Comorbidity profiling identifies potential subtype of elderly patients with nasopharyngeal carcinoma.

BACKGROUND: Few studies have assessed the comprehensive associations among comorbid diseases in elderly patients with nasopharyngeal carcinoma (NPC). This study sought to identify potential comorbidity patterns and explore the relationship of comorbidity patterns with the mortality risk in elderly patients with NPC. METHODS: A total of 452 elderly patients with NPC were enrolled in the study. The network analysis and latent class analysis were applied to mine comorbidity patterns. Propensity score matching was used for adjusting confounders. A restricted cubic spline model was used to analyze the nonlinear association between age and the risk of all-cause mortality. RESULTS: We identified 2 comorbidity patterns, metabolic disease-related comorbidity (MDRC) and organ disease-related comorbidity (ODRC) in elderly patients with NPC. Patients in MDRC showed a significantly higher risk of all-cause mortality (71.41% vs 87.97%, HR 1.819 [95% CI, 1.106-2.994], P = .031) and locoregional relapse (68.73% vs 80.88%, HR 1.689 [95% CI, 1.055-2.704], P = .042). Moreover, in patients with MDRC pattern, we observed an intriguing inverted S-shaped relationship between age and all-cause mortality among patients aged 68 years and older. The risk of mortality up perpetually with age increasing in ODRC group, specifically within the age range of 68-77 years (HR 4.371, 1.958-9.757). CONCLUSION: Our study shed light on the potential comorbidity patterns in elderly patients with NPC, thereby providing valuable insights into the development of comprehensive health management strategies for this specific population.

The causal impact of complement C3d receptor 2 on head and neck cancer microenvironment and its implications for immunotherapy response prediction.

This research dives into the intricate immune landscape of head and neck cancer (HNC), with a keen focus on the roles of specific immune cell subpopulations and their linked genes. We used tumour RNA-seq (in-house cohort: n = 192, TCGA-HNSC: n = 546) and Mendelian randomization to pinpoint key SNPs in immune cells that have a causal connection to HNC. Our discoveries unveil a spectrum of tumour immune phenotypes that either offer protection against or increase the risk of HNC. We underscore the therapeutic promise of Complement C3d Receptor 2 (CR2), a gene closely tied to immune cells, with its increased expression in tumour tissues linked to a more favourable prognosis. This is correlated with heightened immune pathway activity, stronger resistance to radiochemotherapy, and improved immunotherapy responses. Our research emphasises the pivotal role of CR2 in immune regulation and the significance of immune cells in tumour progression, highlighting the potential of CR2-targeted therapeutic interventions.

Early recurrence as a pivotal event in nasopharyngeal carcinoma: identifying predictors and key molecular signals for survivors.

PURPOSE: The duration of response to treatment is a significant prognostic indicator, with early recurrence (ER) often predicting poorer survival outcomes in nasopharyngeal carcinoma (NPC) survivors. This study seeks to elucidate the factors contributing to the onset of ER following radiotherapy in NPC survivors. METHODS: This investigation encompassed 2,789 newly diagnosed NPC patients who underwent radical intensity-modulated radiotherapy. Ordinal logistic regression analysis was employed to evaluate the independent predictors of earlier recurrence. A machine learning-based prediction model of NPC recurrence patterns was developed. Tumorous RNA-sequencing (in-house cohort: N = 192) and biological tipping point analysis were utilized to infer potential molecular mechanisms associated with ER. RESULTS: Our results demonstrated that ER within 24 months post-initial treatment was the optimal time frame for identifying early malignant progression in NPC survivors. The ER cohort (150 of 2,789, 5.38%) exhibited a notably short median overall survival of 48.6 months. Multivariate analyses revealed that male gender, T4 stage, local or regional residual disease, detectable pre- and post-radiotherapy EBV DNA, and the absence of induction chemotherapy were significant predictors of earlier recurrence. The machine learning-based predictive model further underscored the importance of tumor-related factors in NPC recurrence. Moreover, ER emerged as a pivotal stage in NPC progression, with 15 critical transition signals identified potentially associated with the negative modulation of the immune response. CONCLUSIONS: Our comprehensive analysis of NPC recurrence patterns has unveiled insights into the key factors driving ER and provided novel insights into potential early warning biomarkers and the mechanisms underlying NPC progression.

Impact of the radiotherapy rhythm on prognosis in nasopharyngeal carcinoma.

