Abstract
Objectives
Bloodstream infection (BSI) is one of the major causes of death in pediatric tumor patients. Blood samples are relatively easy to obtain and thus provide a ready source of infection-related biological markers for the prompt evaluation of infection risk.
Methods
A total of 259 pediatric tumor patients were included from May 2019 to March 2022. Patients were divided into BSI group (n=70) and control group (n=189). Clinical and biological data were collected using electronic medical records. Differences in biological markers between BSI group and control group and differences before and during infection in BSI group were analyzed.
Results
The infected group showed higher levels of procalcitonin (PCT) and hypersensitive C-reactive-protein (hsCRP), and lower prealbumin (PA) than the uninfected group. Area under the receiver-operating curve (ROC) curves (AUC) of PCT, hsCRP and NLR (absolute neutrophil count to the absolute lymphocyte count) were 0.756, 0.617 and 0.612. The AUC of other biomarkers was ≤0.6. In addition, PCT, hsCRP, NLR and fibrinogen (Fg) were significantly increased during infection, while PA and lymphocyte (LYM) were significantly decreased. Antibiotic resistant of Gram-positive bacteria to CHL, SXT, OXA and PEN was lower than that of Coagulase-negative Staphylococcus. Resistant of Gram-positive bacteria to CHL was lower, while to SXT was higher than that of Gram-negative bacteria.
Conclusions
This study explored the utility of biomarkers to assist in diagnosis and found that the PCT had the greatest predictive value for infection in pediatric tumor patients with BSI. Additionally, the PCT, hsCRP, NLR, PA, LYM and Fg were changed by BSI.
Introduction
Pediatric tumors, especially solid tumors, are uncommon but are the leading cause of childhood tumor-related death [1]. Radiation is an important therapeutic approach in pediatric tumors but can increase the risk of immunosuppression leaving patients highly susceptible to infection by pathogenic microorganisms [2, 3]. In pediatric tumor patients, BSI can readily result in septic shock thus explaining its high mortality rate [4]. A rapid and accurate diagnosis of BSI can provide clinicians with valuable time to institute timely interventions. The gold standard for diagnosis of BSI is still blood culture [5]. However, the commonly utilized blood culture diagnostic method for bloodstream infections (BSI) is limited by a long detection time, poor sensitivity, and the requirement for the collection of a large blood volume [6]. Therefore, there is a critical need to identify sensitive biomarkers that can help diagnose emerging BSI in pediatric tumor patients.
Blood biomarkers pose unique advantages in the diagnosis and treatment monitoring of BSI including easy specimen acquisition, proximity to the condition under investigation since blood is the site of pathology, and a short detection time [7]. Therefore, many studies have focused on the diagnostic efficacy of blood indicators in microbial infection. Commonly utilized clinical markers of BSI include procalcitonin (PCT) and hypersensitive C-reactive-protein (hsCRP) and other inflammatory factors such as the cytokine interleukin-6 (IL-6) [8, 9]. PCT is produced in thyroid and adipose tissue under normal conditions. PCT is released by peripheral blood mononuclear cells (PBMCs) during sepsis [10]. During pathogenic microorganisms infect the body, the level of PCT increases rapidly by 4 h and peaks at 8 h; PCT is closely related to the infection severity and antibiotic treatment [11, 12]. hsCRP level similarly rises rapidly during infection and tissue damage. hsCRP can activate the complement system enhancing phagocyte activity, which is an important protective function in the body’s natural immune defense arsenal [13, 14]. NLR (absolute neutrophil count to the absolute lymphocyte count) is determined by routine hematology and correlates with a variety of diseases, including many tumors and cardiovascular conditions [15, 16]. NLR has been identified as an indicator of inflammation; it is associated with systemic inflammation and is a biomarker of impaired cell-mediated immunity [17, 18]. Multiple cytokines, including IL-6, interleukin-8 (IL-8), interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α), are upregulated by immune defenses and thus are used to aid the diagnosis of sepsis [19, 20]. Prealbumin (PA), also known as transthyretin, is a liver-secreted protein that is thought to be important in assessing nutritional deficiencies and nutritional support [21]. PA has also been implicated in infection and inflammation. The CRP/PA ratio is an inflammatory-based prognostic score that predicts morbidity and mortality of patients on parenteral nutrition [22]. Fibrinogen (Fg) is a clotting factor in that plays an important role in coagulation and thrombosis [23]. Moreover, Fg acts as an acute phase reaction proteins (APRP) and is increased during inflammatory response [24, 25]. Fg is elevated and correlates with excessive inflammation and disease severity in patients with COVID-19 [26].
