Sequential Shrinkage Estimate for COX Regression Models with Uncertain Number of Effective Variables

In the applications of COX regression models, we always encounter data sets that contain too many variables that only a few of them contribute to the model. Therefore, it will waste much more samples to estimate the “noneffective” variables in the inference. In this paper, we use a sequential procedure for constructing the fixed size confidence set for the “effective” parameters to the model based on an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size. Fixed design is considered for numerical simulation. The strong consistency, asymptotic distributions and convergence rates of estimates under the fixed design are obtained. In addition, the sequential procedure is shown to be asymptotically optimal in the sense of Chow and Robbins (1965).

Stratified Cox Regression Analysis of Survival under CIMAvax^(■)EGF Vaccine

Background: The Center of Molecular Immunology (CIM) is a center in Cuba devoted to the research, development and manufacturing of biotechnological products. CIMAvax?EGF is a vaccine for the treatment of non-small cell lung cancer patients (NSCL). Purpose: The aim of this work is to evaluate the effects of some potential prognostic factors on the overall survival of patients treated with CIMAvax?EGF vaccine, based on data collected in a phase II and a phase III clinical trials. Methods: The stratified Cox regression model is used to evaluate the effects of these prognostic factors, based on separate analysis for each trial, and on the combined data from both trials. Results: Patients with Performance status 0 or 1, with IV stage of tumor and male under 60 years obtain more benefit in terms of overall survival if they receive CIMAvax?EGF. Conclusions: Vaccinated group has a better performance if patients have a performance status 0 or 1, stage IV and age under 60 years. These prognostic factors influence overall survival in a positive way for those patients that received CIMAvax?EGF.

Survival Analysis Using Cox Proportional Hazards Regression for Pile Bridge Piles Under Wet Service Conditions

This paper studies the deterioration of bridge substructures utilizing the Long-Term Bridge Performance(LTBP)Program InfoBridge^(TM)and develops a survival model using Cox proportional hazards regression.The survival anal­ysis is based on the National Bridge Inventory(NBI)dataset.The study calculates the survival rate of reinforced and prestressed concrete piles on bridges under marine conditions over a 29-year span(from 1992 to 2020).The state of Maryland is the primary focus of this study,with data from three neighboring regions,the District of Columbia,Vir­ginia,and Delaware to expand the sample size.The data obtained from the National Bridge Inventory are condensed and filtered to acquire the most relevant information for model development.The Cox proportional hazards regres­sion is applied to the condensed NBI data with six parameters:Age,ADT,ADTT,number of spans,span length,and structural length.Two survival models are generated for the bridge substructures:Reinforced and prestressed concrete piles in Maryland and reinforced and prestressed concrete piles in wet service conditions in the District of Columbia,Maryland,Delaware,and Virginia.Results from the Cox proportional hazards regression are used to construct Markov chains to demonstrate the sequence of the deterioration of bridge substructures.The Markov chains can be used as a tool to assist in the prediction and decision-making for repair,rehabilitation,and replacement of bridge piles.Based on the numerical model,the Pile Assessment Matrix Program(PAM)is developed to facilitate the assessment and main­tenance of current bridge structures.The program integrates the NBI database with the inspection and research reports from various states’department of transportation,to serve as a tool for condition state simulation based on mainte­nance or rehabilitation strategies.

COX MULTIVARIATE REGRESSION ANALYSIS OF RECURRENCE FACTORS FOR COLONIC CARCINOMA

Objective: To determine the independent prognostic factors in the recurrence of colonic carcinoma after curative resection. Methods: Two hundred and one patients undergoing curative resections for colonic carcinoma were investigated by univariate and Cox multivariate regression analyses. Ten factors contributed to the rate were analyzed. Results: Dukes stages, obstruction, postoperative chemotherapy as well as the growth manner of the tumor were significantly associated with the recurrence rate of colonic carcinoma (P<0.05) by univariate analysis, while Dukes stages, obstruction, and postoperative chemotherapy were significant factors by the multivariate analysis. Conclusion: Dukes stages, obstruction, and postoperative chemotherapy are independent prognostic factors in the recurrence of colonic carcinoma.

