[Cancer survival analysis in Tianjin, 2010 to 2016].

Objective: Survival analysis of cancers' incidence data in Tianjin from 2010 to 2016 was conducted to provide the basis for formulating and evaluating regional health policies on cancer prevention and treatment. Methods: Registration data in Tianjin were used between January 1, 2010 to December 31, 2016 and patients were followed-up till 31 December, 2021. Life-table method was used to calculate the observed survival rate and Edered Ⅱ was used to calculate the relative survival rate. The data were stratified by year, gender, age group and cancer sites. Difference in survival curves between group was analyzed by Kaplan-Meier method and Log rank test. Joinpoint regression model was used to analyze the trend change. Results: The 5-year relative survival rates of cancer were 41.92% to 53.65% from 2010 to 2016 for residents in Tianjin, with an increasing trend (t=4.81, P=0.005), and the average was 48.56%. The survival rate of females was higher than that of males (57.71%vs. 39.20%), and the survival rate of urban residents was higher than that of rural residents (49.38% vs. 47.24%). The 5-year relative survival rates were 63.14%, 78.39%, 58.25% and 32.67% in 0-14, 15-44, 45-64 and 65 and above age groups, respectively. The median relative survival times of all cancer were 2.34 to 6.00 years from 2010 to 2016 in Tianjin, with an increasing trend (t=3.86, P=0.012). The average of median relative survival times was 4.11 years. The median survival time of females was longer than that of males (11.99 years vs. 2.03 years), and the time of urban residents were longer than that of rural residents (4.60 years vs. 3.43 years). The median relative survival time were 12.07, 11.92 and 1.34 years in 15-44, 45-64 and 65 and above age groups, respectively. Conclusions: The cumulative survival rate of cancer increased significantly from 2010 to 2016 in Tianjin, indicating that the prevention and treatment effect of cancer is obvious. The focus should be on male, rural areas, higher age group, and targeted prevention and treatment measures should be taken to lung, esophagus, liver, gallbladder and pancreatic cancer.

Derivative survival analyses: Analysis methods to derive survival outcomes for the remainder patient cohort without individual patient data.

It is not uncommon for industry-sponsored randomized controlled trials to publish survival curves/data for the overall patient cohort("A+B") and for a favorable subgroup ("A") pre-specified or post hoc, but not the survival curves/data for the remainder cohort("B"). Consequently, following regulatory approval of the intervention treatment for the overall patient population if the primary endpoint is met, it is common for cancer patients representing the remainder cohort (B) to be treated as per the results of the overall cohort (A+B). To overcome this important issue in clinical decision-making, this study aimed to identify methods to accurately derive the survival curves and/or hazard ratio (95% confidence interval) for the remainder cohort (B), utilizing published curves and hazard ratios (95% confidence intervals) of the overall (A+B) and favorable subgroup (A) cohorts. The analysis methods (method I and method II) presented here, termed "derivative survival analyses," enable accurate assessment of survival outcomes in the remainder cohort without individual patient data.

The quasi-xgamma frailty model with survival analysis under heterogeneity problem, validation testing, and risk analysis for emergency care data.

Frailty models are important for survival data because they allow for the possibility of unobserved heterogeneity problem. The problem of heterogeneity can be existed due to a variety of factors, such as genetic predisposition, environmental factors, or lifestyle choices. Frailty models can help to identify these factors and to better understand their impact on survival. In this study, we suggest a novel quasi xgamma frailty (QXg-F) model for the survival analysis. In this work, the test of Rao-Robson and Nikulin is employed to test the validity and suitability of the probabilistic model, we examine the distribution's properties and evaluate its performance in comparison with many relevant cox-frailty models. To show how well the QXg-F model captures heterogeneity and enhances model fit, we use simulation studies and real data applications, including a fresh dataset gathered from an emergency hospital in Algeria. According to our research, the QXg-F model is a viable replacement for the current frailty modeling distributions and has the potential to improve the precision of survival analyses in a number of different sectors, including emergency care. Moreover, testing the ability and the importance of the new QXg-F model in insurance is investigated using simulations via different methods and application to insurance data.

Survival analysis after stereotactic ablative radiotherapy for early stage non-small cell lung cancer: a single-institution cohort study.

