Anatomic pathologists understand that, along with breast cancer, diagnostic testing for prostate cancer accounts for a high volume of clinical laboratory tests. Thus, a recent study indicating that a new artificial intelligence (AI)-based software tool can dramatically improve physicians’ ability to identify the extent of these cancers will be of interest.
“The study found that Unfold AI’s patient-specific encapsulation confidence score (ECS), which is generated based on multiple patient data points, including MRI scans, biopsy results, PSA [prostate-specific antigen] data, and Gleason scores, is critical for predicting treatment success,” an Avenda press release states. “These findings emphasize the importance of Unfold AI’s assessment of tumor margins in predicting treatment outcomes, surpassing the predictive capability of conventional parameters.”
“Unfold AI’s ability to identify tumor margins and provide the ECS will improve treatment recommendations and allow for less-invasive interventions,” said study co-author Wayne Brisbane, MD, a urologic oncologist and UCLA medical professor, in another press release. “This more comprehensive approach enhances our ability to predict treatment outcomes and tailor interventions effectively to individual patient needs.”
“This study is important because it shows the ability of AI to not only replicate expert physicians, but to go beyond human ability,” said study co-author Wayne Brisbane, MD (above), a urologic oncologist and UCLA medical professor, in a press release. “By increasing the accuracy of cancer identification in the prostate, more precise and effective treatment methods can be prescribed for patients.” Clinical laboratories that work with anatomic pathologists to diagnose prostate and other cancers may soon have a new AI testing tool. (Photo copyright: UCLA.)
How Unfold AI Works
To gauge the extent of prostate tumors, surgeons typically evaluate results from multiple diagnostic methods such as PSA tests and imaging scans such as MRIs, according to a UCLA press release. However some portions of a tumor may be invisible to an MRI, causing doctors to underestimate the size.
Unfold AI, originally known as iQuest, was designed to analyze data from PSA, MRI, fusion biopsy, and pathology testing, according to a company brochure. From there, it generates a 3D map of the cancer. Avenda’s website says the technology provides a more accurate representation of the tumor’s extent than conventional methods.
“Accurately determining the extent of prostate cancer is crucial for treatment planning, as different stages may require different approaches such as active surveillance, surgery, focal therapy, radiation therapy, hormone therapy, chemotherapy, or a combination of these treatments,” Brisbane said in the UCLA press release.
Putting AI to the Test
In the new study, the UCLA researchers enlisted seven urologists and three radiologists to review 50 prostate cancer cases. Each patient had undergone prostatectomy—surgical removal of all or part of the prostate—but might have been eligible for focal therapy, a less-aggressive approach that uses heat, cryotherapy, or electric shocks to attack cancer cells more selectively.
The physicians came from five hospitals and had a wide range of clinical experience from two to 23 years, the researchers noted in The Journal of Urology.
They reviewed clinical data and examined MRI scans of each patient, then “manually drew outlines around the suspected cancerous areas, aiming to encapsulate all significant disease,” the press release states. “Then, after waiting for at least four weeks, they reexamined the same cases, this time using AI software to assist them in identifying the cancerous areas.”
The researchers analyzed the physicians’ work, evaluating the accuracy of the cancer margins and the “negative margin rate,” indicating whether the clinicians had identified all of the cancerous tissue. Using conventional approaches, “doctors only achieved a negative margin 1.6% of the time,” the press release states. “When assisted by AI the number increased to 72.8%.”
The clinicians’ accuracy was 84.7% when assisted by AI versus 67.2% to 75.9% for conventional techniques.
They also found that clinicians who used the AI software were more likely to recommend focal therapy over more aggressive forms of treatment.
“We saw the use of AI assistance made doctors both more accurate and more consistent, meaning doctors tended to agree more when using AI assistance,” said Avenda Health co-founder and CEO Shyam Natarajan, PhD, who was senior author of the study.
“These results demonstrate a marked change in how physicians will be able to diagnose and recommend treatment for prostate cancer patients,” said Natarajan in a company press release. “By increasing the confidence in which we can predict a tumor’s margins, patients and their doctors will have increased certainty that their entire tumor is treated and with the appropriate intervention in correlation to the severity of their case.”
UCLA’s study found that AI can outperform doctors both in sensitivity (a higher detection rate of positive cancers) and specificity (correctly detecting the sample as negative). That’s relevant and worth watching for further developments.