Lymph node dissection does not affect the survival of patients with tumor node metastasis stages Ⅰ and Ⅱ colorectal cancer

BACKGROUND The effect of the number of lymph node dissections(LNDs)during radical resection for colorectal cancer(CRC)on overall survival(OS)remains controver-sial.AIM To investigate the association between the number of LNDs and OS in patients with tumor node metastasis(TNM)stage Ⅰ–Ⅱ CRC undergoing radical resection.METHODS Patients who underwent radical resection for CRC at a single-center hospital between January 2011 and December 2021 were retrospectively analyzed.Cox regression analyses were performed to identify the independent predictors of OS at different T stages.RESULTS A total of 2850 patients who underwent laparoscopic radical resection for CRC were enrolled.At stage T1,age[P<0.01,hazard ratio(HR)=1.075,95%confidence interval(CI):1.019-1.134]and tumour size(P=0.021,HR=3.635,95%CI:1.210-10.917)were independent risk factors for OS.At stage T2,age(P<0.01,HR=1.064,95%CI:1.032-1.098)and overall complications(P=0.012,HR=2.297,95%CI:1.200-4.397)were independent risk factors for OS.At stage T3,only age(P<0.01,HR=1.047,95%CI:1.027-1.066)was an independent risk factor for OS.At stage T4,age(P<0.01,HR=1.057,95%CI:1.039-1.075)and body mass index(P=0.034,HR=0.941,95%CI:0.890-0.995)were independent risk factors for OS.However,there was no association between LNDs and OS in stages Ⅰ and Ⅱ.CONCLUSION The number of LDNs did not affect the survival of patients with TNM stages Ⅰ and Ⅱ CRC.Therefore,insufficient LNDs should not be a cause for alarm during the surgery.

Cumulative effects of excess high-normal alanine aminotransferase levels in relation to new-onset metabolic dysfunction-associated fatty liver disease in China

BACKGROUND Within the normal range,elevated alanine aminotransferase(ALT)levels are associated with an increased risk of metabolic dysfunction-associated fatty liver disease(MAFLD).AIM To investigate the associations between repeated high-normal ALT measurements and the risk of new-onset MAFLD prospectively.METHODS A cohort of 3553 participants followed for four consecutive health examinations over 4 years was selected.The incidence rate,cumulative times,and equally and unequally weighted cumulative effects of excess high-normal ALT levels(ehALT)were measured.Cox proportional hazards regression was used to analyse the association between the cumulative effects of ehALT and the risk of new-onset MAFLD.RESULTS A total of 83.13%of participants with MAFLD had normal ALT levels.The incidence rate of MAFLD showed a linear increasing trend in the cumulative ehALT group.Compared with those in the low-normal ALT group,the multivariate adjusted hazard ratios of the equally and unequally weighted cumulative effects of ehALT were 1.651[95%confidence interval(CI):1.199-2.273]and 1.535(95%CI:1.119-2.106)in the third quartile and 1.616(95%CI:1.162-2.246)and 1.580(95%CI:1.155-2.162)in the fourth quartile,respectively.CONCLUSION Most participants with MAFLD had normal ALT levels.Long-term high-normal ALT levels were associated with a cumulative increased risk of new-onset MAFLD.

The burden of upper motor neuron involvement is correlated with the bilateral limb involvement interval in patients with amyotrophic lateral sclerosis:a retrospective observational study

Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.

Predictive model for 5.year mortality after breast cancer surgery in Taiwan residents

Background:Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years.This study aimed to validate the use of the artificial neural network(ANN)model to predict the 5?year mortality of breast cancer patients after surgery and compare predictive accuracy between the ANN model,multiple logistic regression(MLR)model,and Cox regression model.Methods:This study compared the MLR,Cox,and ANN models based on clinical data of 3632 breast cancer patients who underwent surgery between 1996 and 2010.An estimation dataset was used to train the model,and a validation dataset was used to evaluate model performance.The sensitivity analysis was also used to assess the relative signifi?cance of input variables in the prediction model.Results:The ANN model significantly outperformed the MLR and Cox models in predicting 5?year mortality,with higher overall performance indices.The results indicated that the 5?year postoperative mortality of breast cancer patients was significantly associated with age,Charlson comorbidity index(CCI),chemotherapy,radiotherapy,hormone therapy,and breast cancer surgery volumes of hospital and surgeon(all P<0.05).Breast cancer surgery volume of surgeon was the most influential(sensitive)variable affecting 5?year mortality,followed by breast cancer surgery volume of hospital,age,and CCI.Conclusions:Compared with the conventional MLR and Cox models,the ANN model was more accurate in predict?ing 5?year mortality of breast cancer patients who underwent surgery.The mortality predictors identified in this study can also be used to educate candidates for breast cancer surgery with respect to the course of recovery and health outcomes.

