As diabetes testing evolves, labs are seeing growing interest in earlier screening, additional biomarkers, and tools that can support more preventive care.
By Alyx Arnett
Diabetes testing is increasingly being used to support earlier intervention, according to Qian Ding, senior manager of medical and scientific affairs at QuidelOrtho. As that shift continues, Ding says clinical laboratories should pay close attention to how newer platforms are improving speed, reliability, and workflow consistency.
“Early detection is a clinical priority because diabetes often develops silently,” Ding says. “Today’s systems help us obtain reliable answers faster and are built to optimize workflows and reduce variability across the testing process.”
For labs, Ding says the most important changes include assays designed to reduce interference, built-in quality checks, automation-ready workflows, and random-access testing that can give laboratories more flexibility. Together, she says, those features can help labs provide high-quality results with less hands-on time and give clinicians data they can act on sooner.
A Broader View of Metabolic Health
Ding says providers are using traditional markers such as fasting glucose and HbA1c to monitor trends earlier and guide more individualized care plans. In her view, earlier testing can shift diabetes care toward prevention by helping clinicians initiate lifestyle or medical management before disease progression.
“Early testing changes the trajectory of diabetes by shifting care from reactive to proactive,” she says.
Ding also points to growing interest in additional biomarkers, including C-peptide and pro-insulin as indicators of insulin production, adiponectin as a marker of insulin sensitivity, and inflammatory markers such as CRP or interleukins. These markers, she says, are not replacements for established diagnostic criteria such as glucose and HbA1c.
“They can provide a more comprehensive view of metabolic health, often revealing subtle changes well before glucose levels become measurable,” Ding says.
Labs’ Role in Prediabetes and Prevention
As providers focus more attention on prediabetes, Ding says laboratories may be asked to work more closely with clinicians on screening strategies and interpretation.
“Labs generate the data, but that data only drives better outcomes when it is connected to what happens in the clinic,” she says.
That collaboration can include sharing testing trends, flagging subtle changes, and helping clinicians understand when results may require additional context. Ding says co-developing screening protocols can also help align cutoffs and testing approaches across patient groups.
She adds that population-specific considerations are also important. For example, Ding says labs may need to account for hemoglobin variants in communities where they are more common, or for patients who may develop diabetes at lower BMI thresholds.
“At its core, prevention-focused diagnostics aim to ensure that early diagnosis is accurate, accessible, and population-appropriate,” she says.
Questions for New Testing Platforms
When evaluating diabetes testing technologies, Ding says lab leaders should look first at whether a platform improves clinical decision-making.
She recommends assessing analytical performance, including accuracy, precision, and alignment with established standards. Operational factors also matter, she says, including workflow integration, turnaround time, and scalability.
For emerging biomarkers, Ding urges caution. Lab leaders should ask whether the marker is supported by adequate clinical evidence and whether it adds useful information beyond established tests such as glucose and HbA1c.
Core Labs Remain the Reference Point
Point-of-care testing and continuous glucose monitoring are changing how diabetes data reaches clinicians and patients, but Ding says she views these tools as complementary to central lab testing.
“Continuous monitoring and point-of-care tools bring more immediate, patient-level data into care, especially for day-to-day management,” she says. “But the core lab still plays a critical role in standardized A1C testing, diagnosis, and resolving cases where device data and the clinical picture do not fully align.”
Ding says central labs are becoming more integrated into decentralized testing models, serving as the reference point for standardized results.
She also expects regulatory, reimbursement, and guideline activity around continuous glucose monitoring to influence diabetes management. As continuous glucose monitoring gains broader support, Ding says central lab manufacturers and laboratories will continue to face expectations around assay quality, standardization, and interference management.
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