Surgical Aortic Valve Replacement with Concomitant Aortic Surgery in Patients with Purely Bicuspid Aortic Valve and Associated Aortopathy

The bicuspid aortic valve (BAV) is the most common congenital cardiac malformation associated with aortopathy. The current study provides surgical clinical data on the patient characteristics and long-term survival of this less common adult purely BAV population undergoing surgical aortic valve replacement (SAVR) with concomitant aortic surgery. Adult patients with purely BAV who underwent SAVR and concomitant aortic surgery were included. Prevalence, predictors of survival, and outcomes for this patient population were analyzed. A total of 48 patients (mean age 58.7 ± 13.2 years, 33% female) with purely BAV underwent SAVR and concomitant aortic surgery between 1987 and 2016. The majority (62%) of the patients had pure aortic stenosis (AS). A total of 12 patients died. Survival was 92%, 73%, and 69% at 1, 5, and 20 years of follow-up. At 15 years of follow-up, the survival was close to that of the Dutch population, with a relative survival of 77%. Adult patients with a purely bicuspid aortic valve morphology undergoing SAVR and concomitant aortic root and/or ascending aorta present with excellent survival

Hemodialysis vs peritoneal dialysis : comparison of net survival in incident patients on chronic dialysis in Colombia

Background: In the area of nephrology, the practical application of relative survival methodologies can provide information regarding the impact of outcomes for patients with kidney failure on dialysis compared with what would be expected in the absence of this condition. Objective: Compare the net survival of hemodialysis (HD) and peritoneal dialysis (PD) patients in a cohort of incident patients on chronic dialysis in Colombia, according to the dialysis therapy modality. Design: Observational, analytic, historical cohort. Setting: Renal Therapy Services (RTS) clinic network across Colombia. Patients: Patients over 18 years old with chronic kidney disease, incidents in dialytic therapy, which reached day 90 of therapy. Recruitment took place from January 1, 2008, to December 31, 2013, with a follow-up until December 31, 2018. The final cohort for analysis corresponds to a total of 12508 patients, of which 5330 patients (42.6%) began HD and 7178 patients (57.4%) began PD. Measurements: Demographic, socioeconomic, and clinical variables were measured. Methods: Analyses were conducted according to the treatment assigned (PD or HD) at the time of the inception of the cohort and another approach of analysis was done with a subsample of those patients who never changed the initial modality. To calculate expected survival, life tables were constructed for Colombia for the years 2006 to 2018. Net survival estimates were made using the Pohar Perme estimator. The comparison of the net survival curves was done using the method developed by Pavlič and Perme, the log-rank type. Results: Net survival at 5 years compared with the general population was estimated at 0.53 (95% confidence interval 0.52-0.54) in the dialysis cohort. In intention-to-treat analyses of 7178 patients on PD and 5330 patients on HD, by global and Pohar-Perme methods, survival (expressed as a ratio of survival in patients on dialysis to survival in an age-, sex- and geographic-matched general Colombian population) was higher in patients on HD than in those on PD. In year 1, net survival by Pavlov-Perme on PD was 0.79 (95% confidence intervals [CI] 0.78 - 0.80) and on HD 0.85 (95% CI 0.84 - 0.86); in year 5, 0.36 (95% CI 0.34 – 0.38) and 0.57 (95% CI 0.55 – 0.59) for PD and HD respectively. Limitation: There may be imbalances among the populations analyzed (HD vs PD), in which one or more variables other than the type of therapy may influence the survival of the patients. In Colombia there are marginal levels of underreporting of demographic data in some subpopulations that may affect life-tables construction. Conclusion: An important difference was observed in terms of survival between the dialysis population and the population of reference without dialysis. Statistically significant differences were found in net survival between HD and PD, net survival was higher in patients on HD than in those on PD.Q2Revista Internacional - Indexad

Clin Lymphoma Myeloma Leuk

BackgroundNovel targeted therapies offer excellent short-term outcomes in patients with chronic lymphocytic leukemia and small lymphocytic lymphoma (CLL/SLL). However, there is disagreement over how widely these therapies should be used in place of standard chemo-immunotherapy (CIT). We investigated whether stratification on the length of the interval between first-line (T1) and second-line (T2) treatments could identify a subgroup of older patients with relapsed CLL/SLL with an expectation of normal overall survival, and for whom CIT could be an acceptable treatment choice.Patients and MethodsPatients with relapsed CLL/SLL who received T2 were identified from the SEER-Medicare Linked Database. Five-year relative survival (RS5; ie, the ratio of observed survival to expected survival based on population life tables) was assessed after stratifying patients on the interval between T1 and T2. We then validated our findings in the Mayo Clinic CLL Database.ResultsAmong 1974 SEER-Medicare patients (median age = 77 years) who received T2 for relapsed CLL/SLL, longer time-to-retreatment was associated with a modestly improved prognosis (P = .01). However, even among those retreated 65 3 years after T1, survival was poor compared with the general population (RS5 = 0.50 or lower in SEER-Medicare). Similar patterns were observed in the younger Mayo validation cohort, although prognosis was better overall among the Mayo patients, and patients with favorable fluorescence in situ hybridization retreated 65 3 years after T1 had close to normal expected survival (RS5 = 0.87).ConclusionFurther research is needed to quantify the degree to which targeted therapies provide meaningful improvements over CIT in long-term outcomes for older patients with relapsed CLL/SLL.HHSN261201000140C/CA/NCI NIH HHS/United StatesHHSN261201000035C/CA/NCI NIH HHS/United StatesP30 CA086862/CA/NCI NIH HHS/United StatesHHSN261201000035I/CA/NCI NIH HHS/United StatesHHSN261201000034C/CA/NCI NIH HHS/United StatesU58 DP003862/DP/NCCDPHP CDC HHS/United StatesP50 CA097274/CA/NCI NIH HHS/United States2018-12-01T00:00:00Z28802891PMC5769450vault:2584