Diagnostic and Prognostic Significance of Keapl mRNA Expression for Lung Cancer Based on Microarray and Clinical Information from Oncomine Database

We performed a bioinformatics analysis with validation by multiple databases,aiming to evaluate the diagnostic and prognostic value of Kelch-like ECH-associated protein 1(Keapl)mRNA for lung cancer,and to explore possible mechanisms.Diagnostic performance of Keapl mRNA was determined by receiver operating characteristic(ROC)curve analysis.Prognostic implication of Keapl mRNA was estimated by Kaplan-Meier survival analysis.Co-expressed genes with both Keapl and Nfe2L2 were identified by LinkedOmics.Mechanisms of Keapl-Nfe2L2-co-expressed genes underlying the pathogenesis of lung cancer were explored by function enrichment and pathway analysis.The ROC curve analysis determined a good diagnostic performance of Keapl mRNA for lung squamous cell carcinoma(LUSC),with an area under the ROC curve(AUC)of 0.833,sensitivity of 72.7%,and specificity of 90.6%(P<0.001).Multivariate Cox regression recognized high Keapl mRNA to be an independent risk factor of mortality for overall lung cancer[hazard ratio(HR):11.034,P=0.044],but an independent antagonistic factor for lung adenocarcinoma(LUAD)(HR:0.404,P<0.001).Validation by UALCAN and GEPIA supported Oncomine findings regarding the diagnostic value of Keapl mRNA for LUSC,but denied its prognostic value.After screening,we identified 17 co-expressed genes with both Keapl and Nfe2L2 for LUAD,and 22 for LUSC,mainly enriched in signaling pathway of oxidative stress-induced gene expression via Nrf2.In conclusion,Keapl mRNA has a good diagnostic performance,but controversial prognostic efficacy for LUSC.The pathogenesis of lung cancer is associated with Keapl-Nfe2L2-co-expressed genes by signaling pathway of oxidative stress-induced gene expression via Nrf2.

Signature Based on Six Autophagy-related Genes to Predict Prognosis of Head and Neck Squamous Cell Carcinoma

Objective The present study aimed to develop an autophagy-related gene prognostic prediction model to provide survival risk prediction for head and neck squamous cell carcinoma(HNSCC)patients.Methods The K-mean cluster analysis was performed on HNSCC samples based on the expression values of 210 autophagy-related genes for candidate signature gene selection.LASSO Cox regression analysis was generated using the potential genes and the risk score was calculated from the prognosis model.The risk score was processed as an independent prognostic indicator to construct the nomogram model.The immune status including immune cell infiltration ratio and checkpoints of patients with HNSCC in high-and low-risk groups was also explored.Results LASSO Cox regression analysis was performed on the selected autophagy-related genes.According to the lambda value corresponding to the number of different genes in the LASSO Cox analysis,six genes(GABARAPL2,SAR1A,ST13,GAPDH,FADD and LAMP1)were finally chosen.The risk score based on the genes was generated,which was an independent prognostic marker for HNSCC.The prognostic prediction model(nomogram)was further optimized by the independent prognostic factors(risk score),which can better predict the prognosis and survival of patients.With the risk score and prognosis model,eight types of immune cells and six key immune checkpoints(CTLA4,PD1,IDO1,TDO2,LAG3,TIGIT)displayed expression specificity.Conclusion This study identified several potential prognostic biomarkers and established an autophagy-related prognostic prediction model for HNSCC,which provides a valuable reference for future clinical research.

Survival Rate Analysis on Breast Cancer Cases at Univesity College Hospital, Ibadan, Nigeria

