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University of Oslo Research Study Suggests Most Cancer Screenings Do Not Prolong Lives

Norwegian researchers reviewed large clinical trials of six common cancer screenings, including clinical laboratory tests, but some experts question the findings

Cancer screenings are a critical tool for diagnosis and treatment. But how much do they actually extend the lives of patients? According to researchers at the University of Oslo in Norway, not by much. They recently conducted a review and meta-analysis of 18 long-term clinical trials, five of the six most commonly used types of cancer screening—including two clinical laboratory tests—and found that with few exceptions, the screenings did not significantly extend lifespans.

The 18 long-term clinical trials included in the study were randomized trials that collectively included a total of 2.1 million participants. Median follow-up periods of 10 to 15 years were used to gauge estimated lifetime gain and mortality.

The researchers published their findings in JAMA Internal Medicine titled, “Estimated Lifetime Gained with Cancer Screening Tests: A Meta-analysis of Randomized Clinical Trials.”

“The findings of this meta-analysis suggest that current evidence does not substantiate the claim that common cancer screening tests save lives by extending lifetime, except possibly for colorectal cancer screening with sigmoidoscopy,” the researchers wrote in their published paper.

The researchers noted, however, that their analysis does not suggest all screenings should be abandoned. They also acknowledged that some lives are saved by screenings.

“Without screening, these patients may have died of cancer because it would have been detected at a later, incurable stage,” the scientists wrote, MedPage Today reported. “Thus, these patients experience a gain in lifetime.”

Still, some independent experts questioned the validity of the findings.

Gastroenterologist Michael Bretthauer, MD, PhD (above), a professor at the University of Oslo in Norway led the research into cancer screenings. In their JAMA Internal Medicine paper, he and his team wrote, “The findings of this meta-analysis suggest that colorectal cancer screening with sigmoidoscopy may extend life by approximately three months; lifetime gain for other screening tests appears to be unlikely or uncertain.” How their findings might affect clinical laboratory and anatomic pathology screening for cancer remains to be seen. (Photo copyright: University of Oslo.)

Pros and Cons of Cancer Screening

The clinical trials, according to MedPage Today and Oncology Nursing News covered the following tests:

  • Mammography screening for breast cancer (two trials).
  • Prostate-specific antigen (PSA) testing for prostate cancer (four trials).
  • Computed tomography (CT) screening for lung cancer in smokers and former smokers (three trials).
  • Colonoscopy for colorectal cancer (one trial).
  • Sigmoidoscopy for colorectal cancer (four trials).
  • Fecal occult blood (FOB) testing for colorectal cancer (four trials).

As reported in these trials, “colorectal cancer screening with sigmoidoscopy prolonged lifetime by 110 days, while fecal testing and mammography screening did not prolong life,” the researchers wrote. “An extension of 37 days was noted for prostate cancer screening with prostate-specific antigen testing and 107 days with lung cancer screening using computed tomography, but estimates are uncertain.”

The American Cancer Society (ACS) recommends certain types of screening tests to detect cancers and pre-cancers before they can spread, thus improving the chances for survival.

The ACS advises screenings for breast cancer, colorectal cancer, and cervical cancer regardless of whether the individual is considered high risk. Lung cancer screenings are advised for people with a history of smoking. Men who are 45 to 50 or older should discuss the pros and cons of prostate cancer screening with their healthcare providers, the ACS states.

A CNN report about the University of Oslo study noted that the benefits and drawbacks of cancer screening have long been well known to doctors.

“Some positive screening results are false positives, which can lead to unnecessary anxiety as well as additional screening that can be expensive,” CNN reported. “Tests can also give a false negative and thus a false sense of security. Sometimes too, treatment can be unnecessary, resulting in a net harm rather than a net benefit, studies show.”

In their JAMA paper, the University of Oslo researchers wrote, “The critical question is whether the benefits for the few are sufficiently large to warrant the associated harms for many. It is entirely possible that multicancer detection blood tests do save lives and warrant the attendant costs and harms. But we will never know unless we ask,” CNN reported.

Hidden Impact on Cancer Mortality

ACS Chief Scientific Officer William Dahut, MD, told CNN that screenings may have an impact on cancer mortality in ways that might not be apparent from randomized trials. He noted that there’s been a decline in deaths from cervical cancer and prostate cancer since doctors began advising routine testing.