OBJECTIVE: The role of chronoradiobiology in nasopharyngeal carcinoma (NPC) has not been fully elucidated. We sought to investigate the impact of radiotherapy rhythm on the survival outcomes of individuals to explore a chronomodulated radiation strategy to improve prognosis of NPC. METHODS: A cohort comprising non-metastatic NPC patients subjected to intensity-modulated radiotherapy at Fujian Cancer Hospital between Jan. 2016 and Dec. 2019 was assembled. Rhythmic fluctuation of radiotherapy (RFRT) was quantified based on the temporal distribution of radiation delivery. Cox proportional hazard model was performed to explore the impact of radiotherapy rhythm on all-cause mortality. The maximally selected rank statistics method was employed to discern an optimal cutoff. Sensitivity analyses were conducted to ensure the robustness of observed associations. RESULTS: Our analysis encompassed 2245 patients, with a median follow-up duration of 55 months, during which 315 individuals succumbed. Multivariate Cox regression analysis unveiled a significant correlation between prolonged RFRT and heightened mortality risk in NPC patients (HR, 1.17, 95% CI, 1.07-1.27, p < .001), a relationship robust to comprehensive adjustment for confounding variables. A cutoff value of 3 h was selected for potential clinical application, beyond which patients exhibited markedly poorer survival outcomes. Subgroup analyses consistently underscored the directional consistency of observed effects. CONCLUSION: Our study sheds light on the potential advantages of scheduling radiotherapy sessions at consistent times. These findings have implications for optimizing radiotherapy schedules and warrant further investigation into personalized chronotherapy approaches in NPC management.

Prognostic value of immune-inflammatory and nutrition indicators in non-metastatic nasopharyngeal carcinoma with negative plasma Epstein-Barr virus DNA.

Background: Plasma Epstein-Barr virus (EBV) DNA has been identified as a significant prognostic marker for nasopharyngeal carcinoma (NPC), yet there is limited research on the prognosis of NPC patients with negative EBV DNA. Objectives: We explore the prognostic value of comprehensive immune-inflammatory and nutritional indicators to offer personalized treatment recommendations and prognosis predictions for non-metastatic NPC patients with negative EBV DNA. Design: This was a retrospective study. Methods: This study retrospectively analyzed 257 non-metastatic NPC patients with negative EBV DNA between January 2015 and December 2019. The Kaplan-Meier survival curves evaluated survival endpoints, and group discrepancies were assessed with log-rank tests. Principal component analysis (PCA) reduced data dimensionality. Univariate and multivariate Cox regression analyses identified significant prognostic variables. Risk stratification was performed based on recursive partitioning analysis (RPA). A robust prognostic model was constructed by nomogram and evaluated by calibration curves, decision curves, and the time-dependent area under the curve analysis. Results: PCA was employed to compute the immune-inflammation index (III) and nutrition index (NI). Multivariate Cox regression analysis revealed lactate dehydrogenase, III, and NI as significant prognostic variables for overall survival (OS). Utilizing RPA, we stratified the risk into three categories: low-risk group (low III + high NI), middle-risk group (low III + low NI), and high-risk group (high III). Both the middle- (p = 0.025) and high-risk groups (p < 0.001) exhibited poorer OS compared with the low-risk group. The nomogram model exhibited superior predictive accuracy compared to tumor lymph node metastasis stage alone (C-index: 0.774 vs 0.679). Conclusion: Our study validated the prognostic significance of III and NI in non-metastatic NPC patients with negative EBV DNA. Additionally, a clinical risk stratification was constructed to offer valuable insights into the individualized treatment of these patients.

Biomarkers of inflammation and nutrition can effectively predict the prognosis of EBV DNA-negative non-metastatic nasopharyngeal carcinoma Why was the study done? Plasma Epstein-Barr virus (EBV) DNA has shown efficacy in predicting survival and disease progression in individuals with nasopharyngeal carcinoma (NPC). However, a subset of patients exhibit negative EBV DNA levels. Currently, there is limited research available on the prognostic implications for this particular patient population. What did the researchers do? The researchers gathered clinical data from Fujian Cancer Hospital between 2015 and 2019 in order to investigate the potential of immune-inflammatory and nutritional markers in predicting both survival rates and disease progression among patients diagnosed with EBV DNA-negative, non-metastatic NPC. Additionally, the study aimed to assess the feasibility of utilizing these markers to offer personalized treatment recommendations for this specific patient population. What did the researchers find? A total of 257 non-metastatic NPC patients with negative EBV DNA were included in the study for clinical data collection. The findings suggest that a lower immune-inflammation index and a higher nutrition index were correlated with extended overall survival (OS) in this patient population. Furthermore, the study indicates that the survival advantage of abstaining from induction chemotherapy (IC) may be more pronounced in this particular cohort. What do the findings mean? This study has identified immune-inflammatory and nutritional markers as predictive of survival in NPC patients with EBV DNA-negative and raised thinking about reducing treatment intensity and improving the quality of life in this population patients in the future.