Breast cancer is one of the leading diseases that affect women’s lives. It affects their lives in so many ways by denying them the required standard of health needed to carry out all of their daily activities for some days, weeks, months or years before eventually causing death. This research estimates the survival rate of breast cancer patients and investigates the effects of stage of tumor, gender, age, ethnic group, occupation, marital status and type of cancer upon the survival of patients. Data used for the study were extracted from the case file of patients in the Radiation Oncology Department, University College Hospital, Ibadan using a well-structured pro forma in which 74 observations were censored and 30 events occurred. The Kaplan-Meier estimator was used to estimate the overall survival probability of breast cancer patients following their recruitment into the study and determine the mean and median survival times of breast cancer patients following their time of recruitment into the study. Since there are different groups with respect to the stages of tumor at the time of diagnosis, the log-rank test was used to compare the survival curve of the stages of tumor with considering p-values below 0.05 as statistically significant. Multivariate Cox regression was used to investigate the effects of some variables on the survival of patients. The overall cumulative survival probability obtained is 0.175 (17.5%). The overall estimated mean time until death is 28.751 weeks while the median time between admission and death is 23 weeks. As the p-value (0.000032) of the log-rank test for comparing stages of tumor is less than 0.05, it is concluded that there is significant evidence of a difference in survival times for the stages of tumor. The survival function plot for the stages of tumor shows that patients with stage III tumor are less likely to survive. From the estimated mean time until death for the stages of tumor, it was deduced that stage I tumor patients have an increased chance of survival. Types of cancer, gender, marital status, ethnic group, occupation and patient’s age at entry into the study are not important predictors of chances of survival.

Evidence-Based Therapy May Improve Outcome in Glomerulonephritis—A Prospective Field Survey

Introduction and aims: Although glomerulonephritis is rare in the general population it is the second most important cause for end-stage renal failure. The therapy of glomerulonephritis is guided by a limited number of individual clinical trials and treatment recommendations are based on meta-analysis and Cochrane Systematic Reviews. The impact of such therapy standards on the prognosis of glomerulonephritis is not known. Methods: Between October 2002 and December 2008 patients with abnormal urine findings and/or decreasing renal function of unknown cause were referred for renal biopsy. In a collaboration of out-patient nephrologists with a major teaching hospital, all patients received treatment recommendations according to evidence-based therapy guidelines based on Cochrane Systematic Reviews. Patient charts were systematically reviewed and patients were re-examined for follow-up until November 2009. Cox Regression analysis was performed to identify independent prognostic factors. Results: Two hundred patients with primary or secondary glomerulonephritis were identified. Complete follow-up data were available from 196 patients with 324 therapeutic interventions. The mean follow-up was 2.8 ± 2.0 years. Among all patients, 37% remained unchanged ill, 13% died, 17% had progressing renal disease, while 19% had a complete and 14% a partial remission. Proteinuria declined in primary glomerulonephritis (5.0 ± 5.4 g/d to 2.1 ± 3.4 g/d, p Conclusions: In a multivariate model of standardised glomerulonephritis therapy the presence of tubulointerstitial fibrosis was associated with death or progresssive renal disease, while prednisolone-based therapy regimens and intensified nephrological follow-up resulted in a significant delay of endstage-renal failure. This result should direct future health care policies because glomerulonephritis accounts for nearly 20% of the dialysis population.

Retrospective analysis of clinical characteristics and prognostic factors for pathologic fracture in 44 patients with extremity osteosarcoma

Objective: The aim of this study was to identify the clinical features and prognostic factors associated with extremity osteosarcoma with pathologic fracture. Methods: The clinical records of 271 patients with extremity osteosarcomas were retrospectively reviewed. The data obtained covered the period from October 2003 to May 2012, and included sex, age, tumor site etc. The mean follow-up time was 25.2 months(ranged from 1 to 117). Chi-square method and Kaplan-Meier method were used to compare clinical differences and overall survival between patients with or without pathologic fracture, respectively. The univariate analysis was used to determine the prognostic factors related with survival rate by log-rank test. The multivariate analysis of prognosis was performed by COX proportional hazards regression model. Results: The proportions of patients having a tumor's diameter of 10 cm or more(P = 0.038), locating upper limbs(P = 0.004) and receiving amputation surgery(P = 0.02) were significantly higher with pathological fracture group than without pathological fracture group. The local recurrence rate(P = 0.000) was also significantly higher in the pathological fracture group. The median survival time of patients with or without pathological fracture was 16(95% confidence interval: 14.6–17.4) months and 22(95% confidence interval: 19.8–24.1) months(P = 0.002). The Log-rank univariate analysis indicated that the tumor size, Enneking's surgical staging, Karnofsky performance status(KPS) score, cycles of adjuvant chemotherapy, local recurrence and metastasis were significantly related to overall survival. Multivariate Cox regression analysis revealed KPS score, cycles of adjuvant chemotherapy and metastasis were independent prognostic factors(P < 0.05). Conclusion: Compared with the patients without pathological fracture, a higher proportion of patients receiving amputation surgery or having larger tumor size, humeral osteosarcoma or local recurrence was observed in patients with pathological fracture, and the prognosis of these patients was poor. The independent prognostic factors of extremity osteosarcoma with pathologic fracture were the KPS score, cycles of adjuvant chemotherapy and metastasis.