Pathologists and clinical laboratory managers should consider this use of AI as one more example of how artificial intelligence can be incorporated into diagnostic tests in ways that allow medical laboratory professionals to diagnose disease earlier and more accurately. This will improve patient care because early intervention for most diseases leads to better outcomes.
Clinical laboratories and anatomic pathology groups should consider these cyberattacks on major healthcare entities as reminders that they should tighten their cybersecurity protections
Hackers continue to gain access to public health records—including clinical laboratory testing data—putting thousands of patients’ protected health information (PHI) at risk of being exposed. The latest important healthcare entity to become the victim of a ransomware attack is American Associated Pharmacies (AAP). According to The Register, AAP announced a ransomware operation called Embargo had stolen over 1.4 terabytes (TB) of data, encrypted those files, and demanded $1.3 million to decrypt the data.
Embargo claims that Scottsboro, Ala.-based AAP paid $1.3 million to have its systems restored. They are now demanding an additional $1.3 million to keep the stolen data private, the HIPAA Journal reported, adding, “The attack follows ransomware attacks on Memorial Hospital and Manor, an 80-bed community hospital and 107 long-term care facility in Georgia, and Weiser Memorial Hospital, a critical access hospital in Idaho.”
AAP has not publicly confirmed the ransomware attack, nor has it made an official statement regarding the breach. But it did post an “Important Notice” on its website reporting, “limited ordering capabilities for API Warehouse have been restored at APIRx.com.”
API Warehouse is a subsidiary of AAP that helps subscribers save on brand name and generic prescriptions via wholesale purchasing plans. It oversees more than 2,000 independent pharmacies across the US and has over 2,500 stock keeping units (SKUs) in its inventory.
The message further states “All user passwords associated with both APIRx.com and RxAAP.com have been reset, so existing credentials will no longer be valid to access the sites. Please click ‘forgot password’ on the log in screen and follow the prompts accordingly to reset your password.”
“Embargo seems to have international and multi-sector victims and is not focusing on a specific victim profile. They seem opportunistic,” Mike Hamilton (above), founder and chief information security officer (CISO) of cybersecurity firm Critical Insight, told HealthcareInfoSecurity. “However, as they do have multiple victims in healthcare, and their tooling to disable detection is sophisticated, they should not be discounted. If indeed they operate through affiliates, we can expect others to use their infrastructure and tools, and Embargo may emerge as a top threat to healthcare.” Since 80% of all medical records are made up of clinical laboratory testing data, laboratory patients are particularly vulnerable. (Photo copyright: Critical Insight.)
Embargo on the Hunt for PHI
Due to the large amount of data Embargo stole from the AAP servers, it’s likely the hackers were able to procure medical records and account details from all customers of the pharmacies involved in the attack.
Researchers at ESET, an internet security company, first noticed the ransomware organization known as Embargo in June of this year. In a news release, ESET stated that Embargo used an endpoint detection and response (EDR) killer toolkit to steal AAP’s data.
“Based on its modus operandi, Embargo seems to be a well-resourced group. It sets up its own infrastructure to communicate with victims. Moreover, the group pressures victims into paying by using double extortion: the operators exfiltrate victims’ sensitive data and threaten to publish it on a leak site, in addition to encrypting it,” ESET wrote in a news release.
Embargo recently attacked other organizations within the healthcare industry as well. In November, it claimed responsibility for breaching the security of Memorial Hospital and Manor in Bainbridge, Ga. The cyberattack affected Memorial’s email and electronic medical record (EHR) systems, which caused the facility to pivot to a paper-based system, The Cyber Express reported.
Embargo’s attack on Weiser Memorial Hospital in Weiser, Idaho, involved the theft of approximately 200 gigabytes (GB) of sensitive data and caused a four-week-long outage of its computer systems.
Other Cyberattacks on Healthcare Organizations
Dark Daily has covered many cyberattacks on hospital health systems in multiple ebriefs over the past few years.
Safeguarding patient data is critical, and more healthcare organizations are discovering the hard way that they are vulnerable to hackers. This situation serves as another reminder to clinical laboratory and pathology group managers that they need to be proactive and serious about protecting their information systems, and in upgrading their digital security at regular intervals.
Hackers are working hard to obtain access to protected health information, which puts patients at continuous risk of having their private records stolen.
