Abstract:

Objective To establish a Nomogram to predictive the probability of severe neutropenia(grade 3 or 4) caused by first-line chemotherapy in patients with small cell lung cancer(SCLC).

Methods In total,263 cases who had histologically confirmed SCLC and received first-line chemotherapy were selected and enrolled in the predictive cohort. Three procedures(forward, backward and stepwise selections) were applied by using the likelihood ratio test with smallest Akaike′s information criterion as the stopping rule in the multivariable logistic regression analysis to establish a Nomogram. The assessment of this Nomogram was performed by evaluating its discrimination and calibration abilities, as well as clinical utility.

Results Age, current smoking, karnofsky performance status, tumor stage, platelet and chemotherapy regimen were extracted into the predictive model to establish the Nomogram. The results of assessment showed this Nomogram model had a good discrimination with area under the receiver operating characteristics(ROC) curve(AUC) of 0.73, and an acceptable calibration curve. In addition, the decision curve analysis showed when the range of threshold probability was approximately between 15% and 90%, using the nomogram to predict severe neutropenia would get more net benefits than the intervention-all scheme and intervention-none scheme. We suggested doctors should set the threshold or preference at 15%-30%.

Conclusion The established Nomogram can accurately predict the probability of severe neutropenia before each chemotherapy in SCLC and has certain application value in clinical practice.

Key words: small cell lung cancer, drug therapy, neutropenia, nomograms