Survival Analysis of Logistics Service Providers: An Empirical Study of Chengdu, Area in China

This paper worked on a sample of 6791 logistics establishments registered in Chengdu, China over the period 1984-2016 to understand the survival status of logistics service providers (LSPs) by non-parametric Kaplan-Meier estimation, together with Cox proportional hazard regression model, to identify factors affecting the failure of LSPs. In particular, it studies the interaction effect between LSPs’ size and entry timing and location. The empirical results show that: 1) Regarding the survival time, 1365 of the 6791 sample LSPs exited from the market by 2017. The exit rate is 20.1%, and the average life of the 6791 LSPs is about 6 years. 2) The survival of LSPs depends on their typology, ownership structure. And there is no significant difference in the probability of survival for both independent LSPs and logistics branches after controlling the effects of other variables. 3) Location and entry timing also play an important role in the survival of small-scale LSPs, but these factors cannot explain large-scale LSPs’ failure.

The 6-hour lactate clearance rate in predicting 30-day mortality in cardiogenic shock

Background Early evaluation of prognosis in cardiogenic shock(CS)is crucial for tailored treatment selection.Both lactate clearance and lactate levels are considered useful prognostic biomarkers in patients with CS.However,there is yet no literature comparing the 6-hour lactate clearance rate(Δ6Lac)with lactate levels measured at admission(L1)and after 6 h(L2)to predict 30-day mortality in CS.Methods In this observational cohort study,95 patients with CS were treated at Department of Intensive Care Unit,Yiwu Central Hospital between January 2020 and December 2022.Of these,88 patients met the eligibility criteria.The lactate levels were measured after admission(L1)as the baseline lactate value,and were measured after 6 h(L2)following admission.The primary endpoint of the study was survival rate at 30 days.A receiver operating characteristic curve was used for data analysis.Univariate and multivariate Cox regression analyses were performed based onΔ6Lac.Kaplan–Meier(KM)survival curves were generated to compare the 30-day survival rates among L1,L2,andΔ6Lac.Results TheΔ6Lac model showed the highest area under the curve value(0.839),followed by the L2(0.805)and L1(0.668)models.TheΔ6Lac model showed a sensitivity of 84.2%and specificity of 75.4%.The L1 and L2 models had sensitivities of 57.9%each and specificities of 89.9%and 98.6%,respectively.The cut-off values forΔ6Lac,L1,and L2 were 18.2%,6.7 mmol/L,and 6.1 mmol/L,respectively.Univariate Cox regression analysis revealed a significant association betweenΔ6Lac and 30-day mortality.After adjusting for five models in multivariate Cox regression,Δ6Lac remained a significant risk factor for 30-day mortality in patients with CS.In our fifth multivariate Cox regression model,Δ6Lac remained a risk factor associated with 30-day mortality(hazard ratio[HR]=5.14,95%confidence interval[CI]:1.48 to 17.89,P=0.010)as well as L2(HR=8.42,95%CI:1.26 to 56.22,P=0.028).The KM survival curve analysis revealed that L1>6.7 mmol/L(HR=8.08,95%CI:3.23 to 20.20,P<0.001),L2>6.1 mmol/L(HR=25.97,95%CI:9.76 to 69.15,P<0.001),andΔ6Lac≤18.2%(HR=8.92,95%CI:2.95 to 26.95,P<0.001)were associated with a higher risk of 30-day mortality.ConclusionsΔ6Lac is a better predictor for 30-day mortality in CS than lactate levels at admission.It has a predictive value equivalent to that of lactate level at 6 h after admission,making it an important surrogate indicator for evaluating the suitability as well as poor prognosis after CS treatment.We found that a cut-off value of 18.2%forΔ6Lac provided the most accurate assessment of early prognosis in CS.

