scholarly journals A predictive nomogram for mortality of cancer patients with invasive candidiasis: a 10-year study in a cancer center of North China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ding Li ◽  
Tianjiao Li ◽  
Changsen Bai ◽  
Qing Zhang ◽  
Zheng Li ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Invasive Candidiasis ◽  
Multivariate Logistic Regression Analysis ◽  
Bloodstream Infections ◽  
Mortality Prediction ◽  
Source Control ◽  
Cancer Center ◽  
Net Benefit ◽  
Opt Out ◽  
Risk Patients

Abstract Background Invasive candidiasis is the most common fungal disease among hospitalized patients and continues to be a major cause of mortality. Risk factors for mortality have been studied previously but rarely developed into a predictive nomogram, especially for cancer patients. We constructed a nomogram for mortality prediction based on a retrospective review of 10 years of data for cancer patients with invasive candidiasis. Methods Clinical data for cancer patients with invasive candidiasis during the period of 2010–2019 were studied; the cases were randomly divided into training and validation cohorts. Variables in the training cohort were subjected to a predictive nomogram based on multivariate logistic regression analysis and a stepwise algorithm. We assessed the performance of the nomogram through the area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis (DCA) in both the training and validation cohorts. Results A total of 207 cases of invasive candidiasis were examined, and the crude 30-day mortality was 28.0%. Candida albicans (48.3%) was the predominant species responsible for infection, followed by the Candida glabrata complex (24.2%) and Candida tropicalis (10.1%). The training and validation cohorts contained 147 and 60 cases, respectively. The predictive nomogram consisted of bloodstream infections, intensive care unit (ICU) admitted > 3 days, no prior surgery, metastasis and no source control. The AUCs of the training and validation cohorts were 0.895 (95% confidence interval [CI], 0.846–0.945) and 0.862 (95% CI, 0.770–0.955), respectively. The net benefit of the model performed better than “treatment for all” in DCA and was also better for opting low-risk patients out of treatment than “treatment for none” in opt-out DCA. Conclusion Cancer patients with invasive candidiasis exhibit high crude mortality. The predictive nomogram established in this study can provide a probability of mortality for a given patient, which will be beneficial for therapeutic strategies and outcome improvement.

scholarly journals Epidemiology of Bloodstream Infections at a Cancer Center

2000 ◽  
Vol 118 (5) ◽  
pp. 131-138 ◽  
Author(s):  
Eduardo Velasco ◽  
Luiz Claudio Santos Thuler ◽  
Carlos Alberto de Souza Martins ◽  
Márcio Nucci ◽  
Leda Maria Castro Dias ◽  
...  
Keyword(s):  
High Risk ◽  
Cancer Patients ◽  
Care Center ◽  
Bloodstream Infections ◽  
Infectious Complications ◽  
Cancer Center ◽  
Coagulase Negative Staphylococcus ◽  
Oxacillin Resistance ◽  
High Risk Cancer ◽  
Epidemiological Characteristics

CONTEXT: Cancer patients are at unusually high risk for developing bloodstream infections (BSI), which are a major cause of in-hospital morbidity and mortality. OBJECTIVE: To describe the epidemiological characteristics and the etiology of BSI in cancer patients. DESIGN: Descriptive study. SETTING: Terciary Oncology Care Center. PARTICIPANTS: During a 24-month period all hospitalized patients with clinically significant BSI were evaluated in relation to several clinical and demographic factors. RESULTS: The study enrolled 435 episodes of BSI (349 patients). The majority of the episodes occurred among non-neutropenic patients (58.6%) and in those younger than 40 years (58.2%). There was a higher occurrence of unimicrobial infections (74.9%), nosocomial episodes (68.3%) and of those of undetermined origin (52.8%). Central venous catheters (CVC) were present in 63.2% of the episodes. Overall, the commonest isolates from blood in patients with hematology diseases and solid tumors were staphylococci (32% and 34.7%, respectively). There were 70 episodes of fungemia with a predominance of Candida albicans organisms (50.6%). Fungi were identified in 52.5% of persistent BSI and in 91.4% of patients with CVC. Gram-negative bacilli prompted the CVC removal in 45.5% of the episodes. Oxacillin resistance was detected in 26.3% of Staphylococcus aureus isolates and in 61.8% of coagulase-negative Staphylococcus. Vancomycin-resistant enterococci were not observed. Initial empirical antimicrobial therapy was considered appropriate in 60.5% of the cases. CONCLUSION: The identification of the microbiology profile of BSI and the recognition of possible risk factors in high-risk cancer patients may help in planning and conducting more effective infection control and preventive measures, and may also allow further analytical studies for reducing severe infectious complications in such groups of patients.

scholarly journals The Cumulative Perioperative Model: Predicting 30-Day Mortality in Abdominal Surgery Cancer Patients

