Purpose: Hospital readmissions are considered by the Centers for Medicare and Medicaid as a metric for quality of health care delivery. Robust data on the readmission profile of patients with cancer are currently insufficient to determine whether this measure is applicable to cancer hospitals as well. To address this knowledge gap, we estimated the unplanned readmission rate and identified factors influencing unplanned readmissions in a hospitalist service at a comprehensive cancer center. Methods:We retrospectively analyzed unplanned 30-day readmission of patients discharged from the General Internal Medicine Hospitalist Service at a comprehensive cancer center between April 1, 2012, and September 30, 2012. Multiple independent variables were studied using univariable and multivariable logistic regression models, with generalized estimating equations to identify risk factors associated with readmissions. Results:We observed a readmission rate of 22.6% in our cohort. The median time to unplanned readmission was 10 days. Unplanned readmission was more likely in patients with metastatic cancer and those with three or more comorbidities. Patients discharged to hospice were less likely to be readmitted (all P values Ͻ .01). Conclusion:We observed a high unplanned readmission rate among our population of patients with cancer. The risk factors identified appear to be related to severity of illness and open up opportunities for improving coordination with primary care physicians, oncologists, and other specialists to manage comorbidities, or perhaps transition appropriate patients to palliative care. Our findings will be instrumental for developing targeted interventions to help reduce readmissions at our hospital. Our data also provide direction for appropriate application of readmission quality measures in cancer hospitals.

Our nomogram identified patients with LEC who developed DM with a high probability. The model needs to be refined (tumor and blood biomarkers) and validated. This type of model will allow implementation of novel strategies in patients with LEC.

Objective:Here we examine the diagnostic utility of the US Food And Drug Administration (FDA) approved Spatula + endocervical brush combination for the BD SurePath Pap Test (SPPT) and compare it to SPPT collection with the broom alone or to an off-label combination of broom + EC brush. This question is important due to lingering concerns over the value of EC detection to a satisfactory Pap test.Methods:20,125 SPPT vials were examined for the collection devices contained. The SPPT collection device combinations allowed were: Rovers Cervex-Brush (broom, FDA approved), Medscand Pap Perfect Spatula + Medscand CytoBrush Plus GT (spatula + GT brush, FDA approved) or Rovers Cervex-Brush + Surgipath C-E Brush (broom + CE brush, off label).Results:Examination of SPPT vials revealed 11,130 collected with the broom, 4,687 collected with the spatula + GT brush and 2,921 collected with the broom + CE brush. Absence of an endocervical/transformation zone was seen in 22.86% of broom cases, 13.10% of spatula + GT brush cases (p= 0.00005 vs broom) and 10.17% of broom + CE brush cases (p= 0.00005 vs broom, p= 0.00005 vs spatula + GT brush). Importantly, LSIL detection was: broom 2.99%; spatula + GT brush 2.45% (p= 0.053 vs broom); broom + CE brush 4.18% (p= 0.034 vs broom, p= 0.0001 vs spatula + GT brush).Conclusion:When broom + brush combination is compared to broom alone or to spatula + GT brush, the broom + CE brush combination better sampled the endocervical/transformation zone and increased LSIL detection.

Background: Nearly 50% of gastric cancer patients are diagnosed with advanced gastric cancer (AGC). Therapy is palliative but results in ill effects. The median overall survival (OS) of AGC patients is often <12 months. It is unclear if the early initiation of therapy in all AGC patients is beneficial. Methods: A retrospective analysis of AGC patients in our database was carried out. The patients were divided into two groups: asymptomatic or symptomatic. We sought to assess whether the delay of systemic therapy was harmful in asymptomatic patients. Results: A total of 135 patients were analyzed. Most patients were symptomatic (68%), males (67%), and had low ECOG scores (0-1; 85%). In univariate analyses, ECOG performance status 0 (p = 0.005), delayed initiation of therapy (p = 0.03), and lack of symptoms (p = 0.03) were associated with a longer OS. The multivariate model for OS identified only ECOG performance status as an independent prognosticator of longer OS (p = 0.02). Asymptomatic patients who had delayed (≥4 weeks) systemic therapy had an OS rate of 77% at 1 year compared to 58% for patients treated within 4 weeks (p = 0.47). Conclusion: Symptomatic AGC patients had a poor outcome compared to asymptomatic AGC patients. Treatment delay in asymptomatic patients had no detrimental effect on OS, suggesting that the timing of therapy can be based on patient selection.

Background: We have limited knowledge of the geographic distribution of resistant esophageal adenocarcinoma (EAC) in resected specimens, but its clinical importance can be enormous. Method: We selected patients with baseline stage III EAC who had had chemoradiation followed by surgery and had residual EAC (resistant cases only). Outcomes were correlated with various endpoints (percentage of resistant EAC and anatomic distribution). Results: A total of 100 clinical stage III patients were studied; 90% had an R0 resection, and 99% had either moderate or poorly differentiated EAC. Twelve percent had >50% residual cancer, 31% had 11-50% residual cancer, 53% had 1-10% residual cancer, and 3% had positive nodes only. Each compartment was frequently involved: mucosa/submucosa (66%), muscularis propria (76%), and serosa (62%); all compartments were involved in 35% of the cases. Lack of EAC (meaning response) was observed in the mucosa/submucosa (34%), muscularis propria (24%), serosa (38%), and nodes (42%). Although the endoscopic biopsies prior to surgery showed no EAC in 79% of the patients, in the surgical specimens, resistant EAC was frequently occurring in the mucosa/submucosa (66%). Conclusion: Contrary to our hypothesis that resistant EAC would be frequent in the nodes, our data show that its distribution is heterogeneous and unpredictable. Most importantly, the postchemoradiation biopsies are misleading, and a decision to delay/avoid surgery based on negative biopsies can be detrimental for the patients.