Association of stage 1 hypertension defined by the 2017 ACC/AHA guideline with cardiovascular events and mortality in Chinese adults

Background:The 2017 American College of Cardiology/American Heart Association(ACC/AHA)blood pressure(BP)guideline lowered the threshold defining hypertension to 130/80 mmHg.However,how stage 1 hypertension defined using this guideline is associated with cardiovascular events in Chinese adults remains unclear.This study assessed the association between stage 1 hypertension defined by the 2017 ACC/AHA guideline and clinical outcomes in the Chinese population.Methods:Participants with stage 1 hypertension(n=69,509)or normal BP(n=34,142)were followed in this study from 2006/2007 to 2020.Stage 1 hypertension was defined as a systolic blood pressure of 130-139 mmHg or a diastolic blood pressure of 80-89 mmHg.None were taking antihypertensive medication or had a history of myocardial infarction(MI),stroke,or cancer at baseline.The primary outcome was a composite of MI,stroke,and all-cause mortality.The secondary outcomes were individual components of the primary outcome.Cox proportional hazards models were used for the analysis.Results:During a median follow-up of 11.09 years,we observed 10,479 events(MI,n=995;stroke,n=3408;all-cause mortality,n=7094).After multivariable adjustment,the hazard ratios for stage 1 hypertension vs.normal BP were 1.20(95%confidence interval[CI],1.13-1.25)for primary outcome,1.24(95%CI,1.05-1.46)for MI,1.45(95%CI,1.33-1.59)for stroke,and 1.11(95%CI,1.04-1.17)for all-cause mortality.The hazard ratios for participants with stage 1 hypertension who were prescribed antihypertensive medications compared with those without antihypertensive treatment during the follow-up was 0.90(95%CI,0.85-0.96).Conclusions:Using the new definition,Chinese adults with untreated stage 1 hypertension are at higher risk for MI,stroke,and all-cause mortality.This finding may help to validate the new BP classification system in China.

The Effect of Xu’s Influenza Decoction Combined with Oseltamivir on Influenza A:A Propensity Score Matching Study

Background:The resurgence of seasonal influenza virus circulation has been seen in 2021-2022 after the tempo-rary suppression in 2020-2021.Neuraminidase inhibitors(NAIs)are widely applied in the clinical treatment of influenza A despite several limitations.Objective:To access the efficacy of Xu’s influenza decoction(XID)in combination therapy with oseltamivir for the treatment of influenza A.Methods:In this retrospective cohort study,the eligible participants were diagnosed with influenza A between June 1,2018,and May 30,2022,in the First Affiliated Hospital of Zhejiang Chinese Medical University.According to whether Xu’s influenza decoction was applied,patients were divided into two groups:treated with or without XID.Propensity score matching(PSM)was used to further adjust the covariates between groups.The primary outcome was to compare time to defervescence via K-M curves,Breslow tests,and Cox regression analysis.In Cox proportional hazards model,a univariate analysis was performed to obtain preliminary results,while a further multivariate analysis was conducted to study the independent factors that influence defervescence.Subgroup analysis was conducted according to body temperature and time from onset to admission.The secondary outcome consisted of routine blood and C-reactive protein(CRP),length of stay,and medical costs.Results:A total of 336 patients with influenza A were enrolled in this study(i.e.,163 patients in the XID+oseltamivir group;173 patients in the oseltamivir group).After 1:1 matching via PSM,230 patients meeting the criteria were included in the analysis,with 115 in each arm.The XID+oseltamivir group had shorter time to defervescence(36 h vs 44 h,P=0.011),shorter length of stay(3 days vs 4 days,P=0.018),and higher defervescence possibility(HR=1.384,95%CI:1.054-1.818).Subgroup analysis indicated that for patients during non-window period(≥48 h)with medium-grade fever(38.1℃-39℃),the XID+oseltamivir combination therapy reduced time to defervescence(P=0.04995/0.004)with a higher defervescence possibility(HR=1.524/1.683).Meanwhile,there’s no statistical significance but observable trends of the XID+oseltamivir group in the lower medical costs(3068.07 yuan vs 3120.68 yuan),the lower neutrophils%(48.53%vs 51.00%)and the higher lymphocyte%(39.83%vs 37.72%).Conclusion:The combination of XID and oseltamivir can shorten the time to defervescence and length of stay in influenza A.Its antipyretic effect is mainly reflected in the medium-grade and non-window periods.

