HealthVerity COO Andrew Goldberg recently sat down with Quest Diagnostics’ Director, Health Informatics Justin Niles, an epidemiologist with nearly 20 years of experience. What followed was an entertaining and insightful conversation regarding the breadth and scope of use cases that are well served with biomarker data. If you missed the webinar, here is our recap.
Breadth and scope of biomarker data
Quest has a large national testing footprint with nearly 50,000 employees, combining comprehensive technology, methodology and clinical expertise, including doctors of genomics, oncology, cardiology, neurology and others. Quest offers over 14 million discreet, easy-to-query and analyze biomarker records from more than 4.5 million patient lab interactions for nearly 4 million patients. This includes results available for over 15,000 unique biomarkers obtained using a variety of methods, with sequencing accounting for more than half of results.
As an example, Quest has over 70,000 results for PD-L1. Normally, PD-L1 is found on certain healthy cells and can help keep T cells in check, preventing them from attacking healthy cells in the body, but if cancer cells have high amounts of PD-L1, they can prevent T cells from attacking the cancer cells. Differing levels of expression can determine whether a patient is eligible for first-line treatment with certain therapies for non-small cell lung cancer. Evaluation of the PD-L1 data, especially in conjunction with other types of data, can provide insights for pharmaceutical companies to better understand their potential markets or different outcomes for various therapies.
Quest has records on over 100,000 patients for each of these top biomarkers, which are readily available through HealthVerity Marketplace in a de-identified, privacy-protected and research-ready format:
| Genetic disorders | Oncology |
| CFTR - Indicative of cystic fibrosis | JAK2 - Associated with myeloproliferative neoplasms (MPNs) |
| SMN1 and SMN2 - Indicative of spinal muscular atrophy |
MPL - Associated with MPNs |
| F5 and F2 - Indicative of clotting disorders | CALR - Associated with MPNs |
| FMR1 - Indicative of fragile X | CSF3R - Associated with hematologic cancers and severe congenital neutropenia |
| HFE - Indicative of hereditary hemochromatosis | TP53 - One of the most frequent alterations in human cancers that predisposes patients to a wide spectrum of early onset cancers |
| HBA - Indicative of alpha thalassemia | HER2 - Prevalent in early onset breast cancer, as well as many other outcomes such as bladder and cervical cancers |
Revealing the results
While all of this biomarker data is impressive, if it’s buried in reports and comments, it becomes a massive undertaking to perform different types of analyses on outcomes of interest. This can be especially challenging when working with the scale of data available from Quest. Imagine going through comments of over 100,000 records on JAK2 testing results. Recognizing this as a significant drawback, Quest created a discretized, standardized, easily-queryable database that provides actionable insights of interest faster and far more efficiently.
To make the data easy to work with, Quest created separate, standardized fields for outcomes, with some fields specific to methodology, such as CNOMEN and PNOMEN. Some fields are related to sequencing. For example, Copies and Ratio would only be filled for FISH tests. The most critical field is often variant detection. Aptly named, this field allows users of the data to easily detect variants across the scope of Quest’s biomarker offering. Many other fields enable easy access to more specific information, such as EXON and LOCI, which could provide the very insights you’re trying to access. For example, the EXON 14 JAK2 mutation is an established driver of MPNs, but there has been increased research on the EXON 13 mutation. Having the ability to easily discover data on both of these elements gets you to the analysis phase of a project faster and more efficiently.
Generating insights
Biomarker data provides endless possibilities and ample opportunities for truly novel research or you can even try to reproduce important studies with a much larger population, leveraging data available from Quest.
