Cancer and sepsis

Sepsis in patients who are immunocompromised: diagnostic challenges and future therapies

Sepsis is a life-threatening, dysregulated host response to infection. Immunosuppression is a risk factor for infections and sepsis. However, the specific immune derangements elevating the risk for infections and sepsis remain unclear in the individual patient, raising the question of whether a general state of immunosuppression exists. In this Review, we explore the relationship between immunosuppression and sepsis, detailing the definitions, causes, and clinical implications. We address the effect of primary immunodeficiencies, acquired conditions, and drugs on the risk of infection and the development of sepsis. Patients with sepsis who are immunocompromised often present with atypical symptoms and diagnostic test results can differ, making early recognition difficult. Future perspectives entail novel biomarkers to improve early sepsis detection and tailored treatments to modulate immune function. Including patients who are immunocompromised in clinical trials is crucial to enhance the relevance of research findings and improve treatment strategies for this vulnerable population.

Procalcitonin and interleukin- 6 in predicting prognosis of sepsis patients with cancer

OBJECTIVE

To evaluate the ability of infection indicators to predict the prognosis of sepsis patients with tumor.

METHODS

A total of 317 patients admitted to ICU from January 1, 2021 to June 30, 2021 were enrolled. Among them, 163 patients were infected during peri-operative period, and 98 patients were ultimately diagnosed with sepsis. The infection indicators were analyzed for prediction of sepsis prognosis.

RESULTS

Comparison of infection indicators between sepsis and non-sepsis patients showed that procalcitonin (PCT) and interleukin-6 (IL-6) showed significant changes in sepsis patients (p < 0.05), and PCT combined with IL-6 significantly improved the specificity of early screening for sepsis with the highest positivity predictive value for sepsis. A combination of PCT > 5.965 ng/mL and IL-6 > 2808 pg/mL was associated with poor prognosis. Peak value combinations of PCT and IL-6 for prediction specificity, positive predictive value, and negative predictive value were 0.935, 0.692, and 0.682, respectively.

CONCLUSION

Abnormal increase of PCT and IL-6 has a good early warning effect on sepsis in cancer patients, and the combination of PCT and IL-6 can improve predictive specificity and increase positive predictive ability of sepsis diagnosis. PCT combined with IL-6 shows the value in predicting the prognosis of sepsis patients with cancer.

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailored treatment and prognosis. We used the MIMIC-IV database to analyze patients diagnosed with Sepsis-3 within 24 h of ICU admission. Latent class mixed models (LCMM) were applied to leukocyte trajectories to identify sepsis subtypes. The primary outcome was 28-day all-cause mortality, with secondary outcomes including the need for life-support therapies. Associations between leukocyte trajectories and outcomes were assessed using multivariate regression, and findings were externally validated with the eICU database. Use the XGBoost model to identify baseline characteristics of high-risk mortality sepsis subgroups for predicting subgroup allocation upon patient admission to the ICU, and apply the SHAP method to interpret the contributing variables of the model. Among 7410 sepsis patients, eight distinct leukocyte trajectory subtypes were identified. Among those subtypes, patients with persistently high leukocyte levels had the poorest prognosis (HR 3.00; 95% CI 2.48-3.62) and a significantly greater need for life-support therapies; Patients with persistently low white blood cell levels had a higher risk of death (HR 1.68; 95% CI 1.24-2.27) but were less likely to receive invasive mechanical ventilation. Incorporating early ICU baseline variables into an XGBoost algorithm enables effective prediction of high-mortality risk subgroups (AUC > 0.8). SHAP method reveals distinct early clinical characteristics between hyperinflammatory subtypes (class 4, 7, and 8) and the hypoinflammatory subtype (class 1). In ICU-admitted sepsis patients, eight leukocyte trajectories are identified, which is the key independent predictors of prognosis, separating from single leukocyte measurements. High-mortality risk subgroups exhibit distinct clinical characteristics at ICU admission, providing valuable insights for their prediction and personalized early intervention.

Interaction between post-tumor inflammation and vascular smooth muscle cell dysfunction in sepsis-induced cardiomyopathy

Background

Sepsis-induced cardiomyopathy (SIC) presents a critical complication in cancer patients, contributing notably to heart failure and elevated mortality rates. While its clinical relevance is well-documented, the intricate molecular mechanisms that link sepsis, tumor-driven inflammation, and cardiac dysfunction remain inadequately explored. This study aims to elucidate the interaction between post-tumor inflammation, intratumor heterogeneity, and the dysfunction of VSMC in SIC, as well as to evaluate the therapeutic potential of exercise training and specific pharmacological interventions.