“Cancer screening was never really designed to increase longevity,” Dahut said. “Screenings are really designed to decrease premature deaths from cancer.” For example, “if a person’s life expectancy at birth was 80, a cancer screening may prevent their premature death at 65, but it wouldn’t necessarily mean they’d live to be 90 instead of the predicted 80,” CNN reported.

Dahut told CNN that fully assessing the impact of cancer screenings on life expectancy would require a clinical trial larger than those in the new study, and one that followed patients “for a very long time.”

Others Question the OSLO University Findings

Another expert who questioned the findings was Stephen W. Duffy, MSc, Professor of Cancer Screening at the Queen Mary University of London.

“From its title, one would have expected this paper to be based on analysis of individual lifetime data. However, it is not,” he wrote in a compilation of expert commentary from the UK’s Science Media Center. “The paper’s conclusions are based on arithmetic manipulation of relative rates of all-cause mortality in some of the screening trials. It is therefore difficult to give credence to the claim that screening largely does not extend expected lifetime.”

He also questioned the inclusion of one particular trial in the University of Oslo study—the Canadian National Breast Screening Study—“as there is now public domain evidence of subversion of the randomization in this trial,” he added.

Another expert, Leigh Jackson, PhD, of the University of Exeter in the UK, described the University of Oslo study as “methodologically sound with some limitations which the authors clearly state.”

But he observed that “the focus on 2.1 million individuals is slightly misleading. The study considered many different screening tests and 2.1 million was indeed the total number of included patients, however, no calculation included that many people.”

Jackson also characterized the length of follow-up as a limitation. “This may have limited the amount of data included and also not considering longer follow-up may tend to underestimate the effects of screening,” he said.

This published study—along with the range of credible criticisms offered by other scientists—demonstrates how analysis of huge volumes of data is making it possible to tease out useful new insights. Clinical laboratory managers and pathologists can expect to see other examples of researchers assembling large quantities of data across different areas of medicine. This huge pools of data will be analyzed to determine the effectiveness of many medical procedures that have been performed for years with a belief that they are helpful.

—Stephen Beale

Related Information:

Estimated Lifetime Gained with Cancer Screening Tests: A Meta-analysis of Randomized Clinical Trials

The Future of Cancer Screening—Guided without Conflicts of Interest

Most Cancer Screenings Don’t Extend Life, Study Finds, but Don’t Cancel That Appointment

Does Cancer Screening Actually Extend Lives?

Cancer Screening May Not Extend Patients’ Life Spans

Opinion: Cancer Screenings, Although Not Perfect, Remain Valuable Expert Reaction to Study Estimating Lifetime Gained with Cancer Screening Tests

FDA Grants Marketing Authorization to Diagnostic Tests for Chlamydia and Gonorrhea with At-Home Sample Collection

FDA says the move will make it easier to gain authorization for other clinical laboratory tests to utilize at-home collection kits In another sign of how diagnostic testing is responding to changing consumer preferences, the US Food and Drug Administration (FDA) granted marketing authorization to LetsGetChecked for the company’s Simple 2 test for chlamydia and gonorrhea, which includes at-home collection of samples sent to the test developer’s clinical laboratories in the US and in Ireland....

University of Oxford Researchers Use Spectroscopy and Artificial Intelligence to Create a Blood Test for Chronic Fatigue Syndrome

Spectroscopic technique was 91% accurate in identifying the notoriously difficult-to-diagnose disease suggesting a clinical diagnostic test for CFS may be possible

Most clinical pathologists know that, despite their best efforts, scientists have failed to come up with a reliable clinical laboratory blood test for diagnosing myalgic encephalomyelitis (ME), the condition commonly known as chronic fatigue syndrome (CFS)—at least not one that’s ready for clinical use.

But now an international team of researchers at the University of Oxford has developed an experimental non-invasive test for CFS using a simple blood draw, artificial intelligence (AI), and a spectroscopic technique known as Raman spectroscopy.

The approach uses a laser to identify unique cellular “fingerprints” associated with the disease, according to an Oxford news release.

“When Raman was added to a panel of potentially diagnostic outputs, we improved the ability of the model to identify the ME/CFS patients and controls,” Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University, told Advanced Science News. Morton led the research team along with Wei Huang, PhD, Professor of Biological Engineering at Oxford.

The researchers claim the test is 91% accurate in differentiating between healthy people, disease controls, and ME/CFS patients, and 84% accurate in differentiating between mild, moderate, and severe cases, the new release states.

The researchers published their paper in the journal Advanced Science titled, “Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells.”

