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Updated: Aug 14, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small
Xueping Wang1, Zhixing Guo1, Xingping Wu1
1State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Esophageal Cancer Institute; Cancer Center, Sun Yat-sen University, Guangzhou, 510060, People's Republic of China.
Introduction:
Various studies have reported that anti-PD-1/PD-L1 treatment may lead to the rapid development of tumors called hyperprogressive disease (HPD). A nomogram for HPD prediction in NSCLC patients is urgently needed.
Methods:
This retrospective cohort study included 176 cases for establishing a model of HPD prediction and 85 cases for validation in advanced NSCLC patients treated with PD-1/PD-L1 inhibitors. HPD was defined as tumor growth rate (TGR, ≥ 2), tumor growth kinetics (TGK, ≥ 2) or time to treatment failure (TTF, ≤ 2 months). Univariate and multivariate logistic regression were used to estimate the specified factors associated with HPD. Then, the nomogram was developed and validated.
Results:
Anti-PD-1/PD-L1 therapy resulted in a 9.66% (17/176) incidence of HPD in advanced NSCLC. The overall survival (OS) and progression-free survival (PFS) in patients with HPD were significantly shorter than those in patients without HPD (OS: 7.00 vs 12.00 months, P<0.01; PFS: 2.00 vs 5.00 months, P<0.001, respectively). The HPD prediction nomogram included APTT (P<0.01), CD4+ CD25+ CD127-low cells (Treg cells) (P<0.01), the presence of liver metastasis (P<0.05), and more than two metastatic sites (P<0.05). Then, patients were divided into two groups by the "HPD score" calculated by the nomogram. The C-index was 0.845, while the area under the curve (AUC) was 0.830 (sensitivity 75.00%, specificity 91.70%). The calibration plot of HPD probability showed an optimal agreement between the actual observation and prediction by the nomogram. In the validation cohort, the AUC was up to 0.960 (sensitivity 88.70%, specificity 89.80%).
Conclusions:
The nomogram was constructed with the presence of liver metastasis, more than two metastatic sites, lengthened APTT and a high level of Treg cells, which could be used to predict HPD risk.
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