↓ Skip to main content

The Neoadjuvant Model Is Still the Future for Drug Development in Breast Cancer

Overview of attention for article published in Clinical Cancer Research, June 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
8 X users
weibo
2 weibo users

Citations

dimensions_citation
75 Dimensions

Readers on

mendeley
77 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The Neoadjuvant Model Is Still the Future for Drug Development in Breast Cancer
Published in
Clinical Cancer Research, June 2015
DOI 10.1158/1078-0432.ccr-14-1760
Pubmed ID
Authors

Angela DeMichele, Douglas Yee, Donald A. Berry, Kathy S. Albain, Christopher C. Benz, Judy Boughey, Meredith Buxton, Stephen K. Chia, Amy J. Chien, Stephen Y. Chui, Amy Clark, Kirsten Edmiston, Anthony D. Elias, Andres Forero-Torres, Tufia C. Haddad, Barbara Haley, Paul Haluska, Nola M. Hylton, Claudine Isaacs, Henry Kaplan, Larissa Korde, Brian Leyland-Jones, Minetta C. Liu, Michelle Melisko, Susan E. Minton, Stacy L. Moulder, Rita Nanda, Olufunmilayo I. Olopade, Melissa Paoloni, John W. Park, Barbara A. Parker, Jane Perlmutter, Emanuel F. Petricoin, Hope Rugo, Fraser Symmans, Debasish Tripathy, Laura J. van‘t Veer, Rebecca K. Viscusi, Anne Wallace, Denise Wolf, Christina Yau, Laura J. Esserman

Abstract

The many improvements in breast cancer therapy in recent years have so lowered rates of recurrence that it is now difficult or impossible to conduct adequately powered adjuvant clinical trials. Given the many new drugs and potential synergistic combinations, the neoadjuvant approach has been used to test benefit of drug combinations in clinical trials of primary breast cancer. A recent FDA-led meta-analysis showed that pathologic complete response (pCR) predicts disease-free survival (DFS) within patients who have specific breast cancer subtypes. This meta-analysis motivated the FDA's draft guidance for using pCR as a surrogate endpoint in accelerated drug approval. Using pCR as a registration endpoint was challenged at ASCO 2014 Annual Meeting with the presentation of ALTTO, an adjuvant trial in HER2-positive breast cancer that showed a nonsignificant reduction in DFS hazard rate for adding lapatinib, a HER-family tyrosine kinase inhibitor, to trastuzumab and chemotherapy. This conclusion seemed to be inconsistent with the results of NeoALTTO, a neoadjuvant trial that found a statistical improvement in pCR rate for the identical lapatinib-containing regimen. We address differences in the two trials that may account for discordant conclusions. However, we use the FDA meta-analysis to show that there is no discordance at all between the observed pCR difference in NeoALTTO and the observed HR in ALTTO. This underscores the importance of appropriately modeling the two endpoints when designing clinical trials. The I-SPY 2/3 neoadjuvant trials exemplify this approach.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
France 1 1%
Denmark 1 1%
United Kingdom 1 1%
Japan 1 1%
Spain 1 1%
Unknown 70 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 25%
Other 15 19%
Student > Ph. D. Student 11 14%
Student > Bachelor 4 5%
Student > Postgraduate 4 5%
Other 11 14%
Unknown 13 17%
Readers by discipline Count As %
Medicine and Dentistry 30 39%
Agricultural and Biological Sciences 8 10%
Biochemistry, Genetics and Molecular Biology 6 8%
Nursing and Health Professions 3 4%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Other 9 12%
Unknown 18 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 13 July 2015.
All research outputs
#6,365,268
of 25,775,807 outputs
Outputs from Clinical Cancer Research
#5,906
of 13,310 outputs
Outputs of similar age
#66,866
of 278,055 outputs
Outputs of similar age from Clinical Cancer Research
#62
of 170 outputs
Altmetric has tracked 25,775,807 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,310 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.8. This one has gotten more attention than average, scoring higher than 55% 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 278,055 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 170 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.