Evaluation of Efficacy and Prognosis Analysis of Stage III-IV SMARCA4-deficient Non-small Cell Lung Cancer Treated by PD-1 Immune Checkpoint Inhibitors plus Chemotherapy and Chemotherapy / 中国肺癌杂志

BACKGROUND@#The SMARCA4 mutation has been shown to account for at least 10% of non-small cell lung cancer (NSCLC). In the present, conventional radiotherapy and targeted therapy are difficult to improve outcomes due to the highly aggressive and refractory nature of SMARCA4-deficient NSCLC (SMARCA4-DNSCLC) and the absence of sensitive site mutations for targeted drug therapy, and chemotherapy combined with or without immunotherapy is the main treatment. Effective SMARCA4-DNSCLC therapeutic options, however, are still debatable. Our study aimed to investigate the efficacy and prognosis of programmed cell death 1 (PD-1) immune checkpoint inhibitors (ICIs) in combination with chemotherapy and chemotherapy in patients with stage III-IV SMARCA4-DNSCLC.@*METHODS@#46 patients with stage III-IV SMARCA4-DNSCLC were divided into two groups based on their treatment regimen: the chemotherapy group and the PD-1 ICIs plus chemotherapy group, and their clinical data were retrospectively analyzed. Efficacy assessment and survival analysis were performed in both groups, and the influencing factors for prognosis were explored for patients with SMARCA4-DNSCLC.@*RESULTS@#Male smokers are more likely to develop SMARCA4-DNSCLC. There was no significant difference in the objective response rate (76.5% vs 69.0%, P=0.836) between chemotherapy and the PD-1 ICIs plus chemotherapy or the disease control rate (100.0% vs 89.7%, P=0.286). The one-year overall survival rate in the group with PD-1 ICIs plus chemotherapy was 62.7%, and that of the chemotherapy group was 46.0%. The difference in median progression-free survival (PFS) between the PD-1 ICIs plus chemotherapy group and the chemotherapy group was statistically significant (9.3 mon vs 6.1 mon, P=0.048). The results of Cox regression analysis showed that treatment regimen and smoking history were independent influencing factors of PFS in patients with stage III-IV SMARCA4-DNSCLC, and family history was an individual influencing factor of overall survival in patients with stage III-IV SMARCA4-DNSCLC.@*CONCLUSIONS@#Treatment regimen may be a prognostic factor for patients with SMARCA4-DNSCLC, and patients with PD-1 ICIs plus chemotherapy may have a better prognosis.

Survival analysis on patients with occupational pneumoconiosis in Guangdong Province from 1980 to 2019 / 中国职业医学

Objective: To study the survival time and its risk factors of patients with occupational pneumoconiosis. Methods: A total of 11 011 newly diagnosed occupational pneumoconiosis patients in Guangdong Province from 1980 to 2019 were selected as study subjects. The life table method was used for survival analysis. The influencing factors of survival time of occupational pneumoconiosis patients were analyzed using the WilCoxon (Gehan) test and Cox proportional hazards regression model. Results: The median survival time of pneumoconiosis patients was 26.0 years. The median survival period of stage Ⅰpatients was 3.5 years longer than that of stage Ⅱ patients and 10.1 years longer than that of stage Ⅲ patients. The median survival time of patients with an initial diagnosis age under 40.0 years old was 34.8 years longer than that of patients with an initial diagnosis age over 60.0 years old. The median survival time of patients with dust exposure duration under 25.0 years old was 13.6 years longer than patients with dust exposure duration age over 45.0 years old. The results of the Cox proportional hazards regression model showed that the initial diagnosis stage, initial diagnosis age, dust exposure duration, and medical insurance were risk factors of the survival time of occupational pneumoconiosis patients (all P<0.01). The risk of reduced survival time for patients with stage Ⅱ and stage Ⅲ as the initial diagnosis stage was 1.15 and 2.04 times higher, respectively, compared with stage Ⅰ patients (both P<0.01). The risk of reduced survival time for patients without medical insurance was 60.22 times higher than those with medical insurance (P<0.01). Conclusion: The risk factors of the survival time of occupational pneumoconiosis patients in Guangdong Province are initial diagnosis stage, initial diagnosis age, the dust exposure age, and medical insurance. Earlier detection, earlier diagnosis, and improvement of medical insurance coverage for patients can effectively improve the survival time of occupational pneumoconiosis patients.

