Abstract PO1-27-10: Adjunctive statistical standardization of quantitated machine image analysis of Estrogen and Progesterone Receptors: CCTG MA.27 trial
Authors: Judy-Anne Chapman, Jane Bayani, Sandip SenGupta, John MS Bartlett, Tammy Piper, Mary Anne Quintayo, Shakeel Virk, Paul Goss, James Ingle, Matthew Ellis, George Sledge Jr, George Budd, Manuela Rabaglio, Rafat Ansari, Richard Tozer, David D'Souza, Haji Chalchal, Silvana Spadafora, Vered Stearns, Edith A. Perez, Karen Gelmon, Timothy Whelan, Catherine Elliott, Lois Shepherd, Bingshu Chen, Karen Taylor
Journal: Cancer Research (2024)

Abstract Background: Adjuvant breast cancer therapy is informed by whether a tumour is positive or negative for the biomarkers ER, PgR, and HER2, often without regard to level of positivity. Quantitation has been proposed to improve therapeutic management. Adjunctive statistical standardization has been proposed to improve inter-laboratory comparability of biomarkers results. Methods: This primary report utilized adjunctive statistical standardization of machine-quantitated image analysis biomarker assessments. CCTG MA.27 (NCT00066573) is an adjuvant phase III trial of exemestane versus anastrozole in postmenopausal women with ER+ and/or PgR+ tumours. IHC ER, PgR, and HER2 were centrally assessed, with FISH (HER2;HER2/CEP17) determinations for equivocal IHC HER2. HSCOREs were statistically standardized to a mean of 0, standard deviation of 1 following Box-Cox variance stabilization transformations of square for ER and natural logarithm for PgR (0.1 was added to 0 HSCOREs). The primary endpoint was STEEP distant disease-free survival (DDFS) at the longest trial follow-up of median 4.1 years. Survival was described with Kaplan-Meier plots. The univariate Wilcoxon (Peto-Prentice) test statistic was used with usual designation of negative/positive (0; &amp;gt;0), and standardized cut-points at standard deviations about mean of 0(&amp;lt;-1; (-1,0]; (0,1]; &amp;gt;1). Cox multivariate regressions adjusted for age, T and N stage, grade, lymphovascular invasion, treatment, and baseline patient demographics, utilized likelihood ratio tests. Nominal significance was p=0.05. Results: Of the 7576 women accrued, 3048 had machine-quantitated image analysis results: 2900 (95%) for ER; 2726 (89%) for PgR. Only 8 women were ASCO/CAP ER- (HSCORE 0); PgR HSCORE was 0 for 533. Statistically standardized units differentiated DDFS ER levels (p&amp;lt; 0.001) and PgR levels (p&amp;lt; 0.001). In adjusted multivariate analyses, higher ER HSCORE was associated with better DDFS (p=0.05) with weak evidence of an association (p=0.11) for standardized HSCORE, and no significant association (respectively, p=0.28, p=0.54) in models with PgR. Higher PgR was associated with better DDFS (p=0.001) in all multivariate assessments, including those with ER. Conclusions: DDFS was superior for patients with higher ER and PgR standardized units compared with those with HSCOREs &amp;lt;-1. Adjunctive statistical standardization, similar to that mandated for clinical practice by the World Health Organization for BMD, should improve inter-laboratory comparability of biomarker results for similar patient populations. Biomarker N DDFS DDFS 5-year (%) 95% CI ER total 2900 ER &amp;lt;-1 506 86 (82, 91) ER (-1, 0] 934 94 (92, 96) ER ( 0, 1] 919 94 (92, 96) ER &amp;gt;1 541 96 (93, 98) PgR total 2726 PgR &amp;lt;-1 734 89 (86, 92) PgR (-1, 0] 439 92 (89, 95) PgR ( 0, 1] 967 95 (93, 96) PgR &amp;gt;1.0 586 98 (97,100) Citation Format: Judy-Anne Chapman, Jane Bayani, Sandip SenGupta, John MS Bartlett, Tammy Piper, Mary Anne Quintayo, Shakeel Virk, Paul Goss, James Ingle, Matthew Ellis, George Sledge Jr, George Budd, Manuela Rabaglio, Rafat Ansari, Richard Tozer, David D'Souza, Haji Chalchal, Silvana Spadafora, Vered Stearns, Edith A. Perez, Karen Gelmon, Timothy Whelan, Catherine Elliott, Lois Shepherd, Bingshu Chen, Karen Taylor. Adjunctive statistical standardization of quantitated machine image analysis of Estrogen and Progesterone Receptors: CCTG MA.27 trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-27-10.