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Poster viewing and lunch

65P - Association of the Digistain Prognostic Score with outcomes in patients with HR- positive HER2-negative breast cancer

Date

12 May 2023

Session

Poster viewing and lunch

Presenters

Hemmel Amrania

Citation

Annals of Oncology (2023) 8 (1suppl_4): 101218-101218. 10.1016/esmoop/esmoop101218

Authors

H. Amrania1, R..C. Coombes2, C. Palmieri3, E. Rakha4, C. Angelou5, A. Green4, I. Ellis6, N. Wright7, C. Phillips1, S. Shousha8, D. Francescatti9, Z. Al-Khalili1

Author affiliations

  • 1 Imperial College London - South Kensington Campus, London/GB
  • 2 Hammersmith Hospital - Imperial College Healthcare NHS Trust, W12 0HS - London/GB
  • 3 Clatterbridge Cancer Centre, Liverpool/GB
  • 4 Nottingham University Hospital, Nottingham/GB
  • 5 Imperial College London - Hammersmith Campus, London/GB
  • 6 University of Nottingham, School of Medicine, Nottingham/GB
  • 7 Cancer Research UK Barts Centre - Queen Mary University of London, London/GB
  • 8 Charing Cross Hospital - Imperial College Healthcare NHS Trust, London/GB
  • 9 Rush Cancer Institute, Chicago/US

Resources

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Abstract 65P

Background

Digistain is a mid-infrared imaging technology that assesses aneuploidy by measuring the nuclear-to-cytoplasmic chemical ratio in the cellular content of tissues to generate the Digistain Index (DI). The Digistain Prognostic Score (DPS) has been developed by incorporating DI with pathological features. The ability of DPS to predict clinical outcomes in patients with HR-positive HER2-negative primary breast cancer was investigated as a means to guide adjuvant chemotherapy.

Methods

Infrared spectrometry was performed on existing tissue microarrays to determine the DI and DPS of 801 patients with HR-positive HER2-negative primary breast cancer with ≤3 positive lymph nodes who had received systemic endocrine therapy only. AUC for ROC curves were used to assess the ability of DPS to predict 5- and 10-year progression-free survival (PFS), recurrence and overall survival (OS) in the total population and in 3 subgroups: no positive lymph nodes, premenopausal (based on age <45 years) and postmenopausal (>60 years).

Results

DPS was highly accurate for prediction of risk in the total population and by subgroup. In the total population, AUC for PFS and recurrence were the same, 0.81 and 0.75 at 5 and 10 years, respectively, and 0.77 and 0.69 for OS at 5 and 10 years, respectively. In the 3 subgroups, AUC values were similar for all outcomes ranging from 0.67 to 0.76 and 0.59 to 0.74 for 5 and 10 years, respectively. Across the total population and subgroups, negative predictive values were high for all outcomes, ranging from 0.96 to 0.99 at 5 years and 0.84 to 0.95 at 10 years. Across the total population, hazard ratios for PFS, recurrence and OS for low- vs. high-risk classification were significant (1.80, 1.83 and 2.49, respectively; P<0.001). DPS also showed significant (P<0.05) risk prognostication for PFS and recurrence in the lymph node-negative group, and for recurrence and OS in postmenopausal women.

Conclusions

DPS showed high accuracy and predictive performance across the total population and different subgroups, and was able to stratify patients into low or high risk. DPS warrants further development considering its rapid turnaround times, low cost and potential for widespread use.

Legal entity responsible for the study

Chris Phillips.

Funding

The National Institute of Health Research UK.

Disclosure

All authors have declared no conflicts of interest.

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