| Literature DB >> 35892511 |
Estera Boeriu1,2, Alexandra Borda2, Dan Dumitru Vulcanescu3, Vlad Sarbu3, Smaranda Teodora Arghirescu1,2, Ovidiu Ciorica4, Felix Bratosin5, Iosif Marincu5, Florin George Horhat3.
Abstract
Infectious diseases are associated with a high morbidity and mortality rate among pediatric cancer patients undergoing treatment or receiving a transplant. Neutropenia represents a potentially fatal complication of cancer treatment and is associated with a high risk of developing bacterial infections. Although febrile neutropenia (FN) can affect both adults and children, the latter has a higher chance of infections with an unknown origin. Prompt empiric broad-spectrum antibiotic administration is collectively considered the best therapeutic approach. This review aims to analyze the latest works from the literature regarding the therapeutic strategies, schemes, and approaches and the efficacy of these in pediatric febrile neutropenia. Following PRISMA guidelines, an advanced search on PubMed, Scopus, and Cochrane Library, using the keywords "febrile neutropenia", "pediatric", "cancer", and "oncology", was performed. A total of 197 articles were found to be eligible. After screening the abstracts and excluding unfit studies, 16 articles were analyzed. There were eight retrospective studies, five prospective studies, and two clinical trials. Altogether, these studies have described around 5000 episodes of FN. The median age of the participants was 7.6 years, and the underlying condition for most of them was acute leukemia. The infectious agent could only be determined in around one-fifth of cases, from which 90% were of bacterial origin. As such, empirical broad-spectrum antibiotics are used, with the most used treatment scheme comprising third- and fourth-generation cephalosporins and antipseudomonal penicillins. In order to improve the treatment strategies of FN episodes and to successfully de-escalate treatments toward narrower-spectrum antibiotics, hospitals and clinics should increase their efforts in identifying the underlying cause of FN episodes through blood culture urine culture and viral tests, wherever infrastructure enables it.Entities:
Keywords: broad-spectrum antibiotics; febrile neutropenia; pediatric oncology
Year: 2022 PMID: 35892511 PMCID: PMC9394251 DOI: 10.3390/diagnostics12081800
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418
Figure 1PRISMA flowchart for the selection process.
Studies included in the analysis.
| No. | Study Year | Study Type | No. of Studied FN Episodes | No. of | Quality Score |
|---|---|---|---|---|---|
| 1 [ | 2021 | Prospective observational | 204 | 105 | 11 |
| 2 [ | 2020 | Retrospective cohort | 667 | 268 | 10 |
| 3 [ | 2020 | Randomized multicentric clinical trial | 117 | 69 | 12 |
| 4 [ | 2019 | Retrospective cross-sectional | 135 | 135 | 10 |
| 5 [ | 2020 | Retrospective cohort | 95 | 95 | 11 |
| 6 [ | 2020 | Retrospective cohort | 199 | 118 | 10 |
| 7 [ | 2020 | Retrospective cohort | 225 | 164 | 10 |
| 8 [ | 2020 | Retrospective cohort | 585 | 265 | 13 |
| 9 [ | 2020 | Retrospective and prospective descriptive | 563 | 267 | 11 |
| 10 [ | 2019 | Prospective randomized, open-labeled, controlled | 118 | 70 | 12 |
| 11 [ | 2020 | Prospective cohort | 118 | 118 | 9 |
| 12 [ | 2020 | Prospective, multicentric, non-interventional | 858 | 462 | 12 |
| 13 [ | 2019 | Retrospective | 194 | 67 | 11 |
| 14 [ | 2020 | Prospective, randomized | 394 | 99 | 10 |
| 15 [ | 2019 | Non-blinded randomized controlled clinical trial | 100 vs. 76 | 176 | 10 |
| 16 [ | 2021 | Retrospective monocentric descriptive | 310 | 186 | 11 |
Demographic data extracted from the studies.
