Prognostic value of 18F-fluorodeoxyglucose PET parameters and inflammation in patients with nasopharyngeal carcinoma

Novel prediction model combining PET/CT metabolic parameters, inflammation markers, and TNM stage: prospects for personalizing prognosis in nasopharyngeal carcinoma

PURPOSE

This study aims to develop a novel prediction model and risk stratification system that could accurately predict progression-free survival (PFS) in patients with nasopharyngeal carcinoma (NPC).

METHODS

Herein, we included 106 individuals diagnosed with NPC, who underwent 18F-FDG PET/CT scanning before treatment. They were divided into training (n = 76) and validation (n = 30) sets. The prediction model was constructed based on multivariate Cox regression analysis results and its predictive performance was evaluated. Risk factor stratification was performed based on the nomogram scores of each case, and Kaplan-Meier curves were used to evaluate the model's discriminative ability for high- and low-risk groups.

RESULTS

Multivariate Cox regression analysis showed that N stage, M stage, SUVmax, MTV, HI, and SIRI were independent factors affecting the prognosis of patients with NPC. In the training set, the model considerably outperformed the TNM stage in predicting PFS (AUCs of 0.931 vs. 0.841, 0.892 vs. 0.785, and 0.892 vs. 0.804 at 1-3 years, respectively). The calibration plots showed good agreement between actual observations and model predictions. The DCA curves further justified the effectiveness of the model in clinical practice. Between high- and low-risk group, 3-year PFS rates were significantly different (high- vs. low-risk group: 62.8% vs. 9.8%, p < 0.001). Adjuvant chemotherapy was also effective for prolonging survival in high-risk patients (p = 0.009).

CONCLUSION

Herein, a novel prediction model was successfully developed and validated to improve the accuracy of prognostic prediction for patients with NPC, with the aim of facilitating personalized treatment.

Correlation of serum IL-2 and IFN-γ levels with clinical prognosis of nasopharyngeal carcinoma patients and analysis of risk factors

Background

This study aims to investigate the correlation between serum levels of interleukin-2 (IL-2) and interferong (IFN-g) and the clinical prognosis of patients with nasopharyngeal carcinoma (NPC). Additionally, the study aims to analyse the risk factors associated with this correlation.

Methods

The clinical data of 195 NPC patients admitted to our hospital from October 2020 to October 2022 were selected for a retrospective study. Based on the Glasgow score, patients were divided into two groups: the good prognosis group (group g), consisting of patients who scored 0 points, and the poor prognosis group (group p), consisting of patients who scored 1-2 points. The levels of serum IL-2 and IFN-g were compared between the two groups, and the clinical values of serum IL-2 and IFN-g in the prognosis of patients were analysed. The clinical parameters of the patients were collected, and the risk factors affecting the prognosis of NPC were analysed by univariate and multivariate logistic regression.

Radiomics in Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is one of the most common head and neck malignancies, and the primary treatment methods are radiotherapy and chemotherapy. Radiotherapy alone, concurrent chemoradiotherapy, and induction chemotherapy combined with concurrent chemoradiotherapy can be used according to different grades. Treatment options and prognoses vary greatly depending on the grade of disease in the patients. Accurate grading and risk assessment are required. Recently, radiomics has combined a large amount of invisible high-dimensional information extracted from computed tomography, magnetic resonance imaging, or positron emission tomography with powerful computing capabilities of machine-learning algorithms, providing the possibility to achieve an accurate diagnosis and individualized treatment for cancer patients. As an effective tumor biomarker of NPC, the radiomic signature has been widely used in grading, differential diagnosis, prediction of prognosis, evaluation of treatment response, and early identification of therapeutic complications. The process of radiomic research includes image segmentation, feature extraction, feature selection, model establishment, and evaluation. Many open-source or commercial tools can be used to achieve these procedures. The development of machine-learning algorithms provides more possibilities for radiomics research. This review aimed to summarize the application of radiomics in NPC and introduce the basic process of radiomics research.