2020 ◽  
pp. 1-9
Author(s):  
Joseph L Nates ◽  
Christopher M Jermaine ◽  
Joseph Ruiz ◽  
Joseph L Nates ◽  
Risa B Myers
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Abdominal Surgery ◽  
Cancer Patients ◽  
Mortality Risk ◽  
Predictive Ability ◽  
Mortality Prediction ◽  
Multivariate Logistic Regression Model ◽  
Cancer Center ◽  
Prediction Ability

Objectives: 1) To develop a cumulative perioperative model (CPM) using the hospital clinical course of abdominal surgery cancer patients that predicts 30 and 90-day mortality risk; 2) To compare the predictive ability of this model to ten existing other models. Materials and Methods: We constructed a multivariate logistic regression model of 30 (90)-day mortality, which occurred in 106 (290) of the cases, using 13,877 major abdominal surgical cases performed at the University of Texas MD Anderson Cancer Center from January 2007 to March 2014. The model includes race, starting location (home, inpatient ward, intensive care unit or emergency center), Charlson Comorbidity Index, emergency status, ASA-PS classification, procedure, surgical Apgar score, destination after surgery (hospital ward location) and delayed intensive care unit admit within six days. We computed and compared the model mortality prediction ability (C-statistic) as we accumulated features over time. Results: We were able to predict 30 (90)-day mortality with C-statistics from 0.70 (0.71) initially to 0.87 (0.84) within six days postoperatively. Conclusion: We achieved a high level of model discrimination. The CPM enables a continuous cumulative assessment of the patient’s mortality risk, which could then be used as a decision support aid regarding patient care and treatment, potentially resulting in improved outcomes, decreased costs and more informed decisions.

scholarly journals Design and Pilot Implementation of an Electronic Health Record-Based System to Automatically Refer Cancer Patients to Tobacco Use Treatment

2020 ◽  
Vol 17 (11) ◽  
pp. 4054 ◽  
Author(s):  
Thulasee Jose ◽  
Joshua W. Ohde ◽  
J. Taylor Hays ◽  
Michael V. Burke ◽  
David O. Warner
Keyword(s):  
Electronic Health Record ◽  
Cancer Patients ◽  
Tobacco Use ◽  
Mayo Clinic ◽  
Cancer Center ◽  
Health Record ◽  
Oncology Patients ◽  
Tobacco Treatment ◽  
Opt Out ◽  
Electronic Health

Continued tobacco use after cancer diagnosis is detrimental to treatment and survivorship. The current reach of evidence-based tobacco treatments in cancer patients is low. As a part of the National Cancer Institute Cancer Center Cessation Initiative, the Mayo Clinic Cancer Center designed an electronic health record (EHR, Epic©)-based process to automatically refer ambulatory oncology patients to tobacco use treatment, regardless of intent to cease tobacco use(“opt out”). The referral and patient scheduling, accomplished through a best practice advisory (BPA) directed to staff who room patients, does not require a co-signature from clinicians. This process was piloted for a six-week period starting in July of 2019 at the Division of Medical Oncology, Mayo Clinic, Rochester, MN. All oncology patients who were tobacco users were referred for tobacco treatment by the rooming staff (n = 210). Of these, 150 (71%) had a tobacco treatment appointment scheduled, and 25 (17%) completed their appointment. We conclude that an EHR-based “opt-out” approach to refer patients to tobacco dependence treatment that does not require active involvement by clinicians is feasible within the oncology clinical practice. Further work is needed to increase the proportion of scheduled patients who attend their appointments.

scholarly journals Clinical analysis of bloodstream infection of Escherichia coli in patients with pancreatic cancer

2019 ◽  
Author(s):  
Changsen Bai ◽  
Xiuse Zhang ◽  
Dong Yang ◽  
Ding Li ◽  
Wenfang Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Escherichia Coli ◽  
Pancreatic Cancer ◽  
Cancer Patients ◽  
Bloodstream Infection ◽  
Multivariate Logistic Regression Analysis ◽  
Bloodstream Infections ◽  
Clinical Analysis ◽  
Infection Group ◽  
Independent Risk Factors