BACKGROUND: Stereotactic ablative radiotherapy (SABR) is the standard treatment for medically inoperable early-stage non-small cell lung cancer (ES-NSCLC), but which patients benefit from stereotactic radiotherapy is unclear. The aim of this study was to analyze prognostic factors for early mortality. METHODS: From August 2010 to 2022, 617 patients with medically inoperable, peripheral or central ES-NSCLC were treated with SABR at our institution. We retrospectively evaluated the data from 172 consecutive patients treated from 2018 to 2020 to analyze the prognostic factors associated with overall survival (OS). The biological effective dose was > 100 Gy10 in all patients, and 60 Gy was applied in 3-5 fractions for a gross tumor volume (GTV) + 3 mm margin when the tumor diameter was < 1 cm; 30-33 Gy was delivered in one fraction. Real-time tumor tracking or an internal target volume approach was applied in 96% and 4% of cases, respectively. In uni- and multivariate analysis, a Cox model was used for the following variables: ventilation parameter FEV1, histology, age, T stage, central vs. peripheral site, gender, pretreatment PET, biologically effective dose (BED), and age-adjusted Charlson comorbidity index (AACCI). RESULTS: The median OS was 35.3 months. In univariate analysis, no correlation was found between OS and ventilation parameters, histology, PET, or centrality. Tumor diameter, biological effective dose, gender, and AACCI met the criteria for inclusion in the multivariate analysis. The multivariate model showed that males (HR 1.51, 95% CI 1.01-2.28; p = 0.05) and AACCI > 5 (HR 1.56, 95% CI 1.06-2.31; p = 0.026) were significant negative prognostic factors of OS. However, the analysis of OS showed that the significant effect of AACCI > 5 was achieved only after 3 years (3-year OS 37% vs. 56%, p = 0.021), whereas the OS in one year was similar (1-year OS 83% vs. 86%, p = 0.58). CONCLUSION: SABR of ES-NSCLC with precise image guidance is feasible for all medically inoperable patients with reasonable performance status. Early deaths were rare in our real-life cohort, and OS is clearly higher than would have been expected after best supportive care.

Prognostic analysis of hepatocellular carcinoma based on cuproptosis -associated lncRNAs.

OBJECTIVES: Cuproptosis represents an innovative type of cell death, distinct from apoptosis, driven by copper dependency, yet the involvement of copper apoptosis-associated long non-coding RNAs (CRLncRNAs) in hepatocellular carcinoma (HCC) remains unclear. This study is dedicated to unveiling the role and significance of these copper apoptosis-related lncRNAs within the context of HCC, focusing on their impact on both the development of the disease and its prognosis. METHODS: We conducted an analysis of gene transcriptomic and clinical data for HCC cases by sourcing information from The Cancer Genome Atlas database. By incorporating cuproptosis-related genes, we established prognostic features associated with cuproptosis-related lncRNAs. Furthermore, we elucidated the mechanism of cuproptosis-related lncRNAs in the prognosis and treatment of HCC through comprehensive approaches, including Lasso and Cox regression analyses, survival analyses of samples, as well as examinations of tumor mutation burden and immune function. RESULTS: We developed a prognostic model featuring six cuproptosis-related lncRNAs: AC026412.3, AC125437.1, AL353572.4, MKLN1-AS, TMCC1-AS1, and SLC6A1-AS1. This model demonstrated exceptional prognostic accuracy in both training and validation cohorts for patients with tumors, showing significantly longer survival times for those categorized in the low-risk group compared to the high-risk group. Additionally, our analyses, including tumor mutation burden, immune function, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and drug sensitivity, further elucidated the potential mechanisms through which cuproptosis-associated lncRNAs may influence disease outcome. CONCLUSIONS: The model developed using cuproptosis-related long non-coding RNAs (lncRNAs) demonstrates promising predictive capabilities for both the prognosis and immunotherapy outcomes of tumor patients. This could play a crucial role in patient management and the optimization of immunotherapeutic strategies, offering valuable insights for future research.

Liver regeneration after portal and hepatic vein embolization improves overall survival compared with portal vein embolization alone: mid-term survival analysis of the multicentre DRAGON 0 cohort.

