Frontiers in oncology
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Frontiers in oncology · Jan 2020
A Novel Nomogram Model Based on Cone-Beam CT Radiomics Analysis Technology for Predicting Radiation Pneumonitis in Esophageal Cancer Patients Undergoing Radiotherapy.
We quantitatively analyzed the characteristics of cone-beam computed tomography (CBCT) radiomics in different periods during radiotherapy (RT) and then built a novel nomogram model integrating clinical features and dosimetric parameters for predicting radiation pneumonitis (RP) in patients with esophageal squamous cell carcinoma (ESCC). ⋯ The radiomics model based on early lung CBCT is a potentially valuable tool for predicting RP. V5, MLD, and tumor stage have certain predictive effects for RP. The developed nomogram model has a better prediction ability than any of the other predictors and can be used as a quantitative model to predict RP.
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Frontiers in oncology · Jan 2020
Coronavirus: Older Persons With Cancer in Italy in the COVID-19 Pandemic.
Italy is the European country that was hit first and hardest by the COVID-19 epidemic. Since February 2020, the outbreak of the epidemic disease in Italy, with fatal outcomes in up to 10% of cases, made it urgent to implement extraordinary measures to avoid a breakdown of the universal Italian national health system. The update for April 1, 2020, in Italy recorded 102,669 confirmed COVID-19 cases, with a median patient age of 63 years. ⋯ These people face a health- and economics-related emergency that also carries cultural and ethical implications. In accordance with the measures adopted by the Italian government to limit viral transmission, several associations of Italian oncologists have taken action to update Elderly Cancer Care programs. In view of the newly emerging needs, we herein outline practical suggestions aimed at guaranteeing the best continuity to elderly cancer patients.
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Frontiers in oncology · Jan 2020
Significance of Tumor Mutation Burden in Immune Infiltration and Prognosis in Cutaneous Melanoma.
Background: Melanoma is highly immunogenic and therefore suitable for immunotherapy, but the efficacy is limited by response rate. In several types of tumor, tumor mutation burden (TMB) and immune infiltration have been reported to predict the response to immunotherapy, although each has its limitations. In the current study, we aimed to explore the association of TMB with immune infiltration and prognosis in cutaneous melanoma. ⋯ Conclusions: In cutaneous melanoma, TMB was positively correlated with prognosis. The risk score model and nomogram can be conveniently used to predict prognosis. The association of TMB with immune infiltration can help improve the predicting methods for the response to immunotherapy.
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Frontiers in oncology · Jan 2020
Predicting Progression-Free Survival Using MRI-Based Radiomics for Patients With Nonmetastatic Nasopharyngeal Carcinoma.
Objectives: This study aimed to explore the predictive value of MRI-based radiomic model for progression-free survival (PFS) in nonmetastatic nasopharyngeal carcinoma (NPC). Methods: A total of 327 nonmetastatic NPC patients [training cohort (n = 230) and validation cohort (n = 97)] were enrolled. The clinical and MRI data were collected. ⋯ Results: Model 5 incorporating radiomics, overall stage, and EBV DNA yielded the highest C-indices for predicting PFS in comparison with Model 1, Model 2, Model 3, and Model 4 (training cohorts: 0.805 vs. 0.766 vs. 0.749 vs. 0.641 vs. 0.563, validation cohorts: 0.874 vs. 0.839 vs. 836 vs. 0.689 vs. 0.456). The survival curve showed that the high-risk group yielded a lower PFS than the low-risk group. Conclusions: The model incorporating radiomics, overall stage, and EBV DNA showed better performance for predicting PFS in nonmetastatic NPC patients.
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Frontiers in oncology · Jan 2020
Pretreatment Neutrophil-to-Lymphocyte Ratio (NLR) May Predict the Outcomes of Advanced Non-small-cell Lung Cancer (NSCLC) Patients Treated With Immune Checkpoint Inhibitors (ICIs).
Background: Recent studies have demonstrated the predictive value of pretreatment neutrophil-to-lymphocyte ratio (NLR) in advanced cancers; however, the role of NLR in patients with advanced non-small-cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) remained to be explored. Thus, we aimed to investigate whether pretreatment NLR was associated with the outcomes of advanced NSCLC patients treated with ICIs. Methods: A comprehensive literature research was first conducted in PubMed, the Cochrane Central Library, and Embase for studies that evaluated the association between pretreatment NLR and survival of advanced NSCLC patients with ICIs treatment. ⋯ The associations between NLR and survival were consistent in subgroup analysis stratified by age, gender, ECOG PS, histology, stage, smoking history, treatment, and prior lines of therapy. Dynamics of NLR (dNLR) that increased ≥3.0 from baseline was also significantly associated with worse PFS (median: 3.1 vs. 9.1 months; P = 0.01) and OS (median: 6.8 vs. 17.0 months; P < 0.0001). Conclusions: Our study demonstrates that pretreatment NLR and dNLR from baseline are associated with the outcomes of advanced NSCLC patients treated with ICIs; however, it warrants further prospective studies.