Simple Urine Test Significantly Improves Detection of Adrenal Cancer
|
By LabMedica International staff writers Posted on 06 Aug 2020 |

Image: The Xevo mass spectrometer with an Acquity ultra high performance chromatography system (Photo courtesy of Waters Corporation).
Prognosis for patients discovered to have an adrenal cortical carcinoma (ACC), a cancerous adrenal mass, is poor, and a cure is only achievable through early detection and surgery. The incidental discovery of an adrenal mass often triggers additional scans to determine whether the mass is cancerous.
Imaging procedures, such as CT and MRI scans, are used in clinical practice with increasing frequency and often lead incidentally to the discovery of a nodule in the adrenal glands, detected on average in 5% of scans. These so-called adrenal incidentalomas are in the majority harmless, but once an adrenal mass has been discovered it is important to exclude adrenal cancer as well as adrenal hormone excess.
A team of endocrinologists based at the University of Birmingham (Birmingham, UK) and their international associates studied more than 2,000 patients with newly diagnosed adrenal tumors from 14 centers of the European Network for the Study of Adrenal Tumours (ENSAT). They assessed the accuracy of diagnostic imaging strategies based on maximum tumor diameter (≥4 cm versus <4 cm), imaging characteristics (positive versus negative), and urine steroid metabolomics (low, medium, or high risk of ACC), separately and in combination, using a reference standard of histopathology and follow-up investigations.
Enrolled participants collected a 24 hour urine sample that was used for multisteroid profiling by liquid chromatography–tandem mass spectrometry (LC–MS/MS), with quantification of 15 urinary steroid metabolites and application of a machine-learning algorithm. A Xevo mass spectrometer with an Acquity ultra high performance chromatography system (Waters, Milford, MA, USA) with a HSS T3, 1.8µm, 1.2×50mm column (heated at 60oC) was used to analyze the steroids. The algorithm was developed by applying generalized matrix learning vector quantisation to steroid excretion data from a retrospective cohort of 139 patients with adrenal masses (40 ACC and 99 adrenocortical adenoma [ACA]) measured retrospectively by use of the LC–MS/MS method used in the study.
The scientists reported that of 2,169 participants recruited between Jan 17, 2011, and July 15, 2016, they included 2,017 from 14 specialist centers in 11 countries in the final analysis and 98 (4.9%) had histopathologically or clinically and biochemically confirmed ACC. A urine steroid metabolomics result indicating high risk of ACC had a positive predictive value PPV of 34.6%. When the three tests were combined, in the order of tumor diameter, positive imaging characteristics, and urine steroid metabolomics, 106 (5.3%) participants had the result maximum tumor diameter of 4 cm or larger, positive imaging characteristics, and urine steroid metabolomics indicating high risk of ACC, for which the PPV was 76.4% .
Wiebke Arlt, MD, DSc, FRCP, a Professor of Medicine and senior author of the study, said, “Introduction of this new testing approach into routine clinical practice will enable faster diagnosis for those with cancerous adrenal masses. We hope that the results of this study could lead to significant decreases in patient burden and a reduction in healthcare costs, by not only reducing the numbers of unnecessary surgeries for those with benign masses, but also limiting the number of imaging procedures that are required.” The study was published on July 23, 2020 in the journal The Lancet Diabetes & Endocrinology.
Imaging procedures, such as CT and MRI scans, are used in clinical practice with increasing frequency and often lead incidentally to the discovery of a nodule in the adrenal glands, detected on average in 5% of scans. These so-called adrenal incidentalomas are in the majority harmless, but once an adrenal mass has been discovered it is important to exclude adrenal cancer as well as adrenal hormone excess.
A team of endocrinologists based at the University of Birmingham (Birmingham, UK) and their international associates studied more than 2,000 patients with newly diagnosed adrenal tumors from 14 centers of the European Network for the Study of Adrenal Tumours (ENSAT). They assessed the accuracy of diagnostic imaging strategies based on maximum tumor diameter (≥4 cm versus <4 cm), imaging characteristics (positive versus negative), and urine steroid metabolomics (low, medium, or high risk of ACC), separately and in combination, using a reference standard of histopathology and follow-up investigations.
