Procalcitonin and C-Reactive Protein/Procalcitonin Ratio as Markers of Infection in Patients With Solid Tumors

Diagnostic accuracy of procalcitonin in adult non-neutropenic cancer patients with suspected infection: a systematic review and meta-analysis

BACKGROUND

Procalcitonin (PCT) has garnered attention as a potential diagnostic biomarker for infection in cancer patients. We performed a systematic review and meta-analysis to evaluate the diagnostic accuracy of procalcitonin (PCT) and to compare it with C-reactive protein (CRP) in adult non-neutropenic cancer patients with suspected infection.

METHODS

A systematic literature search was performed in MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials to identify all relevant diagnostic accuracy studies. Original articles reporting the diagnostic accuracy of PCT for infection detection in adult patients with solid or hematological malignancies were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, area under the hierarchical summary receiver operator characteristic (HSROC) curve, and corresponding 95% confidence interval (CI) were calculated.

RESULTS

Seven studies were included in the meta-analysis. The pooled sensitivity and specificity of PCT were 60% (95% CI [45-74%]) and 78% (95% CI [69-86%]). The diagnostic odds ratio was estimated at 5.47 (95% CI [2.86-10.46]). Three studies compared the diagnostic accuracies of PCT and CRP. The pooled sensitivity and specificity values for PCT were 57% (95% CI [26-83%]) and 75% (95% CI [68-82%]), and those for CRP were 67% (95% CI [35-88%]) and 73% (95% CI [69-77%]). The pooled sensitivity and specificity of PCT and CRP did not differ significantly (p = 0.61 and p = 0.63). The diagnostic accuracy of PCT was similar to that of CRP as measured by the area under the HSROC curve (0.73, CI = 0.61-0.91 vs. 0.74, CI = 0.61-0.95, p = 0.93).

CONCLUSION

While elevated PCT levels can be indicative of potential infection, they should not be solely relied upon to exclude infection. We recommend not using the PCT test in isolation; Instead, it should be carefully interpreted in the context of clinical findings.

Exploring the diagnostic value of CLR and CPR in differentiating Kawasaki disease from other infectious diseases based on clinical predictive modeling

Background

Kawasaki disease (KD) is an important cause of acquired heart disease in children and adolescents worldwide. KD and infectious diseases can be easily confused when the clinical presentation is inadequate or atypical, leading to misdiagnosis or underdiagnosis of KD. In turn, misdiagnosis or underdiagnosis of KD can lead to delayed use of intravenous immunoglobulin (IVIG), increasing the risk of drug resistance and coronary artery lesions (CAL).

Objectives

The purpose of this study was to develop a predictive model for identifying KD and infectious diseases in children in the hope of helping pediatricians develop timely and accurate treatment plans.

Methods

The data Patients diagnosed with KD from January 2018 to July 2022 in Shenzhen Longgang District Maternity & Child Healthcare Hospital, and children diagnosed with infectious diseases in the same period will be included in this study as controls. We collected demographic information, clinical presentation, and laboratory data on KD before receiving IVIG treatment. All statistical analyses were performed using R-4.2.1 (https://www.rproject.org/). Logistic regression and Least Absolute Shrinkage with Selection Operator (LASSO) regression analyses were used to build predictive models. Calibration curves and C-index were used to validate the accuracy of the prediction models.

Results

A total of 1,377 children were enrolled in this study, 187 patients with KD were included in the KD group and 1,190 children with infectious diseases were included in the infected group. We identified 15 variables as independent risk factors for KD by LASSO analysis. Then by logistic regression we identified 7 variables for the construction of nomogram including white blood cell (WBC), Monocyte (MO), erythrocyte sedimentation rate (ESR), alanine transaminase (ALT), albumin (ALB), C-reactive protein to procalcitonin ratio (CPR) and C-reactive protein to lymphocyte ratio (CLR). The calibration curve and C-index of 0.969 (95% confidence interval: 0.960-0.978) validated the model accuracy.

Conclusion

Our predictive model can be used to discriminate KD from infectious diseases. Using this predictive model, it may be possible to provide an early determination of the use of IVIG and the application of antibiotics as soon as possible.

