Blood Test to Identify Individuals for Lung Cancer Screening

Kristin Jenkins

July 16, 2018

A relatively simple blood test could refine current lung cancer screening eligibility criteria and help identify more high-risk individuals for low-dose CT (LDCT), according to an international research group.

The blood test measures levels of four circulating proteins. The measures are then used to calculate a lung cancer risk score.

A blinded external validation study found that this test discriminated more accurately between future cases of lung cancer and control cases than a traditional smoking history–based risk model and current US screening criteria.

The US Preventive Services Task Force (USPSTF) currently recommends LDCT screening for lung cancer in ever-smokers with a 30 pack-year history who have not smoked for up to 15 years, the researchers note. However, individuals eligible for screening represent fewer than 50% of incident lung cancer cases.

"Biomarker-based risk profiling has the potential to improve eligibility criteria for lung cancer screening," say the researchers, from the University of Texas MD Anderson Cancer Center, Houston, and the International Agency for Research on Cancer (IARC), Lyons, France.

"There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases," the study authors write. "This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening."

A report on their collaborative study, which was part of the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Consortium for Early Detection of Lung Cancer, was published online July 12 in JAMA Oncology.

Study Details

The biomarker-based risk assessment tool consists of a panel of four proteins: cancer antigen 125; carcinoembryonic antigen; cytokeratin-19 fragment; and the precursor of surfactant protein B.

The researchers developed it using prediagnostic blood samples from US patients at high risk for lung cancer. These included 108 ever-smoking patients for whom lung cancer had been diagnosed within 1 year after blood collection, and 216 smoking-matched control patients from the Carotene and Retinol Efficacy Trial (CARET) cohort.

To validate the tool, absolute risk estimates were used for 63 ever-smoking patients for whom lung cancer had been diagnosed within 1 year after blood collection. These patients were matched with 90 control patients from the European Prospective Investigation Into Cancer and Nutrition (EPIC) study and the Northern Sweden Health and Disease Study (NSHDS). Mean age of the patients was 58 years; 69% were men.

The researchers then combined the biomarker score with data on smoking exposure. Using this integrated risk prediction model, they identified 40 of the 63 incident lung cancer cases, or 63% of future lung cancer cases, for LDCT screening. This corresponded to a sensitivity of 0.63.

By comparison, 26 of 62 incident lung cancer cases, or 42% of future lung cancer cases, were identified for LDCT screening using the USPSTF eligibility criteria. This corresponded to a sensitivity of 0.42.

"We feel that these results represent an important stepping stone in improving lung cancer screening using biomarkers," Mattias Johansson, PhD, of the IARC, who is a principal study investigator, told Medscape Medical News.

Johansson said the research will continue to further evaluate these and other risk biomarkers in larger international cohorts. "In Europe, we would like to see implementation studies that evaluate the practical and financial implications of using such a biomarker test for lung cancer screening," he said.

He added that a clinical test based on these results is "still a few years away."

In a statement issued by the IARC, Paul Brennan, PhD, head of the section of genetics at the IARC, who is one of the study's principal investigators, said this is "the first study to systematically demonstrate that a panel of protein markers can improve the identification of future lung cancer cases."

The results also suggest that the integrated risk prediction model could be used to reduce a greater number of false positive screening results than the current smoking model (17% vs 5%, respectively) without affecting the test's ability to predict future lung cancer cases. "These improvements in sensitivity and specificity were consistently observed across each evaluated stratum," the study authors say.

In addition, the study showed that the sensitivity of the integrated risk prediction model was more modest in cases diagnosed up to 2 years after blood draw when compared to the smoking model. This suggests that "an annual biomarker test may be necessary in a screening program," the investigators point out.

The population that would benefit most from a biomarker test prior to LDCT screening still needs to be identified, they add.

The study was funded by the National Cancer Institute and the National Cancer Institute Early Detection Research Network, Fondation ARC Pour la Recherche Sur le Cancer and INCa, the MD Anderson Lung Cancer Moon Shot Program, the Lyda Hill Foundation, the Canary Foundation, the LUNGevity Foundation, and the S. Rubenstein Family Foundation. The study authors have disclosed no relevant financial relationships.

JAMA Oncol. Published online July 12, 2018. Abstract

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