Biomarker data by itself has so many interesting use cases, but when synchronized with other data available from HealthVerity, possible avenues for exploration increase exponentially. As an example, biomarker data can be seamlessly synchronized with other Quest lab data to access the different clinical presentations of genetic variants, such as JAK2, which is associated with MPNs, and BCR-ABL1, which is associated with chronic myeloid leukemia. Using lab data from HealthVerity, you can compare platelet count distribution for patients with and without these variants detected. The charts below show this comparison, demonstrating the dramatic difference between those patients where the JAK2 mutation was detected (in green on the left-hand chart), versus a far less pronounced difference for patients with the BCR-ABL1 variant (in orange on the right-hand chart). While this association has been noted in previous research, to our knowledge, there have been no published studies on a population of this size, which represents over 200,000 patients. This size of population enables more granular analyses, such as drilling down by geography, including states or even three-digit zip codes. You could also determine more meaningful age, gender and payer type distributions with the variables available in data from HealthVerity, all in a privacy-protected and HIPAA-compliant manner and with patient identity accurately resolved across data sources.
With the timeliness of lab data, another beneficial use case is the ability to quickly discover patients with particular biomarker variants for participation in clinical trials. In the example charts below, you can see a comparison of a biomarker distribution for Florida from across all years of available data on the left, compared to January 2024 on the right. When looking across the years, the highest concentration appears to be the Miami area, but when drilling down to January 2024 insights, the Fort Meyers area has the highest concentration. These types of insights can also be useful for discovering physicians treating recently accessed patients to provide outreach on treatment options. The large volumes and timeliness of data available from Quest and HealthVerity allow for granular assessments in timeframes as recent as last month or even last week.
Unlimited use cases
This level of biomarker data offers exciting use cases across the pharmaceutical lifecycle:
| Research & development | Phase I-III clinical trials | Launch | Maximize |
| Novel biomarkers for new therapy targets | Trial site selection for optimal locations | Therapy candidates who meet criteria | Efficacy to understand outcomes |
| Disease prevalence for market sizing | PI candidates to identify investigators | Diagnostic journey from testing through treatment | HEOR to demonstrate economic value |
| Cohort profiling for representative participation | Provider education to optimize test utilization | Pharmacovigilance to monitor safety and efficacy | |
| Patient recruitment for eligible trial participants |
A particular use case where lab data is valuable is physician outreach and education efforts because of the short lag time. Timeliness is critical with these initiatives, as you need to engage with the physician before a treatment decision is made. Quest data is available through HealthVerity in only five days from specimen collection. Delays in receiving alerts about a diagnosis or if a patient isn’t verified as truly new, can result in lost opportunities and wasted promotional dollars.
HealthVerity Precision Event Alerts overcomes these challenges, providing up to 30% more alerts, one to two weeks faster and with 20% greater accuracy than legacy solutions.
More patients
We have combined the optimal mix of data sources, including both open and closed payer claims, and Quest and other major lab data sources to offer the most comprehensive physician alerting solution. With the sheer volume of diagnostic testing data available from Quest, plus the other major lab sources only available from HealthVerity, we can discover up to 30% more patients meeting your specific criteria.
Faster
HealthVerity demonstrated its ability to provide timely lab results during the pandemic when we were able to provide COVID results from yesterday’s tests. With Precision Event Alerts, HealthVerity is able to provide alerts within five to eight days from an event, depending on the data type. With the time it takes legacy physician alerting solutions to process the data and build and deliver the reports, there can be a lag time of up to three weeks.
Higher precision
As mentioned, it is important to understand when a patient is first diagnosed with a condition in order to optimize outreach efforts. Many legacy physician alerting solutions verify that a patient is new by using open claims data derived from clearinghouses that physicians use to route claims to the appropriate payer. But if a patient is seeing multiple doctors or changes doctors, the patient may have been diagnosed a while ago and it is just the first reference in that particular data source. By leveraging both open and closed payer claims, HealthVerity provides greater precision, eliminating false alerts before you deploy resources into the market.
HealthVerity is honored to have data partners, like Quest, that enable the nation’s largest, fully interoperable and privacy-protected healthcare and consumer data ecosystem, which can power invaluable use cases like Precision Event Alerts.
For more information about Quest lab data or Precision Event Alerts:
