Outcomes of Sepsis and Septic Shock in Cancer Patients: Focus on Lactate

A nomogram for predicting hospital mortality of critical ill patients with sepsis and cancer: a retrospective cohort study based on MIMIC-IV and eICU-CRD

OBJECTIVE

Sepsis remains a high cause of death, particularly in immunocompromised patients with cancer. The study was to develop a model to predict hospital mortality of septic patients with cancer in intensive care unit (ICU).

DESIGN

Retrospective observational study.

SETTING

Medical Information Mart for Intensive Care IV (MIMIC IV) and eICU Collaborative Research Database (eICU-CRD).

PARTICIPANTS

A total of 3796 patients in MIMIC IV and 549 patients in eICU-CRD were included.

PRIMARY OUTCOME MEASURES

The model was developed based on MIMIC IV. The internal validation and external validation were based on MIMIC IV and eICU-CRD, respectively. Candidate factors were processed with the least absolute shrinkage and selection operator regression and cross-validation. Hospital mortality was predicted by the multivariable logistical regression and visualised by the nomogram. The model was assessed by the area under the curve (AUC), calibration curve and decision curve analysis curve.

RESULTS

The model exhibited favourable discrimination (AUC: 0.726 (95% CI: 0.709 to 0.744) and 0.756 (95% CI: 0.712 to 0.801)) in the internal and external validation sets, respectively, and better calibration capacity than Acute Physiology and Chronic Health Evaluation IV in external validation.

CONCLUSIONS

Despite that the predicted model was based on a retrospective study, it may also be helpful to predict the hospital morality of patients with solid cancer and sepsis.

The effect of NK cell therapy on sepsis secondary to lung cancer: A case report

Patients with sepsis face high mortality rates and a bleak prognosis, prompting the need for advanced therapeutic interventions. A male patient diagnosed with moderately low-differentiated squamous cell carcinoma received diverse treatments, including radiotherapy, chemotherapy, immunotherapy, and targeted therapy to inhibit angiogenesis. Subsequently, he developed sepsis after comprehensive treatment, and conventional antibiotic combinations proved ineffective in combating the infection. As an experimental approach, allogeneic natural killer (NK) cell infusion was administered. Following the NK cell infusion, the patient regained consciousness, and laboratory analyses showed reduced infection-related markers, suppressed serum inflammatory cytokines, and elevated anti-tumor cytokines. However, the therapeutic effect only lasted 2-3 days. In vitro investigations demonstrated that the allogeneic NK cell product reduced interleukin-6 levels in the patient's serum. Moreover, subsequent co-cultivation of the NK cell product with the patient's serum resulted in a decrease in the proportion of cytotoxic subpopulations of NK cells and a downregulation of the expression of NK-mediated killing molecules. In conclusion, adoptive transfusion of allogeneic NK cells may improve sepsis symptoms in patients with tumor-related sepsis. In vitro co-culture tests hold promise in providing predictive biomarkers for treatment effectiveness.

Early predicting 30-day mortality in sepsis in MIMIC-III by an artificial neural networks model

OBJECTIVE

Early identifying sepsis patients who had higher risk of poor prognosis was extremely important. The aim of this study was to develop an artificial neural networks (ANN) model for early predicting clinical outcomes in sepsis.

METHODS

This study was a retrospective design. Sepsis patients from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were enrolled. A predictive model for predicting 30-day morality in sepsis was performed based on the ANN approach.

RESULTS

A total of 2874 patients with sepsis were included and 30-day mortality was 29.8%. The study population was categorized into the training set (n = 1698) and validation set (n = 1176) based on the ratio of 6:4. 11 variables which showed significant differences between survivor group and nonsurvivor group in training set were selected for constructing the ANN model. In training set, the predictive performance based on the area under the receiver-operating characteristic curve (AUC) were 0.873 for ANN model, 0.720 for logistic regression, 0.629 for APACHEII score and 0.619 for SOFA score. In validation set, the AUCs of ANN, logistic regression, APAHCEII score, and SOFA score were 0.811, 0.752, 0.607, and 0.628, respectively.

CONCLUSION

An ANN model for predicting 30-day mortality in sepsis was performed. Our predictive model can be beneficial for early detection of patients with higher risk of poor prognosis.

Association between site of infection and mortality in patients with cancer with sepsis or septic shock: A retrospective cohort study

Infections are associated with increased mortality in patients with sepsis or septic shock. However, to the best of our knowledge, the influence of the site of infection on patients with cancer remains unclear. The present study aimed to evaluate the association between the site of infection and mortality in patients with cancer and sepsis or septic shock. The present study was conducted in a Lebanon tertiary care centre from July 2010 to April 2015. A total of 176 patients with active cancer presenting to the emergency department with sepsis or sepsis shock were included in the present analysis. Cox regression and Kaplan-Meier analysis of the effect of the site of infection on mortality were performed. The most common site of infection was the lung (37.50%), followed by the urinary tract (26.70%), unknown site (13.63%), gastrointestinal (13.07%) and others (9.10%). The overall mortality rate was 47.73%. Gastrointestinal infection (78.26%) was associated with the highest mortality, followed by pneumonia (62.12%). The urinary tract infection with the lowest mortality rate was the reference group. After adjusting for confounding variables, gastrointestinal infection was associated with the highest in-hospital mortality [hazard ratio (HR), 2.64; 95% CI, 1.25-5.55], followed by pneumonia (HR, 1.95; 95% CI, 1.03-3.68). The association between site of infection and 28-day and 60-day mortality was analysed by Cox regression, as well as by stratified analysis to investigate the association between site of infection and mortality from haematological and solid tumors. Gastrointestinal infection had a higher mortality rate. In conclusion, the site of infection had the same association with mortality in patients with solid and haematological tumours.

Outcomes and Predictors of 28-Day Mortality in Patients With Solid Tumors and Septic Shock Defined by Third International Consensus Definitions for Sepsis and Septic Shock Criteria

BACKGROUND

Data assessing outcomes of patients with solid tumors demonstrating septic shock using the Third International Consensus Definitions for Sepsis and Septic Shock are scarce.

RESEARCH QUESTION

What are the independent predictors of 28-day mortality in critically ill adults with solid tumors and septic shock?

STUDY DESIGN AND METHODS

Cohort of solid tumor patients admitted to the ICU with septic shock. Demographic and clinical characteristics were gathered from the electronic health records. We developed a reduced multivariate logistics regression model to identify independent predictors of 28-day mortality and used Kaplan-Meier plots to assess survival.

RESULTS

A total of 271 patients were included. The median age was 62 years (range, 19-94 years); 57.2% were men and 53.5% were White. The most common underlying malignancies were lung (19.2%), breast (7.7%), pancreatic (7.7%), and colorectal (7.4%) cancers. Most patients (84.5%) harbored metastatic disease. Twenty-eight days after ICU admission, 188 patients (69.4%) had died. Nonsurvivors showed a higher rate of advanced cancer, longer hospital stays before ICU admission, and higher Sequential Organ Failure Assessment scores at admission and throughout the ICU stay (P < .001 for all). The multivariate analysis identified metastatic disease (OR, 3.17; 95% CI, 1.43-7.03), respiratory failure (OR, 2.34; 95% CI, 1.15-4.74), elevated lactate levels (OR, 3.19; 95% CI, 1.90-5.36), and Eastern Cooperative Oncology Group performance scores of 3 or 4 (OR, 2.72; 95% CI, 1.33-5.57) as independent predictors of 28-day mortality. Only 38 patients (14%) were discharged home without medical assistance.

INTERPRETATION

The 28-day mortality rate of patients with solid tumors and septic shock was considerably high. Factors associated with worse survival included advanced oncologic disease, poor performance status, high lactate level, and concomitant acute respiratory failure. Early goals-of-care discussions should be considered for frail patients with septic shock and advanced metastatic disease without denying access to the appropriate level of care.

Impact of cancer on mortality rates in patients with sepsis: A meta-analysis and meta-regression of current studies

BACKGROUND

Research suggests that approximately 6% of adult patients admitted to hospitals in the United States present with sepsis and there has been a minimal change in the incidence of this condition in the last decade. Furthermore, patients with cancer generally have a higher incidence of sepsis due to immunosuppression caused by cancer or its treatment.

