Developing early endpoints in neoadjuvant breast cancer to support accelerated approval.

e12755 Background: Pathologic complete response (pCR) is an early endpoint in neoadjuvant breast cancer considered in accelerated approval decisions by the FDA. However trial-level odds ratios of pCR and mature hazard ratios of disease free survival are only weakly associated in meta-analyses, resulting in approvals being delayed until survival evidence becomes available. We used data from the I-SPY 2 trial to develop early endpoints with better trial level correlations to support accelerated approvals. Methods: The I-SPY 2 trial treated 2117 patients with early stage high-risk breast cancer across 26 regimens between 2010 and 2022. When we separate the regimens into groups by subtype, there were 47 total experimental groups (19 HR+HER2-, 19 HR-HER2- and 9 HER2+). Each group is matched to concurrent control group enrolled within 90 days of the enrollment period, forming a experimental/control comparison. Treatment groups with less than 10 patients or insufficient follow-up were excluded, leaving 27 comparisons across 1577 patients. Hazard ratios for event free survival and negative log odds ratios for various early endpoints (e,g, pCR, RCB Class 0 or1) are computed for each experimental/control comparison. Novel early endpoints, including a binary subtype-specific RCB cutoffs, were developed on a training subset, with 5 comparisons held out for validation. The weighted trial-level correlation (R) was calculated overall and in HRHER2 subgroups. Subtype specific RCB cutoffs were chosen to optimize the overall and within subgroup weighted correlation, while maintaining C indices > .70 for individual survival association. More sophisticated models with RCB index as a continuous variable that incorporated baseline T stage, nodal status and response predictive subtypes were also explored. Results: Overall weighted correlations (R) for PCR, RCB 0/1 and Subtype Specific RCB cutoffs are shown in Table 1. Optimal cutoffs of RCB of 1.1 for HER2+, 1.7 for HR-HER2-, and 2.6 for HR+HER2- were identified giving a correlation of .70 overall in the training set and .54 in training and validation combined. The C index (C) was greater than 0.8 for all endpoints indicating good individual association. Preliminary results using more sophisticated models will be presented. Conclusions: Subtype-specific RCB cutoffs show a modest but clear improvement as an early endpoint over RCB-0/1 and pCR while maintaining a strong patient-level association with survival. External validation efforts are underway. Integrative approaches using continuous RCB improve trial level correlation and will be presented. Trial-level weighted correlation and individual C indices across all 3 subtypes and within each HRHER2 subtype separately. Measure OverallR,C HER2+R,C HR+HER2-R,C HR-HER2-R,C PCR .23, .84 .31, .80 .13, .84 .18, .87 RCB 0-1 .31, .83 .37, .80 .38, .85 .16, .85 Subtype Specific Cutpoint .54, .80 .37, .77 .40, .75 .54, .87 R = correlation; C = C index.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Oncology
Published
2026-05-28
DOI
https://doi.org/10.1200/jco.2026.44.16_suppl.e12755
Primary Topic
Advanced Breast Cancer Therapies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Developing early endpoints in neoadjuvant breast cancer to support accelerated approval.

Denise M. Wolf, L J Esserman, D Yee, N Hylton et al.
Journal of Clinical Oncology
Advanced Breast Cancer Therapies
article

Developing early endpoints in neoadjuvant breast cancer to support accelerated approval.

Denise M. Wolf, L J Esserman, D Yee, N Hylton, J Perlmutter, L Pusztai, Philip Beineke, C Yau, Keli S. Santos-Parker, Andrew Chapple, Peter Norwood, W. Fraser Symmans, Hope S. Rugo, Laura van't Veer, Angela DeMichele
article en

Abstract

e12755 Background: Pathologic complete response (pCR) is an early endpoint in neoadjuvant breast cancer considered in accelerated approval decisions by the FDA. However trial-level odds ratios of pCR and mature hazard ratios of disease free survival are only weakly associated in meta-analyses, resulting in approvals being delayed until survival evidence becomes available. We used data from the I-SPY 2 trial to develop early endpoints with better trial level correlations to support accelerated approvals. Methods: The I-SPY 2 trial treated 2117 patients with early stage high-risk breast cancer across 26 regimens between 2010 and 2022. When we separate the regimens into groups by subtype, there were 47 total experimental groups (19 HR+HER2-, 19 HR-HER2- and 9 HER2+). Each group is matched to concurrent control group enrolled within 90 days of the enrollment period, forming a experimental/control comparison. Treatment groups with less than 10 patients or insufficient follow-up were excluded, leaving 27 comparisons across 1577 patients. Hazard ratios for event free survival and negative log odds ratios for various early endpoints (e,g, pCR, RCB Class 0 or1) are computed for each experimental/control comparison. Novel early endpoints, including a binary subtype-specific RCB cutoffs, were developed on a training subset, with 5 comparisons held out for validation. The weighted trial-level correlation (R) was calculated overall and in HRHER2 subgroups. Subtype specific RCB cutoffs were chosen to optimize the overall and within subgroup weighted correlation, while maintaining C indices > .70 for individual survival association. More sophisticated models with RCB index as a continuous variable that incorporated baseline T stage, nodal status and response predictive subtypes were also explored. Results: Overall weighted correlations (R) for PCR, RCB 0/1 and Subtype Specific RCB cutoffs are shown in Table 1. Optimal cutoffs of RCB of 1.1 for HER2+, 1.7 for HR-HER2-, and 2.6 for HR+HER2- were identified giving a correlation of .70 overall in the training set and .54 in training and validation combined. The C index (C) was greater than 0.8 for all endpoints indicating good individual association. Preliminary results using more sophisticated models will be presented. Conclusions: Subtype-specific RCB cutoffs show a modest but clear improvement as an early endpoint over RCB-0/1 and pCR while maintaining a strong patient-level association with survival. External validation efforts are underway. Integrative approaches using continuous RCB improve trial level correlation and will be presented. Trial-level weighted correlation and individual C indices across all 3 subtypes and within each HRHER2 subtype separately. Measure OverallR,C HER2+R,C HR+HER2-R,C HR-HER2-R,C PCR .23, .84 .31, .80 .13, .84 .18, .87 RCB 0-1 .31, .83 .37, .80 .38, .85 .16, .85 Subtype Specific Cutpoint .54, .80 .37, .77 .40, .75 .54, .87 R = correlation; C = C index.

Journal of Clinical OncologyVol. 44(16_suppl)
University of Minnesota (US), The University of Texas MD Anderson Cancer Center (US), University of California, San Francisco (US), Alliance for Clinical Trials in Oncology (US), Yale Cancer Center (US), Quantum Leap Healthcare Collaborative (US), City of Hope (US), Gemini Computers (United States) (US), University of Pennsylvania (US)
Good health and well-being
Openalex Percentile: Top 6%
Advanced Breast Cancer Therapies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.