Abstract Background To study the common pathogens and cancer types of bloodstream infection (BSI) in cancer patients, find the risk factors and conduct clinical analysis.Methods The clinical data of 2302 patients with BSI in Tianjin Medical University Cancer Institute and Hospital (TMUCIH) from January 2011 to December 2018 were retrospectively analyzed. 31 pancreatic cancer patients complicated with Escherichia coli BSI and 93 pancreatic cancer patients without BSI at the same period with similar sex and age were divided into infection group and non-infection group.Results 645 strains (28%) of Escherichia coli were the main pathogens causing BSI in patients with cancer. 57 cases (8.8%) of cancer patients with Escherichia coli BSI were from pancreatic oncology department, among which 31 cases were diagnosed as pancreatic cancer by pathology. Multivariate logistic regression analysis showed that hospitalization days≥7, chemotherapy and neutrophil>5.5×10 9 /L were independent risk factors for pancreatic cancer patients complicated with BSI (P < 0.05). Quantitative analysis of serum-related indicators in infection patients and non-infection patients showed significant differences between albumin, prealbumin and neutrophils in infection and non-infection group. The ratio of Escherichia coli producing extended-spectrum ß-lactamase is 49.3 and 48.1 in pancreatic cancer and non-pancreatic patients. Escherichia coli resistant to carbapenems is rare, they were highly sensitive to Cephamycin and Piperacillin/tazobactam.Conclusions Escherichia coli, the main pathogen causing BSI of cancer patients, is more common in pancreatic cancer patients. The independent risk factors include hospitalization days≥7 days, chemotherapy and neutrophils larger than 5.5×10 9 /L. Quantitative indicators of neutrophil counts, albumin and prealbumin contribute to the early diagnosis of bloodstream infections. Early use of medication, while timely adjustment based on clinical drug sensitivity results will help reduce patient morbidity and mortality.

Emergence of quinolone-resistant Escherichia coli at a comprehensive cancer center

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 19623-19623
Author(s):  
K. V. Rolston ◽  
E. Coyle ◽  
R. Prince
Keyword(s):  
High Risk ◽  
Cancer Patients ◽  
Broad Spectrum ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
E Coli ◽  
High Risk Patients ◽  
Resistance Patterns ◽  
Risk Patients ◽  
Febrile Episodes

19623 Background: Quinolone prophylaxis is recommended in high-risk neutropenic patients. Although effective in reducing the frequency of febrile episodes and documented gram-negative infections, this approach can lead to the emergence of resistant organisms. Surveillance studies looking for changes in resistance patterns at institutions that care for high-risk patients are also recommended. Methods: Our institution has participated in the meropenem yearly susceptibility test information collection (MYSTIC) program since 2000. The susceptibility of E. coli isolates from our cancer patients to quinolones (ciprofloxacin and levofloxacin) and broad-spectrum agents often used in empiric antimicrobial regimens in such patients, was determined. These studies were conducted by JMI Laboratories, Iowa, USA, and combined results as well as results of each participating institution were provided. CLSI designated breakpoints for susceptibility were used. Ribotyping and PFGE studies were performed on recent isolates. Results: Table 1 documents the declining susceptibility of E. coli isolates to the quinolones. In 2006 only 40.7% were quinolone susceptible compared to 84.2% in 2000 (p = 0.0032). All E. coli isolates remain susceptible to the carbapenems (meropenem, imipenem, ertapenem) and 95.5% remain susceptible to cefepime, ceftazidime, piperacillin-tazobactam, and the aminoglycosides. Twenty-one resistant E. coli isolates underwent ribotyping. Fourteen isolates showed identical ribotype and similar PFGE patterns suggesting the presence of an endemic clone. The other 7 isolates showed variability in their molecular patterns. Conclusions: Quinolone resistance among E. coli strains isolated from cancer patients has increased substantially. Fortunately these isolates remain susceptible to most broad-spectrum beta-lactams and aminoglycosides. Effective infection control methods need to be implemented and enforced in order to reduce the spread of these organisms in high risk patients. No significant financial relationships to disclose. [Table: see text]

Starving for attention: Malnutrition screening in a community cancer center.

2015 ◽  
Vol 33 (29_suppl) ◽  
pp. 96-96
Author(s):  
Shanthi Sivendran ◽  
Patti I. Roda ◽  
Jennifer Sporay ◽  
Ronald Guittar ◽  
Christine Cox ◽  
...  
Keyword(s):  
At Risk ◽  
Cancer Patients ◽  
Screening Tool ◽  
Severe Malnutrition ◽  
Cancer Center ◽  
Specific Recommendation ◽  
Tool Selection ◽  
Nccn Guidelines ◽  
Patient Request ◽  
Risk Patients

