ObjectiveTo review the definition, incidence, risk factors, potential pathogenesis, biomarkers, and choice of follow-up treatment strategies of hyperprogressive disease (HPD).MethodDomestic and international literatures were collected to summarize the research progress of HPD in patients with malignant tumors who treated with immune checkpoint inhibitors (ICIs).ResultsThe research types of HPD were scattered, the sample size was limited, the definition standard was different, and there was lack of prospective validation studies. Therefore, the early warning assessment and molecular mechanism of HPD would become the next focus of the study of immunotherapy.ConclusionICIs can greatly improve the survival time of some patients with advanced malignant tumor, although some patients have HPD during treatment, but the incidence is relatively low.
ObjectiveTo summarize the clinical characteristics, potential molecular mechanisms, and predictive biomarkers of hyperprogressive disease (HPD) induced during the treatment of hepatocellular carcinoma (HCC) with immune checkpoint inhibitors and to explore its clinical implications. MethodsRelevant domestic and international literature was reviewed to analyze the definition, mechanisms, and predictive factors of HPD. Particular attention was given to key factors affecting HPD development, including clinical characteristics, tumor microenvironment, genetic mutations, and inflammatory factors. ResultsHPD significantly reduces the survival of HCC patients. Its occurrence may be associated with individual variability, dysregulation of the tumor microenvironment, tumor-related genetic mutations, and elevated levels of inflammatory factors. Blood-based biomarkers such as neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), and alpha-fetoprotein (AFP) show potential value in predicting HPD. ConclusionsSystematic investigation of the molecular mechanisms and predictive biomarkers of HPD is crucial for optimizing immunotherapy strategies and improving patient outcomes. Large-scale, multi-center studies are needed to achieve precise prediction and personalized intervention in the future.