A prospectively validated nomogram for predicting the risk of chemotherapy-induced febrile neutropenia: a multicenter study

Can MASCC and CISNE scores predict delays of lung cancer chemotherapy after febrile neutropenia?

BACKGROUND

Febrile neutropenia (FN) during cancer chemotherapy can lead to morbidity and mortality. The Multinational Association of Supportive Care in Cancer (MASCC) and clinical index of stable febrile neutropenia (CISNE) scores have been widely used to predict the risk of severe medical complications in patients with FN; however, there are few tools for predicting chemotherapy delays or discontinuation after FN.

METHODS

Patients admitted to two university hospitals between 2014 and 2018 with a FN diagnosis during the first cycle of chemotherapy for lung cancer were reviewed retrospectively.

RESULTS

Among 539 patients who received 813 courses of chemotherapy for lung cancer, 49 (9%) developed FN during the first treatment cycle. Although all the patients recovered from their primary infection, 19 patients (38.8%) developed serious medical complications, 11 (22.4%) were unable to resume chemotherapy and one (2.0%) declined to resume chemotherapy, and nine (18.4%) died within 90 days. Patients who failed to resume chemotherapy had a lower MASCC score (median 8.5 vs. 17, p < 0.01) and a higher CISNE score (median 3 vs. 1, p < 0.01) at the onset of FN. The specificity to predict the patient who failed to resume chemotherapy was 90% or more with MASCC score ≤9 or CISNE score ≥3, with the sensitivity of 61%. MASCC score ≤ 16 can also be a sensitive indicator with the sensitivity and specificity of 89 and 52%, respectively.

CONCLUSION

The MASCC and CISNE scores are useful in identifying lung cancer patients who are unable to resume chemotherapy as scheduled after the onset of FN.

Mitigating acute chemotherapy-associated adverse events in patients with cancer

Despite the enthusiasm surrounding novel targeted agents and immunotherapies, chemotherapy remains the mainstay treatment for most human malignancies, either alone or in combination. Yet, the burden of chemotherapy-associated adverse events (CAAEs) remains high and, importantly, is associated with considerable morbidity, mortality and costs that affect patients across multiple dimensions, including physical, emotional and social functioning. CAAEs can directly affect patient outcomes and indirectly increase the risk of cancer recurrence by compromising treatment intensity and continuity. Systematic efforts to identify and critically summarize the evidence on management approaches for CAAEs remain limited. Herein, we review the most common acute CAAEs having a major effect on survival, quality of life, function and/or continuation of optimal therapy. We focus on selected acute toxicities that occur during treatment, summarizing their underlying pathophysiology, multifactorial aetiologies, evidenced-based treatments, prevention strategies and management recommendations. We also summarize the available evidence on risk factors, validated risk assessment tools and other efforts to optimize symptom control in patients most likely to benefit in order to personalize the prevention and treatment of acute CAAEs. Finally, we discuss innovative symptom monitoring and supportive care interventions that are under development to further improve the outcomes of patients with cancer.

Prospective external validation of an updated algorithm to quantify risk of febrile neutropenia in cancer patients after a cycle of chemotherapy

PURPOSE

Febrile neutropenia resulting from chemotherapy is a significant cause of morbidity and mortality in cancer patients. We had previously published the associates of the risk of febrile neutropenia, and this study now extends and modifies the previous model as well as tests its external validity.

METHODS

We have recruited documented febrile neutropenia cases with solid tumors, in addition to a selected control group of cancer patients from one institution treated between 2015 and 2019. We then united our sample with our previously published original derivation group, to modify and update our previous model by logistic regression analysis. Additionally, consecutive cancer patients from 5 institutions were recruited in 2020 to test external validity of the resultant algorithm.

RESULTS

A total of 4075 cycles of chemotherapy in 1282 cases were recruited in the updated, new model derivation group, and a total of 8 variables were selected for the updated algorithm. In the new external validation group, 653 cycles of chemotherapy in 624 patients were analyzed, to indicate that after cycles without prophylactic granulocyte colony-stimulating factor (GCSF) usage, the algorithm yielded a sensitivity value of 91%, specificity of 40%, and an area under curve (AUC) figure of 0.78, when a risk cutoff threshold value of ≥ 0.20 is chosen. This algorithm is now embedded in a web application for free clinical use.

CONCLUSION

Our algorithm identifies and quantifies the risk of febrile neutropenia in cancer patients. Further studies are required to improve this model with additional predictors.

Development and Internal Validation of a Nomogram Used to Predict Chemotherapy-Induced Neutropenia in Non-Small Cell Lung Cancer Patients: A Retrospective Cohort Study

Purpose

This study was designed to develop a nomogram for predicting neutropenia caused by chemotherapy in non-small cell lung cancer (NSCLC) patients.

