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This paper is in the following e-collection/theme issue:

Reviews on Innovations in Cancer (112) Clinical Information and Decision Making (3863) Decision Support for Health Professionals (2320) Innovations and Technology for Cancer Prevention and Screening (274) Machine Learning (3314) Precision Medicine (453) Cancer Prognosis Models and Machine Learning (142)

Published on in Vol 11 (2025)

This is a member publication of JISC

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70275, first published .
Medical professional in gloves holds blood sample vial for laboratory testing.

Clinical Prediction Models Incorporating Blood Test Trend for Cancer Detection: Systematic Review, Meta-Analysis, and Critical Appraisal

Clinical Prediction Models Incorporating Blood Test Trend for Cancer Detection: Systematic Review, Meta-Analysis, and Critical Appraisal

Authors of this article:

Pradeep S Virdee1 Author Orcid Image ;   Kiana K Collins1 Author Orcid Image ;   Claire Friedemann Smith1 Author Orcid Image ;   Xin Yang2 Author Orcid Image ;   Sufen Zhu1 Author Orcid Image ;   Nia Roberts3 Author Orcid Image ;   Jason L Oke1 Author Orcid Image ;   Clare Bankhead1 Author Orcid Image ;   Rafael Perera1 Author Orcid Image ;   FD Richard Hobbs1 Author Orcid Image ;   Brian D Nicholson1 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Virdee P, Birks J, Holt T, Snell K, Abel G, Nicholson B. Full BLOOD count TRends for colorectal cAnCer deteCtion (BLOODTRACC): external validation of dynamic clinical prediction models for early detection of colorectal cancer in primary care. BMC Cancer 2026;26(1) View
  2. Zhu S, Friedemann Smith C, Collins K, Ziyenge S, Murphy J, de Vere Hunt I, Brubert Z, Roberts N, Morris E, Hobbs R, Nicholson B, Virdee P. The use of blood test trends in cancer detection: a scoping review. Diagnostic and Prognostic Research 2026;10(1) View
  3. Nicholson B, Bankhead C, Zhu S, Oke J, Wright Drakesmith C, Perera R, Hobbs F, Virdee P, Watts E. Blood test trend versus single threshold abnormality to discriminate cancer from non-cancer in patients with unexpected weight loss: A retrospective cohort study. PLOS Medicine 2026;23(9):e1004956 View
  4. Obeagu E. Integrations of Artificial Intelligence to Predict Breast Cancer Risk from Routine Blood Tests: A Narrative Review. Asian Journal of Dental and Health Sciences 2026;6(3):5 View