Validating a new approach to predict breast cancer survival

Our recently published clinical validation study marks what we hope is a landmark moment for breast cancer patients and physicians all around the world.  The study demonstrates strong progress towards Digistain’s mission to overcome the fundamental challenges associated with existing risk recurrence profiling methods by providing patients with an accurate predictive test in good time, at an affordable price.

As with much scientific research, progress often happens slowly then all at once.  A frenetic period of activity has been quietly conducted behind the scenes by some leading minds in physics and cancer research.  The culmination of this hard work is clear evidence that our novel technology approach, combining infrared multi-spectral imaging with artificial intelligence, rapidly and accurately predicts breast cancer survival rates.

While the results highlighted in the clinical validation study are scientifically compelling, what really matters are the practical implications of this research and what it means for breast cancer patients and the physicians treating them.

It means reduced time to treatment

For patients receiving a breast cancer diagnosis and undergoing treatment it is already a deeply traumatic experience.  Following surgery the key question for patients is “will my cancer return”?  Yet, traditional  methods to predict recurrence are slow and expensive.

Waiting long periods for test results not only creates additional unnecessary patient anxiety, but delays in treatment have significant consequences.  When chemotherapy is required and initiated immediately, time makes the difference between life and death with every 30-day delay increasing the chance of death by up to 13%.[1].

Using Digistain’s approach can enable physicians to reduce actionable treatment decision times from months and weeks to days and hours.  The technology also offers the opportunity for hospitals to embed the software into existing pathology pathways enabling a physician to have a clear view on the risk of disease recurrence by the time the patient has woken up from surgery.

It means the right treatment

Assessing if chemotherapy can be avoided is equally critical. Chemotherapy was identified as the main cause of death for 27% of breast cancer patients in a recent national patient enquiry.  For early-stage breast
cancer only 30% of women may benefit from having it[2].

The clinical study demonstrated that Digistain’s technology can accurately predict patients at low or high risk of cancer recurring in the next 10 years.  Information that would allow nearly half (49%) of the patients assessed in this study to avoid chemotherapy after surgery.

It means greater access to treatment

Inequalities in breast cancer care exist all around the world. A chronic undersupply of laboratories to meet biopsy testing demand combined with the prohibitively high cost of traditional testing methods means too many patients simply do not receive a lifesaving diagnostic test.  It’s a global problem that extends across both economically developed countries and the developing world.  No matter where you live, but especially in marginalised communities, critical care decisions are made on affordability criteria – either by the patient directly or the healthcare providers supporting them.

The recent clinical validation study highlights the accuracy and rapidity of Digistain’s approach.  This is clearly encouraging, but it’s only the first  half of the chess board.  A key element of the technology should not only be efficiency and efficacy, but affordability. In other words moving beyond what is technically proven to something that is meaningful, impactful and scalable.

Because Digistain is software driven and avoids the expensive wet lab processes associated with traditional risk scoring methods the technology can generate industry leading precision analysis at a dramatically lower cost.

This provides us with the opportunity to unlock the unmet needs of breast cancer patients and start to overcome key obstacles in breast cancer analytics by enabling many more patients access to best in class care.

[1] Hanna et alBMJ 2020


Supported by:

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