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•This was an observational real-world study to validate and compare existing prediction models in order to identify suitable models for breast cancer patients receiving chemotherapy.•Our results found that using only pretreatment hematology values had low sensitivity and positive predictive value for predicting febrile neutropenia.•The results of this study provide important information for clinicians when selecting models to identify patients at high-risk of febrile neutropenia. Breast cancer patients receiving chemotherapy may develop a serious complication called febrile neutropenia (FN). We aimed to validate and compare three existing FN prediction models for breast cancer patients receiving chemotherapy in Taiwan. This was a retrospective observational real-world study. Data were acquired from the clinical research databases of three study hospitals. Breast cancer patients who have received at least one antineoplastic chemotherapy drug were chosen for the analysis. For evaluating the occurrence of FN, we used both broad (a body temperature above 38°C with an absolute neutrophil count (ANC) below 0.5 × 109/L or a body temperature above 38°C with a diagnosis of neutropenia) and narrow definitions (having both fever and neutropenia diagnoses or having both neutropenia and infection diagnoses). Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each selected FN model. Among the 1903 patients identified, when the broad and narrow definitions of FN were applied, 70 (3.7%) and 60 (3.2%) patients developed FN in the first cycle, respectively. Using the broad FN definition, Aagaard's model was the highest in sensitivity (90.0%), followed by Chantharakhit's (40.0%) and Chen's (7.2%); in specificity, Chen's (93.6%) was the highest. In addition, the accuracy was highest with the Chen model (90.4%). All three models’ PPVs were low, ranging from 0.5% to 4.2%, but all three models’ NPVs were over 96.3%. When the narrow FN definition was used, Chantharakhit's model showed a relatively high improvement in sensitivity (53.3%) and PPV (3.9%) while negligible increases or even slight decreases were seen in the other two models and in the other performance indicators of Chantharakhit's model. The results of this study provide important information for clinicians when selecting models to identify patients at high-risk of FN. As the model performance observed was less than satisfactory, improving the prediction ability of the models is needed.

Purpose Prompt antibiotic therapy is standard of care for patients with fever and neutropenia (FN) during chemotherapy for cancer. We systematically reviewed the association between time to antibiotics (TTA) and clinical outcomes. Methods The search covered seven databases; confounding biases and study quality were assessed with the ROBINS-I tool. Safety (death, intensive care unit (ICU) admission, sepsis) and treatment adequacy (relapse of infection, persistence or recurrence of fever) were assessed as primary outcomes. Results Of 6296 articles identified, 13 observational studies were included. Findings regarding safety were inconsistent. Three studies controlling for triage bias showed a possible association between longer TTA and impaired safety. Meta-analysis for TTA ≤ 60 min versus > 60 min was feasible on four studies, with three studies each reporting on death (OR 0.78, 95%CI 0.16–3.69) and on ICU admission (OR 1.43, 95%CI 0.57–3.60). No study reported data on treatment adequacy. Triage bias, i.e. faster treatment of patients with worse clinical condition, was identified as a relevant confounding factor. Conclusion There seems to be an association between longer TTA and impaired safety. More knowledge about TTA effects on safety are important to optimise treatment guidelines for FN. Controlling for triage and other biases is necessary to gain further evidence. Trial registration Registration: PROSPERO [http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42018092948].