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 Utility of Pre-Treatment Inflammation Markers as Associative Factors to the Adverse Outcomes of Vulvar Cancer: A Study on Staging, Nodal Involvement, and Metastasis Models

BACKGROUND

Given the role of inflammation in carcinogenesis, this study investigated the utility of pre-treatment inflammatory markers as associative indicators for advanced-stage disease, lymph node metastasis (LNM), and distant metastasis (DM) in vulvar cancer (VC).

METHODS

A cross-sectional study was conducted on 86 women with VC in a single centre in Jakarta, Indonesia. The laboratory data was based on C-reactive protein (CRP), procalcitonin, the erythrocyte sedimentation rate (ESR) and fourteen derived, recorded and calculated ratios: leukocyte-to-platelet (LPR), neutrophil-to-lymphocyte (NLR), derived neutrophil-to-lymphocyte (dNLR), neutrophil-to-monocyte (NMR), platelet-to-monocyte (PLR), lymphocyte-to-monocyte (LMR), basophil-to-monocyte (BLR), systemic immune-inflammation index (SII), body mass index, albumin, and NLR (BAN) score, haemoglobin-to-platelet (HPR), prognostic nutritional index (PNI), modified Glasgow Prognostic Score (mGPS), CRP-to-albumin, and CRP-to-procalcitonin. The optimal cut-off for each marker was determined using receiver operating characteristic (ROC) curve analysis, and their diagnostic indicator performances were assessed. The utility of these ratios as associative factors for three endpoints was further evaluated in multivariate regression models.

RESULTS

Investigated inflammatory markers exhibited specific performances for individual adverse outcomes, proving a fair to excellent ability in case finding and screening. After adjustment, the BAN score ≤ 334.89 (OR 9.20, p = 0.001) and ESR ≥ 104 (OR 4.18, p = 0.048) become two advanced-stage associative factors with AUC: 0.769. LNM was solely determined by higher NLR ≥ 2.83 (OR 4.15, p = 0.014) with AUC: 0.615. Meanwhile, BLR ≥ 0.035 (OR 5.67, p = 0.001) and ESR ≥ 84 (OR 6.01, p = 0.003) were contributing factors for DM, with AUC: 0.765.

CONCLUSIONS

Inflammatory markers are crucial for identifying the deleterious outcomes of VC. Accordingly, yielded models require external validation.

C-Reactive Protein, Procalcitonin, and a Novel Pathogenesis and Therapeutic Target of Thrombocytopenia in Sepsis

Objective. The aim of the study is to analyze the clinical characteristics, pathogen distribution, and drug sensitivity information of adult sepsis, and to provide reference for empirical clinical use; to explore the relationship between C-reactive protein (CRP) and calcitonin (PCT) The clinical value in the diagnosis of adult sepsis. Methods. We collected 455 cases of hospitalized patients with positive blood culture, including 352 cases with sepsis and 103 cases without sepsis; 1609 cases of hospitalized patients with suspected infection and negative blood culture, including 287 cases of sepsis, and 518 cases of non-infectious systemic inflammatory response syndrome (SIRS) and 804 cases of local infection. Age, gender, route of admission, admission status, CRP, PCT, and white blood cell (WBC) levels were collected from the patients. The differences between the factors were statistically analyzed, and the receiver operating characteristic curve (ROC curve) was plotted to obtain the optimal cut-off values of CRP and PCT and their area under the curve (AUC), and to compare the CRP, PCT and PCT, and the CRP + PCT tandem to diagnose sepsis sensitivity and specificity. Results. (1) 387 pathogenic strains were isolated from blood cultures of patients with sepsis, 71.06% Gram-negative, 26.87% Gram-positive and 2.07% fungi. (2) Among Gram-positive bacteria, Staphylococcus aureus was 87.5% resistant to penicillin and sensitive to vancomycin, milantropine, and teicoplanin; among Gram-negative bacteria, Escherichia coli was resistant to piracillin The resistance rate was 73.1%, fully susceptible to viraemia (100%) and resistant to imipenem, amikacin, and lacillin/tazole. (3) Among patients with positive blood cultures, CRP and PCT levels were higher in patients with sepsis than in those without sepsis. Pairwise comparison of ROC curves showed that the diagnostic value of PCT was greater than that of CRP ( $P=0.016$ ). Conclusion. CRP and PCT have a good reference value for diagnosis of sepsis patients and determination of the degree of infection in septic patients, especially PCT is more valuable for diagnosis of sepsis.