Establishment and evaluation of a multivariate Cox proportional-hazards prediction model for mortality during short-term hospitalization in patients with liver cirrhosis and sepsis / 临床肝胆病杂志

Objective To establish a Cox proportional-hazards prediction model for mortality during short-term hospitalization in patients with liver cirrhosis and sepsis. Methods A retrospective analysis was performed for the clinical data of 336 patients with liver cirrhosis and sepsis who were admitted to The Third People's Hospital of Kunming from January 2012 to August 2022, and according to whether the patient died during short-term hospitalization, they were divided into death group with 40 patients and survival group with 296 patients. Demographic data, comorbidities, and clinical biochemical parameters were collected and compared between the two groups. The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups. The multivariate Cox analysis was used for screening of variables, then a Cox proportional-hazards prediction model was established, and hazard ratio ( HR ) and its 95% confidence interval [ CI ] were calculated; C-index index was used to evaluate the prediction accuracy of the model. The Cox proportional-hazards prediction model was visualized by a nomogram, and calibration curve was plotted to evaluate the consistency between the prediction results of the model and the actual condition. Results Among the 336 patients, there were 261 male patients (77.7%) and 75 female patients (22.3%), with a mean age of 50.0±10.6 years, and 40 patients died, with a mean hospital stay of 16.8±11.3 days (range 8.2-23.0 days). Compared with the survival group, the death group had a significantly higher proportion of patients with an age of ≥60 years, a history of invasive operation within the past two weeks, gastrointestinal bleeding, hepatic encephalopathy (HE) or hepatorenal syndrome (HRS), a significantly higher Modified Early Warning Score (MEWS) score, and significantly higher levels of prothrombin time (PT), activated partial thromboplastin time, international normalized ratio, D-dimer, CD4/CD8 ratio, lactate, white blood cell count, norepinephrine, total bilirubin, interleukin-6, procalcitonin, high-sensitivity C-reactive protein (hsCRP), blood urea nitrogen, and creatinine (all P < 0.05), as well as significantly lower levels of red blood cell count, hemoglobin, albumin, total cholesterol, low-density lipoprotein, and high-density lipoprotein (all P < 0.05). The multivariate Cox regression analysis showed that age ( HR =2.602, 95% CI : 1.277-5.303, P =0.008), HE ( HR =2.516, 95% CI : 1.258-5.033, P =0.009), HRS ( HR =2.324, 95% CI : 1.010-5.349, P =0.047), hsCRP ( HR =1.008, 95% CI : 1.003-1.013, P =0.004), MEWS score ( HR =1.205, 95% CI : 1.022-1.422, P =0.027), and PT ( HR =1.076, 95% CI : 1.030-1.124, P =0.027) were independent influencing factors for death in patients with liver cirrhosis and sepsis. The model showed a C-index of 0.857 (95% CI : 0.815-0.920), suggesting that the model had relatively high prediction accuracy, and the calibration curve showed good consistency between the predicted risk and the actual risk. Conclusion The Cox proportional-hazards prediction model established for death during short-term hospitalization in patients with liver cirrhosis and sepsis can be used to predict the risk of death during short-term hospitalization in patients with liver cirrhosis and sepsis, thereby guiding clinical medical staff to take targeted intervention measures to avoid or reduce the possibility of death in patients.

COMPARISON OF COX PROPORTIONAL HAZARD MODEL AND ACCELERATED FAILURE TIME (AFT) MODELS: AN APPLICATION TO UNDER-FIVE MORTALITY IN UTTAR PRADESH

The statistical field of survival analysis focuses on the examination of time-to-event data. The proportional hazards (PH) model is the most widely used in multivariate survival analysis to examine the effects of various factors on survival time. The statistics, however, do not always support the PH models assumption of constant hazards. The power of the associated statistical tests is reduced when the PH assumption is broken, which leads to incorrect interpretation of the estimation results. The accelerated failure time (AFT) models, on the other hand, do not, like the PH model, assume constant hazards in the survival data. Additionally, the AFT models can be employed in place of the PH model if the constant hazards assumption violated. This study set out to examine how well the PH model and the AFT models performed when it came to identifying the proximate variables influencing under – five mortality from National Family Health Survey data in Uttar Pradesh. Three AFT models that were based on the Weibull, exponential, and log-normal distributions were the only ones discussed in this article. The research employing a graphical technique and a statistical test revealed that the NFHS-5 data set has non-proportional hazards. The log-normal AFT model was the most acceptable model among the ones studied, according to the Akaike information criterion (AIC).

Determinants of to First Birth among women in Ethiopia using Cox Proportional Hazards Model

Backgroung: the age at first birth corresponds to the age of the mother giving birth to the first child. The delivery of the primary child is an important event that leaves a social mark on a woman's life. It is a woman's clear transition to parenthood with the roles and responsibilities involved. Premature birth can negatively affect women's socio-economic well-being in subsequent years. The study aims at accessing the determinants of age at first birth among Ethiopian women.Methods: the data for this study was extracted from the published reports of Ethiopian Demographic and Health Survey. The study used15, 683women aged 15-49 years from nine regions and two city administrations. Cox Proportional hazards model was used for identifying factors associated with age at first birth.Results: the median time of age at first birth for Ethiopian women was22 years with 95% CI; (21.82, 22.18).Cox Proportional Hazards Model shows that region, place of residence, education, wealth index, religion, work status, age at first marriage, age at first sex, and use of contraceptives have significant effects on the age at first birth at 5% level of significance. From region category, Amhararegion (p-value=0.398), BenishangulGumuz(p-value=0.112) Region, and Gambella region(p-value=0.062) were not significant at 5% level of significance.Conclusions: the age at first birth was positively correlated with the age at first sexual intercourse. A woman who has sexual intercourse much earlier gives birth earlier than a woman who is late for first intercourse.