BACKGROUND: The purpose of this study was to compare 3-year overall survival after simultaneous portal (PVE) and hepatic vein (HVE) embolization versus PVE alone in patients undergoing liver resection for primary and secondary cancers of the liver. METHODS: In this multicentre retrospective study, all DRAGON 0 centres provided 3-year follow-up data for all patients who had PVE/HVE or PVE, and were included in DRAGON 0 between 2016 and 2019. Kaplan-Meier analysis was undertaken to assess 3-year overall and recurrence/progression-free survival. Factors affecting survival were evaluated using univariable and multivariable Cox regression analyses. RESULTS: In total, 199 patients were included from 7 centres, of whom 39 underwent PVE/HVE and 160 PVE alone. Groups differed in median age (P = 0.008). As reported previously, PVE/HVE resulted in a significantly higher resection rate than PVE alone (92 versus 68%; P = 0.007). Three-year overall survival was significantly higher in the PVE/HVE group (median survival not reached after 36 months versus 20 months after PVE; P = 0.004). Univariable and multivariable analyses identified PVE/HVE as an independent predictor of survival (univariable HR 0.46, 95% c.i. 0.27 to 0.76; P = 0.003). CONCLUSION: Overall survival after PVE/HVE is substantially longer than that after PVE alone in patients with primary and secondary liver tumours.

Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics.

Background: Extracting multiregional radiomic features from multiparametric MRI for predicting pretreatment survival in isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients is a promising approach. Methods: MRI data from 49 IDH wild-type glioblastoma patients pre-treatment were utilized. Diffusion and perfusion maps were generated, and tumor subregions segmented. Radiomic features were extracted for each tissue type and map. Feature selection on 1862 radiomic features identified 25 significant features. The Cox proportional-hazards model with LASSO regularization was used to perform survival analysis. Internal and external validation used a 38-patient training cohort and an 11-patient validation cohort. Statistical significance was set at p < 0.05. Results: Age and six radiomic features (shape and first and second order) from T1W, diffusion, and perfusion maps contributed to the final model. Findings suggest that a small necrotic subregion, inhomogeneous vascularization in the solid non-enhancing subregion, and edema-related tissue damage in the enhancing and edema subregions are linked to poor survival. The model's C-Index was 0.66 (95% C.I. 0.54-0.80). External validation demonstrated good accuracy (AUC > 0.65) at all time points. Conclusions: Radiomics analysis, utilizing segmented perfusion and diffusion maps, provide predictive indicators of survival in IDH wild-type glioblastoma patients, revealing associations with microstructural and vascular heterogeneity in the tumor.

Overall Survival with Adjuvant Pembrolizumab in Renal-Cell Carcinoma.

BACKGROUND: Adjuvant pembrolizumab therapy after surgery for renal-cell carcinoma was approved on the basis of a significant improvement in disease-free survival in the KEYNOTE-564 trial. Whether the results regarding overall survival from the third prespecified interim analysis of the trial would also favor pembrolizumab was uncertain. METHODS: In this phase 3, double-blind, placebo-controlled trial, we randomly assigned (in a 1:1 ratio) participants with clear-cell renal-cell carcinoma who had an increased risk of recurrence after surgery to receive pembrolizumab (at a dose of 200 mg) or placebo every 3 weeks for up to 17 cycles (approximately 1 year) or until recurrence, the occurrence of unacceptable toxic effects, or withdrawal of consent. A significant improvement in disease-free survival according to investigator assessment (the primary end point) was shown previously. Overall survival was the key secondary end point. Safety was a secondary end point. RESULTS: A total of 496 participants were assigned to receive pembrolizumab and 498 to receive placebo. As of September 15, 2023, the median follow-up was 57.2 months. The disease-free survival benefit was consistent with that in previous analyses (hazard ratio for recurrence or death, 0.72; 95% confidence interval [CI], 0.59 to 0.87). A significant improvement in overall survival was observed with pembrolizumab as compared with placebo (hazard ratio for death, 0.62; 95% CI, 0.44 to 0.87; P = 0.005). The estimated overall survival at 48 months was 91.2% in the pembrolizumab group, as compared with 86.0% in the placebo group; the benefit was consistent across key subgroups. Pembrolizumab was associated with a higher incidence of serious adverse events of any cause (20.7%, vs. 11.5% with placebo) and of grade 3 or 4 adverse events related to pembrolizumab or placebo (18.6% vs. 1.2%). No deaths were attributed to pembrolizumab therapy. CONCLUSIONS: Adjuvant pembrolizumab was associated with a significant and clinically meaningful improvement in overall survival, as compared with placebo, among participants with clear-cell renal-cell carcinoma at increased risk for recurrence after surgery. (Funded by Merck Sharp and Dohme, a subsidiary of Merck; KEYNOTE-564 ClinicalTrials.gov number, NCT03142334.).

