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. 2011 May 1;117(9):1917-27.
doi: 10.1002/cncr.25691. Epub 2010 Nov 29.

Predicting individual risk of neutropenic complications in patients receiving cancer chemotherapy

Gary H Lyman  1 , Nicole M Kuderer, Jeffrey Crawford, Debra A Wolff, Eva Culakova, Marek S Poniewierski, David C Dale
Affiliations

Predicting individual risk of neutropenic complications in patients receiving cancer chemotherapy

Gary H Lyman et al. Cancer. .

Abstract

Background: A prospective cohort study was undertaken to develop and validate a risk model for neutropenic complications in cancer patients receiving chemotherapy.

Methods: The study population consisted of 3760 patients with common solid tumors or malignant lymphoma who were beginning a new chemotherapy regimen at 115 practice sites throughout the United States. A regression model for neutropenic complications was developed and then validated by using a random split-sample selection process.

Results: No significant differences in the derivation and validation populations were observed. The risk of neutropenic complications was greatest in cycle 1 with no significant difference in predicted risk between the 2 cohorts in univariate analysis. After adjustment for cancer type and age, major independent risk factors in multivariate analysis included: prior chemotherapy, abnormal hepatic and renal function, low white blood count, chemotherapy and planned delivery ≥85%. At a predicted risk cutpoint of 10%, model test performance included: sensitivity 90%, specificity 59%, and predictive value positive and negative of 34% and 96%, respectively. Further analysis confirmed model discrimination for risk of febrile neutropenia over multiple chemotherapy cycles.

Conclusions: A risk model for neutropenic complications was developed and validated in a large prospective cohort of patients who were beginning cancer chemotherapy that may guide the effective and cost-effective use of available supportive care.

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Conflict of interest statement

CONFLICT OF INTEREST DISCLOSURES

Gary Lyman is supported by grants from the National Cancer Institute (RC2CA148041-01) and the National Heart, Lung and Blood Institute (1R01HL095109-01). This study was supported, in part, by an unrestricted research grant to Duke University from Amgen. The funding agency was not involved in the study design, data collection and analysis or in the preparation and approval of this report.

Figures

Figure 1
Figure 1
(A) Frequency distribution of predicted risk of severe or febrile neutropenia in cycle 1 is shown for patients in the model derivation population. Average risk in low-risk patients below the median risk of 10% is 3.9%, whereas the average risk in those above the median risk is 34.2%. (B) The receiver operating characteristic (ROC) curve plots model sensitivity versus 1-specificity for the risk model developed on the derivation population. The straight line indicates the association between sensitivity and 1-specificity under the null hypothesis of no prognostic discrimination. The area under the ROC curve was 0.833 (95% CI, 0.813–0.852; P<.001).
Figure 2
Figure 2
(A) Frequency distribution of predicted risk of severe or febrile neutropenia in cycle 1 is shown for patients in the model validation population. Average risk in low-risk patients below the median risk of 10% is 6.6%, whereas the average risk in those above the median risk is 36.1%. (B) The receiver operating characteristic (ROC) curve for the risk model developed on the derivation population was applied to the validation population and plots model sensitivity versus 1-specificity. The straight line indicates the association of sensitivity and 1-specificity under the null hypothesis of no prognostic discrimination. The area under the ROC curve was 0.805 (95% CI, 0.774–0.836; P<.0001]
Figure 3
Figure 3
Distribution of the actual risk of severe or febrile neutropenia in cycle 1 for various predicted risks is based on the risk model in both the derivation (black bars) and validation (gray bars) populations.
Figure 4
Figure 4
(A) Kaplan-Meier plot displays the cumulative proportion of patients who experienced 1 or more episodes of febrile neutropenia over time in days after chemotherapy initiation for both high-risk and low-risk patients in the derivation population based on the risk model. (B) Kaplan-Meier plot displays the cumulative proportion of patients who experienced 1 or more episodes of febrile neutropenia over time in days after chemotherapy initiation for both high-risk and low-risk patients in the validation population based on the risk model.
Figure 5
Figure 5
(A) Hazard function plot displays the distribution of hazard rates for febrile neutropenia over time in days after chemotherapy initiation for both high-risk and low-risk patients in the derivation population based on the risk model. (B) Hazard function plot displays the distribution of hazard rates for febrile neutropenia over time in days after chemotherapy initiation for both high risk and low risk patients in the validation population based on the risk model.
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References

    1. Kuderer NM, Dale DC, Crawford J, et al. Mortality, morbidity, and cost associated with febrile neutropenia in adult cancer patients. Cancer. 2006;106:2258–2266. - PubMed
    1. Lyman GH, Dale DC, Crawford J. Incidence and predictors of low dose-intensity in adjuvant breast cancer chemotherapy: a nationwide study of community practices. J Clin Oncol. 2003;21:4524–4531. - PubMed
    1. Lyman GH, Dale DC, Friedberg J, et al. Incidence and predictors of low chemotherapy dose-intensity in aggressive non-Hodgkin’s lymphoma: a nationwide study. J Clin Oncol. 2004;22:4302–4311. - PubMed
    1. Lyman GH. Impact of chemotherapy dose intensity on cancer patient outcomes. J Natl Compr Canc Netw. 2009;7:99–108. - PubMed
    1. Shayne M, Culakova E, Wolff D, et al. Dose intensity and hematologic toxicity in older breast cancer patients receiving systemic chemotherapy. Cancer. 2009;115:5319–5328. - PubMed

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