 weeks after therapy onset, before tumor regression could be measured .
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Material and methods
Patient Population
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Response Evaluation
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Imaging Technique
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Table 1
Applied Amount of Contrast Media (Imeron 300, Bracco, Konstanz, Germany)
Body Weight (kg) Volume Contrast Media (mL) Flow Rate (mL/s) <55 85 3.1 55–64.9 115 3.5 65–90 130 4 >90 145 4.5
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Data Analysis
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Results
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Table 2
Size and Density Measurements of Target Lesions
Patient Baseline Follow-up 1 Follow-up 2 1n 4 SDT (mm) 133 137 147 Δ SDT (%) 3 11 SDET (HU) 76 62 59 Δ SDET (%) −18 −22 2n 4 SDT (mm) 80 75 70 Δ SDT (%) −6 −13 SDET (HU) 48 58 57 Δ SDET (%) 21 19 3n 2 SDT (mm) 39 28 16 Δ SDT (%) −28 −59 SDET (HU) 20 7 8 Δ SDET (%) −65 −60 4n 3 SDT (mm) 42 31 20 Δ SDT (%) −26 −52 SDET (HU) 82 53 28 Δ SDET (%) −35 −66 5n 5 SDT (mm) 125 95 82 Δ SDT (%) −24 −34 SDET (HU) 53 58 18 Δ SDET (%) 9 −66 6n 3 SDT (mm) 50 36 29 Δ SDT (%) −28 −42 SDET (HU) 41 39 32 Δ SDET (%) −5 −22 7n 3 SDT (mm) 77 38 31 Δ SDT (%) −51 −60 SDET (HU) 77 75 60 Δ SDET (%) −3 −22 8n 3 SDT (mm) 47 27 27 Δ SDT (%) −43 −43 SDET (HU) 93 84 104 Δ SDET (%) −10 12 9n SDT (mm) 135 96 144 Δ SDT (%) −29 7 SDET (HU) 64 39 48 Δ SDET (%) −39 −25 10n 3 SDT (mm) 91 110 Δ SDT (%) 21 SDET (HU) 76 82 Δ SDET (%) 8 11n 2 SDT (mm) 114 81 109 Δ SDT (%) −29 −4 SDET (HU) 79 48 70 Δ SDET (%) −39 −11 12n 2 SDT (mm) 41 48 61 Δ SDT (%) 17 49 SDET (HU) 108 57 56 Δ SDET (%) −47 −48
n, number of targets; SDT, sum of diameters of target lesions (mm); Δ SDT, change of SDT (%) compared to baseline; SDET, sum of densities of target lesions (HU); Δ SDET, change of SDET (%) compared to baseline.
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Nonprogressive Disease (Stable Disease, Partial Response, Complete Response)
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Table 3
Results
Patient Follow-up 1 Follow-up 2 1 RECIST SD SD Choi PR PR 2 RECIST SD SD Choi SD SD 3 RECIST SD PR Choi PR PR 4 RECIST SD PR Choi PR PR 5 RECIST SD PR Choi PR PR 6 RECIST SD PR Choi PR PR 7 RECIST PR PR Choi PR PR 8 RECIST PR PR Choi PR PR 9 RECIST SD PD Choi PR PD 10 RECIST PD Choi PD 11 RECIST SD PD Choi PR PD 12 RECIST SD PD Choi PR PD
SD, stable disease; PD, progressive disease; PR, partial response; RECIST, Response Evaluation Criteria in Solid Tumors.
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Progressive Disease
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Discussion
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Conclusion
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