Background: First-line treatment for patients with non-small cell lung cancer (NSCLC) with a sensitizing epidermal growth factor receptor (EGFR) mutation is a tyrosine kinase inhibitor (TKI). Despite higher response rates and prolonged progression free survival (PFS) compared with platinum doublet chemotherapy, a subset of these patients do not receive prolonged benefit from these agents. We investigate if the neutrophil-to-lymphocyte ratio (NLR) and other markers of cachexia and chronic inflammation correlate with worse outcomes in these patients. Methods: This study is a retrospective review of 137 patients with advanced EGFR-mutated NSCLC treated with TKIs at Rush University Medical Center and University of Chicago Medicine from August 2011 to July 2019, with outcomes followed through July 2020. The predictive value of NLR and body mass index (BMI) was assessed at the start of therapy, and after 6 and 12 weeks of treatment by univariable and multivariable analyses. Results: On univariable analysis, NLR ≥ 5 or higher NLR on a continuous scale were both associated with significantly worse PFS and overall survival (OS) at treatment initiation, and after 6 or 12 weeks of treatment. On multivariable analysis, NLR ≥ 5 was associated with increased risk of death at 12 weeks of therapy (HR 3.002, 95% CI 1.282–7.029, p = 0.011), as was higher NLR on a continuous scale (HR 1.231, 95% CI 1.063–1.425, p = 0.0054). There was no difference in PFS and OS and amongst BMI categories though number of disease sites and Eastern Cooperative Oncology Group (ECOG) performance status was associated with worse PFS and OS. Conclusions: Patients with NLR ≥ 5 have a worse median PFS and median OS than patients with NLR < 5. NLR may have value as a predictive biomarker and may be useful for selecting patients for therapy intensification in the front-line setting either at diagnosis or after 12 weeks on therapy. NLR needs to be validated prospectively.

Objectives: Previous studies have not evaluated the utility of obtaining chest radiographs (CXR) in patients with acute asthma exacerbation reporting chest pain. The aims of this study were to evaluate the symptom of chest pain as a predictor for clinicians obtaining a CXR in these patients and to evaluate chest pain as a predictor of a positive CXR finding.Methods: This was a retrospective chart review of patients, ages 2 to 18 years, presenting for acute asthma exacerbation to the emergency department from August 1, 2014, to March 31, 2016. Data collected included demographics, clinical data, provider type, and CXR results. Chest radiographs were classified as positive if they showed evidence of pneumonia, pneumothorax, or pneumomediastinum. Multivariate logistic regression models were developed with dependent variables of "obtaining a CXR" and "a positive CXR finding."Results: Seven hundred ninety-three subjects were included in the study.Two hundred thirty-one (29.1%) reported chest pain. Chest radiographs were obtained in 184 patients (23.2%). Of those, 74 patients (40.2%) had chest pain and 21 (11.4%) had a positive CXR. Providers were more likely to obtain CXRs in patients who reported chest pain (odds ratio = 2.2 [95% confidence interval = 1.5-3.2]). Patients reporting chest pain were more likely to have a positive CXR although this difference was not statistically significant (odds ratio = 2.0 [95% confidence interval = 0.7-5.6]).Conclusions: Providers are more likely to obtain CXRs in asthmatic patients complaining of chest pain; however, these CXRs infrequently yield positive findings. This further supports limiting the use of chest radiography in patients with acute asthma exacerbation.

We present a unique case of a patient with a long-standing history of indolent chronic lymphocytic leukaemia (CLL) who suddenly developed autoimmune haemolytic anaemia after starting immune checkpoint inhibitor therapy for bladder cancer. He had no clear indication to start CLL-directed treatment based on current clinical practice guidelines; however, targeted treatment of CLL with ibrutinib proved to be effective in treating the haemolytic anaemia.

Background Accurate diagnostic biomarker testing is crucial to treatment decisions in breast cancer. Biomarker testing is performed on core needle biopsies (CNB) and is often repeated in the surgical specimen (SS) after resection. As differences between CNB and SS testing may alter treatment decisions, we evaluated concordance between CNB and SS as well as associated changes in treatment and clinical outcomes. Methods We performed a retrospective analysis of breast cancer patients at our institution between January 2010 and May 2020. Concordance between CNB and SS was assessed for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). Survival in patients, including recurrence, metastatic recurrence, and death, were assessed using chi‐squared likelihood ratio. Results In total, 961 patients met eligibility criteria. Concordance, minor discordance, total concordance (concordance plus minor discordance), and major discordance between CNB and SS were reported for ER (87.7%, 9.2%, 90.8%, and 2.9%), PR (58.1%, 29.1%, 87.2%, and 12.8%), and HER2 IHC (52.5%, 20.9%, 73.4%, 26.6%), respectively. HER2 FISH concordance and major discordance were 58.5% and 1.2%, respectively. Of major discordance, ER (48.2%, p < 0.001) and HER2 FISH (50.0%) led to more management changes than HER2 IHC (2.4%, p = 0.04) and PR (1.6%, p = 0.10). Patients with ER major discordance had increased risk of death (6.7% concordance vs. 22.2% major discordance, p = 0.004). Conclusion Overall, retesting ER and HER2 was more clinically beneficial than retesting PR. To aid decision‐making and minimize healthcare costs, we propose patient‐centered guidelines on retesting biomarker profiles.