In human BSI, pathogenic microorganisms include bacteria and fungi. Bacteria are classified into Gram-positive and Gram-negative bacteria based on a Gram stain that detects bacterial cell wall characteristics [27, 28]. Interestingly, significant differences in BSI biomarkers have been identified, based on different types of bacteria; in addition biomarkers are differentially affected by bacterial and fungal infection [29]. Precise references range of these biomarkers for the diagnosis of infection have not been identified by patients age, diseases and the pathogenic microorganisms. Changes in these biomarkers are more complex in children, especially those with solid tumors that have been treated with radiation. Therefore, to offer a useful tool for BSI diagnosis, we need to identify the cutoff values of relevant biomarkers in pediatric tumor patients.
In this study, we analyzed the diagnostic value of APRP and routine blood indices for identifying BSI in pediatric tumor patients. We showed that PCT, hsCRP and NLR showed promise in predicting BSI in pediatric tumor patients. By quantifying biological indicators in the same patient before and during infection, we found that levels of hsCRP and PCT were the most elevated during infection and the levels of NLR and Fg were increased moderately, while the levels of lymphocyte (LYM) and PA were decreased. At the same time, we analyzed the antibiotic resistance of different types of bacteria in pediatric tumor patients, to provide a reference for diagnosis and treatment.
Materials and methods
Participants
This retrospective study involved 381 pediatric tumor cases, of which 267 were negative in blood culture while 114 were positive in blood culture. After a series of screening, 189 patients were enrolled in the control group and 70 patients were enrolled in the BSI group. Patients were admitted to Shandong Cancer Hospital and Institute between May 2019 and March 2022. The clinical characteristics of the two groups were collected from the electronic medical records and the Ruimei laboratory information system version 6.0 (rmlis, Huangpu District, Shanghai, China) and are summarized in Table 1. Patients with BSI were diagnosed based on blood culture, but also meet the clinical features and symptoms. Patients experienced at least one episode of fever with temperatures >38 °C, chill or hypotension. Patients with an age of less than or equal to 1 years old, having at least one of the following symptoms or signs: fever with temperatures >38 °C or temperature <37 °C, apnea and bradycardia. Before BSI is the state of the patient before infection with pathogenic microorganisms. We collected the information of 70 patients with BSI, all of them contained the information of PCT, hsCRP and hematological parameters during BSI, 57 and 21 of them contained information of PA and Fg during BSI, respectively. At the same time, among the above patients, 63 cases, 61 cases, 70 cases, 52 cases and 14 cases had PCT, hsCRP, hematological parameters, PA and Fg information before BSI, respectively. Flow diagram of case collection in Supplementary Figure 1. Informed consent was obtained from all individuals included in this study. The research related to human use has been complied with all the relevant national regulations, institutional policies and in accordance with the tenets of the Helsinki Declaration, and has been approved by the Ethics Committee of the Shandong Cancer Hospital and Institute.
Clinical parameters of pediatric tumor patients (BSI and control group).