Half of the people tested were unaware of their genetic risk for contracting the disease
Existing clinical laboratory genetic screening guidelines may be inadequate when it comes to finding people at risk of hereditary breast-ovarian cancer syndromes and Lynch syndrome (aka, hereditary nonpolyposis colorectal cancer). That’s according to a study conducted at the Mayo Clinic in Rochester, Minn., which found that about half of the study participants were unaware of their genetic predisposition to the diseases.
Mayo found that 550 people who participated in the study (1.24%) were “carriers of the hereditary mutations.” The researchers also determined that half of those people were unaware they had a genetic risk of cancer, and 40% did not meet genetic testing guidelines, according to a Mayo Clinic news story.
The discoveries were made following exome sequencing, which the Mayo Clinic news story described as the “protein-coding regions of genes” and the sites for most disease-causing mutations.
“Early detection of genetic markers for these conditions can lead to proactive screenings and targeted therapies, potentially saving lives of people and their family members,” said lead author Niloy Jewel Samadder, MD, gastroenterologist and cancer geneticist at Mayo Clinic’s Center for Individualized Medicine and Comprehensive Cancer Center.
“This study is a wake-up call, showing us that current national guidelines for genetic screenings are missing too many people at high risk of cancer,” said lead author Niloy Jewel Samadder, MD (above), gastroenterologist and cancer geneticist at Mayo Clinic’s Center for Individualized Medicine and Comprehensive Cancer Center. New screening guidelines may increase the role of clinical laboratories in helping physicians identify patients at risk of certain hereditary cancers. (Photo copyright: Mayo Clinic.)
Advancing Personalized Medicine
“The goals of this study were to determine whether germline genetic screening using exome sequencing could be used to efficiently identify carriers of HBOC (hereditary breast and ovarian cancer) and LS (Lynch syndrome),” the authors wrote in JCO Precision Oncology.
For the current study, Helix, a San Mateo, Calif. population genomics company, collaborated with Mayo Clinic to perform exome sequencing on the following genes:
BRCA1 and BRCA2 genes (hereditary breast and ovarian cancer).
Mayo/Helix researchers performed genetic screenings on more than 44,000 study participants. According to their published study, of the 550 people who were found to have hereditary breast cancer or Lynch syndrome:
387 had hereditary breast and ovarian cancer (27.2% BRCA1, 42.8% BRCA2).
163 had lynch syndrome (12.3% MSH6, 8.8% PMS2, 4.5% MLH1, 3.8% MSH2, and 0.2% EPCAM).
Participants recruited by researchers hailed from Rochester, Minn.; Phoenix, Ariz.; and Jacksonville, Fla.
Minorities were less likely to meet the NCCN criteria than those who reported as White (51.5% as compared to 37.5%).
“Our results emphasize the importance of expanding genetic screening to identify people at risk for these cancer predisposition syndromes,” Samadder said.
Exome Data in EHRs
Exomes of more than 100,000 Mayo Clinic patients have been sequenced and the results are being included in the patients’ electronic health records (EHR) as part of the Tapestry project. This gives clinicians access to patient information in the EHRs so that the right tests can be ordered at the right time, Mayo Clinic noted in its article.
“Embedding genomic data into the patient’s chart in a way that is easy to locate and access will assist doctors in making important decisions and advance the future of genomically informed medicine.” said Cherisse Marcou, PhD, co-director and vice chair of information technology and bioinformatics in Mayo’s Clinical Genomics laboratory.
While more research is needed, Mayo Clinic’s accomplishments suggest advancements in gene sequencing and technologies are making way for data-driven tools to aid physicians.
As the cost of gene sequencing continue to fall due to improvement in the technologies, more screenings for health risk factors in individuals will likely become economically feasible. This may increase the role medical laboratories play in helping doctors use exomes and whole genome sequencing to screen patients for risk of specific cancers and health conditions.
Although it is a non-specific procedure that does not identify specific health conditions, it could lead to new biomarkers that clinical laboratories could use for predictive healthcare
Researchers from the Mayo Clinic recently used artificial intelligence (AI) to develop a predictive computational tool that analyzes an individual’s gut microbiome to identify how a person may experience improvement or deterioration in health.