The ability of inflammatory markers to recognize infection in cancer patients with fever at admission

Infection is one of the main causes of death in cancer patients. Accurate identification of fever caused by infection could avoid unnecessary antibiotic treatment and hospitalization. This study evaluated the diagnostic value of procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-10 (IL-10), and other commonly used inflammatory markers in suspected infected adult cancer patients with fever, for better use of antibiotics. This research retrospective analyzed the clinical data of 102 adult cancer patients with fever and compared the serum levels of commonly used inflammatory markers for different fever reasons. Receiver-operating characteristic (ROC) curve and logistic regression analyses were performed. In adult cancer patients with fever, the serum PCT, CRP, IL-6, and IL-10 levels of infected patients were significantly higher than uninfected patients (median 1.19 ng/ml vs 0.14 ng/ml, 93.11 mg/l vs 56.55 mg/l, 123.74 pg/ml vs 47.35 pg/ml, 8.74 pg/ml vs 3.22 pg/ml; Mann-Whitney p = 0.000, p = 0.009, p = 0.004, p = 0.000, respectively). The ROC area under the curve(AUC) was 0.769 (95% confidence interval (CI) 0.681-0.857; p = 0.000) for PCT, 0.664 (95% CI 0.554-0.775; p = 0.009) for CRP, 0.681(95% CI 0.576-0.785; p = 0.004) for IL-6, and 0.731(95% CI 0.627-0.834; p = 0.000) for IL-10. PCT had specificity of 96.67% and positive predictive value (PPV) of 97.6%, when the cut-off value is set as 0.69 ng/ml. The serum IL-6 and IL-10 levels also had significant differences between the infected and uninfected cancer patients with advanced disease (median 128.92 pg/ml vs 36.40 pg/ml, 8.05 pg/ml vs 2.92 pg/ml; Mann-Whitney p = 0.003, p = 0.001, respectively). For the patients with neutropenia, IL-6 and IL-10 had higher AUC of 0.811 and 0.928, respectively. With a cut-off of 9.10 pg/ml, IL-10 had the highest sensitivity 83.33% and specificity 100%. In adult cancer patients, PCT had the best performance compared to CRP, IL-6, and IL-10 in differentiating infected from uninfected causes of fever, with high specificity and PPV. IL-6 and IL-10 might be useful in cancer patients with severe bloodstream infections and advanced disease. However, for patients with neutropenia, IL-10 might be more valuable than PCT in diagnosing infection.

Development and validation of a nomogram for predicting the prognosis in cancer patients with sepsis

BACKGROUND

To develop a multiparameter-based, easy-to-use nomogram and to predict the prognosis of cancer patients with sepsis in the intensive care unit (ICU).

METHODS

Clinical data on cancer patients with sepsis who met the definition of sepsis 3.0 admitted to the ICU from January 2016 to October 2021 were collected. All patients were randomly entered into the development cohort or validation cohort according to the ratio of 7:3. Patients in the development cohort were divided into the survivors and the nonsurvivors according to the outcome of 28 days in ICU. The independent risk factors of mortality due to sepsis were screened out from the two groups (the survivors and the nonsurvivors) in the development cohort through multivariate logistic regression analysis. A nomogram was established with these independent risk factors, and the calibration plot was subsequently evaluated. Finally, the predictive power of the nomogram was verified in the validation cohort.

RESULTS

A total of 317 cancer patients with sepsis who met the requirements were enrolled in this study, of which 229 entered into the development cohort and 88 entered into the validation cohort. The 28-day mortality rates of the two cohorts were 17.5% and 20.5%, respectively. The neutrophil-to-lymphocyte ratio (NLR) on day 3 (d3), brain natriuretic peptide (BNP) d3, fluid accumulation at 72 hours (h), and Sequential Organ Failure Assessment (SOFA) score were independent risk factors for the 28-day mortality between the survivors and the nonsurvivors in the development cohort. A nomogram was established on the above variables. The calibration plots fit well with the nomogram and had good statistical consistency in predicting the 28-day mortality of sepsis (the C value was 0.938 and 0.968 in the two cohorts, respectively). With a nomogram score of 83.8 points, the diagnostic accuracy was 90.8% vs 92.0%, the sensitivity was 72.5% vs 77.7%, the specificity was 94.7% vs 95.7%, the positive predictive value was 72.3% vs 82.4%, and the negative predictive value was 94.2% vs 94.4% for predicting the 28-day mortality in the development cohort and the validation cohort, respectively.