Karl Morten, PhD

“This could be a game changer as we are unsure what causes [ME/CFS] and diagnosis occurs perhaps 10 to 20 years after the condition has started to develop,” said Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University. “An early diagnosis might allow us to identify what is going wrong with the potential to fix it before the more long-term degenerative changes are observed.” Though this research may not lead to a simple clinical laboratory blood test for CFS, any non-invasive diagnostic test would enable doctors to help many people. (Photo copyright: Oxford University.)

Need for an ME/CFS Test

The federal Centers for Disease Control and Prevention (CDC) describes ME/CFS as “a serious, long-term illness that affects many body systems,” with symptoms that include severe fatigue and sleep difficulties. Citing an Institute of Medicine (IoM) report, the agency estimates that 836,000 to 2.5 million Americans suffer from the condition but notes that most cases have not been diagnosed.

“One of the difficulties is the complexity of the disease,” said Jonas Bergquist, MD, PhD, Director of the ME/CFS Research Center of Uppsala University in Sweden, told Advanced Science News. “Because it’s a multi-organ disorder, you get symptoms from many different regions of the body with different onsets, though it’s common with post viral syndrome to have different overlapping [symptoms] that disguise the diagnosis.” Bergquist was not involved with the Oxford study.

One key to the Oxford researchers’ technique is the use of multiple artificial intelligence models to analyze the spectral profiles. “These signatures are complex and by eye there are not necessarily clear features that separate ME/CFS patients from other groups,” Morten told Advanced Science News.

“The AI looks at this data and attempts to find features which can separate the groups,” he continued. “Different AI methods find different features in the data. Individually, each method is not that successful at assigning an unknown sample to the correct group. However, when we combine the different methods, we produce a model which can assign the subjects to the different groups very accurately.”

Without a reliable test, “diagnosis of the condition is difficult, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis,” the Oxford press release noted.

But developing such a test has been challenging, Advanced Science News noted.

How Oxford’s Raman Technique Works

Raman spectroscopy uses a laser to determine the “vibrational modes of molecules,” according to the Oxford press release.

“When a laser beam is directed at a cell, some of the scattered photons undergo frequency shifts due to energy exchanges with the cell’s molecular components,” the press release stated. “Raman micro-spectroscopy detects these shifted photons, providing a non-invasive method for single cell analysis. The resulting single cell Raman spectra serve as a unique fingerprint, revealing the intrinsic and biochemical properties and indicating the physiological and metabolic state of the cell.”

The researchers employed the technique on blood samples from 98 subjects, including 61 ME/CFS patients, 16 healthy controls, and 21 controls with multiple sclerosis (MS), Advanced Science reported.

The Oxford scientists focused their attention on peripheral blood mononuclear cells (PBMCs), as previous studies found that these cells showed “reduced energetic function” in ME/CFS patients. “With this evidence, the team proposed that single-cell analysis of PBMCs might reveal differences in the structure and morphology in ME/CFS patients compared to healthy controls and other disease groups such as multiple sclerosis,” the press release states.

Clinical Laboratory Blood Processing and the Oxford Raman Technique

Oxford’s Raman spectroscopic technique “only requires a small blood sample which could be developed as a point-of-care test perhaps from one drop of blood,” the researchers wrote. However, Advanced Science News pointed out that required laser microscopy equipment costs more than $250,000.

In their Advanced Science paper, the researchers note that the test could be made more widely available by transferring blood samples collected by local clinical laboratories to diagnostic centers that have the needed hardware.

“Alternatively, a compact system containing portable Raman instruments could be developed, which would be much cheaper than a standard Raman microscope, and [which] incorporated with microfluidic systems to stream cells through a Raman laser for detection, eliminating the need for lengthy blood sample processing,” the researchers wrote.

They noted that the technique could be adapted to test for other chronic conditions as well, such as MS, fibromyalgia, Lyme disease, and long COVID.

“Our paper is very much a starting point for future research,” Morten told Advanced Science News. “Larger cohorts need to be studied, and if Raman proves useful, we need to think carefully about how a test might be developed.”

Bergquist agreed, stating it’s “not necessarily something you would see in a doctor’s office. It requires a lot of advanced data analysis to use—I still see it as a research methodology. But in the long run, it could be developed into a tool that could be used in a more simplistic way.”

Though a useable diagnostic test may be far off, clinical laboratories should consider how they can aid in ME/CFS research.