| Clinical parameters | BSI (n=70) | Control group (n=189) | p-Value |
|---|---|---|---|
| Age, median, years | 3 (1–17) | 4 (0.5–18) | 0.0877 |
| Gender, n (%) | 0.5492 | ||
| Male | 44 (62.9%) | 111 (58.7%) | |
| Female | 26 (37.1%) | 78 (41.3%) | |
| Diagnosis, n (%) | |||
| Solid tumor | 70 (100%) | 186 (98.4%) | 0.2943 |
| Hematological malignancy | 0 (0%) | 3 (1.6%) | |
| Microorganism, n (%) | |||
| Gram-positive bacteria | 30 (42.86%) | ||
| Coagulase-negative Staphylococcus | 15 (21.43%) | ||
| Staphylococcus aureus | 7 (10.00%) | ||
| Streptococcus pneumoniae | 4 (5.71%) | ||
| Others | 4 (5.71%) | ||
| Gram-negative bacteria | 35 (50%) | ||
| Acinetobacter spp. | 5 (7.14%) | ||
| Klebsiella spp. | 9 (12.86%) | ||
| E. coli | 5 (7.14%) | ||
| Pseudomonas spp. | 5 (7.14%) | ||
| Enterobacter spp. | 5 (7.14%) | ||
| Others | 6 (8.57%) | ||
| Fungus | 5 (7.14%) |
Collections and analyses of biomarkers associated with inflammation
The following data were collected from Ruimei laboratory information system version 6.0. PCT was quantified in plasma by an electrochemiluminescence immunoassay using a COBAS E801 immunoassay analyzer (Roche Diagnostics GmbH, Mannheim, Germany), with a level of <0.05 μg/L considered normal. Analytical evaluation of the performances showed that BRAHMS PCT on Roche COBAS E801 has significant correlation with other PCT immunoassay detection methods, and their correlation coefficients ranging between 0.918 and 0.997. Although BRAHMS PCT on Roche COBAS E801 exhibited a bias, it is still in the acceptable range [30]. Plasma hsCRP and PA were quantified by immunoturbidimetry assays using a Beckman Coulter analyzer AU5800 (Beckman Coulter, CA, USA). hsCRP<10 mg/L was considered to indicate no systemic infection. The reference range of PA was 0.25–0.4 g/L. Blood cells including white blood cells, lymphocytes and neutrophils were analyzed using an automatic hematological analyzer Sysmex XN9000 (Sysmex Corporation, Kobe, Japan). The NLR was determined from these data. Fg was measured by changes in absorbance using ACL TOP700 (Chicago, IL, USA). The reference range of Fg was 2–4 g/L. All tests were performed according to the manufacturer’s instructions.
Blood cultures and identification
Blood cultures are one of the most important tests performed in clinical microbiology laboratories [31]. Blood samples were routinely taken for culture when pediatric tumor patients are febrile and cultured using a BD BACTEC™ FX automated culturing system (Becton, Dickinson and Company, New Jersey, USA). When the blood culture result was positive, the positive samples were taken and inoculated on a Columbia Blood Agar Base. The microorganism was identified by mass spectrometry using a BRUKER microflex MALDI TOF/TOF Mass Spectrometer (BRUKER Corporation, Massachusetts, USA) after the formation of a single colony. All blood samples were cultivated within 1 h of samples collection and before antibiotic treatment was instituted. Antimicrobial susceptibility tests were processed by a BD Phoenix M50 automated microbial system (Becton, Dickinson and Company, New Jersey, USA). All procedures were conducted in accordance with the manufacturers’ instructions and the BC standards of the Clinical Laboratory Standards Institute [32].
Statistical analysis
GraphPad Prism version 9.0 (GraphPad Software, CA, USA) and SPSS version 23.0 statistical software (SPSS, IL, USA) were used for statistical analysis. All data are shown as the median ± interquartile range. Mann-Whitney U tests were used to compare non-normally distributed data. Comparisons of normally distributed data were performed by independent samples t tests. The utility of biomarkers for a BSI diagnosis was evaluated by receiver-operating curve (ROC) curves. Youden’s index was used to determine cut-off points by optimally balancing sensitivity and specificity. p<0.05 was considered statistically significant.
Results
Cohort characteristics
The clinical and demographic characteristics are shown in Table 1. The median participant age was 3 (range 1–17) years in the BSI group and 4 (range 0.5–18) in the control group. There were no differences in gender (p=0.5492) and clinical diagnostic information (p=0.2943). In the BSI group, the infection rate of Gram-positive bacteria was 42.86%; these mainly included Coagulase-negative Staphylococcus (21.43%), Staphylococcus aureus (10.00%) and Streptococcus pneumoniae (5.71%). In addition, Gram-negative bacteria accounted for half of all pathogenic microorganisms and mainly included Acinetobacter spp. (7.14%), Klebsiella spp. (12.86%), Enterobacter coli (7.14%), Pseudomonas spp. (7.14%) and Enterobacter spp. (7.14%). We also identified 5 cases with fungal infections including Candida tropicalis, Candida albicans and Candida parapsilosis which accounted for 7.14% of the BSI infections.
