RESUMO
BACKGROUND AND AIMS: Digital collection of patient-reported outcome measures [PROMs] is largely unexplored as a basis for follow-up for patients with ulcerative colitis [UC]. Our aim was to develop a model to predict the likelihood of escalation of therapy or intervention at an outpatient appointment that may be used to rationalize follow-up. METHODS: TrueColours-IBD is a web-based, real-time, remote monitoring software that allows longitudinal collection of ePROMs. Data for prediction modelling were derived from a Development Cohort, guided by the TRIPOD statement. Logistic regression modelling used ten candidate items to predict escalation of therapy or intervention. An Escalation of Therapy or Intervention [ETI] calculator was developed, and applied in a Validation Cohort at the same centre. RESULTS: The Development Cohort [nâ =â 66] was recruited in 2016 and followed for 6 months [208 appointments]. From ten items, four significant predictors of ETI were identified: SCCAI, IBD Control-8, faecal calprotectin, and platelets. For practicality, a model with only SCCAI and IBD Control-8, both entered remotely by the patient, without the need for faecal calprotectin or blood tests was selected. Between 2018 and 2020, a Validation Cohort of 538 patients [1188 appointments] was examined. A 5% threshold on the ETI calculator correctly identified 343/388 [88%] escalations and 274/484 [57%] non-escalations. CONCLUSIONS: A calculator based on digital, patient-entered data on symptoms and quality of life can predict whether a patient with UC requires escalation of therapy or intervention at an outpatient appointment. This may be used to streamline outpatient appointments for patients with UC.
Assuntos
Colite Ulcerativa , Humanos , Colite Ulcerativa/diagnóstico , Colite Ulcerativa/terapia , Qualidade de Vida , Complexo Antígeno L1 LeucocitárioRESUMO
BACKGROUND: Patients with cancer are particularly susceptible to SARS-CoV-2 infection. The systemic inflammatory response is a pathogenic mechanism shared by cancer progression and COVID-19. We investigated systemic inflammation as a driver of severity and mortality from COVID-19, evaluating the prognostic role of commonly used inflammatory indices in SARS-CoV-2-infected patients with cancer accrued to the OnCovid study. METHODS: In a multicenter cohort of SARS-CoV-2-infected patients with cancer in Europe, we evaluated dynamic changes in neutrophil:lymphocyte ratio (NLR); platelet:lymphocyte ratio (PLR); Prognostic Nutritional Index (PNI), renamed the OnCovid Inflammatory Score (OIS); modified Glasgow Prognostic Score (mGPS); and Prognostic Index (PI) in relation to oncological and COVID-19 infection features, testing their prognostic potential in independent training (n=529) and validation (n=542) sets. RESULTS: We evaluated 1071 eligible patients, of which 625 (58.3%) were men, and 420 were patients with malignancy in advanced stage (39.2%), most commonly genitourinary (n=216, 20.2%). 844 (78.8%) had ≥1 comorbidity and 754 (70.4%) had ≥1 COVID-19 complication. NLR, OIS, and mGPS worsened at COVID-19 diagnosis compared with pre-COVID-19 measurement (p<0.01), recovering in survivors to pre-COVID-19 levels. Patients in poorer risk categories for each index except the PLR exhibited higher mortality rates (p<0.001) and shorter median overall survival in the training and validation sets (p<0.01). Multivariable analyses revealed the OIS to be most independently predictive of survival (validation set HR 2.48, 95% CI 1.47 to 4.20, p=0.001; adjusted concordance index score 0.611). CONCLUSIONS: Systemic inflammation is a validated prognostic domain in SARS-CoV-2-infected patients with cancer and can be used as a bedside predictor of adverse outcome. Lymphocytopenia and hypoalbuminemia as computed by the OIS are independently predictive of severe COVID-19, supporting their use for risk stratification. Reversal of the COVID-19-induced proinflammatory state is a putative therapeutic strategy in patients with cancer.
