A clinical model incorporating early lymphocyte dynamics in HER2-positive breast cancer

Clicks: 10
ID: 333824
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #400 of 408 articles by views in JNCI Journal of the National Cancer Institute

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 408 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Background Immune activation is central to response to HER2-targeted therapy in HER2-positive breast cancer; however, early and scalable biomarkers that capture this biology remain limited. Methods We developed a predictive model that used early dynamic changes in routinely obtained peripheral blood absolute lymphocyte count (ALC) alongside standard clinical and pathologic features to predict pathologic complete response (pCR) after neoadjuvant therapy in HER2-positive breast cancer. Results In a discovery cohort of patients with stage I–III HER2-positive breast cancer treated per routine care with trastuzumab-based neoadjuvant therapy (n = 154), higher baseline ALC and greater decline in ALC after the first cycle were independently associated with increased likelihood of pCR (p < 0.001 for both). A predictive model using these two ALC variables alongside age, percentage of cells expressing estrogen receptor, progesterone receptor status, HER2 immunohistochemistry score, and tumor stage, demonstrated strong discrimination: the area under the curve (AUC) in the discovery cohort was 0.86, and 0.82 in a separate validation cohort (n = 83). In the validation cohort, the pCR rate was 12% among patients in the discovery model-predicted quartile with lowest pCR probability, 33% in the second quartile, 69% in the third quartile, and 79% in the highest probability quartile. Conclusion These findings suggest that early measures of peripheral blood ALC, alongside standard clinical and pathologic features, offer a simple, scalable biomarker for anticipating response to HER2-targeted neoadjuvant therapy, with potential utility for early treatment adaptation and trial stratification.
Reference Key
openalex_W7223457685 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Colin P. Bergstrom, Ingrid Luo, Gregory R. Bean, Eran Kotler, M Satoyoshi, Christina N. Curtis, Sarah Kurien, Scarlett L. Gomez, Allison W. Kurian, Summer S. Han, Jennifer Lee Caswell-Jin
Are you one of these authors? Claim your profile
Journal JNCI Journal of the National Cancer Institute
Year 2026
DOI
10.1093/jnci/djag400
URL
https://doi.org/10.1093/jnci/djag400
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.