Prognostic Factors for Overall Survival in Nasopharyngeal Cancer and Implication for TNM Staging by UICC: A Systematic Review of the Literature

This study aims to identify prognostic factors in nasopharyngeal carcinoma (NPC) to improve the current 8th edition TNM classification. A systematic review of the literature reported between 2013 and 2019 in PubMed, Embase, and Scopus was conducted. Studies were included if (1) original clinical studies, (2) ≥50 NPC patients, and (3) analyses on the association between prognostic factors and overall survival. The data elements of eligible studies were abstracted and analyzed. A level of evidence was synthesized for each suggested change to the TNM staging and prognostic factors. Of 5,595 studies screened, 108 studies (44 studies on anatomical criteria and 64 on non-anatomical factors) were selected. Proposed changes/factors with strong evidence included the upstaging paranasal sinus to T4, defining parotid lymph node as N3, upstaging N-category based on presence of lymph node necrosis, as well as the incorporation of non-TNM factors including EBV-DNA level, primary gross tumor volume (GTV), nodal GTV, neutrophil-lymphocyte ratio, lactate dehydrogenase, C-reactive protein/albumin ratio, platelet count, SUVmax of the primary tumor, and total lesion glycolysis. This systematic review provides a useful summary of suggestions and prognostic factors that potentially improve the current staging system. Further validation studies are warranted to confirm their significance.

The importance of FDG-PET/CT parameters for the assessment of the immune status in advanced HNSCC

OBJECTIVE

Cancer cells secrete large amounts of lactic acid via aerobic glycolysis. We have shown that lactic acid plays an important role as a proinflammatory and immunosuppressive mediator and promotes tumor progression. Fluorine-18 fluorodeoxyglucose (FDG) uptake detected by positron emission tomography/computed tomography (PET/CT) is considered as a good indicator of aerobic glycolysis in cancer. In this study, we examined the relationships between systemic inflammatory parameters and FDG-PET/CT parameters in advanced head and neck squamous cell carcinoma (HNSCC). Furthermore, we investigated the relationships between FDG-PET/CT parameters and M2-macrophage polarization in HNSCC by assessing the ratio of CD163, a M2-macrophage marker, to CD68, a pan-macrophage marker.

METHODS

This study included 73 advanced HNSCC patients. We assessed the C-reactive protein (CRP) level, white blood cell (WBC) count, neutrophil count, lymphocyte count, and monocyte count as systemic inflammatory markers. Additionally, we assessed the maximum standardized uptake value (SUV_max), mean SUV (SUV_mean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) as FDG-PET/CT parameters.

RESULTS

The CRP level, WBC count, and neutrophil count were correlated with whole-body FDG-PET/CT parameters. The CD163/CD68 ratio was correlated with SUVmax and SUVmean. Our results suggest that systemic inflammation, which is associated with neutrophils, develops in patients with HNSCC having tumors with a larger volume and increased glucose uptake and that M2-macrophage polarization is promoted in HNSCC with increased glucose uptake, SUVmax, and SUVmean. FDG-PET/CT has the potential to reflect cancer-related chronic inflammation and immunosuppressive conditions in cancer patients.

CONCLUSIONS

FDG-PET/CT parameters appear to be useful in assessing the immune status in HNSCC.

The Relationship Between Tumor Glucose Metabolism and Host Systemic Inflammatory Responses in Patients with Cancer: A Systematic Review

One of the most important and long recognized characteristics of tumor cells is their dysregulated cellular energetics with anaerobic driven glucose uptake. In patients with cancer, the prognostic value of the systemic inflammatory response has been well established, and the recent combination of PET and CT scanning combines the assessment of tumor physiologic activity with detailed anatomic localization. The aim of this study was to perform a systematic review of the assessment of the relationship between both the tumor and the host inflammatory responses using PET/CT. Methods: An extensive literature review using targeted subject headings was performed in the U.S. National Library of Medicine, the Excerpta Medica database, and the Cochrane Database of Systematic Reviews on March 31, 2018. On completion of the online search, the title and abstracts of each identified study were examined for relevance. Studies with duplicate datasets, not available in English, and that did not have full text availability were excluded. Full texts of relevant articles were obtained and were then examined to identify any further relevant articles. Results: Twelve studies containing 2,588 patients were included in the final analysis. All of the included studies used the ¹⁸F-FDG tracer in PET/CT imaging and had biochemical assessment of the systemic inflammatory response. Most studies showed a direct relationship between the tumor and bone marrow glucose uptake and host systemic inflammatory responses as measured by C-reactive protein (n = 2), albumin (n = 2), white cell count (n = 3), neutrophils (n = 2), and platelets (n = 2). Most of the studies (n = 8) also showed a direct relationship between tumor and bone marrow glucose uptake and poor outcomes. Conclusion: This review suggests a direct relationship between the tumor and bone marrow glucose uptake and host systemic inflammation. This may suggest new approaches for more optimal therapeutic targeting and monitoring strategies in patients with cancer.