Introdução: a idade do primeiro parto corresponde à idade da mãe que dá à luz ao primeiro filho. O parto do filho primário é um evento importante que deixa uma marca social na vida da mulher. É a transição clara de uma mulher para a paternidade com os papéis e responsabilidades envolvidos. O nascimento prematuro pode afetar negativamente o bem-estar socioeconômico das mulheres nos anos subsequentes. O estudo visa acessar os determinantes da idade ao primeiro parto entre as mulheres etíopes.Método: os dados para este estudo foram extraídos dos relatórios publicados do Ethiopian Demographic and Health Survey. O estudo utilizou15.683 mulheres de 15 a 49 anos de nove regiões e duas prefeituras. O modelo de riscos proporcionais de Cox foi utilizado para identificar os fatores associados à idade ao primeiro parto.Resultados: o tempo mediano de idade ao primeiro parto para mulheres etíopes foi de 22 anos com IC 95%; (21,82; 22,18).O Modelo de Riscos Proporcionais de Cox mostra que região, local de residência, educação, índice de riqueza, religião, situação profissional, idade do primeiro casamento, idade da primeira relação sexual e uso de anticoncepcionais têm efeitos significativos sobre a primeira idade nascimento ao nível de 5% de significância. Da categoria de região, Amhararegion (p-value=0,398), BenishangulGumuz (p-value=0,112) Region, e Gambella region (p-value=0,062) não foram significativos ao nível de significância de 5%.Conclusão: a idade do primeiro parto correlacionou-se positivamente com a idade da primeira relação sexual. Uma mulher que tem relações sexuais muito mais cedo, dá à luz mais cedo do que uma mulher que está atrasada para a primeira relação.

Comparison of Cox proportional hazards model, Cox proportional hazards with time-varying coefficients model, and lognormal accelerated failure time model: Application in time to event analysis of melioidosis patients

Objective: To compare the prognostic factors of mortality among melioidosis patients between lognormal accelerated failure time (AFT), Cox proportional hazards (PH), and Cox PH with timevarying coefficient (TVC) models. Methods: A retrospective study was conducted from 2014 to 2019 among 453 patients who were admitted to Hospital Sultanah Bahiyah, Kedah and Hospital Tuanku Fauziah, Perlis in Northern Malaysia due to confirmed-cultured melioidosis. The prognostic factors of mortality from melioidosis were obtained from AFT survival analysis, and Cox s models and the findings were compared by using the goodness of fit methods. The analyses were done by using Stata SE version 14.0. Results: A total of 242 patients (53.4%) survived. In this study, the median survival time of melioidosis patients was 30.0 days (95% CI 0.0-60.9). Six significant prognostic factors were identified in the Cox PH model and Cox PH-TVC model. In AFT survival analysis, a total of seven significant prognostic factors were identified. The results were found to be only a slight difference between the identified prognostic factors among the models. AFT survival showed better results compared to Cox's models, with the lowest Akaike information criteria and best fitted Cox-snell residuals. Conclusions: AFT survival analysis provides more reliable results and can be used as an alternative statistical analysis for determining the prognostic factors of mortality in melioidosis patients in certain situations.

Establishment and application of a nomogram model for prognostic risk prediction in patients with epithelial ovarian cancer / 中华妇产科杂志

Objective:To explore the prognostic factors of epithelial ovarian carcinoma (EOC), construct a nomogram model, and evaluate the prognosis of EOC patients.Methods:A retrospective analysis was performed on clinicopathological data of 208 cases of EOC patients who received initial treatment in the First Affiliated Hospital of Army Medical University from August 11, 2016 to July 11, 2018, including age, preoperative ascites, preoperative neoadjuvant chemotherapy, surgical method, pathological type, pathological differentiation degree, surgical pathology stage, preoperative and post-chemotherapy serum cancer antigen 125 (CA 125) level, human epididymal protein 4 (HE4) level, platelet count and platelet/lymphocyte number ratio (PLR). The univariate and multivariate Cox risk ratio models were used to analyze the related factors affecting progression free survival (PFS) in EOC patients, and the prediction nomogram of PFS in EOC patients was established to evaluate its efficacy in predicting PFS. Results:Univariate analysis showed that preoperative neoadjuvant chemotherapy, pathological type, pathological differentiation degree, surgical pathology stage, serum CA 125 and HE4 level before operation and after chemotherapy, platelet count and PLR before operation and after chemotherapy were significantly correlated with PFS in EOC patients (all P<0.05). Multivariate analysis showed that surgical pathology stage, preoperative PLR, serum CA 125 and HE4 level after chemotherapy were independent prognostic factors affecting PFS of EOC patients (all P<0.01). The index coefficient of the prediction model for the prognosis of EOC patients established by this method was 0.749 (95% CI: 0.699-0.798), which had good prediction ability, and could help clinicians to more accurately evaluate the prognosis of EOC patients. Conclusion:The nomogram model constructed based on surgical pathology stage, preoperative PLR, serum CA 125 and HE4 level after chemotherapy could effectively predict the PFS of EOC patients after initial treatment, could help clinicians to screen high-risk patients, provide individualized treatment, and improve the prognosis of EOC patients.

