Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study. Issue 10 (October 2022)

• Record Type: Journal Article
• 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; Salgueira Lazo, Mercedes; Psichogiou, Mina; Rajzer, Marek W; Fuławka, Łukasz; 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 D; Czerwieńska, Beata; Peters, Björn; Nilsson, Åsa; Rothfuss, Katja; Lübbert, Christoph; Mischak, Harald; Beige, Joachim; 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; Lazo, Mercedes Salgueira; 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; Ermisch, Jörg; Kellner, Nils; Peruth-Stutzmann, Lydia; Schroth, Stefanie; Schmidt, Jonathan; Schmidt, Ulrike; Breuer, Daniel; Abeud, Fariza; Fournier, Marie-Celine; Louadah, Badr; Molas, Rocio; Rojas, Fraile Loreto; García, Fabiola Alonso; Sánchez, Isabel Garcia; Hrom, Ioana Cezara; Więczek., Andrzej; Schwab, Matthias; K Asayama, Kei; Hansen, Tine W; Maestre, Gladys E; Basoulis, Dimitrios; Karamanakos., Georgios; Lis, Pawel; Olszanecka, Agnieszka; Bellmann-Weiler, Rosa; Lanser, Lucas; Edin, Alicia; Forsell, Matthias NE; Stegmayr, Bernd; Jensen, Björn-Erik Ole; Orth, Hans-Martin; Borstel, Sylke; Mikolajewska, Agata; Hecking, Manfred; Schmölz, Lukas; Hoffmann, Michał; Narkiewicz, Krzysztof; Matera-Witkiewicz, Agnieszka; Zachciał, Justyna; Litwin, Monika; Marciniak, Patrycja;
• Is Part Of: Lancet. Volume 4:Issue 10(2022)
• Page Start: e727
• Page End: e737
• Publication Date: 2022-10
• Subjects: Medical care -- Data processing -- Periodicals; Medical care -- Information technology -- Periodicals; Medical informatics -- Periodicals; 610.285
• DOI: 10.1016/S2589-7500(22)00150-9
• Languages: English
• ISSNs: 2589-7500

Abstract

Summary: Background: The SARS-CoV-2 pandemic is 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 from SARS-CoV-2. After the interim analysis presented for the German Government, here, we aimed to analyse the full dataset to consolidate the findings and propose potential clinical applications of this biomarker. Methods: CRIT-CoV-U was a prospective multicentre cohort study. In eight European countries (Austria, France, Germany, Greece, North Macedonia, Poland, Spain, and Sweden), 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 and receiver operating characteristic curve analysis with a 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 hospitalisation costs adjusted for the gross per capita domestic product of each country. Findings: From June 30 to Nov 19, 2020, 228 participants were recruited, and from April 30, 2020, to April 14, 2021, 784 participants were recruited, resulting in a total of 1012 participants. The entry WHO scores were 1–3 in 445 (44%) participants, 4–5 in 529 (52%) participants, and 6 in 38 (4%) participants; and of all participants, 119 died and 271 had disease progression. The odds ratio (OR) associated with COV50 in all 1012 participants for death was 2·44 (95% CI 2·05–2·92) unadjusted and 1·67 (1·34–2·07) when adjusted for sex, age, BMI, comorbidities, and baseline WHO score; and for disease progression, the OR was 1·79 (1·60–2·01) when unadjusted and 1·63 (1·41–1·91) when adjusted (p<0·0001 for all). The predictive accuracy of the optimised COV50 thresholds was 74·4% (71·6–77·1%) for mortality (threshold 0·47) and 67·4% (64·4–70·3%) for disease progression (threshold 0·04). When adjusted for covariables and the baseline WHO score, these thresholds improved AUCs from 0·835 to 0·853 (p=0·033) for death and from 0·697 to 0·730 (p=0·0008) for progression. Of 196 participants who received ambulatory care, 194 (99%) did not reach the 0·04 threshold. The cost reductions associated with 1 day less hospitalisation per 1000 participants were million Euro (M€) 0·887 (5–95% percentile interval 0·730–1·039) in participants at a low risk (COV50 <0·04) and M€2·098 (1·839-2·365) in participants at a high risk (COV50 ≥0·04). Interpretation: The urinary proteomic COV50 marker might be predictive of adverse COVID-19 outcomes. Even in people with mild-to-moderate PCR-confirmed infections (WHO scores 1–4), the 0·04 COV50 threshold justifies earlier drug treatment, thereby potentially reducing the number of days in hospital and associated costs. Funding: German Federal Ministry of Health.