Inflammatory biomarkers in BSI and control groups
To identify biomarkers associated with BSI in pediatric tumor patients, we analyzed the levels of inflammation-related biomarkers in the two groups. We found that PCT levels were significantly higher in the BSI group (median 0.5 μg/L) than the control group (0.23 μg/L) (Figure 1A). Compared with the control group, levels of hsCRP (median 30.3 mg/L vs. 16.2 mg/L) and NEU (median 1.82 × 109/L vs. 0.63 × 109/L) were higher in the BSI group, while PA (0.17 g/L vs. 0.19 g/L) was lower (Figure 1B–D). There were no significant between-group differences in WBC, LYM, NLR or Fg (Figure 1E–H). The median levels and ranges of biomarkers are shown in Table 2.
Inflammatory biomarkers between BSI group (70) and control group (189) in pediatric tumor patients. The levels of PCT (A), hsCRP (B), PA (C), NEU (D), WBC (E), LYM (F), Fg (G) and NLR (H). *p<0.05, **p<0.01, ****p<0.0001.
Comparison of inflammatory biomarkers between BSI group and control group.
| Variable | BSI group (n=70) | Control group (n=189) | p-Value |
|---|---|---|---|
| PCT median, μg/L | 0.51 (0.1–100) | 0.23 (0.04–24.58) | <0.0001 |
| hsCRP median, mg/L | 30.3 (0.3–419.2) | 16.2 (0.1–252.3) | 0.0204 |
| WBC median, 109/L | 2.29 (0.03–25.52) | 1.26 (0.02–23.7) | 0.1415 |
| NEU median, 109/L | 1.82 (0.01–19.9) | 0.63 (0.01–23.13) | 0.0047 |
| LYM median, 109/L | 0.29 (0.02–2.85) | 0.33 (0.01–17) | 0.2232 |
| NLR median | 3.86 (0.07–0.38) | 1.64 (0.004–165.8) | 0.6812 |
| PA median, g/L | 0.17 (0.002–0.31) | 0.19 (0.06–0.48) | 0.0258 |
| Fg median, g/L | 3.21 (2.21–5.15) | 2.72 (2.41–3.07) | 0.8035 |
Diagnostic utility of inflammatory biomarkers
To evaluate the diagnostic utility of inflammatory biomarkers, we constructed ROC curves. The analysis is shown in Table 2 and Supplementary Table 1. We found that in BSI group, PCT had a discriminative power, with an area under the curve (AUC) of 0.756 (95% confidence interval [CI] 0.699–0.807), sensitivity of 75.71%, and specificity of 66.67% compared with the control group (Figure 2A). For hsCRP, the AUC was 0.617 (95% CI 0.554–0.676), sensitivity of 58.57%, and specificity of 64.02% (Figure 2B). For NLR, the AUC was 0.612 (95% CI 0.550–0.672), sensitivity of 69.57%, and specificity of 51.32% (Figure 2C). We also constructed ROC curves of NEU, LYM, WBC, Fg and PA, but their AUCs were small and showed low sensitivity or specificity (Supplementary Figure 2). Next, we evaluated the diagnostic capability of a combination of PCT, hsCPR and NLR and the analysis showed an AUC of 0.771 (95% CI 0.715–0.821) (Figure 2D). In order to provide a tool for the identification of BSI in pediatric tumor patients, we also calculated cut-off values of PCT (3.06 μg/L), hsCRP (27 mg/L) and NLR (1.71) in Table 3. These results suggest that the PCT has a good diagnostic value in identifying BSI in pediatric tumor patients. We also found that a composite of the three indicators could better identify BSI than the individual indicators.
