Predicting risk of chemotherapy-induced severe neutropenia: A pooled analysis in individual patients data with advanced lung cancer.

TitlePredicting risk of chemotherapy-induced severe neutropenia: A pooled analysis in individual patients data with advanced lung cancer.
Publication TypeJournal Article
Year of Publication2020
AuthorsCao, Xiaowen, Apar Kishor Ganti, Thomas Stinchcombe, Melisa L. Wong, James C. Ho, Chen Shen, Yingzhou Liu, Jeffery Crawford, Herbert Pang, and Xiaofei Wang
JournalLung Cancer
Volume141
Pagination14-20
Date Published2020 03
ISSN1872-8332
KeywordsAged, Antineoplastic Combined Chemotherapy Protocols, Carcinoma, Non-Small-Cell Lung, Clinical Trials, Phase II as Topic, Clinical Trials, Phase III as Topic, Female, Follow-Up Studies, Humans, Incidence, Lung Neoplasms, Male, Models, Statistical, Neutropenia, Prognosis, Randomized Controlled Trials as Topic, ROC Curve, Small Cell Lung Carcinoma, United States
Abstract

OBJECTIVES: Neutropenia is associated with the risk of life-threatening infections, chemotherapy dose reductions and delays that may compromise outcomes. This analysis was conducted to develop a prediction model for chemotherapy-induced severe neutropenia in lung cancer.MATERIALS AND METHODS: Individual patient data from existing cooperative group phase II/III trials of stages III/IV non-small cell lung cancer or extensive small-cell lung cancer were included. The data were split into training and testing sets. In order to enhance the prediction accuracy and the reliability of the prediction model, lasso method was used for both variable selection and regularization on the training set. The selected variables was fit to a logistic model to obtain regression coefficients. The performance of the final prediction model was evaluated by the area under the ROC curve in both training and testing sets.RESULTS: The dataset was randomly separated into training [7606 (67 %) patients] and testing [3746 (33 %) patients] sets. The final model included: age (>65 years), gender (male), weight (kg), BMI, insurance status (yes/unknown), stage (IIIB/IV/ESSCLC), number of metastatic sites (1, 2 or ≥3), individual drugs (gemcitabine, taxanes), number of chemotherapy agents (2 or ≥3), planned use of growth factors, associated radiation therapy, previous therapy (chemotherapy, radiation, surgery), duration of planned treatment, pleural effusion (yes/unknown), performance status (1, ≥2) and presence of symptoms (yes/unknown).CONCLUSIONS: We have developed a relatively simple model with routinely available pre-treatment variables, to predict for neutropenia. This model should be independently validated prospectively.

DOI10.1016/j.lungcan.2020.01.004
Alternate JournalLung Cancer
Original PublicationPredicting risk of chemotherapy-induced severe neutropenia: A pooled analysis in individual patients data with advanced lung cancer.
PubMed ID31926983
PubMed Central IDPMC7063587
Grant ListKL2 TR001870 / TR / NCATS NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R21 AG042894 / AG / NIA NIH HHS / United States