AIM

To assess if cancer increases the mortality rates in sepsis patients by pooling evidence from contemporary studies.

METHODS

PubMed, Embase, and Google Scholar databases were searched from January 1, 2001 to December 15, 2021 for studies comparing outcomes of sepsis patients based on the presence of active cancer. Mortality data were pooled using a random-effects model, with the odds ratio (OR) and 95% confidence interval (CI) calculated. Meta-regression was conducted to assess the influence of confounders on mortality rates.

RESULTS

Nine studies were included. The meta-analysis demonstrated a non-significant tendency towards increased risk of early mortality (OR = 2.77, 95%CI: 0.88-8.66, I² = 99%) and a statistically significantly increased risk of late mortality amongst sepsis patients with cancer as compared to non-cancer sepsis patients (OR = 2.46, 95%CI: 1.42-4.25, I² = 99%). Overall, cancer was found to significantly increase the risk of mortality in sepsis patients (OR = 2.7, 95%CI: 1.07-6.84, I² = 99%). Meta-analysis indicated a statistically significantly increased risk of mortality in patients with solid tumors as well as hematological malignancies. Meta-regression indicated that an increase in the prevalence of comorbid pulmonary and renal diseases increased the risk of mortality in cancer patients with sepsis. Mortality rates increased with an increase in the percentage of patients with urinary tract infections while an inverse relationship was seen for infections of cutaneous origin.

CONCLUSION

Contemporary evidence indicates that the presence of any cancer in sepsis patients significantly increases the risk of mortality. Scarce data suggest that mortality is equally increased for both solid and hematological cancers. Current evidence is limited by high heterogeneity and there is a need for further studies taking into account several confounding variables to present better evidence.

Comparison of Short- and Long-Term Mortality in Patients with or without Cancer Admitted to the ICU for Septic Shock: A Retrospective Observational Study

Introduction: Cancer patients are at high risk of developing septic shock (SSh) and are increasingly admitted to ICU given their improved long-term prognosis. We, therefore, compared the prognosis of cancer and non-cancer patients with SSh. Methods: We conducted a monocentric, retrospective cohort study (2013−2019) on patients admitted to ICU for SSh. We compared the clinical characteristics and management and studied short- and long-term mortality with ICU and in-hospital mortality and 1-year survival according to cancer status. Results: We analyzed 239 ICU stays in 210 patients, 59.5% of whom were men (n = 125), with a median age of 66.5 (IQR 56.3−77.0). Of the 121 cancer patients (57.6% of all patients), 70 had solid tumors (33.3%), and 51 had hematological malignancies (24.3%). When comparing ICU stays of patients with versus without cancer (n = 148 vs. n = 91 stays, respectively), mortality reached 30.4% (n = 45) vs. 30.0% (n = 27) in the ICU (p = 0.95), and 41.6% (n = 59) vs. 35.6% (n = 32) in hospital (p = 0.36), respectively. ICU length of stay (LOS) was 5.0 (2.0−11.3) vs. 6.0 (3.0−15.0) days (p = 0.27), whereas in-hospital LOS was 25.5 (13.8−42.0) vs. 19.5 (10.8−41.0) days (p = 0.33). Upon multivariate analysis, renal replacement therapy (OR = 2.29, CI95%: 1.06−4.93, p = 0.03), disseminated intravascular coagulation (OR = 5.89, CI95%: 2.49−13.92, p < 0.01), and mechanical ventilation (OR = 7.85, CI95%: 2.90−21.20, p < 0.01) were associated with ICU mortality, whereas malignancy, hematological, or solid tumors were not (OR = 1.41, CI95%: 0.65−3.04; p = 0.38). Similarly, overall cancer status was not associated with in-hospital mortality (OR = 1.99, CI95%: 0.98−4.03, p = 0.06); however, solid cancers were associated with increased in-hospital mortality (OR = 2.52, CI95%: 1.12−5.67, p = 0.03). Lastly, mortality was not significantly different at 365-day follow-up between patients with and without cancer. Conclusions: In-hospital and ICU mortality, as well as LOS, were not different in SSh patients with and without cancer, suggesting that malignancies should no longer be considered a barrier to ICU admission.