Patients and Methods

Information was collected from 376 patients between November 2017 and November 2020. The endpoint was chemotherapy-induced neutropenia (absolute neutrophil count <2×10⁹/L). Logistic regression was performed to appraise the prognostic value of each potential predictor. Risk predictors from the final predictive model were used to generate a nomogram. C-index and calibration curve as well as decision curve analysis (DCA) was applied to evaluate model performance.

Results

The multivariate regression model ultimately included three predictors: previous radiotherapy, the current cycle of chemotherapy and neutrophil counts before current chemotherapy. A nomogram was developed and displayed better discrimination (with C-index of 0.875 in the development group and 0.907 in the validation group). Favorable consistency was shown between predicted probability and observed probability in the calibration curves. DCA illustrated that when the threshold probability was 8%-90%, the predictive model provided a net benefit relative to the intervention-all or the intervention-none strategy, indicating that the nomogram had favorable potential clinical utility.

Conclusion

This nomogram will be an available tool to quantify the risk of neutropenia after chemotherapy in patients who suffer from NSCLC and deserves further external validation.

Predictive Models of Fever, ICU Transfer, and Mortality in Hospitalized Patients With Neutropenia

Supplemental Digital Content is available in the text.

Neutropenia is a common side effect of myelosuppressive chemotherapy and is associated with adverse outcomes. Early Warning Scores are used to identify at-risk patients and facilitate rapid clinical interventions. Since few Early Warning Scores have been validated in patients with neutropenia, we aimed to create predictive models and nomograms of fever, ICU transfer, and mortality in hospitalized neutropenic patients.

Machine learning improves the prediction of febrile neutropenia in Korean inpatients undergoing chemotherapy for breast cancer

Febrile neutropenia (FN) is one of the most concerning complications of chemotherapy, and its prediction remains difficult. This study aimed to reveal the risk factors for and build the prediction models of FN using machine learning algorithms. Medical records of hospitalized patients who underwent chemotherapy after surgery for breast cancer between May 2002 and September 2018 were selectively reviewed for development of models. Demographic, clinical, pathological, and therapeutic data were analyzed to identify risk factors for FN. Using machine learning algorithms, prediction models were developed and evaluated for performance. Of 933 selected inpatients with a mean age of 51.8 ± 10.7 years, FN developed in 409 (43.8%) patients. There was a significant difference in FN incidence according to age, staging, taxane-based regimen, and blood count 5 days after chemotherapy. The area under the curve (AUC) built based on these findings was 0.870 on the basis of logistic regression. The AUC improved by machine learning was 0.908. Machine learning improves the prediction of FN in patients undergoing chemotherapy for breast cancer compared to the conventional statistical model. In these high-risk patients, primary prophylaxis with granulocyte colony-stimulating factor could be considered.

Preoperative Nutritional Status Contributes to the Development of Neutropenia Event in Patients With Gastric Cancer Receiving CAPEOX Adjuvant Chemotherapy

Purpose: The aim of this study is to evaluate the risk factors for ≥ grade 3 neutropenia in gastric cancer patients receiving postoperative adjuvant chemotherapy. Methods: This is a retrospective study from a single tertiary referral hospital. Patients diagnosed with gastric cancer who met the inclusion criteria were included in this study. Baseline and clinicopathological characteristics of the patients were collected. Patients were followed-up for 12 months and the incidence of neutropenia were recorded. Factors associated with neutropenia of chemotherapy in cycle 1 were investigated. Results: A total of 202 patients with gastric cancer were included. All patients received oxaliplatin plus oral capecitabine (CAPEOX) as the adjuvant chemotherapy. The incidence of ≥ grade 3 neutropenia is 11.9% (24/202) in cycle 1 among all patients. In multivariate analysis, independent risk factors for ≥ grade 3 neutropenia were serum prealbumin level (p = 0.041), prognostic nutritional index (PNI) (p = 0.049) and pre-cycle neutrophil count (p = 0.007). Conclusions: Our findings for the first time showed that nutritional parameter as prealbumin level and PNI are independent risk factors for neutropenia in gastric cancer patients receiving adjuvant chemotherapy. This may provide evidence for further investigation on prophylaxis use of granulocyte colony-stimulating factor in selected high-risk patients to prevent sever neutropenia in cycle 1 of adjuvant chemotherapy.

Predictive value of monocytes and lymphocytes for short-term neutrophil changes in chemotherapy-induced severe neutropenia in solid tumors

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.

Development and Validation of a Risk Score for Febrile Neutropenia After Chemotherapy in Patients With Cancer: The FENCE Score

BACKGROUND

Febrile neutropenia (FN) after chemotherapy causes a high burden of morbidity and mortality. We aimed to develop and validate a risk score to predict FN in the first cycle of chemotherapy.