Development and validation of nomograms for predicting stroke recurrence after firstepisode ischemic stroke / 南方医科大学学报

OBJECTIVE@#To explore the risk factors for recurrence in first-episode ischemic stroke survivors and establish a model for predicting stroke recurrence using a nomogram.@*METHODS@#We collected the data from a total of 821 first-episode ischemic stroke survivors admitted in the Department of Neurology, West China Hospital, Sichuan University from January, 2010 to December, 2018. R software was used for random sampling of the patients, and 70% of the patients were included in the training set to establish the prediction model and 30% were included in the validation set. Cox proportional risk regression model was used to analyze the factors affecting stroke recurrence, and R software rms package was used to construct the histogram and establish the visual prediction model. C-index and calibration curve were used to evaluate the performance of the model for predicting stroke occurrence.@*RESULTS@#Among the 821 survivors, the recurrence rate was 16.81% at 3 years and 19.98% at 5 years. Multivariate analysis of the training set by Cox regression model showed that an age over 65 years (HR= 2.596, P=0.024), an age of 45-64 years (HR=2.510, P=0.006), a mRS score beyond 3 (HR=2.284, P=0.004) and a history of coronary heart disease (HR=1.353, P=0.034) were all risk factors for stroke recurrence. The C-indexes of the nomogram for the 3-and 5-year relapse prediction model were 0.640 and 0.671, respectively.@*CONCLUSION@#Age, mRS score and peripheral vascular disease are the factors affecting stroke recurrence in first-episode ischemic stroke survivors, and the nomogram has a high discrimination and predictive power for predicting ischemic stroke recurrence.

Construction and verification of tumor microenvironment-related gene prognostic model for adrenocortical carcinoma / 肿瘤研究与临床

Objective:Bioinformatics method was used to screen out prognostic model constructed by the tumor microenvironment (TME)- related genes of adrenocortical carcinoma (ACC), and the prognostic model was verified to provide clinical guidances and related biomarkers for the diagnosis and treatment of ACC.Methods:Transcriptome and clinicopathological data of 79 ACC patients were collected from the Cancer Genome Atlas (TCGA) database. ESTIMATE algorithm was used to calculate immune score, stromal score (both reflect TME) and ESTIMATE score; VennDiagram was used to select differentially expressed genes among immune score, high and low stromal score groups (grouped by median value); Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genome (KEGG) database were used to perform functional enrichment analysis on selected genes and to explore the potential function and pathway of genes. Univariate Cox analysis, lasso regression analysis and multivariate Cox analysis were used to screen out genes related to ACC TME and to establish risk score (RS) model for ACC patients. The receiver operating characteristic (ROC) curve was used to evaluate the prognostic value of RS. The data sets GSE33371 and GSE19750 of Gene Expression Omnibus (GEO) were used as external validation sets to validate the prognostic model. The data of 79 ACC patients were extracted from the TCGA database, and the clinicopathological factors and the RS of the established prognostic model were included in the Cox regression analysis to obtain the prognostic factors of ACC patients.Results:According to the immune score and stromal score, 1 205 differentially expressed genes from intersection of both scores were screened out by using VennDiagram, including 833 up-regulated genes and 372 down-regulated genes. After continuing the regression analysis and screening of differentially expressed genes, the ACC prognostic model containing 9 TME-related genes (GREB1, POU4F1, HIC1, HOXC9, CACNB2, RAB27B, ZIC2, C3, CYP2D6) was finally constructed, that was, RS = GREB1×0.223 6+POU4F1×0.671 7+HIC1×0.167 5+HOXC9×0.211 3+CACNB2×0.156 0+RAB27B×0.956 5+ZIC2×0.582 7+C3×(-0.003 1)+CYP2D6×0.819 3. The area under the curve (AUC) of ROC for the 1, 3, and 5-year overall survival of 79 ACC patients predicted by the model in the TCGA database was 0.876, 0.919, 0.917, respectively. In the GEO validation set, the AUC of the 1, 3, and 5-year overall survival for 45 ACC patients predicted by the model was 0.689, 0.704, and 0.708, respectively, indicating that the model had a high prediction accuracy for survival results of ACC patients. Cox regression analysis on the data of 79 ACC patients in the TCGA database showed that the TME-related gene prognostic model RS was an independent factor influencing the prognosis of ACC patients ( HR = 1.011, 95% CI 1.005-1.016, P < 0.01). Conclusions:The established ACC TME-related gene prognostic model can be used to predict the prognosis of ACC patients. The model including 9 genes may become a new target for studying the pathogenesis and immunotherapy of ACC, and it is worthy of further research.