Relationship between COX-2 expression and clinicopathological features of colorectal cancers

Background Cyclo-oxgenase 2 (COX-2) is involved in prostaglandin synthesis in central nervous system, and it also plays a role in human carcinogenesis Our purpose of this study is to investigate the COX-2 expression in different development stages of colorectal cancer, and to discuss the relationship between the gene expression and clinicopathological features of the cancer Methods COX-2 expression was examined by immunohistochemical staining in 76 surgical specimens of colorectal cancer (44 of advanced stage and 32 of early stage), thirty-three adenomas and 18 normal colonic mucosal tissues taken by endoscopic biopsy Kaplan-Meier survival curves and Cox proportional hazards regression were used to evaluate the relation of COX-2 to prognosis Results COX-2 expression, divided into 4 grades from “-” to“+++”, is respectively 83 3%, 16 7%, 0% and 0% in normal colonic mucosal tissues; 12 1%, 42 4%, 36 4% and 9 1% in adenomas; 6 3%, 28 1%, 46 9% and 18 7% in early colorectal cancers (ECCs), and 6 8%, 20 5%, 18 2% and 54 5% in advanced colorectal cancers (CRCs) The differences in COX-2 expression between advanced CRCs and early colorectal cancers (ECCs) as well as between the advanced CRCs and adenomas were statistically significant ( P <0 01); but there was no significant difference between ECCs and adenomas Kaplan-Meier survival analysis showed a significant difference in the survival curves between low high COX-2 groups ( P <0 05) Cox proportional hazards regression showed that COX-2 expression was related to poorer long-term outcome with a hazard ratio of 2 665 unadjusted for other variables ( P <0 05), and COX-2 expression was an independent risk factor of poor prognosis KH*2/5DConclusions COX-2 expression is gradually up-regulated in the development from normal epithelium to adenomas and from ECCs to advanced CRCs Alhough the COX-2 protein can not be regarded as a tumor marker to diagnose CRCs early, COX-2 expression can be regarded as an independent risk factor of poor prognosis for postoperative patients with advanced CRCs

Study for Prognosis and Survival Rate of Ovarian Cancer

In this paper, we analyze ovarian cancer cases from six hospitals in China, screen the prognostic factors and predict the survival rate. The data has the feature that all the covariates are categorical. We use three methods to estimate the survival rate–the traditional Cox regression, the two-step Cox regression and a method based on conditional inference tree. By comparison, we know that they are all effective and can predict the survival curve reasonably. The analysis results show that the survival rate is determined by a combination of risk factors, where clinical stage is the most important prognosis factor.

Transcriptomic analysis reveals key lnc RNAs associated with ribosomal biogenesis and epidermis differentiation in head and neck squamous cell carcinoma

Objective： In this study, we aimed to expand current knowledge of head and neck squamous cell carcinoma （HNSCC）-associated long noncoding RNAs （IncRNAs）, and to discover potential IncRNA prognostic biomarkers for HNSCC based on next-generation RNA-seq. Methods： RNA-seq data of 546 samples from patients with HNSCC were downloaded from The Cancer Genome Atlas （TCGA）, including 43 paired samples of tumor tissue and adjacent normal tissue. An integrated analysis incorporating differential expression, weighted gene co-expression networks, functional enrichment, clinical parameters, and survival analysis was conducted to discover HNSCC-associated IncRNAs. The function of CYTOR was verified by cell-based experiments. To further identify IncRNAs with prognostic significance, a multivariate Cox proportional hazard regression analysis was performed. The identified IncRNAs were validated with an independent cohort using clinical feature relevance analysis and multivariate Cox regression analysis. Results： We identified nine HNSCC-relevant IncRNAs likely to play pivotal roles in HNSCC onset and development. By functional enrichment analysis, we revealed that CYTOR might participate in the multistep pathological processes of cancer, such as ribosome biogenesis and maintenance of genomic stability. CY-I-OR was identified to be positively correlated with lymph node metastasis, and significantly negatively correlated with overall survival （OS） and disease free survival （DFS） of HNSCC patients. Moreover, CYTOR inhibited cell apoptosis following treatment with the chemotherapeutic drug diamminedichloroplatinum （DDP）. HCG22, the most dramatically down-regulated IncRNA in tumor tissue, may function in epidermis differentiation. It was also significantly associated with several clinical features of patients with HNSCC, and positively correlated with patient survival. CYTOR and HCG22 maintained their prognostic values in- dependent of several clinical features in multivariate Cox hazards analysis. Notably, validation either based on an independent HNSCC cohort or by laboratory experiments confirmed these findings. Conclusions： Our transcriptomic analysis suggested that dysregulation of these HNSCC-associated IncRNAs might be involved in HNSCC oncogenesis and progression. Moreover, CYTOR and HCG22 were confirmed as two independent prognostic factors for HNSCC patient survival, providing new insights into the roles of these IncRNAs in HNSCC as well as clinical applications.