Kaplan-Meier Survival Analysis: Practical Insights for Clinicians.

This article aims to provide a guide that will help healthcare professionals and clinical researchers from all fields that deal with Kaplan-Meier curves. Survival analysis methods are among the most frequently used in the medical sciences and in clinical research. Overall survival, progression free survival, time to recurrence, or any other clinically relevant parameter represented by a Kaplan-Meier curve will be discussed. We will present a practical and straightforward interpretation of these curves, setting aside intricate mathematical considerations. Our focus will be on essential concepts that interface with biological sciences and medicine in order to guarantee proficiency in one of the most popular yet frequently misunderstood methods in clinical research. Being familiar with these concepts is not only essential for designing new clinical studies but also for critically assessing and interpreting published data.

Survival Analysis of Patients Undergoing Intraoperative Contrast-enhanced Ultrasound in the Surgical Treatment of Malignant Glioma.

OBJECTIVE: Complete resection of malignant gliomas is often challenging. Our previous study indicated that intraoperative contrast-enhanced ultrasound (ICEUS) could aid in the detection of residual tumor remnants and the total removal of brain lesions. This study aimed to investigate the survival rates of patients undergoing resection with or without the use of ICEUS and to assess the impact of ICEUS on the prognosis of patients with malignant glioma. METHODS: A total of 64 patients diagnosed with malignant glioma (WHO grade HI and IV) who underwent surgery between 2012 and 2018 were included. Among them, 29 patients received ICEUS. The effects of ICEUS on overall survival (OS) and progression-free survival (PFS) of patients were evaluated. A quantitative analysis was performed to compare ICEUS parameters between gliomas and the surrounding tissues. RESULTS: The ICEUS group showed better survival rates both in OS and PFS than the control group. The univariate analysis revealed that age, pathology and ICEUS were significant prognostic factors for PFS, with only age being a significant prognostic factor for OS. In multivariate analysis, age and ICEUS were significant prognostic factors for both OS and PFS. The quantitative analysis showed that the intensity and transit time of microbubbles reaching the tumors were significantly different from those of microbubbles reaching the surrounding tissue. CONCLUSION: ICEUS facilitates the identification of residual tumors. Age and ICEUS are prognostic factors for malignant glioma surgery, and use of ICEUS offers a better prognosis for patients with malignant glioma.

Statistical primer: individual patient data meta-analysis and meta-analytic approaches in case of non-proportional hazards.

Individual patient data (IPD) meta-analyses build upon traditional (aggregate data) meta-analyses by collecting IPD from the individual studies rather than using aggregated summary data. Although both traditional and IPD meta-analyses produce a summary effect estimate, IPD meta-analyses allow for the analysis of data to be performed as a single dataset. This allows for standardization of exposure, outcomes, and analytic methods across individual studies. IPD meta-analyses also allow the utilization of statistical methods typically used in cohort studies, such as multivariable regression, survival analysis, propensity score matching, uniform subgroup and sensitivity analyses, better management of missing data, and incorporation of unpublished data. However, they are more time-intensive, costly, and subject to participation bias. A separate issue relates to the meta-analytic challenges when the proportional hazards assumption is violated. In these instances, alternative methods of reporting time-to-event estimates, such as restricted mean survival time should be used. This statistical primer summarizes key concepts in both scenarios and provides pertinent examples.

Deep partially linear cox model for current status data.

Deep learning has continuously attained huge success in diverse fields, while its application to survival data analysis remains limited and deserves further exploration. For the analysis of current status data, a deep partially linear Cox model is proposed to circumvent the curse of dimensionality. Modeling flexibility is attained by using deep neural networks (DNNs) to accommodate nonlinear covariate effects and monotone splines to approximate the baseline cumulative hazard function. We establish the convergence rate of the proposed maximum likelihood estimators. Moreover, we derive that the finite-dimensional estimator for treatment covariate effects is $\sqrt{n}$-consistent, asymptotically normal, and attains semiparametric efficiency. Finally, we demonstrate the performance of our procedures through extensive simulation studies and application to real-world data on news popularity.

Subsequent management and outcomes after first-line PARP inhibitors progression in ovarian cancer patients.