Diagnostic utility of inflammatory biomarkers in pediatric tumor patients. (A) ROC curves analyzed that the AUC of PCT prediction was 0.756. (B) ROC curves analyzed that the AUC of hsCRP prediction was 0.617. (C) ROC curves analyzed that the AUC of NLR prediction was 0.612. (D) ROC curves analyzed that the AUC of the combined prediction of PCT, hsCRP and NLR was 0.771.
The diagnostic performance comparison of PCT, hsCRP and NLR in pediatric tumor patients.
| Diagnostic performance | PCT | hsCRP | NLR |
|---|---|---|---|
| AUC | 0.756 | 0.617 | 0.612 |
| 95% CI | 0.699–0.807 | 0.554–0.676 | 0.550–0.672 |
| Cut-off value | 3.06 μg/L | 27 mg/L | 1.71 |
| Sensitivity | 75.71% | 58.57% | 69.57% |
| Specificity | 66.67% | 64.02% | 51.32% |
| PPV | 78.95% | 30.50% | 34.29% |
| NPV | 77.08% | 84.74% | 81.51% |
| Youden index | 0.4238 | 0.2259 | 0.2098 |
| p-Value | <0.001 | 0.002 | 0.005 |
-
AUC, area under the ROC curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value.
Next, we analyzed Spearman’s correlations among the inflammatory markers in pediatric tumor patients with BSI, as shown in Table 4. We found that PCT and hsCPR were significantly correlated. hsCRP was negatively correlated with WBC, NEU and LYM. Meanwhile, WBC and NEU were positively correlated with LYM and NLR.
Spearman’s correlations among the blood inflammatory biomarkers in pediatric tumor patients with BSI.
| PCT | hsCRP | WBC | NEU | LYM | NLR | PA | Fg | |
|---|---|---|---|---|---|---|---|---|
| PCT | ||||||||
| r | 1.00 | 0.295 | 0.00 | −0.047 | −0.137 | 0.034 | 0.046 | 0.093 |
| p | 0.013 | 0.999 | 0.699 | 0.259 | 0.778 | 0.733 | 0.689 | |
| hsCRP | ||||||||
| r | −0.311 | −0.259 | −0.352 | −0.218 | −0.200 | −0.091 | ||
| p | 0.009 | 0.013 | 0.003 | 0.070 | 0.137 | 0.695 | ||
| WBC | ||||||||
| r | 0.083 | 0.626 | 0.598 | 0.087 | −0.071 | |||
| p | <0.01 | <0.01 | <0.01 | 0.518 | 0.760 | |||
| NEU | ||||||||
| r | 0.624 | 0.853 | 0.054 | −0.136 | ||||
| p | <0.01 | <0.01 | 0.691 | 0.557 | ||||
| LYM | ||||||||
| r | 0.220 | 0.179 | −0.329 | |||||
| p | 0.067 | 0.183 | 0.146 | |||||
| NLR | ||||||||
| r | −0.023 | −0.094 | ||||||
| p | 0.868 | 0.687 | ||||||
| PA | ||||||||
| r | 0.217 | |||||||
| p | 0.373 | |||||||
| Fg | ||||||||
| r | 1 | |||||||
| p |
-
r, correlation coefficient calculated using Spearman’s methods.
Changes in inflammatory markers before and during BSI
To accurately evaluate the diagnostic value of inflammatory indicators in BSI, we evaluated changes of inflammation-related indicators in the same patient from before to during BSI. We found that PCT and hsCRP were significantly upregulated during BSI compared with before BSI (Figure 3A, B). There were no marked changes in WBC and NEU, but LYM and PA were significantly decreased (Figure 3C–F). NLR and Fg showed a moderately increase during BSI (Figure 3G, H). We show the median values of inflammatory biomarkers in Table 5.
Differences of inflammatory markers before and during BSI in pediatric tumor patients. The differences of PCT (A), hsCRP (B), WBC (C), NEU (D), LYM (E), PA (F), NLR (G) and Fg (H) before and during infection in pediatric tumor patients. *p<0.05, **p<0.01, ****p<0.0001.