IntroductionWhile intensive protocols in onco-haematology have improved survival rates for patients with haematological malignancies, they have also resulted in an increased incidence of infection associated with therapy-induced immunosuppression (including chemotherapy-induced febrile neutropenia; FN). The occurrence of FN, associated with high morbidity and mortality, necessitates broad-spectrum antibiotic therapy, occasioning delayed chemotherapy and resulting in a loss of opportunity for the patient. Considering that without an identified pathogen, a 10% mortality rate can ensue, documentation is essential to the optimisation of antibiotic therapy. However, blood culture (the reference test) is limited for several reasons: such as fastidious culture, antibiotic treatment prior to sampling or insufficient sample volume. Sequencing technologies have led to the development of diagnostic approaches based on the detection of circulating DNA in blood. This study will aim to assess the clinical utility of metagenomic next-generation sequencing (mNGS)-DISQVER technology in detecting pathogenic microorganisms from blood samples of patients undergoing high-risk FN treatment.Methods and analysisThis nationwide, prospective, multicentre, interventional, proof-of-concept clinical trial will enrol 200 patients. Will include patients≥18 years old, treated for malignancy, at high risk of FN (Multinational Association for Supportive Care in Cancer score≤21) with an expected duration of neutropenia≥7 days. Patients who received antibiotic treatment within 24 hours prior to enrolment, have previously participated and/or have enhanced protection will be excluded. The primary outcome will be determined by considering the microorganisms responsible for this FN, weighted by the assessment of an adjudication committee. Secondary outcomes will evaluate patient management depending on the arm. The second secondary outcome will be determined by the duration of conventional assessment, frequency of microorganisms detected during routine care and percentage distribution of theoretical adjustments made to anti-infective treatment based on microorganisms diagnosed using the mNGS-DISQVER tool as compared with conventional practices. Identifying the pathogens responsible for high-risk FN from a blood sample, using an unbiased technique, can provide microbiological documentation and may even reveal unexpected microorganisms in these profoundly immunocompromised patients.Ethics and disseminationThe protocol received approval from the Comité de Protection des Personnes Sud-Méditerranée II. All participants will provide informed consent before participation. The trial has been registered on ClinicalTrials.gov (identifier NCT06075888). The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.Trial registration numberClinicalTrials.gov NCT06075888.

PurposeNeutropenic complications remain the major dose-limiting toxicities of cancer chemotherapy. The aim of this study was to develop and internally validate a comprehensive and easily measurable scoring system for prediction of severe or febrile neutropenia in the first chemotherapy cycle of patients with solid tumors or lymphoma.MethodsThis prospective cohort study included consecutive patients at a tertiary referral hospital. Many clinical and laboratory-independent variables were measured at baseline. A multivariable logistic regression analysis was applied after unadjusted analysis, and the multivariable model was transformed into a simplified risk score based on 6 bootstrapped regression coefficients. The simplified scoring system was internally validated using cross-validation. All statistical tests were two-sided.ResultsA total of 305 patients were enrolled and followed during 1732 chemotherapy cycles. Of these, 259 were eligible for analysis. The multivariable model revealed 6 predictive factors for severe or febrile neutropenia (scores in parentheses): high-risk regimen without colony-stimulating factor (4 points), intermediate-risk regimen without colony-stimulating factor (3 points), age > 65 years and elevated ferritin (3 points), body mass index < 23 kg/m2 and body surface area < 2 m2 (2 points), estimated glomerular filtration rate < 60 mL/min/1.73m2 (2 points), and elevated C-reactive protein (1 point). The receiver operating characteristic curve was 0.832 (95% confidence interval [Cl], 0.767–0.897) for the simplified model and 0.816 (95% Cl, 0.771–0.860) for the cross-validation.ConclusionsWe developed and internally validated a user-friendly prediction model to guide personalized decision-making using available clinical data and few cost-effective laboratory tests. External validation in other centers with different patients is required.

Background Few studies regarding infectious causes of febrile neutropenia (FN) in Mexico are available. Aims We aimed to describe clinical and microbiological characteristics of FN episodes during induction chemotherapy in adults with acute leukemia. Methods and Results This retrospective cohort from a Mexican tertiary care center included adults with newly diagnosed acute leukemia between January 2014, and December 2018. Clinical and microbiological characteristics were summarized using descriptive statistics. Univariate analyses for associations between clinical characteristics and FN and/or death were made; logistic regression analysis was performed to assess relationships with FN. Kaplan–Meier survival estimates were modeled for antimicrobial prophylaxis and FN. Ninety‐five patients were included. Median age was 28 (IQR 20–43), 49 (52%) were males, and 74 (78%) developed FN (74/95). Among these, 98% had an identified source of infection (73/74) and 65% had >1. Common infections were urinary tract infection (24%), bacterial sinusitis (20%), and bacterial pneumonia (19%). Gram‐negatives were the most frequently isolated microorganisms (69%), followed by Gram‐positives (21%), and fungi (9%). Antimicrobial prophylaxis was inversely associated with FN (aOR = 0.07, CI 0.008–0.060, p = 0.02). Invasive fungal diseases were associated with 30‐day mortality (aOR = 9.46, 95% CI 1.66–54.05). Conclusion Infections caused 98% of the FN episodes. Gram‐negative bacteria are the most common pathogens.