Nonparametric Relative Survival Analysis with the R Package relsurv

Relative survival methods are crucial with data in which the cause of death information is either not given or inaccurate, but cause-specific information is nevertheless required. This methodology is standard in cancer registry data analysis and can also be found in other areas. The idea of relative survival is to join the observed data with the general mortality population data and thus extract the information on the disease-specific hazard. While this idea is clear and easy to understand, the practical implementation of the estimators is rather complex since the population hazard for each individual depends on demographic variables and changes in time. A considerable advance in the methodology of this field has been observed in the past decade and while some methods represent only a modification of existing estimators, others require newly programmed functions. The package relsurv covers all the steps of the analysis, from importing the general population tables to estimating and plotting the results. The syntax mimics closely that of the classical survival packages like survival and cmprsk, thus enabling the users to directly use its functions without any further familiarization. In this paper we focus on the nonparametric relative survival analysis, and in particular, on the two key estimators for net survival and crude probability of death. Both estimators were first presented in our package and are still missing in many other software packages, a fact which greatly hampers their frequency of use. The paper offers guidelines for the actual use of the software by means of a detailed nonparametric analysis of the data describing the survival of patients with colon cancer. The data have been provided by the Cancer Registry of Slovenia

mexhaz: An R Package for Fitting Flexible Hazard-Based Regression Models for Overall and Excess Mortality with a Random Effect

We present mexhaz, an R package for fitting flexible hazard-based regression models with the possibility to add time-dependent effects of covariates and to account for a twolevel hierarchical structure in the data through the inclusion of a normally distributed random intercept (i.e., a log-normally distributed shared frailty). Moreover, mexhazbased models can be fitted within the excess hazard setting by allowing the specification of an expected hazard in the model. These models are of common use in the context of the analysis of population-based cancer registry data. Follow-up time can be entered in the right-censored or counting process input style, the latter allowing models with delayed entries. The logarithm of the baseline hazard can be flexibly modeled with B-splines or restricted cubic splines of time. Parameters estimation is based on likelihood maximization: in deriving the contribution of each observation to the cluster-specific conditional likelihood, Gauss-Legendre quadrature is used to calculate the cumulative hazard; the cluster-specific marginal likelihoods are then obtained by integrating over the random effects distribution, using adaptive Gauss-Hermite quadrature. Functions to compute and plot the predicted (excess) hazard and (net) survival (possibly with cluster-specific predictions in the case of random effect models) are provided. We illustrate the use of the different options of the mexhaz package and compare the results obtained with those of other available R packages

Temporal trends in relative survival following percutaneous coronary intervention

OBJECTIVE: Percutaneous coronary intervention (PCI) has seen substantial shifts in patient selection in recent years that have increased baseline patient mortality risk. It is unclear to what extent observed changes in mortality are attributable to background mortality risk or the indication and selection for PCI itself. PCI-attributable mortality can be estimated using relative survival, which adjusts observed mortality by that seen in a matched control population. We report relative survival ratios and compare these across different time periods. METHODS: National Health Service PCI activity in England and Wales from 2007 to 2014 is considered using data from the British Cardiovascular Intervention Society PCI Registry. Background mortality is as reported in Office for National Statistics life tables. Relative survival ratios up to 1?year are estimated, matching on patient age, sex and procedure date. Estimates are stratified by indication for PCI, sex and procedure date. RESULTS: 549?305 procedures were studied after exclusions for missing age, sex, indication and mortality status. Comparing from 2007 to 2008 to 2013-2014, differences in crude survival at 1?year were consistently lower in later years across all strata. For relative survival, these differences remained but were smaller, suggesting poorer survival in later years is partly due to demographic characteristics. Relative survival was higher in older patients. CONCLUSIONS: Changes in patient demographics account for some but not all of the crude survival changes seen during the study period. Relative survival is an under-used methodology in interventional settings like PCI and should be considered wherever survival is compared between populations with different demographic characteristics, such as between countries or time periods