96 Background: It is estimated that 50% of cancer patients are at risk for malnutrition, causing physical and emotional distress that interferes with cancer treatment. Early detection and intervention may prevent severe malnutrition. Assessment and management of malnutrition are included in National Comprehensive Cancer Network (NCCN) guidelines but no specific recommendation regarding screening tool selection is provided. The Malnutrition Screening Tool (MST) is a short, easily administered screening tool, validated for identification of malnutrition in cancer patients. In this study, we describe the results of MST administration in a large community cancer institute. Methods: The MST was administered during all patient visits to our cancer institute in 2015. Patients scoring 2 or higher were identified as ‘at risk’ for malnutrition, resulting in electronic dietitian referral prompts. We retrospectively reviewed MST results from April through June 2015 and compared to dietitian referrals during the same period in 2014. At that time, dietitian consults were prompted by physician referral, patient request, or triggered by NCCN distress thermometer screen. Results: The MST identified 84% more patients in need of dietitian referral in 2015 compared to usual care in 2014. From April through June 2015, the MST was administered during 4082 discrete patient encounters. 6.7% of these visits resulted in MST score of 2 or greater for a total of 193 ‘at risk’ patients in need of referral to dietitian. Weight loss of 2 pounds or greater was reported by patients in 16% of encounters. Eating poorly because of a decreased appetite was reported by patients in 13% of the encounters. From April through June 2014, 105 patients were referred for dietitian consult, indicating the MST identified 88 more ‘at risk’ patients. Conclusions: The MST is a simple, valid tool for malnutrition screening in cancer patients that resulted in an 84% increase in identification of ‘at risk’ patients. This tool should be considered for standard malnutrition screening of cancer patients, to prompt referral for dietitian intervention.

Demographic factors associated with missed follow-up among solid tumor patients treated at a large multi-site academic institution

2020 ◽  
Vol 16 (32) ◽  
pp. 2635-2643
Author(s):  
Samantha L Freije ◽  
Jordan A Holmes ◽  
Saleh Rachidi ◽  
Susannah G Ellsworth ◽  
Richard C Zellars ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Odds Ratio ◽  
Regression Models ◽  
Tumor Patients ◽  
Logistic Regression Models ◽  
Factors Associated ◽  
Follow Up Care ◽  
Risk Patients ◽  
African American Race

Aim: To identify demographic predictors of patients who miss oncology follow-up, considering that missed follow-up has not been well studies in cancer patients. Methods: Patients with solid tumors diagnosed from 2007 to 2016 were analyzed (n = 16,080). Univariate and multivariable logistic regression models were constructed to examine predictors of missed follow-up. Results: Our study revealed that 21.2% of patients missed ≥1 follow-up appointment. African–American race (odds ratio [OR] 1.33; 95% CI: 1.17–1.51), Medicaid insurance (OR 1.59; 1.36–1.87), no insurance (OR 1.66; 1.32–2.10) and rural residence (OR 1.78; 1.49–2.13) were associated with missed follow-up. Conclusion: Many cancer patients miss follow-up, and inadequate follow-up may influence cancer outcomes. Further research is needed on how to address disparities in follow-up care in high-risk patients.

scholarly journals ECG Scoring for the Evaluation of Therapy-Naïve Cancer Patients to Predict Cardiotoxicity

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1197
Author(s):  
Julia Pohl ◽  
Raluca-Ileana Mincu ◽  
Simone M. Mrotzek ◽  
Reza Wakili ◽  
Amir A. Mahabadi ◽  
...  
Keyword(s):  
High Risk ◽  
Cancer Patients ◽  
Left Ventricular ◽  
Cardiac Biomarkers ◽  
Cancer Therapies ◽  
University Hospitals ◽  
Anti Cancer ◽  
Risk Patients ◽  
Qrs Duration ◽  
Ecg Score

Objective: To evaluate a new electrocardiographic (ECG) score reflecting domains of electrical and structural alterations in therapy-naïve cancer patients to assess their risk of cardiotoxicity. Methods: We performed a retrospective analysis of 134 therapy-naïve consecutive cancer patients in our two university hospitals concerning four ECG score parameters: Contiguous Q-waves, markers of left ventricular (LV) hypertrophy, QRS duration and JTc prolongation. Cardiotoxicity was assessed after a short-term follow-up (up to 12 months). Results: Of all the patients (n = 25), 19% reached 0 points, 50% (n = 67) reached 1 point, 25% (n = 33) reached 2 points, 5% (n = 7) reached 3 points and 0.7% reached 4 or 5 points (n = 1 respectively). The incidence of cardiotoxicity (n = 28 [21%]) increased with the ECG score, with 0 points at 0%, 1 point 7.5%, 2 points 55%, 3 points 71% and ≥3 points 50%. In the ROC (Receiver operating curves) analysis, the best cut-off for predicting cardiotoxicity was an ECG score of ≥2 points (sensitivity 82%, specificity 82%, AUC 0.84, 95% CI 0.77–0.92, p < 0.0001) which was then defined as a high-risk score. High-risk patients did not differ concerning their age, LV ejection fraction, classical cardiovascular risk factors or cardiac biomarkers compared to those with a low-risk ECG score. Conclusion: ECG scoring prior to the start of anti-cancer therapies may help to identify therapy-naïve cancer patients at a higher risk for the development of cardiotoxicity.

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