—Stephen Beale

Related Information:

First Steps Towards Developing a New Diagnostic Test to Accurately Identify Hallmarks of Chronic Fatigue Syndrome in Blood Cells

First Ever Diagnostic Test for Chronic Fatigue Syndrome Sparks Hope

Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells

Blood Test for Chronic Fatigue Syndrome Found to Be 91% Accurate

Scientists Develop Blood Test for Chronic Fatigue Syndrome

Biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): A Systematic Review

Biomarker for Chronic Fatigue Syndrome Identified

Google DeepMind Says Its New Artificial Intelligence Tool Can Predict Which Genetic Variants Are Likely to Cause Disease

Genetic engineers at the lab used the new tool to generate a catalog of 71 million possible missense variants, classifying 89% as either benign or pathogenic

Genetic engineers continue to use artificial intelligence (AI) and deep learning to develop research tools that have implications for clinical laboratories. The latest development involves Google’s DeepMind artificial intelligence lab which has created an AI tool that, they say, can predict whether a single-letter substitution in DNA—known as a missense variant (aka, missense mutation)—is likely to cause disease.

The Google engineers used their new model—dubbed AlphaMissense—to generate a catalog of 71 million possible missense variants. They were able to classify 89% as likely to be either benign or pathogenic mutations. That compares with just 0.1% that have been classified using conventional methods, according to the DeepMind engineers.

This is yet another example of how Google is investing to develop solutions for healthcare and medical care. In this case, DeepMind might find genetic sequences that are associated with disease or health conditions. In turn, these genetic sequences could eventually become biomarkers that clinical laboratories could use to help physicians make earlier, more accurate diagnoses and allow faster interventions that improve patient care.

The Google engineers published their findings in the journal Science titled, “Accurate Proteome-wide Missense Variant Effect Prediction with AlphaMissense.” They also released the catalog of predictions online for use by other researchers.

Jun Cheng, PhD (left), and Žiga Avsec, PhD (right)

“AI tools that can accurately predict the effect of variants have the power to accelerate research across fields from molecular biology to clinical and statistical genetics,” wrote Google DeepMind engineers Jun Cheng, PhD (left), and Žiga Avsec, PhD (right), in a blog post describing the new tool. Clinical laboratories benefit from the diagnostic biomarkers generated by this type of research. (Photo copyrights: LinkedIn.)

AI’s Effect on Genetic Research

Genetic experiments to identify which mutations cause disease are both costly and time-consuming, Google DeepMind engineers Jun Cheng, PhD, and Žiga Avsec, PhD, wrote in a blog post. However, artificial intelligence sped up that process considerably.

“By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritize resources and accelerate more complex studies,” they noted.

Of all possible 71 million variants, approximately 6%, or four million, have already been seen in humans, they wrote, noting that the average person carries more than 9,000. Most are benign, “but others are pathogenic and can severely disrupt protein function,” causing diseases such as cystic fibrosis, sickle-cell anemia, and cancer.

“A missense variant is a single letter substitution in DNA that results in a different amino acid within a protein,” Cheng and Avsec wrote in the blog post. “If you think of DNA as a language, switching one letter can change a word and alter the meaning of a sentence altogether. In this case, a substitution changes which amino acid is translated, which can affect the function of a protein.”

In the Google DeepMind study, AlphaMissense predicted that 57% of the 71 million variants are “likely benign,” 32% are “likely pathogenic,” and 11% are “uncertain.”

The AlphaMissense model is adapted from an earlier model called AlphaFold which uses amino acid genetic sequences to predict the structure of proteins.

“AlphaMissense was fed data on DNA from humans and closely related primates to learn which missense mutations are common, and therefore probably benign, and which are rare and potentially harmful,” The Guardian reported. “At the same time, the program familiarized itself with the ‘language’ of proteins by studying millions of protein sequences and learning what a ‘healthy’ protein looks like.”

The model assigned each variant a score between 0 and 1 to rate the likelihood of pathogenicity [the potential for a pathogen to cause disease]. “The continuous score allows users to choose a threshold for classifying variants as pathogenic or benign that matches their accuracy requirements,” Avsec and Cheng wrote in their blog post.

However, they also acknowledged that it doesn’t indicate exactly how the variation causes disease.

The engineers cautioned that the predictions in the catalog are not intended for clinical use. Instead, they “should be interpreted with other sources of evidence.” However, “this work has the potential to improve the diagnosis of rare genetic disorders, and help discover new disease-causing genes,” they noted.

