Dataset Information

Clinical predictive models for chemotherapy-induced febrile neutropenia in breast cancer patients: a validation study.

ABSTRACT:

Background

Predictive models for febrile neutropenia (FN) would be informative for physicians in clinical decision making. This study aims to validate a predictive model (Jenkin's model) that comprises pretreatment hematological parameters in early-stage breast cancer patients.

Patients and methods

A total of 428 breast cancer patients who received neoadjuvant/adjuvant chemotherapy without any prophylactic use of colony-stimulating factor were included. Pretreatment absolute neutrophil counts (ANC) and absolute lymphocyte counts (ALC) were used by the Jenkin's model to assess the risk of FN. In addition, we modified the threshold of Jenkin's model and generated Model-A and B. We also developed Model-C by incorporating the absolute monocyte count (AMC) as a predictor into Model-A. The rates of FN in the 1st chemotherapy cycle were calculated. A valid model should be able to significantly identify high-risk subgroup of patients with FN rate >20%.

Results

Jenkin's model (Predicted as high-risk when ANC?3.1*10^9/L;ALC?1.5*10^9/L) did not identify any subgroups with significantly high risk (>20%) of FN in our population, even if we used different thresholds in Model-A(ANC?4.4*10^9/L;ALC?2.1*10^9/L) or B(ANC?3.8*10^9/L;ALC?1.8*10^9/L). However, with AMC added as an additional predictor, Model-C(ANC?4.4*10^9/L;ALC?2.1*10^9/L; AMC?0.28*10^9/L) identified a subgroup of patients with a significantly high risk of FN (23.1%).

Conclusions

In our population, Jenkin's model, cannot accurately identify patients with a significant risk of FN. The threshold should be changed and the AMC should be incorporated as a predictor, to have excellent predictive ability.

SUBMITTER: Chen K

PROVIDER: S-EPMC4063732 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Clinical predictive models for chemotherapy-induced febrile neutropenia in breast cancer patients: a validation study.

Chen Kai K Zhang Xiaolan X Deng Heran H Zhu Liling L Su Fengxi F Jia Weijuan W Deng Xiaogeng X

PloS one 20140619 6

<h4>Background</h4>Predictive models for febrile neutropenia (FN) would be informative for physicians in clinical decision making. This study aims to validate a predictive model (Jenkin's model) that comprises pretreatment hematological parameters in early-stage breast cancer patients.<h4>Patients and methods</h4>A total of 428 breast cancer patients who received neoadjuvant/adjuvant chemotherapy without any prophylactic use of colony-stimulating factor were included. Pretreatment absolute neutr ...[more]

PMID: 24945817

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Project description:BackgroundRisk models of chemotherapy-induced (CIN) and febrile neutropenia (FN) have to date focused on determinants measured at the start of chemotherapy. We extended this static approach with a dynamic approach of CIN/FN risk modeling at the start of each cycle.DesignWe applied predictive modeling using multivariate logistic regression to identify determinants of CIN/FN episodes and related hospitalizations and chemotherapy disturbances (CIN/FN consequences) in analyses at the patient ('ever' during the whole period of chemotherapy) and cycle-level (during a given chemotherapy cycle). Statistical dependence of cycle data being 'nested' under patients was managed using generalized estimation equations. Predictive performance of each model was evaluated using bootstrapped c concordance statistics.ResultsStatic patient-level risk models of 'ever' experiencing CIN/FN adverse events and consequences during a planned chemotherapy regimen included predictors related to history, risk factors, and prophylaxis initiation and intensity. Dynamic cycle-level risk models of experiencing CIN/FN adverse events and consequences in an upcoming cycle included predictors related to history, risk factors, and prophylaxis initiation and intensity; as well as prophylaxis duration, CIN/FN in prior cycle, and treatment center characteristics.ConclusionsThese 'real-world evidence' models provide clinicians with the ability to anticipate CIN/FN adverse events and their consequences at the start of a chemotherapy line (static models); and, innovatively, to assess risk of CIN/FN adverse events and their consequences at the start of each cycle (dynamic models). This enables individualized patient treatment and is consistent with the EORTC recommendation to re-appraise CIN/FN risk at the start of each cycle. Prophylaxis intensity (under-, correctly-, or over-prophylacted relative to current EORTC guidelines) is a major determinant. Under-prophylaxis is clinically unsafe. Over-prophylaxis of patients administered chemotherapy with intermediate or low myelotoxicity levels may be beneficial, both in patients with and without risk factors, and must be validated in future studies.

Project description:PURPOSE:Despite widespread use of fluorouracil, epirubicin, cyclophosphamide, docetaxel (FEC-D) chemotherapy in breast cancer, the optimal strategy for primary febrile neutropenia (FN) prophylaxis remains unknown. A systematic review was therefore performed. METHODS:Embase, Ovid MEDLINE, PubMed, Cochrane Database of Systematic Reviews, Cochrane Register of Controlled Trials, and conference proceedings were searched from 1946 to April 2016 for trials that reported the effectiveness of primary FN prophylaxis with FEC-D chemotherapy. Outcome measures were incidence of FN; treatment-related hospitalizations; chemotherapy dose delays, reductions, and discontinuations; and adverse events from prophylaxis. RESULTS:Of 2,205 identified citations, eight studies (n = 1,250) met our eligibility criteria. Three additional studies (n = 293) were identified from a prior systematic review. Three randomized controlled trials (n = 576), one phase IV single-arm trial (n = 69), one prospective observational study (n = 37), and six retrospective studies (n = 861) were identified. Agents investigated were pegfilgrastim (n = 108), filgrastim (n = 1,119), and ciprofloxacin (n = 89). The heterogeneity of studies meant that a narrative synthesis of results was performed. Median FN rates for patients who received FEC-D with and without primary prophylaxis were 10.1% (interquartile range [IQR], 3.9% to 22.6%) and 23.9% (IQR, 9.2% to 27.3%), respectively. In the absence of primary prophylaxis, FN was more common during docetaxel than during FEC. Data from six studies showed a median rate of dose reductions and delays of 6.1% (IQR, 3.1% to 14.3%) and 19.3% (IQR, 10.5% to 32.8%), respectively, that occurred as a consequence of FN. Toxicity from prophylaxis itself was rarely reported. CONCLUSION:Primary FN prophylaxis is effective in patients who receive FEC-D chemotherapy. The paucity of prospective data makes optimal recommendations about the choice and timing of prophylaxis challenging.

Dataset Information

Clinical predictive models for chemotherapy-induced febrile neutropenia in breast cancer patients: a validation study.

Background

Patients and methods

Results

Conclusions

Publications

Clinical predictive models for chemotherapy-induced febrile neutropenia in breast cancer patients: a validation study.

Similar Datasets

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