Screening and identification of potential long non-coding RNA for the prognosis evaluation of glioma patients based on bioinformatics analysis / 肿瘤研究与临床

Objective:To investigate the possibility of screened long non-coding RNA (lncRNA) as a prognostic marker in evaluating glioma.Methods:A total of 694 glioma samples and 5 tumor-adjacent tissues were selected in the Cancer Genome Atlas (TCGA) database from the establishment of the database to December 2018. The differential lncRNA, microRNA (miRNA) and mRNA between glioma tissues and 5 tumor-adjacent tissues were screened out, the correlation between the three and the prognosis of glioma patients was analyzed, and a competitive endogenous RNA (ceRNA) network was constructed. The biological functions of mRNA were enriched and analyzed based on Gene Ontology (GO) database and Kyoto encyclopedia of genes and genomes (KEGG) database. The survival analysis of patients with different expression levels of lncRNA, miRNA or mRNA were performed by using Kaplan-Meier method to obtain lncRNA, miRNA and mRNA related to prognosis. Univariate and multivariate Cox proportional hazards regression models were used to analyze the different lncRNAs in the ceRNA network, and an lncRNA prognosis model for predicting the 5-year overall survival rate of patients was constructed. According to the constructed model, the risk value of each sample in 694 samples in TCGA database was calculated. Taking the median risk value as the critical value, patients were divided into high-risk group (≥ median risk value) and low-risk group (< median risk value), and the survival curves of the two groups were drawn. The receiver operating characteristic (ROC) curve was drawn for predicting the 5-year overall survival rate of glioma patients in TCGA database according to the risk value of lncRNA prognosis model. The heat map of lncRNA gene expression levels in the prognostic model of patients in high-risk and low-risk groups was drawn with pheatmap R software package.Results:A total of differential 44 lncRNAs, 19 miRNAs and 54 mRNAs between glioma and tumor-adjacent tissues were obtained from TCGA database, and the ceRNA network map was drawn. Kaplan-Meier method showed that among them, 22 differential lncRNAs, 7 miRNAs and 38 mRNAs were related to the overall survival of patients. The univariate Cox regression analysis obtained 28 lncRNAs related to prognosis. After multivariate Cox regression analysis, Akaike information criterion (AIC) was used to seek the optimal prognostic risk model involving 16 lncRNAs, that was, risk value = ARHGAP31-AS1×(-0.357 7)+LY86-AS1×(0.155 1)+WARS2-IT1×(0.206 4)+PART1×(-0.110 0)+AC110491.1×(-0.142 6)+CACNA1C-IT2×(-0.381 3)+HAS2-AS1×(0.128 8)+AC092171.1×(-0.161 3)+CCDC26×(-0.144 2)+HCG15×(0.384 0)+AL359541.1×(-0.289 2)+GRM5-AS1×(0.120 5)+LINC00237×(-0.085 1)+LINC00310×(-0.213 0)+VCAN-AS1×(-0.090 3)+ LINC00303×(0.091 5). The median risk value was 0.758 calculated by the constructed model. The 5-year overall survival rate in the high-risk group was 16.8% (95% CI 11.4%-24.7%) and 75.7% (95% CI 68.5%-83.7%) in the low-risk group. The area under of ROC curve of 5-year overall survival predicted by lncRNA model was 0.893. Through the heat map, it can be found that the expression level of all lncRNAs in the model was different between high-risk and low-risk patients. Conclusions:The prognostic risk model constructed based on the screened lncRNAs can better evaluate the prognosis of glioma patients. These lncRNAs are expected to become new candidate biomarkers related to the prognosis of glioma.

Survival of HIV/AIDS patients treated under ART follow-up at the University hospital, northwest Ethiopia

INTRODUCTION@#The survival of HIV/AIDS patients on antiretroviral therapy (ART) is determined by a number of factors, including economic, demographic, behavioral, and institutional factors. Understanding the survival time and its trend is crucial to developing policies that will result in changes. The aim of this study was to compare the survival estimates of different subgroups and look into the predictors of HIV/AIDS patient survival.@*METHODS@#A retrospective cohort study of HIV/AIDS patients receiving ART at the University of Gondar teaching hospital was carried out. To compare the survival of various groups, a Kaplan-Meier survival analysis was performed. The Cox proportional hazards model was used to identify factors influencing HIV/AIDS patient survival rates.@*RESULTS@#In the current study, 5.91% of the 354 HIV/AIDS patients under ART follow-up were uncensored or died. Age (HR = 1.051) and lack of formal education (HR = 5.032) were associated with lower survival rate, whereas family size of one to two (HR = 0.167), three to four (HR = 0.120), no alcoholic consumption (HR = 0.294), no smoking and chat use (HR = 0.101), baseline weight (HR = 0.920), current weight (HR = 0.928), baseline CD4 cell count (HR = 0.990), baseline hemoglobin (HR = 0.800), and no TB diseases were associated with longer survival rate.@*CONCLUSIONS@#Fewer deaths were reported in a study area due to high patient adherence, compared to previous similar studies. Age, educational status, family size, alcohol consumption, tobacco and chat usage, baseline and current weight, baseline CD4 cell count, baseline hemoglobin, and tuberculosis (TB) diseases were all significant predictors of survival of HIV/AIDS patients.