Methods

Transcriptomic data from NCBI and GEO databases were analyzed to identify differentially expressed genes (DEGs) associated with SIC. Weighted gene co-expression network analysis (WGCNA), gene ontology (GO), and KEGG pathway enrichment analyses were utilized to elucidate the biological significance of these genes. Molecular docking and dynamics simulations were used to investigate drug-target interactions, and immune infiltration and gene mutation analyses were carried out by means of platforms like TIMER 2.0 and DepMap to comprehend the influence of DVL1 on immune responsiveness.

Results

Through the utilization of the datasets, we discovered the core gene DVL1 that exhibited remarkable up-regulated expression both in SIC and in diverse kinds of cancers, which were associated with poor prognosis and inflammatory responses. Molecular docking revealed that Digoxin could bind to DVL1 and reduce oxidative stress in SIC. The DVL1 gene module related to SIC was identified by means of WGCNA, and the immune infiltration analysis demonstrated the distinctive immune cell patterns associated with DVL1 expression and the impact of DVL1 on immunotherapeutic resistance.

Conclusions

DVL1 is a core regulator of SIC and other cancers and, therefore, can serve as a therapeutic target. The present study suggests that targeted pharmacological therapies to enhance response to exercise regimens may be a novel therapeutic tool to reduce the inflammatory response during sepsis, particularly in cancer patients. The identified drugs, Digoxin, require further in vivo and clinical studies to confirm their effects on SIC and their potential efforts to improve outcomes in immunotherapy-resistant cancer patients.

Unpacking the sepsis controversy

Despite its many definitions and revisions, consensus statements and clinical guidelines, the term 'sepsis' continues to be referred to as a discrete clinical entity that is often claimed to be a direct cause of mortality. The assertion that sepsis can be defined as a 'life-threatening organ dysfunction caused by a dysregulated host response to infection,' has led to a field dominated by failed clinical trials informed by host-centered, pathogen-agnostic, animal experiments in which animal models do not recapitulate the clinical condition. The observations from the National Health Service from England that claim that 77.5% of sepsis deaths occur in those aged 75 years or older and those from the USA indicating that most patients dying of sepsis have also been diagnosed with 'hospice qualifying conditions,' seem to refute the assertion that sepsis is caused by, rather than associated with, a 'dysregulated host response.' This piece challenges the current conceptual framework that forms the basis of the sepsis definition. Here we posit that as a result of both its definition and the use of inappropriate animal models, ineffective clinical treatments continue to be pursued in this field.

Clinical characteristics and prognostic factors of sepsis in patients with malignancy

Sepsis is a severe complication in patients with malignant tumors, leading to high mortality and increased need for intensive care. This study aimed to investigate the clinical characteristics and prognostic factors influencing sepsis outcomes in patients with malignant tumors. We included 4,858 patients with cancer diagnosed with sepsis between September 2019 and February 2020 whose data were collected from the Korean Sepsis Alliance, a nationwide multicenter cohort study. Cox regression analysis was used to identify predictors of 30-day and in-hospital mortality. In total, 65% of the patients survived, whereas 35% did not. Non-survivors were more likely to require intensive care, including mechanical ventilation and continuous renal replacement therapy. Key predictors of mortality included renal dysfunction, higher Sequential Organ Failure Assessment scores, and reliance on life-sustaining treatments. Non-survivors exhibited lower adherence to the implementation of sepsis care bundles, particularly to later-stage interventions. Gram-negative bacterial infections and multidrug resistance were more prevalent in non-survivors, complicating treatment efficacy. In conclusion, tailored treatment strategies that consider specific patient characteristics and disease dynamics are needed in managing sepsis with malignancy. Early identification and treatment of organ dysfunction, coupled with strict adherence to sepsis treatment protocols, are critical to improving survival in this population.

Current trends in antimicrobial use and the role of antimicrobial stewardship in palliative oncology: a narrative review

BACKGROUND

The overuse of antimicrobials is prevalent in palliative oncology care, with up to 86.9% of terminal cancer patients receiving these agents during end-of-life care. This overutilization stems from recurrent infections due to immunosuppression, malnutrition, and frequent hospitalizations, as well as difficulty differentiating infection-related symptoms from cancer-related complications.

DISCUSSION

Antimicrobial use in palliative cancer care offers limited symptomatic relief while posing significant risks, including Clostridioides difficile infections, multidrug resistance, and patient dissatisfaction. The lack of clear survival benefit highlights the need for judicious antimicrobial use, particularly in terminally ill patients. Effective antimicrobial stewardship strategies, such as integrating infection management into goals-of-care discussions, early referrals to specialized palliative care teams, and implementing early intravenous-to-oral antimicrobial switches, are critical for balancing patient comfort and minimizing unnecessary antibiotic exposure.