Enrolled participants collected a 24 hour urine sample that was used for multisteroid profiling by liquid chromatography–tandem mass spectrometry (LC–MS/MS), with quantification of 15 urinary steroid metabolites and application of a machine-learning algorithm. A Xevo mass spectrometer with an Acquity ultra high performance chromatography system (Waters, Milford, MA, USA) with a HSS T3, 1.8µm, 1.2×50mm column (heated at 60oC) was used to analyze the steroids. The algorithm was developed by applying generalized matrix learning vector quantisation to steroid excretion data from a retrospective cohort of 139 patients with adrenal masses (40 ACC and 99 adrenocortical adenoma [ACA]) measured retrospectively by use of the LC–MS/MS method used in the study.
The scientists reported that of 2,169 participants recruited between Jan 17, 2011, and July 15, 2016, they included 2,017 from 14 specialist centers in 11 countries in the final analysis and 98 (4.9%) had histopathologically or clinically and biochemically confirmed ACC. A urine steroid metabolomics result indicating high risk of ACC had a positive predictive value PPV of 34.6%. When the three tests were combined, in the order of tumor diameter, positive imaging characteristics, and urine steroid metabolomics, 106 (5.3%) participants had the result maximum tumor diameter of 4 cm or larger, positive imaging characteristics, and urine steroid metabolomics indicating high risk of ACC, for which the PPV was 76.4% .
Wiebke Arlt, MD, DSc, FRCP, a Professor of Medicine and senior author of the study, said, “Introduction of this new testing approach into routine clinical practice will enable faster diagnosis for those with cancerous adrenal masses. We hope that the results of this study could lead to significant decreases in patient burden and a reduction in healthcare costs, by not only reducing the numbers of unnecessary surgeries for those with benign masses, but also limiting the number of imaging procedures that are required.” The study was published on July 23, 2020 in the journal The Lancet Diabetes & Endocrinology.
Latest Pathology News
- Engineered Yeast Cells Enable Rapid Testing of Cancer Immunotherapy
- First-Of-Its-Kind Test Identifies Autism Risk at Birth
- AI Algorithms Improve Genetic Mutation Detection in Cancer Diagnostics
- Skin Biopsy Offers New Diagnostic Method for Neurodegenerative Diseases
- Fast Label-Free Method Identifies Aggressive Cancer Cells
- New X-Ray Method Promises Advances in Histology
- Single-Cell Profiling Technique Could Guide Early Cancer Detection
- Intraoperative Tumor Histology to Improve Cancer Surgeries
- Rapid Stool Test Could Help Pinpoint IBD Diagnosis
- AI-Powered Label-Free Optical Imaging Accurately Identifies Thyroid Cancer During Surgery
- Deep Learning–Based Method Improves Cancer Diagnosis
- ADLM Updates Expert Guidance on Urine Drug Testing for Patients in Emergency Departments
- New Age-Based Blood Test Thresholds to Catch Ovarian Cancer Earlier
- Genetics and AI Improve Diagnosis of Aortic Stenosis
- AI Tool Simultaneously Identifies Genetic Mutations and Disease Type
- Rapid Low-Cost Tests Can Prevent Child Deaths from Contaminated Medicinal Syrups
Channels
Molecular Diagnostics
view channel
Diagnostic Device Predicts Treatment Response for Brain Tumors Via Blood Test
Glioblastoma is one of the deadliest forms of brain cancer, largely because doctors have no reliable way to determine whether treatments are working in real time. Assessing therapeutic response currently... Read more
Blood Test Detects Early-Stage Cancers by Measuring Epigenetic Instability
Early-stage cancers are notoriously difficult to detect because molecular changes are subtle and often missed by existing screening tools. Many liquid biopsies rely on measuring absolute DNA methylation... Read more
“Lab-On-A-Disc” Device Paves Way for More Automated Liquid Biopsies
Extracellular vesicles (EVs) are tiny particles released by cells into the bloodstream that carry molecular information about a cell’s condition, including whether it is cancerous. However, EVs are highly... Read more
Blood Test Identifies Inflammatory Breast Cancer Patients at Increased Risk of Brain Metastasis
Brain metastasis is a frequent and devastating complication in patients with inflammatory breast cancer, an aggressive subtype with limited treatment options. Despite its high incidence, the biological... Read moreHematology
view channel
New Guidelines Aim to Improve AL Amyloidosis Diagnosis
Light chain (AL) amyloidosis is a rare, life-threatening bone marrow disorder in which abnormal amyloid proteins accumulate in organs. Approximately 3,260 people in the United States are diagnosed... Read more
Fast and Easy Test Could Revolutionize Blood Transfusions
Blood transfusions are a cornerstone of modern medicine, yet red blood cells can deteriorate quietly while sitting in cold storage for weeks. Although blood units have a fixed expiration date, cells from... Read more