Comparison of blood inflammatory markers in pathogenic microorganism-infected group and control group.
| Variable | Pathogenic microorganism-infected group | Germ-free | p-Value |
|---|---|---|---|
| PCT median, μg/L | 0.51 (0.1–100) | 0.14 (0.03–1.2) | 0.0068 |
| CRP median, mg/L | 30.3 (0.3–419.2) | 5.1 (0.4–83.1) | <0.0001 |
| WBC median, 109/L | 2.29 (0.03–25.52) | 4.57 (1.43–24.39) | 0.0985 |
| NEU median, 109/L | 1.82 (0.01–19.9) | 3.07 (0.51–24.3) | 0.1877 |
| LYM median, 109/L | 0.29 (0.02–2.85) | 0.71 (0.12–3.24) | <0.0001 |
| NLR median | 3.86 (0.07–0.38) | 0.86 (0.01–67.4) | 0.0158 |
| PA median, g/L | 0.17 (0.002–0.31) | 0.202 (0.022–0.309) | <0.0001 |
| Fg median, g/L | 3.21 (2.21–5.15) | 1.2 (0.79–2.12) | 0.0138 |
Correlation analysis between inflammatory indicators and microbes
We divided the microorganisms into Gram-negative bacteria, Gram-positive bacteria and fungi and analyzed the changes in PCT, hsCRP and NLR during infection with these different microorganisms. As shown in the heat map, PCT and hsCRP levels trended higher in Gram-negative than Gram-positive bacterial infections (Figure 4). PCT trended higher in Gram-negative than in fungus infections (Figure 4). However, these PCT and hsCRP differences were not statistically significant due to the low number of cases. We did not see any other significant correlations with pathogen type (Figure 4 and Supplementary Figure 3). The variation range and median of those inflammatory indicators are presented in Table 6 and Supplementary Table 2.
Heat map was used to show the variation of PCT, hsCRP and NLR in Gram-negative bacteria, Gram-positive bacteria and Fungus in pediatric tumor patients.
Changes of blood inflammatory markers.
| Variable | Gram-negative bacteria | Gram-positive bacteria | Fungus |
|---|---|---|---|
| PCT median, μg/L | 0.62 (0.12–100) | 0.45 (0.11–25.01) | 0.35 (0.10–0.67) |
| CRP median, mg/L | 30.3 (0.50–419.2) | 29.1 (0.30–172.8) | 39.1 (20.9–177.3) |
| NLR median | 2.52 (0–39.9) | 4.78 (0.15–46.24) | 3.43 (0.80–32.00) |
Analysis of drug resistance of pathogenic bacteria
We first analyzed the types of pathogenic microorganisms, and found that the top ones included Coagulase-negative Staphylococcus (15/70, 21.43%), Klebsiella spp. (9/70, 12.86%), S. aureus (7/70, 10.00%), E. coli (5/70, 7.14%), Acinetobacter spp. (5/70, 7.14%), Pseudomonas spp. (5/70, 7.14%), Enterobacter spp. (5/70, 7.14%) and fungus (5/70, 7.14%) (Figure 5A). It can be seen from the above results that Coagulase-negative Staphylococcus was the most frequently isolated pathogen. Next, we compared the resistance of different bacterial types. We found that Coagulase-negative Staphylococcus were 100% resistant to penicillin (PEN), while the resistance rate in Gram-positive bacteria was 71.1%. The drug resistance rate of Coagulase-negative Staphylococcus to oxacillin (OXA) was 86.7% and the sensitivity was only 13.3%, while the drug resistance rate and sensitivity rate of Gram-positive bacteria to OXA were 59.1 and 40.9%, respectively. For sulfamethoxazole (SXT), the resistance rate of Gram-positive bacteria was 53.8%, while that of Coagulase-negative Staphylococcus reached 80% (Figure 5B, C). Therefore, special attention should be paid to treating of BSI caused by Coagulase-negative Staphylococcus. Compared with Gram-positive bacteria, Gram-negative bacteria were less sensitive to ampicillin (AMP) (12.5 vs. 33.3%). The sensitivity to SXT was lower in Gram-positive bacteria (46.2%) than Gram-negative bacteria (66.7%); the latter showed higher sensitivity to ciprofloxacin (CIP) (86.4 vs. 65.6%) and ampicillin (AMP) (33.3 vs. 12.5%) (Figure 5B, D). Information of resistance rates of antimicrobial agents was listed in Tables 7 and 8.