CONCLUSION

Optimizing antimicrobial use in palliative oncology care requires a multidisciplinary approach that prioritizes patient-centered goals, minimizes harm, and addresses misconceptions about antibiotic efficacy in end-of-life care. Antimicrobial stewardship programs, when tailored to palliative settings, play a vital role in reducing overuse and improving care quality in this vulnerable patient population.

Predictive value of peripheral blood indicators plus procalcitonin clearance rate for mortality in cancer patients with sepsis

This study investigated the predictive value of combining peripheral blood indicators with procalcitonin clearance rate (PCTc) to assess mortality risk in cancer patients with sepsis, aiming to develop a more sensitive and specific clinical tool. A retrospective analysis was conducted on 393 cancer patients with sepsis admitted to South China Hospital of Shenzhen University from January 2019 to January 2024. Collected data included clinical demographics, laboratory indicators such as white blood cell count, neutrophil count (NEUT), platelet count (PLT), lymphocyte count (LYC), C-reactive protein, procalcitonin (PCT), alanine aminotransferase, and the ratio of arterial oxygen partial pressure to inspired oxygen fraction, as well as functional scores like Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment. Multivariate logistic regression and receiver operating characteristic curves assessed the predictive ability of these factors for 28-day survival. Results showed significantly higher NEUT (P<0.001) and lower PLT and LYC (P<0.001) in the death group, while APACHE II score (area under the curve (AUC) = 0.776) and PCT 24h (AUC = 0.723) demonstrated strong predictive value for mortality risk. The joint projection model's AUC reached 0.966, significantly outperforming individual indicators, indicating that combining multiple indicators offers a more accurate prediction of survival versus mortality risk. Additionally, 24h LCR and 24h PCTc were notably lower in the death group compared to the survival group, reinforcing the advantage of combined indicators for prognosis. Overall, using both peripheral blood indicators and PCTc significantly improves the accuracy of mortality risk assessment in cancer patients with sepsis, enhancing prognostic evaluation and supporting optimized clinical decision-making.

Comprehensive risk factor-based nomogram for predicting one-year mortality in patients with sepsis-associated encephalopathy

Sepsis-associated encephalopathy (SAE) is a frequent and severe complication in septic patients, characterized by diffuse brain dysfunction resulting from systemic inflammation. Accurate prediction of long-term mortality in these patients is critical for improving clinical outcomes and guiding treatment strategies. We conducted a retrospective cohort study using the MIMIC IV database to identify adult patients diagnosed with SAE. Patients were randomly divided into a training set (70%) and a validation set (30%). Least absolute shrinkage and selection operator regression and multivariate logistic regression were employed to identify significant predictors of 1-year mortality, which were then used to develop a prognostic nomogram. The model's discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis, respectively. A total of 3,882 SAE patients were included in the analysis. The nomogram demonstrated strong predictive performance with AUCs of 0.881 (95% CI: 0.865, 0.896) in the training set and 0.859 (95% CI: 0.830, 0.888) in the validation set. Calibration plots indicated good agreement between predicted and observed 1-year mortality rates. The decision curve analysis showed that the nomogram provided greater net benefit across a range of threshold probabilities compared to traditional scoring systems such as Glasgow Coma Scale and Sequential Organ Failure Assessment. Our study presents a robust and clinically applicable nomogram for predicting 1-year mortality in SAE patients. This tool offers superior predictive performance compared to existing severity scoring systems and has significant potential to enhance clinical decision-making and patient management in critical care settings.

Assessing the causal relationship between non-small cell lung cancer and sepsis: a Mendelian randomization study

BACKGROUND

A Two-sample Mendelian randomization (MR) Analysis was used to assess the causal relationship between non-small cell lung cancer (NSCLC) and sepsis.

METHOD

Single nucleotide polymorphisms (SNPs) closely associated with NSCLC were utilized as instrumental variables (IVs) in this study. The Inverse Variance Weighted (IVW) method was used as the primary method for MR analysis, supplemented by the Weighted median, Weighted model, and MR-Egger regression method. Sensitivity analysis was conducted to improve result robustness, and data from various sources were validated and integrated. Bonferroni tests were applied to adjust for multiple comparisons.

RESULTS

After Bonferroni tests correcting the combined results, MR analysis revealed a significant association between genetically predicted NSCLC and an increased susceptibility to sepsis (odds ratios [OR]: 1.140, 95% confidence interval [CI]: 1.085-1.199, P = 2.61 × 10- 7). The combined results demonstrated that NSCLC is associated with a heightened risk of sepsis in patients under 75 years of age (OR: 1.085, 95%CI: 1.037-1.353, P = 3.84 × 10- 4). Furthermore, lung adenocarcinoma (LUAD) was found to be potentially associated with an increased susceptibility to sepsis (OR: 1.040, 95% CI: 1.009-1.073, P = 1.16 × 10- 2). These results withstood multiple sensitivity analyses, demonstrating their robustness.

