ANALISIS KETAHANAN HIDUP PENDERITA DENGUE HEMORRHAGIC FEVER (DEMAM BERDARAH) DENGAN REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus : Rumah Sakit Islam Nahdlatul Ulama Demak)

Dengue hemorrhagic fever is an acute febrile disease caused by the dengue virus, which enters the human bloodstream through the bite of a mosquito of the genus Aedes Aegypti or Aedes Albopictus. Based on World Health Organization (WHO) records, it is estimated that 500,000 dengue hemorrhagic fever patients require hospital treatment every year and most of the sufferers are children. To analyze the relationship between recovery time in dengue fever patients and the factors that influence it using regression analysis, the dependent variable is the failure time and the function of the response variable tends to fail constant so to find out the relationship using Cox proportional hazard regression. Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is a method used to describe data analysis in terms of time from the time of origin defined until a certain event occurs. In this study, the recovery time of dengue fever patients as a function of failure is proportional. The observations used by the researchers for each patient were not the same. The population of this study were all patients with dengue fever. The data used was obtained from the medical record section for data on the length of hospitalization of patients regarding the recovery of patients with dengue fever. The conclusion of the research shows that the factors that affect the recovery time of dengue fever patients are hematocrit, platelets, immunoglobulin G, and immunoglobulin M.

Computational Identification of Immune- and Ferroptosis-Related LncRNA Signature for Prognosis of Hepatocellular Carcinoma

Long non-coding RNAs (lncRNAs), which were implicated in many pathophysiological processes including cancer, were frequently dysregulated in hepatocellular carcinoma (HCC). Studies have demonstrated that ferroptosis and immunity can regulate the biological behaviors of tumors. Therefore, biomarkers that combined ferroptosis, immunity, and lncRNA can be a promising candidate bioindicator in clinical therapy of cancers. Many bioinformatics methods, including Pearson correlation analysis, univariate Cox proportional hazard regression analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox proportional hazard regression analysis were applied to develop a prognostic risk signature of immune- and ferroptosis-related lncRNA (IFLSig). Finally, eight immune- and ferroptosis-related lncRNAs (IFLncRNA) were identified to develop and IFLSig of HCC patients. We found the prognosis of patients with high IFLSig will be worse, while the prognosis of patients with low IFLSig will be better. The results provide an efficient method of uniting critical clinical information with immunological characteristics, enabling estimation of the overall survival (OS). Such an integrative prognostic model with high predictive power would have a notable impact and utility in prognosis prediction and individualized treatment strategies.

Blood transfusion had no influence on the 5-year biochemical recurrence after robot-assisted radical prostatectomy: a retrospective study

Background Although red blood cells (RBC) transfusion is known to be significantly associated with biochemical recurrence in patients undergoing open prostatectomy, its influence on biochemical recurrence after robot-assisted laparoscopic radical prostatectomy remains unclear. Therefore, this study aimed to validate the effect of RBC transfusion on the 5-year biochemical recurrence in patients undergoing robot-assisted laparoscopic radical prostatectomy. Methods This study retrospectively analyzed the medical records of patients who underwent robot-assisted laparoscopic radical prostatectomy at single tertiary academic hospital between October 2007 and December 2014. Univariate and multivariate Cox proportional hazard regression analysis was performed to identify any potential variables associated with 5-year biochemical recurrence. Results A total of 1311 patients were included in the final analysis. Of these, 30 patients (2.3%) were transfused with RBC either during robot-assisted laparoscopic radical prostatectomy or during their hospital stay, which corresponded to 5-year biochemical recurrence of 15.7%. Multivariate Cox proportional hazard regression analysis showed that RBC transfusion had no influence on the 5-year biochemical recurrence. Variables including pathologic T stage (Hazard ratio [HR] 3.5, 95% confidence interval [CI] 2.4–5.1 p < 0.001), N stage (HR 2.3, 95% CI 1.5–3.7, p < 0.001), Gleason score (HR 2.4, 95% CI 1.8–3.2, p < 0.001), and surgical margin (HR 2.0, 95% CI 1.5–2.8, p < 0.001) were independently associated with the 5-year biochemical recurrence. Conclusions RBC transfusion had no significant influence on the 5-year biochemical recurrence in patients undergoing robot-assisted laparoscopic radical prostatectomy.