| No. | Male % | Age * | Malignancy | ANC Before Treatment n (Mean) | Central Line n | Last Chemo-Therapy Range (Median) | Fever Days n (Median) |
|---|---|---|---|---|---|---|---|
| 1 [ | 54.91 | 7.83 | Leukemia: 157, Lymphoma: 7, Others: 40 | <100: 95 (NR), 100–500: 86 (223) | NR | NR | NR |
| 2 [ | 53.84 | 10 (median) | ALL 203, AML 115, lymphoma 68, neuroblastoma 110, others 171 | 667 (NR) | NR | <14 d: 43 | 1–20 (4) |
| 3 [ | 41.02 | 7 | ALL 56%; Rhabdomyosarcoma 9%; AML 7% | 149 (264) | NR | NR | NR |
| 4 [ | 68.88 | 5.5 | ALL: 71, AML: 10, NHL: 10, Blastomas: 17, Sarcomas: 15, Other: 12 | 135 (120) | NR | <14 d: 88 | NR |
| 5 [ | 57.89 | 6 (median) | ALL: 57, AML 12, Non-leukemia: 26 | 95 (180) | 16 | 0–147 (8) | 0–30 (1) |
| 6 [ | 49.2 | 8.8 | Leukemia: 23, Lymphoma: 7, Sarcoma: 29, Retinoblastoma: 7, Neuroblastoma: 6, Others: 45 | 199 (NR) | 180 | NR | NR |
| 7 [ | 50.98 | 7.75 | ALL: 30, AML:41, Lymphoma: 25, Neuroblastoma: 33, Nephroblastomas: 5, Hepatoblastoma: 4, Other: 66 | <100: 184 (NR), <500: 194 (NR) | 154 | 1–23 (11) | 0–19 (1.2) |
| 8 [ | NR | 11 | ALL: 173, AML: 84, Lymphoma: 66, Neuroblastoma: 103, Other: 117 | 204 (NR) | NR | 384 | NR |
| 9 [ | 56.55 | 5.1 (median) | ALL: 114, AML: 44, Lymphoma: 20, Neuroblastoma: 17, Hepatoblastoma: 4, Retinoblastoma: 4, Sarcoma: 16, Other: 48 | 267 (170) | 226 | 0–148 (10) | 4.8 ± 4.7 (mean ± SD) |
| 10 [ | 57.62 | 7 (median) | ALL: 55, AML:10, Lymphoma: 8, Neuroblastoma: 9, Sarcoma: 8 | 90 (122) | 0 | NR | 1–4 (2) |
| 11 [ | 66.94 | 4.7 (median) | Hematological: 82, Solid tumors: 36 | 118 (110) | NR | <7 d: 85, >7 d: 33 | 4–6 (5) |
| 12 [ | 51.63 | 5.8 (median) | ALL: 375, AML: 67, NHL: 55, Hodgkin: 11, Neuroblastoma: 48, Medulloblastoma: 37, Nephroblastoma: 19, Sarcoma: 177, Other: 88 | 858 (NR) | 845 | NR | NR |
| 13 [ | 47.76 | 6.7 | ALL: 44, AML: 23 | 67 (NR) | 184 | NR | NR |
| 14 [ | 63.63 | 9.9 (median) | ALL: 52, AML: 12, NHL:9, Solid tumors: 14, Other: 11 | 394 (103) | 380 | NR | NR |
| 15 [ | 59.55 | 9.5 (median) | ALL: 24, AML: 10, NHL: 40, Solid tumors: 76, Other: 26) | 176 (NR) | NR | NR | NR |
| 16 [ | NR | 5.3 | ALL: 79, AML: 21, NHL:11, Solid tumors: 114, Others: 37 | NR | 310 | NR | NR |
* Data reported as mean, unless specified differently; ALL, acute lymphocytic leukemia; AML, acute myeloid leukemia; NHL, non-Hodgkin lymphoma; NR, not reported.
Etiologic agents’ data extracted from the studies.
| No. | Infection | Hospital Stay/Duration of Antibiotic Therapy | Etiological Agent | MDR Strains | Most Frequent Bacterium |
|---|---|---|---|---|---|
| 1 [ | Chest: 40, BSI: 14, GI: 29, Others: 36, Unknown: 69 | 13 ± 8.5 | Bacterial: 27 (64.5% G-), Viral: 7, Fungal: 3 | NR | Klebsiella pneumoniae |
| 2 [ | BSI: 143 | NR | G+ 95, G- 64, Other Bacteria 17, Fungal: 5 | 21 | Alpha-hemolytic streptococcus: 35 |
| 3 [ | NR | 4.25 ± 2.5 | NR | NR | NR |
| 4 [ | Chest: 15, GI: 5, Urinary: 2, Unknown: 113 | NR | NR | NR | NR |
| 5 [ | BSI: 12, Urinary: 8, GI: 2, Respiratory: 8, Other: 2 | NR | G- bacteria: 14, G+ bacteria: 5, Viral: 2, Fungal: 5 | 2 | Klebsiella pneumoniae |
| 6 [ | NR | NR | G- bacteria: 35, G+ bacteria: 27, Fungal: 8 | NR | Klebsiella pneumoniae (14.2%) and Pseudomonas aeruginosa (14.2% |
| 7 [ | BSI: 221, Skin/soft tissue: 14, GI: 30, Oral: 16, Other: 5 | 5 to 93 | G- bacteria: 132, G+ bacteria: 93 | 60 | Escherichia coli: 98 |
| 8 [ | BSI: 141 | 10 (median) | G- bacteria: 64, G+ bacteria: 199, Fungal: 47 | NR | NR |
| 9 [ | NR | NR | Bacterial: 154, Viral: 32, Fungal: 27 | NR | NR |
| 10 [ | BSI: 6, Urinary: 11 | 7 to 12 | G- bacteria: 13, G+ bacteria: 4 | NR | Escherichia coli: 3 |
| 11 [ | Respiratory: 81, GI: 10, Urinary: 1, Unknown: 26 | 5 to 11 | NR | NR | NR |
| 12 [ | NR | NR | NR | NR | NR |
| 13 [ | BSI: 67 | 2 to 24 | G- bacteria: 23, G+ bacteria: 16 | 5 | Escherichia coli: 10 |
| 14 [ | NR | 2 to 19 | G- bacteria: 16, G+ bacteria: 8 | 4 | Staphylococcus. aureus: 4 |
| 15 [ | NR | NR | G- bacteria: 14 | 2 | Pseudomonas aeruginosa: 5 |
| 16 [ | BSI: 310 | 10 to 21 | G- bacteria: 25.2%, G+ bacteria: 68.4%, | 65 | Coagulase-Negative Staphylococci: 34 |
BSI: bloodstream infections; NR: not reported; NA: not applicable; G-: Gram negative; G+: Gram positive.