Automated Hemostasis System Helps Labs of All Sizes Optimize Workflow
High-volume hemostasis sections must sustain rapid turnaround while managing reruns and reflex testing. Manual tube handling and preanalytical checks can strain staff time and increase opportunities for error.... Read more
High-Sensitivity Blood Test Improves Assessment of Clotting Risk in Heart Disease Patients
Blood clotting is essential for preventing bleeding, but even small imbalances can lead to serious conditions such as thrombosis or dangerous hemorrhage. In cardiovascular disease, clinicians often struggle... Read moreImmunology
view channelBlood Test Identifies Lung Cancer Patients Who Can Benefit from Immunotherapy Drug
Small cell lung cancer (SCLC) is an aggressive disease with limited treatment options, and even newly approved immunotherapies do not benefit all patients. While immunotherapy can extend survival for some,... Read more
Whole-Genome Sequencing Approach Identifies Cancer Patients Benefitting From PARP-Inhibitor Treatment
Targeted cancer therapies such as PARP inhibitors can be highly effective, but only for patients whose tumors carry specific DNA repair defects. Identifying these patients accurately remains challenging,... Read more
Ultrasensitive Liquid Biopsy Demonstrates Efficacy in Predicting Immunotherapy Response
Immunotherapy has transformed cancer treatment, but only a small proportion of patients experience lasting benefit, with response rates often remaining between 10% and 20%. Clinicians currently lack reliable... Read moreMicrobiology
view channel
Comprehensive Review Identifies Gut Microbiome Signatures Associated With Alzheimer’s Disease
Alzheimer’s disease affects approximately 6.7 million people in the United States and nearly 50 million worldwide, yet early cognitive decline remains difficult to characterize. Increasing evidence suggests... Read moreAI-Powered Platform Enables Rapid Detection of Drug-Resistant C. Auris Pathogens
Infections caused by the pathogenic yeast Candida auris pose a significant threat to hospitalized patients, particularly those with weakened immune systems or those who have invasive medical devices.... Read morePathology
view channel
Engineered Yeast Cells Enable Rapid Testing of Cancer Immunotherapy
Developing new cancer immunotherapies is a slow, costly, and high-risk process, particularly for CAR T cell treatments that must precisely recognize cancer-specific antigens. Small differences in tumor... Read more
First-Of-Its-Kind Test Identifies Autism Risk at Birth
Autism spectrum disorder is treatable, and extensive research shows that early intervention can significantly improve cognitive, social, and behavioral outcomes. Yet in the United States, the average age... Read moreTechnology
view channel
Robotic Technology Unveiled for Automated Diagnostic Blood Draws
Routine diagnostic blood collection is a high‑volume task that can strain staffing and introduce human‑dependent variability, with downstream implications for sample quality and patient experience.... Read more
ADLM Launches First-of-Its-Kind Data Science Program for Laboratory Medicine Professionals
Clinical laboratories generate billions of test results each year, creating a treasure trove of data with the potential to support more personalized testing, improve operational efficiency, and enhance patient care.... Read moreAptamer Biosensor Technology to Transform Virus Detection
Rapid and reliable virus detection is essential for controlling outbreaks, from seasonal influenza to global pandemics such as COVID-19. Conventional diagnostic methods, including cell culture, antigen... Read more
AI Models Could Predict Pre-Eclampsia and Anemia Earlier Using Routine Blood Tests
Pre-eclampsia and anemia are major contributors to maternal and child mortality worldwide, together accounting for more than half a million deaths each year and leaving millions with long-term health complications.... Read moreIndustry
view channelNew Collaboration Brings Automated Mass Spectrometry to Routine Laboratory Testing
Mass spectrometry is a powerful analytical technique that identifies and quantifies molecules based on their mass and electrical charge. Its high selectivity, sensitivity, and accuracy make it indispensable... Read more
AI-Powered Cervical Cancer Test Set for Major Rollout in Latin America
Noul Co., a Korean company specializing in AI-based blood and cancer diagnostics, announced it will supply its intelligence (AI)-based miLab CER cervical cancer diagnostic solution to Mexico under a multi‑year... Read more
Diasorin and Fisher Scientific Enter into US Distribution Agreement for Molecular POC Platform
Diasorin (Saluggia, Italy) has entered into an exclusive distribution agreement with Fisher Scientific, part of Thermo Fisher Scientific (Waltham, MA, USA), for the LIAISON NES molecular point-of-care... Read more







