Predicting checkpoint inhibitors pneumonitis in non-small cell lung cancer using a dynamic online hypertension
Xiaohui Jia1, Xiangling Chu2, Lili Jiang1
1Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China.
Objectives:
Checkpoint inhibitors pneumonitis (CIP) is one of the most lethal adverse events in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). Currently, there is no recognized and effective predictive model to predict CIP in NSCLC.
Materials And Methods:
This study retrospectively analyzed 460 NSCLC patients who were first treated with ICIs. Patients were divided into three cohorts based on the occurrence of CIP: any grade CIP cohort, grade ≥ 2 CIP cohort and grade ≥ 3 CIP cohort.
Results:
A dynamic hypertension nomogram was constructed with elements including hypertension, interstitial lung disease (ILD), emphysema at baseline, and higher baseline platelet/lymphocyte ratio (PLR). The C indices of the training cohort and the internal and external validation cohort in any grade CIP cohort were 0.872, 0.833 and 0.840, respectively. The constructed hypertension nomogram was applied to grade ≥ 2 cohort and grade ≥ 3 cohort, and their C indices were 0.844 and 0.866, respectively. Compared with the non-hypertension nomogram, the hypertension nomogram presented better predictive power.
Conclusions:
After validated by internal and external validation cohorts, the dynamic online hypertension has the potential to become a convenient, intuitive, and personalized clinical tool for assessing the risk of CIP in NSCLC patients.
