Abstract 73P
Background
Immune checkpoint inhibitor (ICI) therapy is an emerging type of treatment for lung cancer (LC). However, hyperprogressive disease (HPD) has been observed in patients treated with ICIs. This study aimed to establish a novel scoring system based on a nomogram for the occurrence of HPD.
Methods
We retrospectively identified patients with LC who had undergone ICI therapy at the Shanghai Chest Hospital between January 2017 and June 2021. Data from these patients blood laboratory test results were used to develop and internally validate the predictive model.
Results
A total of 844 patients were included in this study. Multivariate logistic regression analyses demonstrated that lactate dehydrogenase (LDH) (P<.001; odd Ratio [OR] =0.987; 95% CI 0.984–0.990), mean corpuscular hemoglobin concentration (MCHC)(P= .039; OR=1.013; 95% CI 1.001–1.026), and erythrocyte sedimentation rate (ESR)(P=.011; OR=0.991; 95% CI, 0.983–0.998) were significantly different. The prediction model was established based on these 3 variables. Internal validation indicated that concordance index was 0.899, and calibration curve was acceptable.
Conclusions
This model, which was developed from a laboratory examination of LC patients undergoing ICI treatment, is the first nomogram model to be developed for the prediction of HPD occurrence and exhibited good sensitivity and specificity.
Legal entity responsible for the study
Hua Zhong.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.