A novel multivariate cancer risk score model demonstrated 60% sensitivity at 98.5% specificity. These findings demonstrate that a blood-based cancer screening assay with a novel risk score model may be a viable method for detecting cancer in asymptomatic individuals, especially in populations at high risk for cancer. The study by Mao et was presented at ASCO Breakthrough: A Global Summit for Oncology Innovators (Abstract 45).

Although advances in cancer therapy are resulting in more people surviving the disease, cancer remains the second-leading cause of death globally and caused an estimated 9.6 million deaths worldwide in 2018. Detecting and treating cancer at an early stage—when the prognosis is better—can reduce both cancer mortality and treatment costs, according to the World Health Organization.

“Taken together, these data demonstrate the multivariate cancer risk score model holds promise for detecting cancer in asymptomatic individuals, particularly in the populations at high risk of cancer."

— Mao et al

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Study Details

The researchers used a novel multivariate cancer risk score model that interrogates shallow whole-genome sequencing data from cell-free DNA (cfDNA) and protein markers from a single blood draw. In their prospective clinical study of 76 patients with stage I through IV cancer and 152 healthy individuals, the multivariate cancer risk score model demonstrated 60% sensitivity at 98.5% specificity.

To validate the clinical utility of the multivariate cancer risk score model in the detection of cancer, the researchers collated data from a previous study of occult maternal malignancies from 1.93 million pregnant women undergoing noninvasive prenatal testing between 2016 and 2017. The researchers found that 466 out of the 639 pregnant women who tested positive for multiple chromosomal aneuploidies in the initial noninvasive prenatal test had undergone the protein markers test. Among the 466 subjects, 39 maternal malignant cancer cases were diagnosed with a median follow-up of 399 days by imaging and histology.

The patients with cancer presented a wide spectrum of cancer types, the most frequent being breast cancer (10 cases), liver cancer (8 cases), and lymphoma (8 cases), at disease stages II to IV. This subgroup of 466 subjects was selected as an independent validation cohort for the study. Through this new method, the researchers analyzed shallow whole-genome sequencing and proteins data. The multivariate cancer risk score model allowed 28 of the 39 (71.8%) cancer cases to be identified, with a positive predictive value of 73.7% and specificity of 97.7%.

“Taken together, these data demonstrate the multivariate cancer risk score model holds promise for detecting cancer in asymptomatic individuals, particularly in the populations at high risk of cancer,” concluded the study authors.

Disclosure: This research was sponsored by Seekin Inc. For full disclosures of the study authors, visit coi.asco.org.