Development and validation on death risk model of Stanford type A aortic dissection based on Cox regression / 中华危重病急救医学

Objective:To construct the prediction model of death risk of Stanford type A aortic dissection (AAD) based on Cox proportional risk regression model.Methods:AAD patients who were diagnosed and received surgical treatment admitted to the department of cardiothoracic surgery of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology from January 1st, 2019 to April 30th, 2020 were enrolled. The general situation, clinical manifestations, pre-hospital data, laboratory examination and imaging examination results of the patients were collected. The observation period was up to the death of the patients or ended on April 30th, 2021. They were divided into the model group and the verification group according to the ratio of 7∶3. Lasso method was used to screen prognostic variables from the data of the modeling group, and multivariate Cox regression analysis was included to construct the AAD death risk prediction model, which was displayed by nomogram. The receiver operator characteristic curve (ROC curve) was used to evaluate the discrimination of the model, the calibration curve to evaluate the accuracy of the model, and the clinical decision curve (DCA) to evaluate the effectiveness of the model.Results:A totel of 454 patients with AAD were finally included, and the mortality was 19.4% (88/454). Lasso regression analysis was used to screen out 10 variables from the data of 317 patients in the model group, and the prediction model of death risk was constructed: 0.511×abdominal pain+1.061×syncope+0.428×lower limb pain/numbness-0.365×emergency admission-1.933×direct admission-1.493×diagnosis before referral+0.662×preoperative systolic blood pressure (SBP) < 100 mmHg (1 mmHg = 0.133 kPa)+0.632×hypersensitivity cardiac troponin I (hs-cTnI) > 34.2 ng/L+1.402×De Bakey type+0.641× pulmonary infection+1.472×postoperative delirium. The area under the ROC curve (AUC) and 95% confidence interval (95% CI) of the AAD death risk prediction model were 0.873 (0.817-0.928), and that of the verification group was 0.828 (0.740-0.916). DCA showed that the net benefit value of the model was higher. The calibration curve showed that there was a good correlation between the actual observation results and the model prediction results. Conclusion:The AAD death risk prediction model based on abdominal pain, syncope, lower limb pain/numbness, mode of admission, diagnosis before referral, preoperative SBP < 100 mmHg, hs-cTnI > 34.2 ng/L, De Bakey type , pulmonary infection, and postoperative delirium can effectively help clinicians identify patients at high risk for AAD, evaluate their postoperative survival and timely adjust treatment strategies.

Expression and clinical significance of miR-191 in cervical cancer tissues / 中国肿瘤生物治疗杂志

@#[Abstract] Objective: To investigate the expression of miR-191 in cervical cancer tissues and its effect on the patients' prognosis. Methods: One hundred and seven cervical cancer tissue specimens from patients who underwent surgical treatment and 46 normal cervical tissue specimens from patients who underwent surgical resection of uterine fibroids (the control group) in Xinxiang Central Hospital were collected from December 2012 to December 2014. The expression of miR-191 in cancer tissues was detected by qPCR. All patients were followed up from the first day after surgery, and the follow-up deadline was December 31, 2019. All patients were followed up for 5 years, with death as the end event. The survival time and 5-year survival rate of the patients were recorded. Survival analysis was performed using Kaplan-Meier method and the factors affecting survival prognosis were analyzed using Cox proportional hazard regression model. Results: The expression level of miR-191 in cervical cancer tissues was significantly higher than that in the tissues from control group (P<0.01). There were significant differences in miR-191 expression among patients with different high-risk HPV infection status, different pathological grades and FIGO stages, and different lymph node metastasis status (all P<0.01). The 5-year survival rate of patients in the miR-191 low expression group was significantly higher than those patients in the high expression group (81.48% vs 33.75%, χ 2 =16.905, P<0.01). Pathological grade, FIGO stage, lymph node metastasis and the expression of miR-191 were risk factors affecting the prognosis of cervical cancer patients (HR=0.486, 3.065, 2.339 and 2.755, all P<0.05). Conclusion: miR-191 is highly expressed in cervical cancer tissues, and its expression level increases with the progression of malignancy. It is expected to become a potential biomarker for early diagnosis and prognosis evaluation of cervical cancer.

