![]() This is true for both clinical characteristics and molecular‐based biomarkers. ![]() As a result, many physicians require patients to have one or more of these characteristics to be considered good candidates for treatment with EGFR inhibitors.īefore any factor is included in guidelines for treatment selection, it is important to distinguish its prognostic effects from its ability to predict a differential clinical benefit from the specific treatment. It has also been observed that patients whose tumors have activating mutations in the EGFR tyrosine kinase domain also are more likely to have tumor responses, and that these mutations are more frequent among Asians, nonsmokers, women, and patients with adenocarcinoma ( Hsieh et al., 2005 Tsao et al., 2006 Matsuo et al., 2007). It has been observed that women with non‐small cell lung cancer (NSCLC), patients with adenocarcinoma, and never smokers are more likely to have major objective responses when treated with EGFR inhibitors than other patients ( Birnbaum and Ready, 2005 Shah et al., 2005 Goodin, 2006). Therefore, patients and their physicians are turning to clinical characteristics to make treatment decisions. None of the currently available assays accurately identifies patients who will definitely not benefit from EGFR inhibitors, and none accurately identifies patients who will definitely benefit from these treatments. Unfortunately, efforts to develop and validate the clinical utility of companion, tumor‐based assays that measure abnormalities in the EGF pathway (e.g., protein overexpression by immunohistochemistry, gene copy number by in situ fluorescence hybridization, gene mutation by sequencing) have been disappointing. Recently, several agents that inhibit the epidermal growth factor receptor (EGFR) or the EGF pathway have been evaluated in clinical trials. Targeted therapies provide opportunities for identifying subsets of patients who will derive the most benefit, providing that the target can accurately be measured in patients and that the patient's tumor depends on activity of the target for its growth and survival. ![]() Prospero registration number: CRD42020178802. Identified prognostic factors can help clinicians and policy makers in tailoring management strategies for patients with COVID-19 infectious disease while researchers can utilise our findings to develop multivariable prognostic models that could eventually facilitate decision-making and improve patient important outcomes. We included 207 studies and found high or moderate certainty that the following 49 variables provide valuable prognostic information on mortality and/or severe disease in patients with COVID-19 infectious disease: Demographic factors (age, male sex, smoking), patient history factors (comorbidities, cerebrovascular disease, chronic obstructive pulmonary disease, chronic kidney disease, cardiovascular disease, cardiac arrhythmia, arterial hypertension, diabetes, dementia, cancer and dyslipidemia), physical examination factors (respiratory failure, low blood pressure, hypoxemia, tachycardia, dyspnea, anorexia, tachypnea, haemoptysis, abdominal pain, fatigue, fever and myalgia or arthralgia), laboratory factors (high blood procalcitonin, myocardial injury markers, high blood White Blood Cell count (WBC), high blood lactate, low blood platelet count, plasma creatinine increase, high blood D-dimer, high blood lactate dehydrogenase (LDH), high blood C-reactive protein (CRP), decrease in lymphocyte count, high blood aspartate aminotransferase (AST), decrease in blood albumin, high blood interleukin-6 (IL-6), high blood neutrophil count, high blood B-type natriuretic peptide (BNP), high blood urea nitrogen (BUN), high blood creatine kinase (CK), high blood bilirubin and high erythrocyte sedimentation rate (ESR)), radiological factors (consolidative infiltrate and pleural effusion) and high SOFA score (sequential organ failure assessment score). We performed meta-analyses and used GRADE to assess the certainty of the evidence for each prognostic factor and outcome. Reviewers working in pairs independently screened studies for eligibility, extracted data and assessed the risk of bias. We included studies that assessed patients with confirmed or suspected SARS-CoV-2 infectious disease and examined one or more prognostic factors for mortality or disease severity. No study design, publication status or language restriction were applied. The searches covered the period from the inception date of each database until April 28, 2020. We conducted highly sensitive searches in PubMed/MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL) and Embase. The objective of our systematic review is to identify prognostic factors that may be used in decision-making related to the care of patients infected with COVID-19.
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