Dubbed the Gut Microbiome Wellness Index 2 (GMWI2), Mayo’s new tool does not identify the presence of specific health conditions but can detect even minor changes in overall gut health.
Built on an earlier prototype, GMWI2 “demonstrated at least 80% accuracy in differentiating healthy individuals from those with any disease,” according to a Mayo news release. “The researchers used bioinformatics and machine learning methods to analyze gut microbiome profiles in stool samples gathered from 54 published studies spanning 26 countries and six continents. This approach produced a diverse and comprehensive dataset.”
“Our tool is not intended to diagnose specific diseases but rather to serve as a proactive health indicator,” said senior study author Jaeyun Sung, PhD (above), a computational biologist at the Mayo Clinic Center for Individualized Medicine: Microbiomics Program in the news release ease. “By identifying adverse changes in gut health before serious symptoms arise, the tool could potentially inform dietary or lifestyle modifications to prevent mild issues from escalating into more severe health conditions, or prompt further diagnostic testing.” For microbiologists and clinical laboratory managers, this area of new knowledge about the human microbiome may lead to multiplex diagnostic assays. (Photo copyright: Mayo Clinic.)
Connecting Specific Diseases with Gut Microbiome
Gut bacteria that resides in the gastrointestinal tract consists of trillions of microbes that help regulate various bodily functions and may provide insights regarding the overall health of an individual. An imbalance in the gut microbiome is associated with an assortment of illnesses and chronic diseases, including cardiovascular issues, digestive problems, and some cancers and autoimmune diseases.
To develop GMWI2, the Mayo scientists provided the machine-learning algorithm with data on microbes found in stool samples from approximately 8,000 people collected from 54 published studies. They looked for the presence of 11 diseases, including colorectal cancer and inflammatory bowel disease (IBS). About 5,500 of the subjects had been previously diagnosed with one of the 11 diseases, and the remaining people did not have a diagnosis of the conditions.
The scientists then tested the efficacy of GMWI2 on an additional 1,140 stool samples from individuals who were diagnosed with conditions such as pancreatic cancer and Parkinson’s disease, compared with those who did not have those illnesses.
The algorithm gives subjects a score between -6 and +6. People with a higher GMWI2 score have a healthier microbiome that more closely resembles individuals who do not have certain diseases.
Likewise, a low GMWI2 score suggests the individual has a gut microbiome that is similar to those who have specific illnesses.
Highly Accurate Results
According to their study, the researchers determined that “GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence,” they wrote in Nature Communications.
Launched in 2020, the original GMWI (Gut Microbiome Wellness Index) was trained on a much smaller number of samples but still showed similar results.
The researchers tested the enhanced GMWI2 algorithm across various clinical schemes to determine if the results were similar. These scenarios included individuals who had previous fecal microbiota transplants and people who had made dietary changes or who had exposure to antibiotics. They found that their improved tool detected changes in gut health in those scenarios as well.
“By being able to answer whether a person’s gut is healthy or trending toward a diseased state, we ultimately aim to empower individuals to take proactive steps in managing their own health,” Sung said in the news release.
The Mayo Clinic team is developing the next version of their tool, which will be known as the Gut Microbiome Wellness Index 3. They plan to train it on at least 12,000 stool samples and use more sophisticated algorithms to decipher the data.
More research and studies are needed to determine the overall usefulness of Mayo’s Gut Microbiome Wellness Index and its marketability. Here is a world-class health institution disclosing a pathway/tool that analyzes the human microbiome to identify how an individual may be experiencing either an improvement in health or a deterioration in health.
The developers believe it will eventually help physicians determine how patients’ conditions are improving or worsening by comparing the patients’ microbiomes to the profiles of other healthy and unhealthy microbiomes. As this happens, it would create a new opportunity for clinical laboratories to perform the studies on the microbiomes of patients being assayed in this way by their physicians.
Though the cost of clinical laboratory testing is not highlighted in KFF’s annual survey, it is a component in how much employers pay for healthcare plans for their employees
Employers now pay higher health insurance premiums than ever for family coverage. However, because of the current tight labor market, they are generally absorbing much of that increase rather than passing the higher costs on to their workers. That’s one key takeaway from KFF’s 26th annual Employer Health Benefits Survey, which the non-profit published on Oct. 9, 2024. While the report does not comment specifically about the cost of clinical laboratory testing or genetic testing and how they may contribute to rising insurance costs, it stands to reason they are part of growing healthcare costs for corporate health benefits.
