Dr Davey Daniel Navigates Precision Medicine With Real-World Evidence

Davey Daniel, MD, chief medical officer at OneOncology, and panelist at the Patient-Centered Oncology Care^® 2024 meeting, asserts that real-world evidence is essential for understanding the full potential of genomic testing, patient outcomes of sequential testing, and cost-effectiveness of efficacious drugs.

This transcript has been lightly edited for clarity.

How do you incorporate real-world evidence and patient outcomes into your decision-making process for precision genomic testing?

In every point in technology, there's a tipping point, a point where we understand this is new standard of care. I think that we're on the cusp; we've long understood that NGS [next-generation sequencing] testing, particularly with multiple targets now approved across multiple tumor types, that NGS is a standard of care in advanced cancer.

I think we're at a tipping point understanding MRD [minimal residual disease] testing and I think that is where real-world evidence may help me understand better over time which patients benefit from that information, but I do think further testing and prospective trials are going to be necessary.

When it comes down to identifying individual drugs for individual mutations, I'm a bit of a purist, it has to make scientific sense, but also I feel much better if I have some application of case series or identification that others have seen value to it. Then at that point, it's a discussion with the patient of if this is worth it to that individual patient, the potential toxicity for the potential benefit.

How can the cost-effectiveness of these tests be evaluated to ensure they provide value for patients and the practice?

I think the key is that the most expensive drug is actually the drug that doesn't work. It sometimes has huge economic consequences and huge costs to the patients. I would say if we're better able to identify drugs that have high likelihood of working and getting those to the patients, that's of the greatest value. Over time, we need to make sure that we look at real-world evidence to say predictors of unresponsiveness are almost as important as predictors of response, so incorporating that into clinical decision-making is really important.

What are the main challenges and opportunities associated with implementing sequential testing in cancer care?

When I think of sequential testing, for instance, I think of 2 different groups. If I'm looking at minimal residual disease, I do think we've got to figure out, does it affect patient outcomes? Are you able to add additional treatment that may affect long-term survival, or are you able to subtract treatment that is unlikely to work? I think both are really important and we have to ultimately show that we actually can make a difference in those long-term survivals or can reduce toxicity, if and without affecting those survivals.

The other way I look at is actually something that's a little easier. If you found a driver mutation and you're following it over time and you see resistance, we've got to look for it, and we've got to figure out why an individual patient may lose those responsiveness. When I think of sequential testing, I'm often thinking of those we've already identified a driver or those that we may be answering a question of recurrence vs lowering of the treatment paradigm.