CONCLUSION

This study confirms that NSCLC can significantly increase susceptibility to sepsis at the genetic level, providing valuable insights for the early identification of individuals at risk for sepsis.

A real-world pharmacovigilance study of polatuzumab vedotin based on the FDA adverse event reporting system (FAERS)

Background

Polatuzumab vedotin, the first FDA-approved antibody-drug conjugate (ADC) targeting CD79b, is utilized in the treatment of previously untreated diffuse large B-cell lymphoma (DLBCL) or high-grade B-cell lymphoma (HGBL), as well as relapsed or refractory (R/R) DLBCL. Despite its approval, concerns persist regarding the long-term safety profile of polatuzumab vedotin. This study aims to evaluate the adverse events (AEs) associated with polatuzumab vedotin since its approval in 2019, utilizing data mining strategies applied to the FDA Adverse Event Reporting System (FAERS).

Methods

Signal detection employed four methodologies, including reporting odds ratio (ROR), proportional reporting ratio (PRR), bayesian confidence propagation neural network (BCPNN), and multi-item gamma poisson shrinker (MGPS), to evaluate and quantify the signals of polatuzumab vedotin-associated AEs. Additionally, subgroup analyses based on patients age, gender, and fatal cases were conducted to investigate AEs occurrences in specific subpopulations.

Results

A total of 1,521 reports listing polatuzumab vedotin as a "principal suspect (PS)" drug were collected from the FAERS database. Through concurrent compliance with four algorithms, 19 significant Standardized MedDRA Query (SMQ) AEs and 92 significant Preferred Term (PT) AEs were detected. Subgroup analyses revealed a higher incidence of PTs in male patients compared to female patients, increased likelihood of polatuzumab vedotin-associated AEs in elder patients (>65 years), and AEs with a high risk of fatal cases include: blood lactate dehydrogenase increased, cytopenia, and hydronephrosis. The median time to AEs occurrence following polatuzumab vedotin initiation was 18.5 (5∼57.75) days, with 95% of AEs occurred within 162 days.

Conclusion

This study identified various AEs associated with polatuzumab vedotin, offering critical insights for clinical monitoring and risk identification in patients receiving polatuzumab vedotin therapy.

Characteristics and outcomes of cancer patients admitted to intensive care units in cancer specialized hospitals in China

PURPOSE

Standard intensive care unit (ICU) admission policies and treatment strategies for patients with cancer are still lacking. To depict the current status of admission, characteristics, and outcomes of patients with cancer in the ICU.

METHODS

A multicenter cross-sectional study was performed from May 10, 2021 to July 10, 2021, in the ICU departments of 37 cancer-specialized hospitals in China. Clinical records of all admitted patients aged ≥ 14 years and ICU duration > 24 h with complete data were included. Demographic information, clinical history, severity score at admission, ICU critical condition diagnosis and treatment, ICU and in-hospital outcomes and 90 days survival were also collected. A total of 1455 patients were admitted and stayed for longer than 24 h. The most common primary cancer diagnoses included lung, colorectal, esophageal, and gastric cancer.

RESULTS

Patients with lung cancer were admitted more often because of worsening complications that occurred in the clinical ward. However, other cancer patients may be more likely to be admitted to the ICU because of postoperative care. ICU-admitted patients with lung or esophageal cancer tended to have more ICU complications. Patients with lung cancer had a poor overall survival prognosis, whereas patients with colorectal cancer appeared to benefit the most according to 90 days mortality rates.

CONCLUSION

Patients with lung cancer require more ICU care due to critical complications and the overall survival prognosis is poor. Colorectal cancer may benefit more from ICU management. This information may be considered in ICU admission and treatment strategies.

Optimizing Blood Culture Collection Volumes

ABSTRACT

Infection in an immunocompromised person can be a life-threatening emergency. Collection of blood culture specimens is an important method for detecting organisms when infection is suspected. One aspect of proper blood culture collection is obtaining an accurate blood volume in the sample in accordance with the blood culture bottle manufacturer's recommendation. Underfilling the culture bottle can lead to false-negative results, while overfilling it can lead to false-positive results. At our institution, the Department of Laboratory Medicine (DLM) routinely monitors blood culture bottle volumes and notifies the nursing department of underfill/overfill events, which the department then reviews. Over several years, the DLM and the nursing department noted an increase in these events. A clinical nurse specialist and three staff nurses in the oncology/critical care services area partnered with the DLM to determine why. Upon investigation, two key issues-imprecise weighing of bottles and staff misunderstanding of the proper blood culture collection technique-were discovered. In response, the nursing standard of practice and guidance on the DLM webpage were updated and nursing education was performed. As a result, underfill/overfill events decreased by 71% in a little over a year.