Genomics England Sees a Helpful Tool

BBC noted that AlphaMissense has been tested by Genomics England, which works with the UK’s National Health Service. “The new tool is really bringing a new perspective to the data,” Ellen Thomas, PhD, Genomics England’s Deputy Chief Medical Officer, told the BBC. “It will help clinical scientists make sense of genetic data so that it is useful for patients and for their clinical teams.”

AlphaMissense is “a big step forward,” Ewan Birney, PhD, Deputy Director General of the European Molecular Biology Laboratory (EMBL) told the BBC. “It will help clinical researchers prioritize where to look to find areas that could cause disease.”

Other experts, however, who spoke with MIT Technology Review were less enthusiastic.

“DeepMind is being DeepMind,” Insilico Medicine founder/CEO Alex Zhavoronkov, PhD, told the MIT publication. “Amazing on PR and good work on AI.”

Heidi Rehm, PhD, co-director of the Program in Medical and Population Genetics at the Broad Institute, suggested that the DeepMind engineers overstated the certainty of the model’s predictions. She told the publication that she was “disappointed” that they labeled the variants as benign or pathogenic.

“The models are improving, but none are perfect, and they still don’t get you to pathogenic or not,” she said.

“Typically, experts don’t declare a mutation pathogenic until they have real-world data from patients, evidence of inheritance patterns in families, and lab tests—information that’s shared through public websites of variants such as ClinVar,” the MIT article noted.

Is AlphaMissense a Biosecurity Risk?

Although DeepMind has released its catalog of variations, MIT Technology Review notes that the lab isn’t releasing the entire AI model due to what it describes as a “biosecurity risk.”

The concern is that “bad actors” could try using it on non-human species, DeepMind said. But one anonymous expert described the restrictions “as a transparent effort to stop others from quickly deploying the model for their own uses,” the MIT article noted.

And so, genetics research takes a huge step forward thanks to Google DeepMind, artificial intelligence, and deep learning. Clinical laboratories and pathologists may soon have useful new tools that help healthcare provider diagnose diseases. Time will tell. But the developments are certain worth watching.

—Stephen Beale

Related Information:

AlphaFold Is Accelerating Research in Nearly Every Field of Biology

A Catalogue of Genetic Mutations to Help Pinpoint the Cause of Diseases

Accurate Proteome-wide Missense Variant Effect Prediction with AlphaMissense

Google DeepMind AI Speeds Up Search for Disease Genes

DeepMind Is Using AI to Pinpoint the Causes of Genetic Disease

DeepMind’s New AI Can Predict Genetic Diseases

Florida Nurse Practitioner Convicted for Involvement in $200 Million Medicare Fraud Scheme Involving Clinical Laboratory Tests, Other Procedures

Federal prosecutors allege that this nurse practitioner ordered more genetic tests for Medicare beneficiaries than any other provider during 2020

Cases of Medicare fraud involving clinical laboratory testing continue to be prosecuted by the federal Department of Justice. A jury in Miami recently convicted a nurse practitioner (NP) for her role in a massive Medicare fraud scheme for millions of dollars in medically unnecessary genetic testing and durable medical equipment. She faces 75 years in prison when sentenced in December.  

In their indictment, federal prosecutors alleged that from August 2018 through June 2021 Elizabeth Mercedes Hernandez, NP, of Homestead, Florida, worked with more than eight telemedicine and marketing companies to sign “thousands of orders for medically unnecessary orthotic braces and genetic tests, resulting in fraudulent Medicare billings in excess of $200 million,” according to a US Department of Justice (DOJ) news release announcing the conviction.

“Hernandez personally pocketed approximately $1.6 million in the scheme, which she used to purchase expensive cars, jewelry, home renovations, and travel,” the press release noted.

Hernandez was indicted in April 2022 as part of a larger DOJ crackdown on healthcare fraud related to the COVID-19 outbreak.

Luis Quesada

“Throughout the pandemic, we have seen trusted medical professionals orchestrate and carry out egregious crimes against their patients all for financial gain,” said Assistant Director Luis Quesada (above) of the FBI’s Criminal Investigative Division, in a DOJ press release. Clinical laboratory managers would be wise to monitor these Medicare fraud cases. (Photo copyright: Federal Bureau of Investigation.)

Nurse Practitioner Received Kickbacks and Bribes

Federal prosecutors alleged that the scheme involved telemarketing companies that contacted Medicare beneficiaries and persuaded them to request genetic tests and orthotic braces. Hernandez, they said, then signed pre-filled orders, “attesting that she had examined or treated the patients,” according to the DOJ news release.