The KFF survey found that premiums for family coverage increased 7% in 2024, reaching an average of $25,572. That follows a 7% increase in 2023. “Over the past five years—a period of high inflation (23%) and wage growth (28%)—the cumulative increase in premiums has been similar (24%),” KFF stated in a press release.
However, the amount paid by workers has gone up by less than $300 since 2019. It now stands at an average of $6,296, a total increase of 5% over five years. On average, workers covered 25% of family premium costs in 2024, down from 29% in 2023. Workers with single coverage paid an average of $1,368—16% of the annual premium cost—compared with 17% in 2023.
“Employers are shelling out the equivalent of buying an economy car for every worker every year to pay for family coverage,” KFF President and CEO Drew Altman, PhD (above), said in a press release. “In the tight labor market in recent years, they have not been able to continue offloading costs onto workers who are already struggling with healthcare bills.” Rising costs of clinical laboratory testing is always part of the mix contributing to increased worker insurance premiums for employers. (Photo copyright: KFF.)
HDHP/SO plans, as defined by KFF, “have a deductible of at least $1,000 for single coverage and $2,000 for family coverage and are offered with an HRA [Health Reimbursement Arrangement] or are HSA [health savings account]-qualified.” Point-of-service plans “have lower cost sharing for in-network provider services and do not require a primary care gatekeeper to screen for specialist and hospital visits,” the report states.
Cost Sharing via Deductibles
Average deductible amounts—which KFF identified as another form of cost-sharing—varied depending on the type of plan, employer size, and whether the worker had family or single coverage.
For workers with single coverage, average deductibles across all plan types rose from $1,655 in 2019 to $1,787 in 2024, a total five-year increase of about 8%. The average in 2023 was $1,735. These numbers were for in-network providers.
The report noted that some family plans calculate deductibles using an aggregate structure, “in which all family members’ out-of-pocket expenses count toward the deductible,” whereas others use a separate per-person structure. The report includes breakdowns of average deductibles across all types.
Who Offers the Best Benefits?
In general, the KFF report found that large companies—defined as those with 200 or more workers—tend to offer more generous health benefits than smaller ones. Virtually all large companies (98%) offered health benefits, while slightly more than half of small companies (53%) do so.
Among companies that do offer health benefits, the average deductible at a small firm was $2,575 compared to $1,538 at large firms. Among workers with family coverage, the average contribution toward overall premium costs was $7,947 (33%) at small firms compared to $5,697 (23%) at large firms. Among workers with single coverage, the numbers were $1,429 (16%) at small firms compared to $1,204 (14%) at large firms.
The report also found variations in overall premiums and health benefits across nine different industries. For example, healthcare firms paid the highest premiums for family coverage—an average of $26,864—followed by transportation/communications/utilities at $26,601. Companies in agriculture, mining, and construction paid the lowest premiums, an average of $22,654.
There were wide variations by industry in terms of how many firms offer any health benefits. Among state and local government entities, 83% offered health benefits, followed by transportation/communications/utilities (69%), manufacturing (65%), wholesale (62%), healthcare (58%), and finance (56%). Just 40% of retail businesses and 49% of agriculture/mining/construction businesses offered health benefits.
Health Screening Coverage
The KFF report did not include data about insurance coverage for clinical laboratory services. However, one section did address employer willingness to provide opportunities for health screening.
Among large businesses, 56% offered health risk assessments, in which individuals answer questions about their medical history, lifestyle, and other areas relevant to their health risks. A smaller number (44%) offer biometric screening, which “could include meeting a target body mass index (BMI) or cholesterol level, but not goals related to smoking,” the report said. Only 9% of small businesses offered biometric screening, the report found.
KFF conducted its survey between January and July 2024 among a random selection of public and private employers with at least three workers. The survey excluded federal government entities but included state and local government. A total of 2,142 employers responded.
Inflation during this current administration definitely hit consumers in the health insurance premium pocketbook. At the same time providers raised their own prices making it more expensive for people with HDHPs to come up with the cash required by their annual deductible. While clinical laboratory and genetic testing are not highlighted in KFF’s survey, they certainly play a role in increasing costs to healthcare consumers and are worth considering.