Application of conditional inference forest in time-to-event data analysis / 南方医科大学学报

OBJECTIVE@#To explore the application and advantages of conditional inference forest in survival analysis.@*METHODS@#We used simulated experiment and actual data to compare the predictive performance of 4 models, including Coxproportional hazards model, accelerated failure time model, random survival forest model and conditional inference forest model based on their Brier scores.@*RESULTS@#Simulation experiment suggested that both of the two forest models had more accurate and robust predictive performance than the other two regression models. Conditional inference forest model was superior to the other models in analyzing time-to-event data with polytomous covariates, collinearity or interaction, especially for a large sample size and a high censoring rate. The results of actual data analysis demonstrated that conditional inference forest model had the best predictive performance among the 4 models.@*CONCLUSIONS@#Compared with the commonly used survival analysis methods, conditional inference forest model performs better especially when the data contain polytomous covariates with collinearity and interaction.

Estrategia de autocuidado en los adultos mayores con cáncer colorrectal en la comunidad / Self-care strategy in elderly adults with colorrectal cancer in the community

RESUMEN Fundamento: la probabilidad de adquirir cáncer colorrectal en Cuba a lo largo de la vida es del cuatro al seis por ciento. Alrededor del 80 % de los casos son esporádicos, pero el 20 % tiene una influencia genética. Objetivo: evaluar la estrategia de autocuidado en los adultos mayores con cáncer colorrectal en la comunidad. Métodos: se realizó un estudio de intervención y desarrollo el cual muestra la estrategia de autocuidado en los adultos mayores con cáncer colorrectal en la comunidad contextualizada en el Policlínico Dr. Rudesindo Antonio García del Rijo del municipio y provincia Sancti Spíritus desde el 2007 hasta 2017. Variables utilizadas: nivel de información de los médicos de la familia, autocuidado, estado de salud, prolongación de la sobrevida, alivio del dolor. Se utilizó entrevista estructurada, a los adultos mayores con cáncer colorrectal para conocer la mejoría del estado de salud, después de aplicada la estrategia se compararon las proporciones poblacionales mediante prueba de McNemar. Resultados: se lograron cambios significativos en el nivel de información de los médicos de la familia, al finalizar el programa de capacitación se obtuvo 78,37 %, lo que muestra un nivel aceptable. El 36,62 % del estado de salud de los adultos mayores fue bueno; el autocuidado se alcanzó de forma aceptable en el 44,82 %. La prolongación de la sobrevida después de aplicada la estrategia fue de 49,13 %. El alivio del dolor fue de 76,72 %. Conclusiones: se logró la evaluación de la estrategia de autocuidados en los adultos mayores con cáncer colorrectal, que incluye acciones y actividades que favorecen el logro de cambios significativos en el autocuidado.

ABSTRACT Background: the probability of acquiring colorectal cancer in Cuba throughout life is four to six percent. Approximately 80 % of cases are sporadic, but 20% have a genetic influence. Objective: to evaluate the strategy of self-care in the elderly with colorectal cancer in the community. Method: intervention and development study was carried out, which shows the strategy of self-care in older adults with colorectal cancer in the community contextualized in the Dr. Rudesindo Antonio García del Rijo Polyclinic of the Municipality and Province of Sancti Spíritus in the period 2007-2017. The used variables were level of information of family doctors, self-care, health status, prolongation of survival, pain relief. Structured interview to older adults with colorectal cancer was used to know the improvement of the state of health, after applying the strategy, population proportions were compared by McNemar test. Results: significant changes were achieved in the level of information of family doctors at the end of the training program obtained 78.37 % which shows an acceptable level. 36.62 % of the health status of the elderly was good; self-care was achieved in an acceptable way in 44.82 %. The prolongation of the survival after applying the strategy was 49.13 %. The pain relief was 76.72 %. Conclusions: the evaluation of the self-care strategy in the elderly with colorectal cancer was achieved, which includes actions and activities that favor the achievement of significant changes in self-care.

Application of restricted mean survival time in clinical follow-up study / 中华流行病学杂志

In clinical follow-up studies,hazard ratio (HR) is routinely used to quantify the differences between-groups,however,it is being estimated by the Cox procedure.HR,the ratio of two hazard functions has abstract meaning only and is in lack of the context to give an intuitive explanation of the survival of patients and the assumption of proportional hazards (PH) must be satisfied.Under this context,the restricted mean survival time (RMST) can be used as a relatively effective measure or index of statistics.This paper introduces the RMST-based statistical analysis methods,including estimation of RMST and its difference,hypothesis testing and regression analysis.The application of RMST in data analysis is also introduced.All the evidence demonstrates that RMST can be used as an effective analytical tool with straightforward interpretation.RMST is also more effective than HR in comparing differences between groups,when non-PH is observed.Therefore,RMST is suggested to be stated along with HR in the process of disease efficacy evaluation and prognosis analysis.Cooperation and complement of the two,a precise reflection on the characteristics of data can be expected.