A novel ferroptosis-related lncRNA signature for prognosis prediction in gastric cancer

Background Gastric cancer (GC) is a common malignant cancer with a poor prognosis. Ferroptosis has been shown to play crucial roles in GC development. Long non-coding RNAs (lncRNAs) is also associated with tumor progression in GC. This study aimed to screen the prognostic ferroptosis-related lncRNAs and to construct a prognostic risk model for GC. Methods Ferroptosis-related lncRNAs from The Cancer Genome Atlas (TCGA) GC expression data was downloaded. First, single factor Cox proportional hazard regression analysis was used to select seven prognostic ferroptosis-related lncRNAs from TCGA database. And then, the selected lncRNAs were further included in the multivariate Cox proportional hazard regression analysis to establish the prognostic model. A nomogram was constructed to predict individual survival probability. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the risk model. Results We constructed a prognostic ferroptosis-related lncRNA signature in this study. Kaplan-Meier curve analysis revealed a significantly better prognosis for the low-risk group than for the high-risk group (P = 2.036e-05). Multivariate Cox proportional risk regression analysis demonstrated that risk score was an independent prognostic factor [hazard ratio (HR) = 1.798, 95% confidence interval (CI) =1.410–2.291, P < 0.001]. A nomogram, receiver operating characteristic curve, and principal component analysis were used to predict individual prognosis. Finally, the expression levels of AP003392.1, AC245041.2, AP001271.1, and BOLA3-AS1 in GC cell lines and normal cell lines were tested by qRT-PCR. Conclusions This risk model was shown to be a novel method for predicting prognosis for GC patients.

Association between Preoperative Monocyte-to-Lymphocyte Ratio and Late Arteriovenous Fistula Dysfunction in Hemodialysis Patients: A Cohort Study

<b><i>Background:</i></b> Inflammation appears to be at the biological core of arteriovenous fistula (AVF) dysfunction, and the occurrence of AVF dysfunction is related to high death and disability in hemodialysis (HD) patients. Despite several studies on the correlations between AVF dysfunction and inflammatory indicators, how AVF dysfunction is related to the monocyte-to-lymphocyte ratio (MLR) is much unclear. We hypothesize that preoperative MLR is associated with AVF dysfunction in Chinese HD patients. <b><i>Methods:</i></b> In this single-center retrospective cohort study, totally 769 adult HD patients with a new AVF created between 2011 and 2019 were included. Association of preoperative MLR with AVF dysfunction (thrombosis or decrease of normal vessel diameter by &#x3e;50%, requiring either surgical revision or percutaneous transluminal angioplasty) was assessed by multivariable Cox proportional hazard regression. <b><i>Results:</i></b> The patients were aged 55.8 ± 12.2 years and were mostly males (55%). During the average 32-month follow-up (maximum 119 months), 223 (29.0%) patients had permanent vascular access dysfunction. In adjusted multivariable Cox proportional hazard regression analyses, the risk of AVF dysfunction was 4.32 times higher with 1 unit increase in MLR (hazard ratio [HR]: 5.32; 95% confidence interval [CI]: 3.1–9.11). Compared with patients with MLR &#x3c;0.28, HRs associated with an MLR of 0.28–0.41 and ≥0.41 are 1.54 (95% CI: 1.02–2.32) and 3.17 (2.18–4.62), respectively. <b><i>Conclusions:</i></b> A higher preoperative MLR is independently connected with a severer risk of AVF dysfunction in HD patients. Its clinical value should be determined in the future.

Clinicopathological Characteristics and Survival Outcomes of Primary Renal Leiomyosarcoma