Treatment data extracted from the studies.
| No. | Most Used Antibiotic | Second Most Used Antibiotic | Time to Antibiotic Administration (min) | Treatment Modifications | Other |
|---|---|---|---|---|---|
| 1 [ | Cefepime | Meropenem + Vancomycin | 47.17 | NR | NR |
| 2 [ | Ceftazidime: 50% | Ceftazidime + Vancomycin: 33% | NR | NR | Antifungals |
| 3 [ | Cefepime | Cefixime | NR | 3 | NA |
| 4 [ | Ceftriaxone + Gentamycin: 97 | Ceftriaxone: 6 | NR | 22 | Antiviral: 30, Antifungal: 52 |
| 5 [ | Ceftazidime + Amikacin | Piperacillin/Tazobactam | <120 | NR | NR |
| 6 [ | Cefepime | Meropenem or Piperacillin/Tazobactam | NR | NR | NR |
| 7 [ | Cefepime: 121 | Cefepime + Amikacin: 83 | 120 (median) | 57 | NR |
| 8 [ | Ceftazidime + Vancomycin | Cefepime + Vancomycin | NR | NR | Antifungals |
| 9 [ | NR | NR | NR | NR | Antifungal: 123 |
| 10 [ | Piperacillin/Tazobactam: 59 | Ceftazidime + Amikacin: 59 | 30 | 44 | Antifungal: 21 |
| 11 [ | Amoxicillin/Clavulanate + Amikacin (respiratory), Cefoperazone/Sulbactam + Metronidazole (GI) | Meropenem + Vancomycin or Teicoplanin | NR | 34 | Antifungal: 19 |
| 12 [ | NR | NR | 552 | NR | Antiviral: 72, Antifungal: 290 |
| 13 [ | Cefepime: 157 | Cefepime + Vancomycin: 16 | NR | 35 | NA |
| 14 [ | Meropenem: 200 | Piperacillin/Tazobactam: 193 | NR | NA | NA |
| 15 [ | Intermittent Piperacillin/Tazobactam: 100 | Continuous Piperacillin/Tazobactam: 76 | NR | 6 | NA |
| 16 [ | Vancomycin: 134 | Amikacin: 90 | NR | NR | Antifungal: 44 |
Main outcomes as reported from the studied records.
| No. | Persistent Fever | Central Line Removal | Sepsis | ICU | Deaths | Treated |
|---|---|---|---|---|---|---|
| 1 [ | NR | NR | 32 | 23 | 4 | 200 |
| 2 [ | NR | NR | NR | 4 | 35 | 139 |
| 3 [ | 1 | NR | NR | NR | 0 | 117 |
| 4 [ | 2 | NR | NR | NR | 7 | 95 |
| 5 [ | NR | NR | 3 | 11 | 0 | 95 |
| 6 [ | NR | NR | NR | 8 | 1 | 117 |
| 7 [ | NR | 1 | 16 | 4 | 0 | 225 |
| 8 [ | NR | NR | NR | 87 | 8 | 577 |
| 9 [ | NR | NR | NR | 78 | 21 | 542 |
| 10 [ | NR | NR | NA | NR | 0 | 118 |
| 11 [ | 11 | NR | 5 | 8 | 6 | 112 |
| 12 [ | NR | NR | 13 | 24 | 4 | 424 |
| 13 [ | NR | 1 | 1 | 5 | 1 | 66 |
| 14 [ | NR | NR | NR | NR | 0 | 288 |
| 15 [ | 1 | NR | 1 | NR | 2 | 136 |
| 16 [ | NR | 60 | 14 | 0 | 0 | 310 |
Figure 2Pathogens involved in the microbiologically documented infections.
Figure 3Individual look upon the pathogens involved in the MDIs: Alali M. et al. (2020) [13]; Suttitossatam I. et al. (2020) [15]; Janssens K.P. et al. (2020) [4]; Lee N.H. et al. (2020) [16]; Kamonrattana R. et al. (2019) [19]; Reinecke J. et al. (2018) [22]; Kobayashi R. et al. (2020) [23]; Fortino S.S. et al. (2019) [24]; Raad C. et al. (2021) [25].