In many cases, Hernandez had not even spoken with the patients, prosecutors said. “She then billed Medicare as though she were conducting complex office visits with these patients, and routinely billed more than 24 hours of ‘office visits’ in a single day,” according to the news release.

In total, Hernandez submitted fraudulent claims of approximately $119 million for genetic tests, the indictment stated. “In 2020, Hernandez ordered more cancer genetic (CGx) tests for Medicare beneficiaries than any other provider in the nation, including oncologists and geneticists,” according to the news release.

The indictment noted that because CGx tests do not diagnose cancer, Medicare covers them only “in limited circumstances, such as when a beneficiary had cancer and the beneficiary’s treating physician deemed such testing necessary for the beneficiary’s treatment of that cancer. Medicare did not cover CGx testing for beneficiaries who did not have cancer or lacked symptoms of cancer.”

In exchange for signing the orders, Hernandez received kickbacks and bribes from companies that claimed to be in the telemedicine business, the indictment stated.

“These healthcare fraud abuses erode the integrity and trust patients have with those in the healthcare industry … the FBI, working in coordination with our law enforcement partners, will continue to investigate and pursue those who exploit the integrity of the healthcare industry for profit,” said Assistant Director Luis Quesada of the Federal Bureau of Investigation’s Criminal Investigative Division, in the DOJ press release.

Conspirators Took Advantage of COVID-19 Pandemic

Prosecutors alleged that as part of the scheme, she and her co-conspirators took advantage of temporary amendments to rules involving telehealth services—changes that were enacted by Medicare in response to the COVID-19 pandemic.

The indictment noted that prior to the pandemic, Medicare covered expenses for telehealth services only if the beneficiary “was located in a rural or health professional shortage area,” and “was in a practitioner’s office or a specified medical facility—not at a beneficiary’s home.”

But in response to the pandemic, Medicare relaxed the restrictions to allow coverage “even if the beneficiary was not located in a rural area or a health professional shortage area, and even if the telehealth services were furnished to beneficiaries in their home.”

Hernandez was convicted of:

  • One count of conspiracy to commit healthcare fraud and wire fraud.
  • Four counts of healthcare fraud.
  • Three counts of making false statements.

Medscape noted that she was acquitted of two counts of healthcare fraud. The trial lasted six days, Medscape reported.

Hernandez’s sentencing hearing is scheduled for Dec. 14.

Co-Conspirators Plead Guilty

Two other co-conspirators in the case, Leonel Palatnik and Michael Stein, had previously pleaded guilty and received sentences, the Miami Herald reported.

Palatnik was co-owner of Panda Conservation Group LLC, which operated two genetic testing laboratories in Florida. Prosecutors said that Palatnik paid kickbacks to Stein, owner of 1523 Holdings LLC, “in exchange for his work arranging for telemedicine providers to authorize genetic testing orders for Panda’s laboratories,” according to a DOJ press release. The kickbacks were disguised as payments for information technology (IT) and consulting services.

“1523 Holdings then exploited temporary amendments to telehealth restrictions enacted during the pandemic by offering telehealth providers access to Medicare beneficiaries for whom they could bill consultations,” the press release states. “In exchange, these providers agreed to refer beneficiaries to Panda’s laboratories for expensive and medically unnecessary cancer and cardiovascular genetic testing.”

Palatnik pleaded guilty to his role in the kickback scheme in August 2021 and was sentenced to 82 months in prison, a DOJ press release states.

Stein pleaded guilty in April and was sentenced to five years in prison, the Miami Herald reported. He was also ordered to pay $63.3 million in restitution.

These federal cases involving clinical laboratory genetic testing and other tests and medical equipment indicate a commitment on the DOJ’s part to continue cracking down on healthcare fraud.

—Stephen Beale

Related Information:

Nurse Practitioner Convicted of $200M Health Care Fraud Scheme

Florida Nurse Practitioner Convicted in $200 Million Medicare Scheme

Florida Nurse Convicted for Fraudulent Orders Billing Medicare for $200M

South Florida Nurse Convicted of Medicare Scheme for Approving $200 Million in Bogus Products

Justice Department Announces Nationwide Coordinated Law Enforcement Action to Combat COVID-19 Health Care Fraud

Laboratory Owner Pleads Guilty to $73 Million Medicare Kickback Scheme

Laboratory Owner Sentenced to 82 Months in Prison for COVID-19 Kickback Scheme

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