OBJECTIVES: This retrospective study aims to evaluating the subsequent management and outcomes after first-line PARPi progression in Chinese ovarian cancer population. METHODS: Clinical and pathologic variables, treatment modalities, and outcomes were assessed. We investigated the subsequent management and outcomes after first-line PARPi progression. The objective response rate (ORR) and disease control rate (DCR) parameters were evaluated to determine the response to subsequent chemotherapy. For the survival analyses, progression-free survival 1 (PFS1), PFS2, overall survival (OS) and PFS2 - PFS1 were analysed. RESULTS: A total of 124 patients received PARPi maintenance treatment after first-line chemotherapy during the study period in our center. 44 of them (35.5%) experienced a recurrence. The median duration of PARPi in these patients was 11.1 months (range: 1.2-75.1 months). A total of 40 patients (40/44, 90.9%) received subsequent chemotherapy with 35 (35/44, 79.5%) and 5 (5/44, 11.4%) patients received platinum-based and non-platinum-based chemotherapy in our center. 2 patients (4.5%) received target therapy and other 2 patients (4.5%) received best supportive care. 27.3% (12/44) patients received secondary cytoreduction surgery (SCS). After subsequent chemotherapy, 14 patients received PARPi retreatment as maintenance therapy. In patients who received platinum-based regimens (n = 35), 23 of 35 patients (65.7%) had complete/partial response (CR/PR), 8 of 35 (22.9%) had stable disease (SD), and 4 of 35 (12.1%) had progressive disease (PD). The ORR and DCR of patients who received subsequent chemotherapy was 65.7% and 88.6%, respectively. 15 patients (57.7%, 15/26) were reported to be platinum resistant with a platinum-free interval (PFI) of < 6 months in patients whose platinum sensitivity of the second line platinum-based regimens was evaluable. Patients who received SCS after PARPi resistant associated with a borderline better PFS2 (median PFS2: 41.9 vs. 29.2 months, P = 0.051) and a non-significantly increased PFS2-PFS1 (median PFS2-PFS1: 12.2 vs. 9.8 months, P = 0.551). Patients with a PFI ≥ 12 months had a significantly better PFS2 (median PFS2: 37.0 vs. 25.3 months, P < 0.001) and a tendency towards a better PFS2-PFS1 than those with a PFI < 12 months (median PFS2-PFS1: 11.2 vs. 8.5 months, P = 0.334). A better PFS2 was observed in patients who received second PARPi maintenance therapy (median PFS2 of 35.4 vs. 28.8 months); however, the difference was not statistically significant (P = 0.200). A better PFS2-PFS1 was observed in patients who received second PARPi maintenance therapy (median PFS2-PFS1: 13.6 vs. 8.9 months, P = 0.002) than those without. CONCLUSIONS: In summary, some degree of resistance to standard subsequent platinum and non-platinum chemotherapy is noted in the entire cohort. A trend towards higher benefit from subsequent chemotherapy after first-line PARP inhibitors progression was observed in the PFI ≥ 12 months subgroup than those with PFI < 12 months. PARPi retreatment as maintenance therapy and SCS can be offered to some patients with PARPi resistance.

Modeling time to death for under-five children in Malawi using 2015/16 Demographic and Health Survey: a survival analysis.

BACKGROUND: Malawi has one of the highest under-five mortality rates in Sub Sahara Africa. Understanding the factors that contribute to child mortality in Malawi is crucial for the development and implementation of effective interventions to reduce child mortality. The aim of this study is to use survival analysis in modeling time to death for under-five children in Malawi. In turn, identify potential risk factors for child mortality and inform the development of interventions to reduce child mortality in the country. METHOD: This study used data from all births that occurred in the five years leading up to the 2015/16 Malawi Demographic and Health Survey. The Frailty hazard model was applied to predict infant survival in Malawi. In this analysis, the outcome of interest was death and it had two possible outcomes: "dead" or "alive". Age at death was regarded as the survival time variable. Infants who were still alive at the time of the study as of the day of the interview were considered as censored observations in the analysis. RESULTS: A total of 17,286 live births born during the 5 years preceding the survey were analysed. The study found that the risk of death was higher among children born to mothers aged 30-39 and 40 or older compared to teen mothers. Infants whose mothers attended fewer than four antenatal care visits were also found to be at a higher risk of death. On the other hand, the study found that using mosquito nets and early breastfeeding were associated with a lower risk of death, as were being male and coming from a wealthier household. CONCLUSION: The study reveals a notable decline in infant mortality rates as under-five children age, underscoring the challenge of ensuring newborn survival. Factors such as maternal age, birth order, socioeconomic status, mosquito net usage, early breastfeeding initiation, geographic location, and child's sex are key predictors of under-five mortality. To address this, public health strategies should prioritize interventions targeting these predictors to reduce under-five mortality rates.