Pathogenic microorganism and their drug resistance in pediatric tumor patients. (A) The frequency of isolates in pediatric tumor patients with BSI. (B) Antimicrobial susceptibility results of Gram-positive bacteria isolates recovered from blood culture. (C) Antimicrobial susceptibility results of Coagulase-negative Staphylococcus isolates recovered from blood culture. (D) Antimicrobial susceptibility results of Gram-negative bacteria isolates recovered from blood culture.
Comparison of drug resistance of Gram-positive bacteria and Coagulase-negative Staphylococcus in pediatric tumor patients.
| Antimicrobial agents | Drug resistance rate | |
|---|---|---|
| Gram-positive bacteria, % | Coagulase-negative Staphylococcus, % | |
| TCY | 13.6 | 20 |
| MNO | 8.3 | 0 |
| CHL | 12.5 | 21.4 |
| TEC | 0 | 0 |
| VAN | 0 | 0 |
| LNZ | 0 | 0 |
| ERY | 86.7 | 93.3 |
| DAP | 4 | 0 |
| CLI | 25.9 | 20 |
| SXT | 53.8 | 80 |
| MFX | 4 | 7.1 |
| LVX | 7.4 | 13.3 |
| CIP | 13.6 | 20 |
| RIF | 14.8 | 20 |
| GEN | 13.6 | 20 |
| OXA | 59.1 | 86.7 |
| PEN | 71.1 | 100 |
-
TCY, tetracycline; MNO, minocycline; CHL, chloramphenicol; TEC, teicoplanin; VAN, vancomycin; LNZ, linezolid; LNZ, linezolid; ERY, erythromycin; DAP, daptomycin; CLI, clindamycin; SXT, Sulfamethoxazole Tablets; MFX, moxifloxacin; LVX, levofloxacin; CIP, ciprofloxacin; RIF, rifampin; GEN, gentamicin; OXA, oxacillin; PEN, penicillin.
Compare of drug resistance of Gram-positive bacteria and Gram-negative bacteria in pediatric tumor patients.
| Antimicrobial agents | Drug resistance rate | |
|---|---|---|
| Gram-positive bacteria, % | Gram-negative bacteria, % | |
| TCY | 13.6 | 22.2 |
| MNO | 8.3 | 4.8 |
| CHL | 12.5 | 22.2 |
| SXT | 53.8 | 33.3 |
| MFX | 4 | 0 |
| LVX | 7.4 | 6.5 |
| CIP | 13.6 | 18.8 |
| GEN | 13.6 | 12.9 |
| CRO | 0 | 21.4 |
| AMC | 0 | 20 |
| AMP | 66.7 | 75 |
-
TCY, tetracycline; MNO, minocycline; CHL, chloramphenicol; SXT, Sulfamethoxazole Tablets; MFX, moxifloxacin; LVX, levofloxacin; CIP, ciprofloxacin; GEN, penicillin; CRO, ceftriaxone; AMC, Amoxicillin and Clavulanate Potassium; AMP, ampicillin.
Discussion
Pediatric tumors are rare but they represent the most common cause of death in children [33, 34]. Due to the young age and poor immunity of pediatric tumor patients, the risks of morbidity and mortality due to bacterial and other invasive infections during treatment are greatly increased [35], [36], [37]. Therefore, a timely diagnosis of BSI and early use of antibiotics are critical. Traditional diagnostic indicators of infection include factors, such as PCT, hsCRP, IL6, but their reference ranges have been identified in adults, which limit their precise translation to children. Additional factors such as WB and NLR levels can also indicate infection. During bacterial infection, a large number of neutrophils are consumed. Thus, white blood cell counts and left-shift (increase in immature cells) data change dynamically from the onset of infection to recovery, reflecting the progression of bacterial infection [38, 39]. Compared with non-infectious patients, a heightened NLR indicates severe infection or inflammation, and has good diagnostic value in nonneutropenic lung cancer patients [40]. Although several blood markers can reflect infection status, the diagnostic value of infection in children with tumor needs to be further evaluated.
