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. 2024 Apr;57(4):668-676.
doi: 10.1007/s11239-024-02960-9. Epub 2024 Mar 14.

Prediction of mortality in acute pulmonary embolism in cancer-associated thrombosis (MAUPE-C): derivation and validation of a multivariable model

Mario Aramberri  1 , Jesús González-Olmedo  2 , Adrián García-Villa  3 , Ane Villanueva  4 , Cristina Castillo Maza  5 , Susana García-Gutiérrez  4 , Carmen Diaz-Pedroche  2
Affiliations

Prediction of mortality in acute pulmonary embolism in cancer-associated thrombosis (MAUPE-C): derivation and validation of a multivariable model

Mario Aramberri et al. J Thromb Thrombolysis. 2024 Apr.

Abstract

Optimal risk stratification of patients with cancer and pulmonary embolism (PE) remains unclear. We constructed a clinical prediction rule (CPR) named 'MAUPE-C' to identify patients with low 30 days mortality. The study retrospectively developed and internally validated a CPR for 30 days mortality in a cohort of patients with cancer and PE (both suspected and unsuspected). Candidate variables were chosen based on the EPIPHANY study, which categorized patients into 3 groups based on symptoms, signs, suspicion and patient setting at PE diagnosis. The performance of 'MAUPE-C' was compared to RIETE and sPESI scores. Univariate analysis confirmed that the presence of symptoms, signs, suspicion and inpatient diagnosis were associated with 30 days mortality. Multivariable logistic regression analysis led to the exclusion of symptoms as predictive variable. 'MAUPE-C' was developed by assigning weights to risk factors related to the β coefficient, yielding a score range of 0 to 4.5. After receiver operating characteristic (ROC) curve analysis, a cutoff point was established at ≤ 1. Prognostic accuracy was good with an area under the curve (AUC) of 0.77 (95% CI 0.71-0.82), outperforming RIETE and sPESI scores in this cohort (AUC of 0.64 [95% CI 0.57-0.71] and 0.57 [95% CI 0.49-0.65], respectively). Forty-five per cent of patients were classified as low risk and experienced a 2.79% 30 days mortality. MAUPE-C has good prognostic accuracy in identifying patients at low risk of 30 days mortality. This CPR could help physicians select patients for early discharge.

Keywords: Cancer; Clinical prediction rule; Prognosis; Pulmonary embolism; Thrombosis.

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References

    1. Mulder FI, Horváth-Puhó E, van Es N et al (2021) Venous thromboembolism in cancer patients: a population-based cohort study. Blood 137(14):1959–1969. https://doi.org/10.1182/blood.2020007338 - DOI - PubMed
    1. Khorana AA, Connolly GC (2009) Assessing risk of venous thromboembolism in the patient with cancer. J Clin Oncol 27(29):4839–4847. https://doi.org/10.1200/JCO.2009.22.3271 - DOI - PubMed - PMC
    1. Douma RA, Kok MGM, Verberne LM, Kamphuisen PW, Büller HR (2010) Incidental venous thromboembolism in cancer patients: prevalence and consequence. Thromb Res 125(6):e306–e309. https://doi.org/10.1016/j.thromres.2010.02.010 - DOI - PubMed
    1. Gosselin MV, Rubin GD, Leung AN, Huang J, Rizk NW (1998) Unsuspected pulmonary embolism: prospective detection on routine helical CT scans. Radiology 208(1):209–215. https://doi.org/10.1148/radiology.208.1.9646815 - DOI - PubMed
    1. Font C, Carmona-Bayonas A, Beato C et al (2017) Clinical features and short-term outcomes of cancer patients with suspected and unsuspected pulmonary embolism: the EPIPHANY study. Eur Respir J 49(1):1600282. https://doi.org/10.1183/13993003.00282-2016 - DOI - PubMed

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