Background: Primary renal leiomyosarcoma (LMS) is an exceedingly rare entity with a poor prognosis. We summarized the clinicopathological characteristics, treatment choice, and survival outcomes of LMS from the Surveillance, Epidemiology, and End Results (SEER) database.Methods: Renal LMS and kidney renal clear cell carcinoma (KIRC) data from 1998 to 2016 were collected from the SEER database. The continuous variables were analyzed using t-tests, while the categorical variables were analyzed using Pearson's chi-squared or Fisher's exact tests. Propensity score matching (PSM) was also performed. The cancer-specific survival (CSS) and overall survival (OS) curves were estimated using Kaplan-Meier analyses and compared by log-rank tests. The risk factors for CSS and OS were estimated using univariable and multivariable Cox proportional hazard regression models.Results: A total of 140 patients with renal LMS and 75,401 patients with KIRC were enrolled. These groups differed significantly in sex, race, tumor size, grade, SEER stage, surgery, radiation, and chemotherapy. Renal LMS exhibited poorer CSS and OS compared with KIRC before and after PSM. For renal LMS, the univariate Cox proportional hazard regression model indicated that larger tumor size, higher tumor grade, higher SEER stage, and chemotherapy were risk factors for CSS and OS, while surgery appeared to be a protective factor. However, only tumor grade, SEER stage, and receiving surgery remained independent prognostic factors in the multivariable Cox proportional hazard regression model. In addition, subgroup analyses indicated that surgery remained a protective factor for advanced renal LMS. However, there was no survival benefit for patients receiving chemotherapy.Conclusions: Primary renal LMS is an exceedingly rare entity with distinct clinicopathological features and a poor prognosis. A higher tumor grade and late stage may indicate a poor prognosis. Complete tumor resection remains to be the first treatment choice, while chemotherapy may be a palliative treatment for patients with advanced disease.

The cumulative dose-dependent effects of metformin on the development of tuberculosis in patients newly diagnosed with type 2 diabetes mellitus

Background Diabetes mellitus (DM) is a well-known risk factor for tuberculosis (TB). Metformin, which is an essential anti-diabetic drug, has been shown to exhibit anti-TB effects in patients with DM. Its effect on preventing the development of TB among patients who are newly diagnosed with DM remains unclear. Methods This was a retrospective cohort study using the claims database of the Korean Health Insurance Review and Assessment Service. The study population included patients who were newly diagnosed with type 2 DM and who were treated with anti-diabetic drugs between 1 January 2003 and 31 March 2011. A patient was defined as a metformin user if he/she had taken metformin for more than 28 days within 6 months since cohort entry, and as a metformin non-user if he/she had never been treated with metformin. The development of TB within 2 years after the index date was compared by Cox proportional hazard regression models between metformin users and 1:1 propensity score (PS)-matched non-users. Results Among 76,973 patients who were newly diagnosed with type 2 DM, 13,396 were classified as metformin users, 52,736 were classified as metformin non-users, and 10,841 were excluded from the final analysis. PS-matched Cox proportional hazard regression models revealed that metformin use was not associated overall with the prevention of TB development (HR 1.17; 95% CI 0.75–1.83; P = 0.482). There was a trend, however, towards a reduction in the development of TB among patients taking a higher cumulative dose of metformin. Patients who were in the highest quartile (Q4) of cumulative metformin dose had only a 10% risk of developing TB compared to metformin non-users. In contrast, during the early phases of metformin treatment, patients in the second quartile (Q2) of cumulative metformin use had a higher risk of developing TB than patients in the first quartile (Q1). Conclusions Only the highest cumulative doses of metformin were protective against the development of TB among patients who were newly diagnosed with type 2 DM; lower cumulative doses of metformin did not appear to reduce the incidence of active TB infection.

Dealing with missing information on covariates for excess mortality hazard regression models – Making the imputation model compatible with the substantive model

Missing data is a common issue in epidemiological databases. Among the different ways of dealing with missing data, multiple imputation has become more available in common statistical software packages. However, the incompatibility between the imputation and substantive model, which can arise when the associations between variables in the substantive model are not taken into account in the imputation models or when the substantive model is itself nonlinear, can lead to invalid inference. Aiming at analysing population-based cancer survival data, we extended the multiple imputation substantive model compatible-fully conditional specification (SMC-FCS) approach, proposed by Bartlett et al. in 2015 to accommodate excess hazard regression models. The proposed approach was compared with the standard fully conditional specification multiple imputation procedure and with the complete-case analysis using a simulation study. The SMC-FCS approach produced unbiased estimates in both scenarios tested, while the fully conditional specification produced biased estimates and poor empirical coverages probabilities. The SMC-FCS algorithm was then used for handling missing data in the evaluation of socioeconomic inequalities in survival from colorectal cancer patients diagnosed in the North Region of Portugal. The analysis using SMC-FCS showed a clearer trend in higher excess hazards for patients coming from more deprived areas. The proposed algorithm was implemented in R software and is presented as Supplementary Material.