Application of restricted mean survival time in clinical follow-up study / 中华流行病学杂志

In clinical follow-up studies,hazard ratio (HR) is routinely used to quantify the differences between-groups,however,it is being estimated by the Cox procedure.HR,the ratio of two hazard functions has abstract meaning only and is in lack of the context to give an intuitive explanation of the survival of patients and the assumption of proportional hazards (PH) must be satisfied.Under this context,the restricted mean survival time (RMST) can be used as a relatively effective measure or index of statistics.This paper introduces the RMST-based statistical analysis methods,including estimation of RMST and its difference,hypothesis testing and regression analysis.The application of RMST in data analysis is also introduced.All the evidence demonstrates that RMST can be used as an effective analytical tool with straightforward interpretation.RMST is also more effective than HR in comparing differences between groups,when non-PH is observed.Therefore,RMST is suggested to be stated along with HR in the process of disease efficacy evaluation and prognosis analysis.Cooperation and complement of the two,a precise reflection on the characteristics of data can be expected.

Construction and evaluation of a predictive model for post-operative prognosis of hepatitis B virus-related hepatocelluar carcinoma / 肿瘤

Objective: To construct and evaluate a nomogram model for predicting the survival rate of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients after radical resection. Methods: The clinical parameters of 396 patients with HBV-related HCC who underwent radical resection were enrolled and sorted out as the training cohort of nomogram model. The data of 200 patients with HBV-related HCC after operation were used as the independent validation cohort to construct the a survival predicting nomogram model. Results: After univariate and multivariate COX regression analyses, the five independent risk factors significantly associated with the overall survival (OS) of patients with HBV-related HCC were identified (all P < 0.01). The five variables were portal vein tumor thrombosis, post-operative antiviral treatment, tumor differentiation, tumor capsule and pre-operative HBV DNA. A nomogram model was constructed based on these five variables. The calibration curves of 1-and 3-year OS showed good concordance between the prediction and actual observation. The concordance index (C-index) obtained from training cohort was 0.74 [95% confidence interval (CI): 0.70-0.77], while that obtained from validation cohort was 0.70 (95% CI: 0.65-0.76). Based on the nomogram scores, the patients in validation cohort were stratified into high-and low-risk groups. The survival rate of the patients in high-risk group was significantly lower than that in low-risk group (P = 9.79×10-6). Conclusion: The nomogram model constructed with 5 independent factors can predict the post-operative OS of HBV-related HCC patients.

Survival analysis: Part I — analysis of time-to-event / 대한마취과학회지

Length of time is a variable often encountered during data analysis. Survival analysis provides simple, intuitive results concerning time-to-event for events of interest, which are not confined to death. This review introduces methods of analyzing time-to-event. The Kaplan-Meier survival analysis, log-rank test, and Cox proportional hazards regression modeling method are described with examples of hypothetical data.

Interactions between Alcohol Consumption and Adjuvant Hormone Therapy in Relation to Breast Cancer-Free Survival / 한국유방암학회지

PURPOSE: Alcohol consumption is associated with an increase in breast cancer risk, but findings on the association of alcohol with survival after breast cancer diagnosis have been inconsistent. Further, whether these associations could differ by adjuvant hormone therapy status is unknown. We examined interactions between alcohol consumption and adjuvant hormone therapy in relation to breast cancer-free survival among women with a primary breast cancer diagnosis. METHODS: Participants in this study included 1,399 women diagnosed with primary breast cancer between 2007 and 2012 at the Moffitt Cancer Center. Alcohol consumption during the year preceding diagnosis was assessed in a patient survey. Information on tumor characteristics, breast cancer treatment and outcomes was available from the Moffitt Cancer Registry. Associations were examined using Cox proportional hazards models in stratified analyses by adjuvant hormone therapy status, after adjustment for potential confounders. RESULTS: Overall, alcohol consumption was associated with significantly improved breast cancer-free survival (any vs. none: hazard ratio [HR], 0.77; 95% confidence interval [CI], 0.65–0.92). Among women without adjuvant hormone therapy, alcohol consumption was associated with better survival in heavy drinkers (HR, 0.63; 95% CI, 0.43–0.93). Among women with adjuvant hormone therapy, survival was better in women consuming alcohol as compared to nondrinkers (moderate: HR, 0.69, 95% CI, 0.51–0.93; heavy: HR, 0.74, 95% CI, 0.57–0.96; any: HR, 0.71, 95% CI, 0.57–0.87). There was no significant interaction between alcohol and adjuvant hormone therapy (p-interaction=0.54 for alcohol modeled as none or any and p=0.34 for alcohol modeled as none, moderate, and heavy). CONCLUSION: Associations of alcohol consumption with breast cancer-free survival are similar in women with and without adjuvant hormone therapy. Future studies are warranted to elucidate potential mechanisms underlying the observed inverse associations.