New clinical laboratory test could replace conventional spinal tap for diagnosing neurodegenerative disease
In a proof-of-concept study, University of Pittsburgh (Pitt) scientists validated a clinical laboratory test that measures more than 100 different genetic sequences associated with Alzheimer’s disease. The Pitt researchers believe the new diagnostic platform could help clinicians “capture the multifaceted nature of Alzheimer’s pathology and streamline early disease diagnostics,” according to a news release.
Clinical laboratory blood tests that detect biomarkers such as phosphorylated tau protein (pTau) have emerged in studies as diagnostic possibilities for Alzheimer’s disease, which is traditionally diagnosed using a lumbar puncture (spinal tap) procedure.
In their paper, neuroscientist Thomas Karikari, PhD, Assistant Professor of Psychiatry at University of Pittsburgh, lead author of the study, and his research team acknowledged that progress has been made in detecting Alzheimer’s disease with blood-based biomarkers. However, they note that “two key obstacles remain: the lack of methods for multi-analyte assessments and the need for biomarkers for related pathophysiological processes like neuroinflammation, vascular, and synaptic dysfunction.”
The Pitt scientists believe the focus on so-called “classical Alzheimer’s blood biomarkers” limits exploration of neurodegenerative disease.
“Alzheimer’s disease should not be looked at through one single lens. Capturing aspects of Alzheimer’s pathology in a panel of clinically validated biomarkers would increase the likelihood of stopping the disease before any cognitive symptoms emerge,” said neuroscientist Thomas Karikari, PhD (above), Assistant Professor of Psychiatry, University of Pittsburgh, and lead author of the study in a news release. Should further studies prove Pitt’s research sound, clinical laboratories may have a replacement test for diagnosing neurodegenerative disease. (Photo copyright: University of Pittsburgh.)
On its website, Alamar Biosciences explains that the disease panel offers neurological researchers:
“Multiplexed analysis of 120 neuro-specific and inflammatory proteins from 10 µl of plasma or CSF (cerebrospinal fluid).
Detection of “critical biomarkers—including pTau-217, GFAP (glial fibrillary acidic protein), NEFL (neurofilament light polypeptide) and alpha-synuclein.”
The NULISAseq test works with “a proprietary sequential immunocomplex capture and release mechanism and the latest advances in next-generation sequencing,” according to the company.
Inside Precision Medicine noted that the Alamar Biosciences assay enabled Pitt scientists to detect:
Biomarkers (usually found in CSF) “correlating with patients’ amyloid positivity status and changes in amyloid burden over time,” and,
Biomarkers including “neuroinflammation, synaptic function, and vascular health, which had not previously been validated in blood samples.”
“The performance of the NULISA platform was independently validated against conventional assays for classic Alzheimer’s biomarkers for each sample. Biomarker profiles over two years were also compared with imaging-based measures of amyloid, tau, and neurodegeneration,” LabMedica reported.
Opportunity to Track Alzheimer’s
Karikari sees the diagnostic platform being used to track individuals’ blood biomarker changes over time.
In their Molecular Neurodegeneration paper, the Pitt researchers wrote, “These (results) were not limited to markers such as pTau217, p-Tau231, p-Tau181, and GFAP, the elevation of which have consistently shown strong associations with brain Aβ [amyloid beta] and/or tau load, but included novel protein targets that inform about the disease state of the individual in different pathological stages across the biological Alzheimer’s disease continuum.”
About seven million Americans are affected by Alzheimer’s disease, according to the Alzheimer’s Association, which estimated that figure will grow to 13 billion by 2050.
Further studies by Karikari may include larger samples and greater diversity among the people studied, Inside Precision Medicine noted.
“[Karikari’s] lab is developing a predictive model that correlates biomarker changes detected using NULISAseq with brain autopsy data and cognitive assessments collected over the course of several years. Their goal is to identify blood biomarkers that can help stage the disease and predict its progression, both for decision-making around clinical management and treatment plans,” the Pitt news release states.
The Pitt scientists have developed a multiplex test that works with 100 different genetic sequences associated with Alzheimer’s. Such advances in the understanding of the human genome are giving scientists the opportunity to combine newly identified gene sequences that have a role in specific disease states.
In turn, as further studies validate the value of these biomarkers for diagnosing disease and guiding treatment decisions, clinical laboratories will have new assays that deliver more value to referring physicians and their patients.
