CanAssist Breast uses a proteomics- based method and a proprietary machine learning-based algorithm to to analyze a patented combination of protein biomarkers from the patient’s tumour to compute the risk of recurrence of cancer.
CanAssist Breast integrates IHC (immunohistochemistry) data and clinical parameters to calculate a risk score that classifies patients as ‘low-risk’ or ‘high-risk’ for breast cancer recurrence over five years. By integrating the tumour biology of the disease with time-tested clinico-pathological parameters we assist physicians in developing optimal treatment plans for cancer patients. The CanAssist Breast test result allows breast cancer patients who are classified as ‘low-risk’ to potentially avoid chemotherapy and its side effects.
CanAssist Breast is an immunohistochemistry (IHC)-based novel risk classifier combining five patented biomarkers and three clinico- pathological parameters to calculate risk of cancer recurrence at a site other than breast within five years from diagnosis.
The 5 biomarkers chosen play critical roles in cancer recurrence.
The machine learning-based techniques used help assess non-linear interactions between the various signaling pathways that play a role in cancer recurrence.
CanAssist Breast has been rigorously validated based on various international guidelines. Multiple variables that play a role in test precision have been assessed and the test has been found to be repeatable and reproducible
Stringent QC and validation have been done on all IHC protocols used in the CanAssist Breast test performed in the reference laboratory at Bengaluru.
Our reference laboratory in Bengaluru is accredited by College of American Pathologists (CAP) and NABL, and participates in various External Quality Assessment Schemes (EQAS).
CanAssist Breast has been validated in a retrospective multi-centric clinical study (15+ centres in India, USA & Europe) on close to 2000 patients
A significant proportion of the validation cohort were aged 50 or younger, making the test suitable for both young pre-menopausal and older post-menopausal patients.
The validation data has been published in several international peer- reviewed journals like Biomarker Insights and Cancer Medicine:
Kaplan-Meier survival analysis showed that chemotherapy leads to better results for high-risk patients, but didn’t lead to statistically significant benefit in low-risk patients
Cox proportional hazards analysis showed that significant prognostic value was provided by CanAssist Breast compared with other traditional clinicopathological parameters
CanAssist Breast provided significant prognostic value, superior to that provided by traditional clinicopathological parameters and tests such as Ki67 and IHC4.
