Through population screening, 26.6% of lung cancer cases were identified at risk up to five years earlier using C the Signs, compared to the diagnoses made by physicians.

Since implementing C the Signs, Horizon PCN has consistently outperformed both GM-ICB and NHS England in Cancer Detection Rates (CDR), improving from 55.7% to 62.9%—a 12.9% improvement. In comparison, GM-ICB improved by 0.2%, and NHS England by 1.5% over the same period. C the Signs also improved stage shift, with 60.2% of staged cancers diagnosed at an early stage, compared to 56.5% in Greater Manchester ICB

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Through population screening, 31.8% of prostate cancer cases were identified at risk up to five years earlier by the model compared to traditional physician clinical diagnosis. C the Signs also showed a higher specificity for identifying prostate cancer compared to PSA testing.

Through population screening, 29.4% of patients with colorectal cancer were identified as being at risk up to 5 years earlier by C the Signs compared to diagnoses made by primary care physicians.

Through population screening, 23.0% of patients with pancreatic cancer were diagnosed up to 5 years before the diagnosis made by primary care physicians.

Through population screening, 20.7% of breast cancer patients were detected up to five years earlier using C the Signs, compared to detection through standard physician-led pathways.

In GP practices using C the Signs the cancer detection rate increased from 58.7% to 66.0%, reflecting an increase rate of 12.3% (p <0.05).

Of the patients diagnosed with cancer, 7,257 patients were identified at risk of cancer by C the Signs (99% sensitivity). The platform predicted cancer origin accurately in 9 in 10 patients.

C the Signs conducted 235, 662 risk assessments in 1, 084 GP practices. In total, 13, 585 cancers were diagnosed, a 7.3% conversion rate to cancers diagnosed—20.9% higher than the NHS England, whilst removing 1 in 5 patients from the pathway.

Non-specific symptoms make early detection in ovarian cancer extremely challenging. After implementing C the Signs, early diagnosis of ovarian cancer improved by 53.3 %, highlighting the potential of AI technologies to improve early diagnosis and patient survival.

In areas of high deprivation C the Signs significantly improved cancer detection rates.In practices using C the Signs, cancer detection rates significantly improved from 48.6% to 50.8% (p <0.05), compared to practices not using C the Signs, which saw their cancer detection rate fall from 48.2% to 47.7%.

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