Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a cohort study
Authors: Staessen Jan A. , Wendt Ralph , Yu Yu-Ling , Kalbitz Sven , Thijs Lutgarde , Siwy Justyna , Raad Julia , Metzger Jochen , Neuhaus Barbara , Papkalla Armin , von der Leyen Heiko , Mebazaa Alexandre , Dudoignon Emmanuel , Spasovski Goce , Milenkova Mimoza , Canevska-Taneska Aleksandra , Psichogiou Mina , Rajzer Marek W. , Fulawka Lukasz , Dzitkowska-Zabielska Magdalena , Weiss Guenter , Feldt Torsten , Stegemann Miriam , Normark Johan , Zoufaly Alexander , Schmiedel Stefan , Seilmaier Michael , Rumpf Benedikt , Banasik Mirosław , Krajewska Magdalena , Catanese Lorenzo , Rupprecht Harald , Czerwienska Beata , Peters Björn , Nilsson Åsa , Rothfuss Katja , Lübbert Christoph , Mischak Harald , Beige Joachim ,   the CRIT-Cov-U investigators
Published: January 2022

Background

The SARS-CoV-2 pandemic remains a worldwide challenge. The CRIT-Cov-U pilot study generated a urinary proteomic biomarker consisting of 50 peptides (COV50), which predicted death and disease progression. Following the interim analysis demanded by the German government, the full dataset was analysed to consolidate findings and propose clinical applications.

Methods

In eight European countries, 1012 adults with PCR-confirmed COVID-19 were followed up for death and progression along the 8-point WHO scale. Capillary electrophoresis coupled with mass spectrometry was used for urinary proteomic profiling. Statistical methods included logistic regression, receiver operating curve analysis with comparison of the area under curve (AUC) between nested models. Hospitalisation costs were derived from the care facility corresponding with the Markov chain probability of reaching WHO scores ranging from 3 to 8 and flat-rate hospitalistion costs standardised across countries.

Findings

The entry WHO scores were 1-3, 4-5 and 6 in 445 (44·0%), 529 (52·3%), and 38 (3·8%) patients, of whom 119 died and 271 progressed. The standardised odds ratios associated with COV50 for death were 2·44 (95% CI, 2·05-2·92) unadjusted and 1·67 (1·34-2·07) if adjusted for sex, age, body mass index, comorbidities and baseline WHO score, and 1·79 (1·60-2·01) and 1·63 (1·40-1·90), respectively, for disease progression (p<0·0001 for all). The predictive accuracy of optimised COV50 thresholds were 74·4% (95% CI, 71·6-77·1) for mortality (threshold 0·47) and 67·4% (64·1-70·3) for disease progression (threshold 0·04). On top of covariables and the baseline WHO score, these thresholds improved AUCs from 0·835 to 0·853 (p=0·0331) and from 0·697 to 0·730 (p=0·0008) for death and progression, respectively. Of 196 ambulatory patients, 194 (99·0%) did not reach the 0·04 threshold. Earlier intervention guided by high-risk COV50 levels should reduce hospital days with cost reductions expressed per 1000 patient-days ranging from M€ 1·208 (95% percentile interval, 1·035-1·406) at low risk (COV50 <0·04) to M€ 4·503 (4·107-4·864) at high risk (COV50 ≥0·04 and age ≥65 years).

Interpretation

The urinary proteomic COV50 marker is accurate in predicting adverse COVID-19 outcomes. Even in mild-to-moderate PCR-confirmed infections (WHO scores 1-5), the 0·04 threshold justifies earlier drug treatment, thereby reducing hospitalisation days and costs.

Funding

German Federal Ministry of Health acting upon a decree from the German Federal Parliament.