METHODS

We included patients with solid cancers and diffuse large B-cell lymphomas at Rigshospitalet, University of Copenhagen, 2010-2016. Predictors of FN were analyzed using Poisson regression and random split-sampling.

RESULTS

Among 6294 patients in the derivation cohort, 360 developed FN. Female sex, older age, cancer type, disease stage, low albumin, elevated bilirubin, low creatinine clearance, infection before chemotherapy, and number of and type of chemotherapy drugs predicted FN. Compared with those at low risk (n = 2520, 40.0%), the incidence rate ratio of developing FN was 4.8 (95% confidence interval [CI] = 2.9 to 8.1), 8.7 (95% CI = 5.3 to 14.1) and 24.0 (95% CI = 15.2 to 38.0) in the intermediate (n = 1294, 20.6%), high (n = 1249, 19.8%) and very high (n = 1231, 19.6%) risk groups, respectively, corresponding to a number needed to treat with granulocyte colony-stimulating factors to avoid one FN event in the first cycle of 284, 60, 34 and 14. The discriminatory ability (Harrell's C-statistic = 0.80, 95% CI = 0.78 to 0.82) was similar in the validation cohort (n = 3163) (0.79, 95% CI = 0.75 to 0.82).

CONCLUSION

We developed and internally validated a risk score for FN in the first cycle of chemotherapy. The FENCE score is available online and provides good differentiation of risk groups.

Pegfilgrastim for primary prophylaxis of febrile neutropenia in breast cancer patients undergoing TAC chemotherapy

Purpose

Primary prophylaxis with granulocyte colony-stimulating factor can effectively prevent febrile neutropenia (FN) during breast cancer treatment. The aims of this study were to evaluate the incidence of FN and the ANC profile in patients undergoing chemotherapy and pegfilgrastim primary prophylaxis.

Methods

Patients receiving 6 cycles of adjuvant docetaxel, doxorubicin, and cyclophosphamide (TAC) chemotherapy were included in this study. Pegfilgrastim was administered with analgesics 24 hours after treatment. Laboratory tests were performed on day 0 (before chemotherapy) and ANC was measured daily starting day 5 until it were restored to 1,000/mm³. Bone pain was checked via the numeral rating scale (NRS).

Results

A total of 61 patients and 366 cycles were evaluated. Mean age was 49.2 ± 7.1 years. FN was seen in 5 patients (16.4%) and 12 cycles (3.3%) with pegfilgrastim. Grades 3 and 4 neutropenia was seen in 91.5% of cycles with FN. The ANC nadir was most commonly seen at day 7 and the mean ANC nadir depth was 265.7/m³. Age was negatively correlated with nadir depth (r = −0.137, P = 0.009). Severe pain higher than NRS 7 occurred in less than 20% of patients after the administration of pegfilgrastim.

Conclusion

Incidence of FN was low during the chemotherapy by primary prophylaxis with pegfilgrastim. The ANC nadir was seen on day 7 after chemotherapy. Bone pain with pegfilgrastim was well tolerated during TAC chemotherapy.

Pretreatment monocyte counts and neutrophil counts predict the risk for febrile neutropenia in patients undergoing TPF chemotherapy for head and neck squamous cell carcinoma

Background

Febrile neutropenia (FN) is the most serious hematologic toxicity of systemic chemotherapy. However, accurate prediction of FN development has been difficult because the risk varies largely depending on the chemotherapy regimen and various individual factors.

Methods

We retrospectively analyzed diverse clinical factors including pretreatment hematological parameters to clarify the reliable predictors of FN development during chemotherapy with a docetaxel, cisplatin, and fluorouracil (TPF) regimen in patients with head and neck squamous cell carcinoma.

Results

Among the 50 patients, grade ≥3 neutropenia, grade 4 neutropenia, and FN developed in 36 (72%), 21 (42%), and 12 (24%) patients, respectively. Multivariate logistic regression revealed that a pretreatment absolute monocyte count (AMC) <370/mm³ is an independent predictor of TPF chemotherapy-induced FN (odds ratio=6.000, p=0.017). The predictive performance of the model combining AMC and absolute neutrophil count (ANC), in which the high-risk group was defined as having an AMC <370/mm³ and/or ANC <3500/mm³, was superior (area under the curve [AUC]=0.745) to that of the model with a cutoff for AMC alone (AUC=0.679).

Conclusions

On the basis of our results, we recommend primary prophylactic use of granulocyte colony-stimulating factor and/or antibiotics selectively for patients predicted to be at high risk for TPF chemotherapy-induced FN.