At present, most studies on pediatric tumor patients have focused on hematological cancer, but few have investigated solid tumors. In this retrospective study, we included 159 pediatric tumor patients, most of whom had solid tumors (only three patients had hematological malignancy). The area under the curve of PCT was less than 0.8 and that of hsCRP was less than 0.65 in childhood tumors, but which were generally greater in adults [40, 41]. The AUC of PCT, hsCRP and NLR combined was 0.771, which was only slightly higher than that of PCT (AUC=0.756) (Figure 2A–D). These results confirm the unique advantages of PCT in diagnosing infection and correspond with the findings of other reports [11, 42]. Consistent with this study, PCT, CRP and NLR are closely related to the severity and risk stratification of infection in adult patients and evaluation of their levels can improve the diagnosis, treatment and management of patients with pathogenic microbial infection, and improve the prognosis of patients [43], [44], [45]. Our results showed that PCT and hsCRP levels were significantly upregulated during infection, compared with the uninfected group (Figure 3A, B), this is also consistent with other studies [46]. In addition to significant changes in PCT values during infection, study has found that PCT values were significantly lower in preterm compared to term newborns, and its application in the diagnosis of sepsis in preterm newborns was not as reliable as in term newborns [47]. Moreover, we found a significant correlation between PCT and CRP levels. However, we found no significant correlation between PCT and other routine blood indicators.
Blood cells can be significantly reduced after chemotherapy and radiation. In this study, we found that over 40 percent of pediatric tumor patients had WBC levels below 109/L after radiation or chemotherapy, which may be the main reason for the lack of significant changes in WBC before and during pathogen infection. We also investigated the changes of two APRPs before and during infection. Compared with the control group, PA levels were lower in the infected group, suggesting a negative association with infection and inflammation (Figure 3F). Fg is important for both coagulation and inflammation, suggesting that coagulation cascade factors can be used as a new therapeutic target for human inflammatory diseases. Fg could trigger inflammatory effects when bacterial infection, vascular wall disease, stroke, spinal and injury, brain trauma, and lung and kidney fibrosis [48]. Consistent with this, Fg levels were significantly increased during pathogen infection in our cohort. ROC curves suggested that PA and Fg could not differentiate groups, but they did differentiate the pre-infection state from the infection state within the same individual (Figure 3F, H). Therefore, tracking PA and Fg levels following treatment may help clinicians identify emerging BSI.
To further explore what drives the changes in inflammatory indicators, we divided the pathogenic microorganisms infected in this study into Gram-positive bacteria, Gram-negative bacteria and fungus. Meta-analyses have reported that the concentration of PCT and hsCRP is higher in Gram-negative than Gram-positive bacteria or fungal infections [29]. However, we found that in our cohort, PCT and hsCRP did not differentiate the infection type, this may be due to the small number of pediatric tumor patients and need to be explored further (Figure 4). There were no other statistically significant differences (Supplementary Figure 3). Therefore, the study of inflammatory markers still needs to be explored in more cases. Gram-negative bacteria (E. coli and Pseudomonas aeruginosa) were the most common bacteria in adult tumor patients with BSI [49, 50]. In our cohort, the most common bacteria were Coagulase-negative Staphylococcus (Figure 5A). Finally, we analyzed the drug sensitivity of Gram-positive bacteria, Coagulase-negative Staphylococcus and Gram-negative bacteria, hoping that the results can provide some reference for clinical drug treatment of BSI in children tumor patients (Figure 5B, D).
Funding source: Natural Science Foundation of Shandong Province
Award Identifier / Grant number: ZR2021QH069
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Research funding: This work was supported by the Natural Science Foundation of Shandong Province (ZR2021QH069). The funding organization played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: Authors state no conflict of interest.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Ethical approval: The research related to human use has been complied with all the relevant national regulations, institutional policies and in accordance the tenets of the Helsinki Declaration, and has been approved by the Ethics Committee of the Shandong Cancer Hospital and Institute.
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