N.K.Y., P.C., & P.R.Y. contributed equally to this study Introduction: Many studies have concluded that active cancer patients infected with SARS-CoV-2 have a more complicated infection course and worse outcomes compared to the general patient population hospitalized with COVID-19. However, little evidence exists whether having a history of cancer plays a significant role in these observations. Patients with hematologic malignancy (HM) might have worse prognosis among all cancer patients but the reason remains unclear. Our objective is to evaluate outcomes and severity of COVID-19 in patients with Hematological Malignancy (HM) versus Solid-tumors (ST) in different clinical settings and also compare these outcomes within the group of patients with hematological malignancies. Methods: This retrospective study examines risk factors and outcomes of COVID-19 in patients with a history of cancer and laboratory-confirmed COVID-19 diagnosis between March 1 st, 2020, and December 31 st, 2020, at Rush University Medical Center, one of the largest COVID-19 tertiary care hospitals in Chicago. Baseline characteristics, malignancy type and types of cancer treatment within the last 30 days were recorded. Measures of COVID-19 severity included hospital admission versus outpatient care, use of oxygen, intensive care unit (ICU) admission, and mechanical ventilation. The primary outcome was death. Statistical analysis was conducted using optimal discriminant analysis, a non-parametric exact machine-learning algorithm which identifies the relationship between independent and dependent variables that maximizes model predictive accuracy adjusted to remove the effect of chance. Analysis was performed separately for each attribute using the entire sample ("training" analysis), then one-sample jackknife analysis was conducted to estimate cross-generalizability of findings using the model to classify an independent random sample. Results: 378 total patients with a history of cancer tested positive for COVID-19 within the time frame of the study. Of these, 294 (78%) patients had ST malignancy and 84 (22%) patients had HM. Characteristics and outcomes are summarized in Table 1. ST patients were marginally older than HM patients (p&lt;0.025). A significantly greater proportion of HM patients were male (p&lt;0.0023). HM and ST patients did not differ with respect to percentage receiving active cancer treatment (p&lt;0.81). Compared to ST patients, more HM patients had received corticosteroids in the 30 days prior to COVID-19 diagnosis (p&lt;0.017), had higher rates of hospitalization (p&lt;0.0013) and ICU requirement (p&lt;0.0001) with a significantly longer length of ICU stay (p&lt;0.0036). Compared to ST patients, HM patients also required oxygen (p&lt;0.002) and mechanical ventilation (p&lt;0.0005) more often and had a 3.88-fold statistically higher death rate (OR 3.88 [95% CI 1.62-9.29] p&lt;0.003). Patients with HM are categorized by disease subtype and summarized in Table 2. The case fatality rate from COVID-19 was 33.3% for patients with myeloproliferative neoplasms/myelodysplastic syndromes (MPN/MDS), 21.4% for patients with chronic lymphocytic leukemia (CLL), 13.6% for patients with non-Hodgkin lymphoma, 10.5% for patients with plasma cell neoplasms, and 4.5% for patients with acute leukemia. When looking at outcomes, CLL had the highest percentage of patients requiring hospital admission, oxygen, and ICU admission, and MPN/MDS had the highest percentage of patients requiring mechanical ventilation. Conclusions: Patients with hematologic malignancies had more severe COVID-19 illness and hospitalization rates and a 3.88-fold higher rate of death than patients with solid tumors. The comparable proportion of patients on anti-cancer therapy despite differences in survival suggests that being on anti-cancer therapy is less important than the underlying diagnosis of HM versus ST as a determinant of poor outcomes. Clinicians should closely monitor and initiate early COVID-19 treatments for all patients with HM and COVID-19. Because HM are highly heterogenous group of cancers, it is important to look at subtypes in greater detail. Numerous patient-level, disease-specific, and therapy-related factors may impact outcomes of COVID-19 among patients with HM, and we are currently analyzing additional data to better understand the factors which make this disease group more susceptible to severe infection. Figure 1 Figure 1. Disclosures Kuzel: Sanofi-Genzyme Genomic Health Tempus laboratories Bristol Meyers Squibb: Honoraria; Genomic Health: Membership on an entity's Board of Directors or advisory committees; Exelixis: Membership on an entity's Board of Directors or advisory committees; Cardinal Health: Membership on an entity's Board of Directors or advisory committees; Abbvie: Other; Curio Science: Membership on an entity's Board of Directors or advisory committees; AmerisourceBergen Corp: Membership on an entity's Board of Directors or advisory committees; CVS: Membership on an entity's Board of Directors or advisory committees; Tempus Laboratories: Membership on an entity's Board of Directors or advisory committees; Bristol Meyers Squibb: Membership on an entity's Board of Directors or advisory committees; Merck: Other: Data Monitoring Committee Membership; Amgen: Other: Data Monitoring Committee Membership; SeaGen: Other: Data Monitoring Committee Membership; Medpace: Other: Data Monitoring Committee Membership.