A distributed feature selection pipeline for survival analysis using radiomics in non-small cell lung cancer patients.

Predictive modelling of cancer outcomes using radiomics faces dimensionality problems and data limitations, as radiomics features often number in the hundreds, and multi-institutional data sharing is ()often unfeasible. Federated learning (FL) and feature selection (FS) techniques combined can help overcome these issues, as one provides the means of training models without exchanging sensitive data, while the other identifies the most informative features, reduces overfitting, and improves model interpretability. Our proposed FS pipeline based on FL principles targets data-driven radiomics FS in a multivariate survival study of non-small cell lung cancer patients. The pipeline was run across datasets from three institutions without patient-level data exchange. It includes two FS techniques, Correlation-based Feature Selection and LASSO regularization, and Cox Proportional-Hazard regression with Overall Survival as endpoint. Trained and validated on 828 patients overall, our pipeline yielded a radiomic signature comprising "intensity-based energy" and "mean discretised intensity". Validation resulted in a mean Harrell C-index of 0.59, showcasing fair efficacy in risk stratification. In conclusion, we suggest a distributed radiomics approach that incorporates preliminary feature selection to systematically decrease the feature set based on data-driven considerations. This aims to address dimensionality challenges beyond those associated with data constraints and interpretability concerns.

Amoebicidal effect of chlorine dioxide gas against pathogenic Naegleria fowleri and Acanthamoeba polyphaga.

The pathogenic free-living amoebae, Naegleria fowleri and Acanthamoeba polyphaga, are found in freshwater, soil, and unchlorinated or minimally chlorinated swimming pools. N. fowleri and A. polyphaga are becoming problematic as water leisure activities and drinking water are sources of infection. Chlorine dioxide (ClO2) gas is a potent disinfectant that is relatively harmless to humans at the concentration used for disinfection. In this study, we examined the amoebicidal effects of ClO2 gas on N. fowleri and A. polyphaga. These amoebae were exposed to ClO2 gas from a ready-to-use product (0.36 ppmv/h) for 12, 24, 36, and 48 h. Microscopic examination showed that the viability of N. fowleri and A. polyphaga was effectively inhibited by treatment with ClO2 gas in a time-dependent manner. The growth of N. fowleri and A. polyphaga exposed to ClO2 gas for 36 h was completely inhibited. In both cases, the mRNA levels of their respective actin genes were significantly reduced following treatment with ClO2 gas. ClO2 gas has an amoebicidal effect on N. fowleri and A. polyphaga. Therefore, ClO2 gas has been proposed as an effective agent for the prevention and control of pathogenic free-living amoeba contamination.

Survival analysis of Sudanese oral squamous cell carcinoma patients with field of cancerization.

BACKGROUND: The late presentation and diagnosis of OSCC account for the large number of patients with the advanced form of the disease. In Sudan, cases with delayed presentation, particularly those with risk factors such as Toombak dipping and alcohol consumption, frequently present with extensive lesions and a wide area of Field cancerization which characterized by the presence of genetic and epigenetic changes in histologically normal-appearing tissues, and have increased risk for recurrent and second primary tumors. This necessitates more aggressive treatment and is usually associated with poorer outcomes. The present study aims to investigate the survival of oral squamous cell carcinoma patients with a wide field of cancerization. METHODS: This prospective longitudinal study includes ninety-three oral cancer patients with extensive fields of cancerization who underwent surgical treatment at Khartoum Teaching Dental Hospital (KTDH) conducted from 2019 to 2023. These patients were regularly assessed for clinical changes such as recurrence, the development of second primary tumours, and overall survival over a period of one year. RESULTS: Out of the 93 patients, 57 (61.3%) were males, and 36 (38.7%) were females. The majority of the patients (82%) had stage IV tumours, and 62.3% had nodal metastasis. Twenty-eight (30%) patients developed recurrences, and 14 (15%) developed second primary tumours. The overall one-year survival rate was 89%, and all deceased patients passed away within 12 months. The survival rate for patients with different types of recurrences varied, with patients who had regional, local, and locoregional recurrences having survival rates of 87%, 74%, and 72%, respectively. Patients who did not experience a recurrence had a one-year survival rate of 92%. Patients who developed second primary tumours had an 86% survival rate. The survival rates for OSCC patients at stages III, IVa, and IVb were 90%, 90%, and 71%, respectively. CONCLUSION: In this study, 62% of patients had nodal metastasis, 30% developed recurrence, and 15% developed second primary tumours. The overall one-year survival rate was 89%, although the development of recurrences and second primary tumours had a negative impact on the survival rate.