PurposeTo explore the efficacy and safety of daily administration of recombinant human granulocyte colony-stimulating factor (rhG-CSF), and a single subcutaneous injection of polyethylene glycol recombinant human granulocyte colony-stimulating factor (PEG-rhG-CSF, a sustained-duration rhG-CSF) in neutropenia induced after chemotherapy.MethodsEach patient received two cycles of chemotherapy. In the trial cycle, the patients received a single subcutaneous injection of PEG-rhG-CSF 100 µg/kg 72 h after completion of chemotherapy; and in the control cycle, rhG-CSF 5 µg/kg/day was subcutaneous injected once a day which began 72 h after completion of chemotherapy for continued 14 days or until the absolute neutrophil count (ANC) was ≥ 10.0 × 109/l twice. Therapeutic effect on primary endpoint was the incidence and duration of grade IV ANC neutropenia: comparing the incidence and the mean time of duration of PEG-rhG-CSF with those of rhG-CSF under the circumstance of ANC < 0.5 × 109/l. The immune populations evaluated included, CD3+ T cells, CD4+ T cells, CD8+ T cells, and NK cells.ResultsAfter chemotherapy, comparing to PEG-rhG-CSF, the CD4/CD8 ratio (0.84 ± 0.19 vs.1.06 ± 0.25) and the number of NK cells of rhG-CSF group (12.18 ± 2.13 vs. 15.78 ± 2.57) decreased significantly. The number of NK cells (12.18 ± 2.13 vs. 13.78 ± 2.57) of rhG-CSF group after chemotherapy is significantly less than that before chemotherapy, and the number of CD3+ (54.31 ± 7.51 vs. 57.96 ± 5.55), CD4+ (26.28 ± 6.25 vs. 29.48 ± 6.44), CD8+ (29.97 ± 6.47 vs. 31.68 ± 5.96) is lower than that before chemotherapy in rhG-CSF group, but the difference is not significant.ConclusionThe efficacy and side effects of a single subcutaneous injection of PEG-rhG-CSF were similar to that of rhG-CSF multiple administrations. PEG-rhG-CSF may have the effect of promoting immune function repairing.

Background Febrile neutropenia (FN) is a common occurrence during chemotherapy. Granulocyte colony-stimulating factors (G-CSFs) can significantly reduce the risk of FN. International guidelines recommend G-CSF for patients receiving chemotherapy with FN risk of ≥20% or 10% to 20% with defined risk factors. Prophylaxis is not typically recommended for FN risk of < 10%; however, few studies have investigated FN incidence in lower-risk patients in real-world settings and tried to identify higher-risk subgroups. Methods This real-world prospective, observational, multinational study aims to estimate the rate of development of FN with a chemotherapy line expected to be associated with a 10% to 20% risk of FN. Eligible patients (> 18 years of age) will have a solid tumour or Hodgkin/non-Hodgkin lymphoma and a planned chemotherapy regimen with expected risk of FN of 10% to 20% (according to published guidelines). Patients will be observed for the duration of the chemotherapy line (first cycle administered without FN prophylaxis). Primary endpoint is incidence of FN after the first chemotherapy cycle. Secondary outcomes include: FN-associated morbidity and mortality; time to first FN occurrence; other FN risk factors and impact of FN on quality of life. A risk model using occurrence of FN as a binary outcome will be developed. Data will be stratified by age, comorbidities and other risk factors. Discussion This study will provide insight into the real FN risk for common chemotherapy regimens and predictive factors for FN, including patients generally excluded from randomised clinical trials, from which reported FN rates have been variable. This study builds on knowledge of predictive factors from other research and will provide information on patients with 10% to 20% FN risk.

