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Predicting early post-chemotherapy adverse events in patients with hematological malignancies: a retrospective study

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Abstract

Purpose

The purpose of this study was to develop a mathematical model that predicts the definite adverse events following chemotherapy in patients with hematological malignancies (HMs).

Methods

This is a retrospective cohort study including 1157 cases with HMs. Firstly, we screened and verified the independent risk factors associated with post-chemotherapy adverse events by both univariate and multivariate logistic regression analysis using 70 % of randomly selected cases (training set). Secondly, we proposed a mathematical model based on those selected factors. The calibration and discrimination of the model were assessed by Hosmer-Lemeshow (H-L) test and area under the receiver operating characteristic (ROC) curve, respectively. Lastly, the predicative power of this model was further tested in the remaining 30 % of cases (validation set).

Results

Our statistical analysis indicated that liver dysfunction (OR = 2.164), active infection (OR = 3.619), coagulation abnormalities (OR = 4.614), intensity of chemotherapy (OR = 10.001), acute leukemia (OR = 2.185), and obesity (OR = 1.604) were independent risk factors for post-chemotherapy adverse events in HM patients (all P < 0.05). Based on the verified risk factors, a predictive model was proposed. This model had good discrimination and calibration. When 0.648 was selected as the cutoff point, the sensitivity and specificity of this predictive model in validation sets was 72.7 and 87.4 %, respectively. Furthermore, this proposed model’s positive predictive value, negative predictive value, and consistency rate were 87.3, 73.0 and 80.0 %, respectively.

Conclusions

Our study indicated that this six risk factor-based mathematical model is accurate and sufficient enough to predict definite post-chemotherapy adverse events in a HM patient and it may aid clinicians to optimize treatment for a HM patient.

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Acknowledgments

This study was supported by National Nature Science Grant (81202358 & 81571582), Jiangsu health medical research grant (Z 20 1 512), and Jiangsu Health International Exchange Program. We thank Associate Professor Li of Jiangsu University for his technical support.

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Authors and Affiliations

  1. Affiliated Hospital of Jiangsu University, Jiangsu University, 438# Jiefang Road, 212001, Zhenjiang, Jiangsu Province, People’s Republic of China

    Xiaoming Fei, Fang Lei, Yan Zhu & Yu Tang

  2. First Affiliated Hospital of Nanjing Medical University, 140# Hanzhong Road, Nanjing, 210029, Jiangsu Province, People’s Republic of China

    Haifeng Zhang & Hua Lu

  3. Hematology Research Institute, Jiangsu University, 438# Jiefang Road, Zhenjiang, 212001, Jiangsu Province, People’s Republic of China

    Xiaoming Fei

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  1. Xiaoming Fei
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  2. Fang Lei
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  3. Haifeng Zhang
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  4. Hua Lu
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  5. Yan Zhu
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  6. Yu Tang
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Correspondence to Yu Tang.

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Informed consent was obtained from all patients and all protocols were in accordance with ethical standards and approved by local institutional ethics committee.

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The authors declare that they have no competing interests.

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Fei, X., Lei, F., Zhang, H. et al. Predicting early post-chemotherapy adverse events in patients with hematological malignancies: a retrospective study. Support Care Cancer 24, 2727–2733 (2016). https://doi.org/10.1007/s00520-016-3085-6

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  • DOI: https://doi.org/10.1007/s00520-016-3085-6

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