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Circulating Tumor DNA–Based MRD Assessment in Patients with CLL Treated with Obinutuzumab, Acalabrutinib, and Venetoclax

Overview of attention for article published in Clinical Cancer Research, June 2022
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Average Attention Score compared to outputs of the same age and source

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10 tweeters

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4 Mendeley
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Title
Circulating Tumor DNA–Based MRD Assessment in Patients with CLL Treated with Obinutuzumab, Acalabrutinib, and Venetoclax
Published in
Clinical Cancer Research, June 2022
DOI 10.1158/1078-0432.ccr-22-0433
Pubmed ID
Authors

Moritz Fürstenau, Jonathan Weiss, Adam Giza, Fabian Franzen, Sandra Robrecht, Anna-Maria Fink, Kirsten Fischer, Christof Schneider, Eugen Tausch, Stephan Stilgenbauer, Matthias Ritgen, Anke Schilhabel, Monika Brüggemann, Barbara Eichhorst, Michael Hallek, Paula Cramer

Abstract

With the advent of highly efficacious time-limited combination treatments in CLL, minimal residual disease (MRD) assessment has gained importance as a measure for therapeutic success. The currently most widely used method is multicolor flow cytometry, which detects circulating CLL cells in the peripheral blood. However, it seems to be less sensitive for the detection of MRD in the lymph node compartment. To evaluate whether a cell-free approach can overcome this limitation, we performed serial assessments of circulating tumor DNA (ctDNA) in patients with CLL treated with obinutuzumab, acalabrutinib and venetoclax in the CLL2-BAAG trial. Patient-specific VDJ rearrangements as well as somatic driver mutations were tracked before, during and after treatment by digital droplet PCR in blood plasma. Furthermore, these were systematically compared to matched flow cytometry data. In the 381 sample pairs, ctDNA and flow cytometry yielded highly concordant results. However, clone-specific ctDNA was detected in 44 of 152 samples (29%) that were assessed as undetectable MRD by flow cytometry (uMRD, <10-4). Twenty-nine ctDNA-negative samples showed detectable MRD >10-4 by flow cytometry. Somatic driver mutations were detected with a similar sensitivity compared to patient-specific VDJ rearrangements in plasma. In patients with predominantly nodal residual disease, ctDNA compared favorably with flow cytometry and seemed to more accurately reflect the entire disease burden across compartments. Based on these findings, ctDNA-based MRD assessment appears to be a promising method to complement cell-based MRD approaches like flow cytometry that focus on circulating CLL cells in the peripheral blood.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 100%
Readers by discipline Count As %
Unspecified 4 100%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 June 2022.
All research outputs
#4,321,663
of 21,468,133 outputs
Outputs from Clinical Cancer Research
#3,922
of 12,210 outputs
Outputs of similar age
#74,992
of 302,044 outputs
Outputs of similar age from Clinical Cancer Research
#77
of 144 outputs
Altmetric has tracked 21,468,133 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,210 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 302,044 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.