Purpose To explore whether monocytes, lymphocytes, and platelets have a predictive value for short-term neutrophil changes in patients with severe neutropenia (SN) induced by chemotherapy. Methods Complete blood counts (CBC) were collected from a total of 62 patients with chemotherapy-induced SN from December 2013 to March 2018. CBCs at intervals of 1 day, 2 days, 3 days, 4 days, and 5 days were recorded, and logistic regression analyses were performed to determine whether the monocyte percentage (MP), absolute monocyte count (AMC), lymphocyte percentage (LP), absolute lymphocyte count (ALC), or platelet count (PC) were correlated with short-term neutrophil changes. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for parameters with a P value < 0.05. Results The MP was significantly correlated with changes in neutrophils for intervals of 1 to 5 days, while the LP was significantly correlated with changes in neutrophils for intervals of 2 to 5 days. A cutoff value of 6.5% for the MP yielded a sensitivity of 80%, a specificity of 88.6%, and an AUC of 0.908 for predicting an increase in neutrophils on the third day. A cutoff value of 14.75% for the LP yielded a sensitivity of 93.3%, a specificity of 70.3%, and an AUC of 0.812 for predicting an increase in neutrophils on the sixth day. Conclusions In chemotherapy-induced neutropenia patients, the MP is the best predictor of short-term neutrophil changes. Close monitoring and proper interpretation of the MP and LP are informative in managing chemotherapy-induced neutropenia.

Purpose Chemotherapy-induced neutropenia is a serious and potentially life-threatening consequence of cancer treatment. Prophylactic treatment with granulocyte-colony stimulating factor (G-CSF) decreases the incidence of febrile neutropenia, the rate of hospitalization, and the use of antibiotics in patients at risk. The aim of this study was to assess efficacy, safety, and use of Zarzio ® —biosimilar of Neupogen ® (G-CSF; filgrastim)—in prophylaxis of chemotherapy-induced neutropenia in current practice in cancer patients. Methods We conducted an observational, prospective, longitudinal, and multicentric study in France. The incidence of neutropenia was evaluated at each cycle of chemotherapy. Results One hundred eighty-four patients (women, 64.7 %; mean age, 61.7 years) with solid tumor (89.7 %; breast cancer, 50.5 %) or non-Hodgkin lymphoma (10.3 %) were included. The risk of febrile neutropenia based on chemotherapy regimen was >20 % for 32.1 % of patients. No case of febrile neutropenia was reported. Neutropenia was the cause of hospitalization and/or antibiotic therapy in 10 patients. The most frequent adverse events related to Zarzio ® were pain, in particular bone pain. No serious adverse event related to Zarzio ® was reported. Conclusion The results obtained in real-life conditions confirm that Zarzio ® is efficient and well tolerated in cancer patients.

Background The existing risk prediction models for chemotherapy‐induced febrile neutropenia (FN) do not necessarily apply to real‐life patients in different healthcare systems and the external validation of these models are often lacking. Our study evaluates whether a machine learning‐based risk prediction model could outperform the previously introduced models, especially when validated against real‐world patient data from another institution not used for model training. Methods Using Turku University Hospital electronic medical records, we identified all patients who received chemotherapy for non‐hematological cancer between the years 2010 and 2017 (N = 5879). An experimental surrogate endpoint was first‐cycle neutropenic infection (NI), defined as grade IV neutropenia with serum C‐reactive protein >10 mg/l. For predicting the risk of NI, a penalized regression model (Lasso) was developed. The model was externally validated in an independent dataset (N = 4594) from Tampere University Hospital. Results Lasso model accurately predicted NI risk with good accuracy (AUROC 0.84). In the validation cohort, the Lasso model outperformed two previously introduced, widely approved models, with AUROC 0.75. The variables selected by Lasso included granulocyte colony‐stimulating factor (G‐CSF) use, cancer type, pre‐treatment neutrophil and thrombocyte count, intravenous treatment regimen, and the planned dose intensity. The same model predicted also FN, with AUROC 0.77, supporting the validity of NI as an endpoint. Conclusions Our study demonstrates that real‐world NI risk prediction can be improved with machine learning and that every difference in patient or treatment characteristics can have a significant impact on model performance. Here we outline a novel, externally validated approach which may hold potential to facilitate more targeted use of G‐CSFs in the future. There are several risk prediction models for chemotherapy‐induced neutropenia, but the existing models may not always apply to real‐life patients in different healthcare systems. A novel machine learning‐based model improved neutropenic infection risk prediction as compared to previously introduced models. Our validated model may facilitate more targeted use of granulocyte colony‐stimulating factors in the future.