CONCLUSION

This easy-to-use nomogram based on NLR d3, BNP d3, and fluid accumulation at 72 h and SOFA score provides an accurate 28-day prognosis prediction for cancer patients with sepsis admitted to the ICU.

Magnetic Nanorobots as Maneuverable Immunoassay Probes for Automated and Efficient Enzyme Linked Immunosorbent Assay

As a typical, classical, but powerful biochemical sensing technology in analytical chemistry, enzyme-linked immunosorbent assay (ELISA) shows excellence and wide practicability for quantifying analytes of ultralow concentration. However, long incubation time and burdensome laborious multistep washing processes make it inefficient and labor-intensive for conventional ELISA. Here, we propose rod-like magnetically driven nanorobots (MNRs) for use as maneuverable immunoassay probes that facilitate a strategy for an automated and highly efficient ELISA analysis, termed nanorobots enabled ELISA (nR-ELISA). To prepare the MNRs, the self-assembled chains of Fe₃O₄ magnetic particles are chemically coated with a thin layer of rigid silica oxide (SiO₂), onto which capture antibody (Ab1) is grafted to further achieve magnetically maneuverable immunoassay probes (MNR-Ab1s). We investigate the fluid velocity distribution around the MNRs at microscale using numerical simulation and empirically identify the mixing efficiency of the actively rotating MNRs. To automate the analysis process, we design and fabricate by 3-D printing a detection unit consisting of three function wells. The MNR-Ab1s can be steered into different function wells for required reaction or wishing process. The actively rotating MNR-Ab1s can enhance the binding efficacy with target analytes at microscale and greatly decrease incubation time. The integrated nR-ELISA system can significantly reduce the assay time, more importantly during which process manpower input is greatly minimized. Our simulation of the magnetic field distribution generated by Helmholtz coils demonstrates that our approach can be scaled up, which proves the feasibility of using current strategy to construct high throughput nR-ELISA detection instrument. This work of taking magnetic micro/nanobots as active immunoassay probes for automatic and efficient ELISA not only holds great potential for point-of-care testing (POCT) in future but also extends the practical applications of self-propelled micro/nanorobots into the field of analytical chemistry.

Comparison of sPLA2IIA performance with high-sensitive CRP neutrophil percentage PCT and lactate to identify bacterial infection

Early bacterial infection (BI) identification in resource-limiting Emergency Departments (ED) is challenging, especially in low- and middle-income counties (LMIC). Misdiagnosis predisposes to antibiotic overuse and propagates antimicrobial resistance. This study evaluates new emerging biomarkers, secretory phospholipase A2 group IIA (sPLA2-IIA) and compares with other biomarkers on their performance characteristic of BI detection in Malaysia, an LMIC. A prospective cohort study was conducted involving 151 consecutive patients admitted to the ED. A single measurement was taken upon patient arrival in ED and was analysed for serum levels of sPLA2-IIA, high-sensitive C-reactive protein (CRP), procalcitonin (PCT), neutrophil percentage (N%), and lactate. All biomarkers' performance was compared for the outcomes using area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. The performance of sPLA2-IIA (AUROC 0.93 [95% CI: 0.89-0.97]; Sn 80% [95% CI: 72-87]; Sp 94% [95% CI: 81-89]) was the highest among all. It was comparable with high-sensitive CRP (AUROC 0.93 [95% CI: 0.88-0.97]; Sn 75% [95% CI: 66-83]; Sp 91 [95% CI: 77-98]) but had a higher Sn and Sp. The sPLA2-IIA was also found superior to N%, PCT, and lactate. This finding suggested sPLA2-IIA was recommended biomarkers for BI detection in LMIC.