Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data.

doi:10.1038/s41591-024-03398-5

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Article

Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data.

Nature medicine - 1 Mar 2025

Yoo Seong-Keun, Fitzgerald Conall W, Cho Byuri Angela, Fitzgerald Bailey G, Han Catherine, Koh Elizabeth S, Pandey Abhinav, Sfreddo Hannah, Crowley Fionnuala, Korostin Michelle Rudshteyn, Debnath Neha, Leyfman Yan, Valero Cristina, Lee Mark, Vos Joris L, Lee Andrew Sangho, Zhao Karena, Lam Stanley, Olumuyide Ezekiel, Kuo Fengshen, Wilson Eric A, Hamon Pauline, Hennequin Clotilde, Saffern Miriam, Vuong Lynda, Hakimi A Ari, Brown Brian, Merad Miriam, Gnjatic Sacha, Bhardwaj Nina, Galsky Matthew D, Schadt Eric E, Samstein Robert M, Marron Thomas U, Gönen Mithat, Morris Luc G T, Chowell Diego

Abstract excerpt

Predicting whether a patient with cancer will benefit from immune checkpoint inhibitors (ICIs) without resorting to advanced genomic or immunologic assays is an important clinical need. To address this, we developed and evaluated SCORPIO, a machine learning system that utilizes routine blood tests (complete blood count and comprehensive metabolic profile) alongside clinical characteristics from 9,745 ICI-treated...

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Identifiers

PMID: 39762425
DOI: 10.1038/s41591-024-03398-5
PMCID: PMC11922749

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