Machine learning-based survival prediction nomogram for postoperative parotid mucoepidermoid carcinoma.

Parotid mucoepidermoid carcinoma (P-MEC) is a significant histopathological subtype of salivary gland cancer with inherent heterogeneity and complexity. Existing clinical models inadequately offer personalized treatment options for patients. In response, we assessed the efficacy of four machine learning algorithms vis-à-vis traditional analysis in forecasting the overall survival (OS) of P-MEC patients. Using the SEER database, we analyzed data from 882 postoperative P-MEC patients (stages I-IVA). Single-factor Cox regression and four machine learning techniques (random forest, LASSO, XGBoost, best subset regression) were employed for variable selection. The optimal model was derived via stepwise backward regression, Akaike Information Criterion (AIC), and Area Under the Curve (AUC). Bootstrap resampling facilitated internal validation, while prediction accuracy was gauged through C-index, time-dependent ROC curve, and calibration curve. The model's clinical relevance was ascertained using decision curve analysis (DCA). The study found 3-, 5-, and 10-year OS rates of 0.887, 0.841, and 0.753, respectively. XGBoost, BSR, and LASSO stood out in predictive efficacy, identifying seven key prognostic factors including age, pathological grade, T stage, N stage, radiation therapy, chemotherapy, and marital status. A subsequent nomogram revealed a C-index of 0.8499 (3-year), 0.8557 (5-year), and 0.8375 (10-year) and AUC values of 0.8670, 0.8879, and 0.8767, respectively. The model also highlighted the clinical significance of postoperative radiotherapy across varying risk levels. Our prognostic model, grounded in machine learning, surpasses traditional models in prediction and offer superior visualization of variable importance.

Risk of intracranial hemorrhage with direct oral anticoagulants: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: We performed a systematic review and meta-analysis to compare the risk of intracranial hemorrhage (ICH) between direct oral anticoagulants (DOACs) and other antithrombotic drugs in detail across all diseases. METHODS: PubMed, EMBASE, Web of Science, and the Cochrane Library were searched for relevant randomized controlled trials (RCTs). Heterogeneity was examined using the I2 statistic. Risk ratio (RR) and 95% confidence interval (CI) were calculated using random-effects meta-analysis. RESULTS: Fifty-five RCTs were included in this meta-analysis. Compared with vitamin K antagonists (VKAs), dabigatran reduced the risk of ICH by 60% (RR 0.40; 95% CI 0.28-0.57), apixaban by 57% (RR 0.43; 95% CI 0.31-0.58), edoxaban by 56% (RR 0.44; 95% CI 0.29-0.67) and rivaroxaban by 41% (RR 0.59; 95%CI 0.44-0.80). Compared with low-molecular-weight heparins (LMWHs), apixaban, edoxaban and rivaroxaban had a similar risk of ICH. Compared with aspirin, dabigatran and apixaban had a similar risk of ICH, while rivaroxaban posed an increased risk of ICH (RR 2.12; 95% CI 1.31-3.44). For secondary prevention stroke, DOACs reduced the risk of ICH by 46% compared with warfarin (RR 0.54; 95% CI [0.42-0.70]) and had a similar risk of ICH compared with aspirin. CONCLUSION: All DOACs had a lower risk of ICH than VKAs. In terms of the risk of ICH, DOACs were overall as safe as LMWHs, and apixaban and dabigatran were as safe as aspirin, but rivaroxaban was not. For secondary prevention stroke, the risk of ICH with DOACs was overall lower than warfarin and similar to aspirin, but it should be noted that compared with aspirin, rivaroxaban may increase the risk of ICH. This is the first pair-wise meta-analysis that compares the risk of ICH between DOACs and other antithrombotic drugs in detail across all diseases, which may have certain significance for patients with high risk of ICH to choose antithrombotic drugs in clinical practice.