Clinicopathologic analysis of nodal T-follicular helper cell lymphomas, a multicenter retrospective study from China.

Background: Nodal T-follicular helper cell lymphomas (nTFHLs) represent a new family of peripheral T-cell lymphomas (PTCLs), and comparative studies of their constituents are rare. Methods: This study retrospectively enrolled 10 patients with nTFHL-F and 30 patients with nTFHL-NOS diagnosed between December 2017 and October 2023 at six large comprehensive tertiary hospitals; 188 patients with nTFHL-AI were diagnosed during the same period at the First Affiliated Hospital of Zhengzhou University for comparison. Results: Compared with nTFHL-AI, nTFHL-NOS patients exhibited better clinical manifestations, lower TFH expression levels, and a lower Ki-67 index. However, no differences in clinicopathological features were observed between nTFHL-F and nTFHL-AI patients as well as nTFHL-NOS patients. According to the survival analysis, the median OS for patients with nTFHL-NOS, nTFHL-AI, and nTFHL-F were 14.2 months, 10 months, and 5 months, respectively, whereas the median TTP were 14 months, 5 months, and 3 months, respectively. Statistical analysis revealed differences in TTP among the three subtypes(P=0.0173). Among the population of patients receiving CHOP-like induction therapy, there were significant differences in the OS and TTP among the nTFHL-NOS, nTFHL-AI, and nTFHL-F patients (P=0.0134, P=0.0205). Both the GDPT and C-PET regimens significantly improved the ORR, OS, and PFS in nTFHL patients. Conclusion: There are significant differences in the clinical manifestations, pathology, and survival outcomes among the three subtypes of nTFHLs. However, further research with a larger sample size, and involving clinical pathology and molecular genetics is needed to determine the distinctive biological characteristics of these tumors.

Identification of Novel Molecular and Clinical Biomarkers of Survival in Glioblastoma Multiforme Patients: A Study Based on The Cancer Genome Atlas Data.

Glioblastoma multiforme (GBM) is the most prevalent type of brain tumour; although advancements in treatment have been made, the median survival time for GBM patients has persisted at 15 months. This study is aimed at investigating the genetic alterations and clinical features of GBM patients to find predictors of survival. GBM patients' methylation and gene expression data along with clinical information from TCGA were retrieved. The most overrepresented pathways were identified independently for each omics dataset. From the genes found in at least 30% of these pathways, one gene that was identified in both sets was further examined using the Kaplan-Meier method for survival analysis. Additionally, three groups of patients who started radio and chemotherapy at different times were identified, and the influence of these variations in treatment modality on patient survival was evaluated. Four pathways that seemed to negatively impact survival and two with the opposite effect were identified. The methylation status of PRKCB was highlighted as a potential novel biomarker for patient survival. The study also found that treatment with chemotherapy prior to radiotherapy can have a significant impact on patient survival, which could lead to improvements in clinical management and therapeutic approaches for GBM patients.

A simple and robust parametric shared frailty model for recurrent events with the competing risk of death: An application to the Carvedilol Prospective Randomized Cumulative Survival trial.

Many non-fatal events can be considered recurrent in that they can occur repeatedly over time, and some researchers may be interested in the trajectory and relative risk of non-fatal events. With the competing risk of death, the treatment effect on the mean number of recurrent events is non-identifiable since the observed mean is a function of both the recurrent event and terminal event processes. In this paper, we assume independence between the non-fatal and the terminal event process, conditional on the shared frailty, to fit a parametric model that recovers the trajectory of, and identifies the effect of treatment on, the non-fatal event process in the presence of the competing risk of death. Simulation studies are conducted to verify the reliability of our estimators. We illustrate the method and perform model diagnostics using the Carvedilol Prospective Randomized Cumulative Survival trial which involves heart-failure events.