Elsevier

Annals of Oncology

Volume 32, Issue 9, September 2021, Pages 1167-1177
Annals of Oncology

Original Article
Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set

https://doi.org/10.1016/j.annonc.2021.05.806Get rights and content
Under a Creative Commons license
open access

Highlights

  • In a validation study, an MCED test identified a diversity of cancer signals with high specificity.

  • The MCED test predicted the origin of the cancer signal with high accuracy across multiple cancer types.

  • Results support the use of this MCED test on a population scale as a complement to existing single-cancer screening tests.

Background

A multi-cancer early detection (MCED) test used to complement existing screening could increase the number of cancers detected through population screening, potentially improving clinical outcomes. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was a prospective, case-controlled, observational study and demonstrated that a blood-based MCED test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin (CSO) with high accuracy. The objective of this third and final CCGA substudy was to validate an MCED test version further refined for use as a screening tool.

Patients and methods

This pre-specified substudy included 4077 participants in an independent validation set (cancer: n = 2823; non-cancer: n = 1254, non-cancer status confirmed at year-one follow-up). Specificity, sensitivity, and CSO prediction accuracy were measured.

Results

Specificity for cancer signal detection was 99.5% [95% confidence interval (CI): 99.0% to 99.8%]. Overall sensitivity for cancer signal detection was 51.5% (49.6% to 53.3%); sensitivity increased with stage [stage I: 16.8% (14.5% to 19.5%), stage II: 40.4% (36.8% to 44.1%), stage III: 77.0% (73.4% to 80.3%), stage IV: 90.1% (87.5% to 92.2%)]. Stage I-III sensitivity was 67.6% (64.4% to 70.6%) in 12 pre-specified cancers that account for approximately two-thirds of annual USA cancer deaths and was 40.7% (38.7% to 42.9%) in all cancers. Cancer signals were detected across >50 cancer types. Overall accuracy of CSO prediction in true positives was 88.7% (87.0% to 90.2%).

Conclusion

In this pre-specified, large-scale, clinical validation substudy, the MCED test demonstrated high specificity and accuracy of CSO prediction and detected cancer signals across a wide diversity of cancers. These results support the feasibility of this blood-based MCED test as a complement to existing single-cancer screening tests.

Clinical trial number

NCT02889978.

Key words

cancer
multi-cancer early detection
liquid biopsy
methylation
cell-free nucleic acids
machine learning

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