OverC®'s clinical performance was evaluated in THUNDER, the first prospective, independent and blinded validation study of multi-cancer early detection conducted in China (NCT04820868). This article compiles the study design, results and references.
Study Design
- Type: prospective, independent, blinded validation study.
- Registration: ClinicalTrials.gov NCT04820868.
- Objective: validating sensitivity and specificity of cfDNA methylation-based detection across six cancer types (lung, esophageal, colorectal, liver, pancreatic, ovarian); measuring tissue-of-origin prediction accuracy when a signal is detected.
- Index test: the OverC® protocol with the ELSA-seq platform and BRMERMAID® algorithm.
Key Results
| Metric | Result |
|---|---|
| Sensitivity (six cancer types) | 69.1% |
| Specificity | 98.9% |
| Tissue-of-origin accuracy (top prediction) | 83.2% |
| Tissue-of-origin accuracy (top two predictions) | 91.7% |
Interpretation
- The high specificity (98.9%) limits the burden of unnecessary work-up in a screening context; the sensitivity (69.1%) shows it is insufficient as standalone screening — the test does not replace guideline screening.
- Tissue-of-origin prediction (83.2% / 91.7%) targets the subsequent diagnostic work-up when a signal is positive; a definitive diagnosis is made through clinical examination and diagnostic methods.
- Study results belong to the study population; individual patient interpretation is done through physician evaluation.
References
- Q Gao et al. Ann Oncol. 2023 May;34(5):486-495. (THUNDER — development and independent validation studies).
- Liang N et al. Nat Biomed Eng. 2021 Jun;5(6):586-599. (ELSA-seq).
- Rongshou Zheng et al. J Natl Cancer Cent. 2022 Mar;5(38):1-9. (China cancer incidence/mortality data).
- W. Liang et al. Ann Oncol. 2022 Sep;33:S1414. (Real-world lung screening data).
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