Abstract P2-03-07: Multi-parametric algorithm integrating on-treatment Ki67 value and standard clinicopathological variables to predict risk of recurrences for women > 70 years old with early ER+HER2- tumours in POETIC trial

Abstract Background: Prognosis in older patients with breast cancer (BC) is worse compared to younger patients. No robust and specific tool to predict the risk of recurrence (TTR) for women aged 70 and over is likely due to the lack of representation of this group in the data from clinical trials. In the POETIC trial, of estrogen receptor-positive (ER+) and mainly human epidermal growth factor receptor 2 negative (HER2-) BC (88%), peri-operative aromatase inhibitor (POAI) did not improve treatment outcome, but patients with low baseline Ki67 value (Ki67B) or low POAI-induced Ki67 value (Ki67_2wk) had good outcome with standard of care therapy (usually adjuvant endocrine therapy (adjET) with the addition of chemotherapy as clinically indicated). In this study, we sought to develop a multi-parametric algorithm, named Ki67Cal, by integrating Ki67_2wk value with tumour characteristics to predict TTR for patients > 70 years old (yr) with early ER+HER2- BC treated with adjET only. Methods: Within POETIC, 39% (n=1744) of the randomised patients (n = 4480) were >70 years old. There were 813 patients aged > 70yr, with ER+HER2- BC, randomised to POAI treatment and treated with adjET only. A power calculation indicated that 811 such patients were sufficient to develop a prediction model that minimized overfitting, allowed up to 8 predictors, for predicting 5-years TTR with a median follow-up of 5.24 years and an overall event rate per 1000 person-years = 0.027, and provided an anticipated performance in terms of model fit R2 = 0.08 (Riley et al. BMJ 2020). A three-fold cross-validation approach was applied; an optimal list of features was selected in the training set (n = 538, events = 70); the agreement between expected and observed outcomes from the algorithm on the validation set (n = 275, events = 37) was evaluated by calibration plot. Multivariable Ridge Cox Regression model of significant parameters was built on the dataset merging training and validation datasets (n = 813) for precise estimates of the coefficients of parameters. A subset of post-POAI samples (n = 99) was gene expression profiled with Nanostring to allow pseudo-Oncotype, pseudo-EndoPredict, and RUO-Prosigna scores calculated (Buus et al. npj Breast cancer 2021). The risk groups classified by the Ki67Cal and gene-expression assays (GEP) were compared. Results: Within this cohort, the 5-year TTR was 34.5% (C.I. 24.9-47.9) for those with a high Ki67_2wk (>=10%) and 12.3% (C.I. 9.1-16.7) in those with a high Ki67B that was suppressed to Ki672wk < 10%. The significant features were Ki67_2wk, sampling type (core vs. excision) at surgery, and pathological variables (tumour size, grade, and nodal status) for the final Ki67Cal algorithm. Stratifying patients into five groups (quintiles) by Ki67Cal identified 60% of patients with TTR of < 5% at 5yrs, and 20% of patients with TTR of > 30% at 5yrs. As an exploratory analysis, the risk groups by Ki67Cal and GEP were compared (Table 1). To date, these assays are optimized to be used on untreated ER+HER2- samples; there were fairly good agreements between the high-risk group defined by Ki67Cal with pseudo-EndoPredict and RUO-Prosigna respectively, and low-risk groups by Ki67Cal with Prosigna probably because Prosigna scores are driven by proliferation score. Conclusion: The relatively poor outcome of patients >70yrs in POETIC emphasizes the need for prognostic tools that identify patients who may be treated with endocrine therapy alone or conversely should be considered for additional therapy. Ki67Cal provides a simple tool that identified very low-risk and high-risk patients in 80% of patients with ER+HER2- BC. Table 1: Comparison of the risk groups defined by Ki67Cal algorithm with the three commonly used gene-expression assays (pseudo-EndoPredict, pseudo-Oncotype and RUO-Prosigna) applied on the post-peri-operative aromatase inhibitor samples. Citation Format: Maggie Chon U Cheang, Monisha Dewan, Lucy Kilburn, Gabriele Morani, Lila Zabaglo, Kally Sidhu, Holly Tovey, Xixuan Zhu, Chris Holcombe, Anthony Skene, Ian Smith, John Robertson, Alistair Ring, Nicholas Turner, Judith Bliss, Mitch Dowsett. Multi-parametric algorithm integrating on-treatment Ki67 value and standard clinicopathological variables to predict risk of recurrences for women > 70 years old with early ER+HER2- tumours in POETIC trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-03-07.

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