Early Lymphocyte Changes Help Predict Response to HER2-Targeted Therapy

A clinical model using early changes in absolute lymphocyte count and standard tumor features predicted pathologic complete response after neoadjuvant therapy for stage I–III HER2-positive breast cancer. The model was developed in 154 patients and validated in a separate cohort of 83; further study is needed before it can guide treatment changes.

Model combined early ALC changes with clinical and tumor features.
Validation AUC was 0.82 in 83 patients.
Observed pCR rates ranged from 12% to 79% across quartiles.
Prospective testing is needed before treatment adaptation.

Researchers developed a predictive model using routinely measured peripheral blood absolute lymphocyte counts (ALC) alongside clinical and pathologic features to estimate pathologic complete response (pCR) after trastuzumab-based neoadjuvant therapy. The discovery cohort included 154 patients with stage I–III HER2-positive breast cancer treated in routine care; the model was tested in a separate validation cohort of 83 patients.

In the discovery cohort, higher baseline ALC and a greater decline in ALC after the first treatment cycle were independently associated with pCR (p<0.001 for both). The model also incorporated age, estrogen receptor expression, progesterone receptor status, HER2 immunohistochemistry score, and tumor stage. Its area under the curve was 0.86 in the discovery cohort and 0.82 in validation. In the validation cohort, pCR rates ranged from 12% in the lowest predicted-probability quartile to 79% in the highest.

The findings suggest that early ALC dynamics may help stratify response risk using a routine blood test. The study supports further evaluation for trial stratification or treatment adaptation, but does not establish that changing therapy based on the model improves outcomes. The supplied abstract does not report details on calibration or prospective testing.

In practice

For patients with stage I–III HER2-positive breast cancer receiving trastuzumab-based neoadjuvant therapy, baseline ALC and its change after the first cycle may add response-prediction information when considered with standard clinical and pathologic features. The model showed discrimination in a separate validation cohort, with pCR rates of 12% to 79% across predicted-risk quartiles. These results may support further evaluation for stratification, but the study does not show that altering treatment based on the prediction improves outcomes; prospective clinical-utility testing is needed.

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Source

JNCI: Journal of the National Cancer Institute: A clinical model incorporating early lymphocyte dynamics in HER2-positive breast cancer ↗

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