Survival Data (survival + data)

Distribution by Scientific Domains
Distribution within Medical Sciences

Kinds of Survival Data

  • long-term survival data

  • Selected Abstracts

    Improved Logrank-Type Tests for Survival Data Using Adaptive Weights

    BIOMETRICS, Issue 1 2010
    Song Yang
    Summary For testing for treatment effects with time-to-event data, the logrank test is the most popular choice and has some optimality properties under proportional hazards alternatives. It may also be combined with other tests when a range of nonproportional alternatives are entertained. We introduce some versatile tests that use adaptively weighted logrank statistics. The adaptive weights utilize the hazard ratio obtained by fitting the model of Yang and Prentice (2005,,Biometrika,92, 1,17). Extensive numerical studies have been performed under proportional and nonproportional alternatives, with a wide range of hazard ratios patterns. These studies show that these new tests typically improve the tests they are designed to modify. In particular, the adaptively weighted logrank test maintains optimality at the proportional alternatives, while improving the power over a wide range of nonproportional alternatives. The new tests are illustrated in several real data examples. [source]

    A Semiparametric Joint Model for Longitudinal and Survival Data with Application to Hemodialysis Study

    BIOMETRICS, Issue 3 2009
    Liang Li
    Summary In many longitudinal clinical studies, the level and progression rate of repeatedly measured biomarkers on each subject quantify the severity of the disease and that subject's susceptibility to progression of the disease. It is of scientific and clinical interest to relate such quantities to a later time-to-event clinical endpoint such as patient survival. This is usually done with a shared parameter model. In such models, the longitudinal biomarker data and the survival outcome of each subject are assumed to be conditionally independent given subject-level severity or susceptibility (also called frailty in statistical terms). In this article, we study the case where the conditional distribution of longitudinal data is modeled by a linear mixed-effect model, and the conditional distribution of the survival data is given by a Cox proportional hazard model. We allow unknown regression coefficients and time-dependent covariates in both models. The proposed estimators are maximizers of an exact correction to the joint log likelihood with the frailties eliminated as nuisance parameters, an idea that originated from correction of covariate measurement error in measurement error models. The corrected joint log likelihood is shown to be asymptotically concave and leads to consistent and asymptotically normal estimators. Unlike most published methods for joint modeling, the proposed estimation procedure does not rely on distributional assumptions of the frailties. The proposed method was studied in simulations and applied to a data set from the Hemodialysis Study. [source]

    Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data

    BIOMETRICS, Issue 2 2008
    Jimin Ding
    Summary In clinical studies, longitudinal biomarkers are often used to monitor disease progression and failure time. Joint modeling of longitudinal and survival data has certain advantages and has emerged as an effective way to mutually enhance information. Typically, a parametric longitudinal model is assumed to facilitate the likelihood approach. However, the choice of a proper parametric model turns out to be more elusive than models for standard longitudinal studies in which no survival endpoint occurs. In this article, we propose a nonparametric multiplicative random effects model for the longitudinal process, which has many applications and leads to a flexible yet parsimonious nonparametric random effects model. A proportional hazards model is then used to link the biomarkers and event time. We use B-splines to represent the nonparametric longitudinal process, and select the number of knots and degrees based on a version of the Akaike information criterion (AIC). Unknown model parameters are estimated through maximizing the observed joint likelihood, which is iteratively maximized by the Monte Carlo Expectation Maximization (MCEM) algorithm. Due to the simplicity of the model structure, the proposed approach has good numerical stability and compares well with the competing parametric longitudinal approaches. The new approach is illustrated with primary biliary cirrhosis (PBC) data, aiming to capture nonlinear patterns of serum bilirubin time courses and their relationship with survival time of PBC patients. [source]

    Quantifying the Predictive Performance of Prognostic Models for Censored Survival Data with Time-Dependent Covariates

    BIOMETRICS, Issue 2 2008
    R. Schoop
    Summary Prognostic models in survival analysis typically aim to describe the association between patient covariates and future outcomes. More recently, efforts have been made to include covariate information that is updated over time. However, there exists as yet no standard approach to assess the predictive accuracy of such updated predictions. In this article, proposals from the literature are discussed and a conditional loss function approach is suggested, illustrated by a publicly available data set. [source]

    A Spatial Scan Statistic for Survival Data

    BIOMETRICS, Issue 1 2007
    Lan Huang
    Summary Spatial scan statistics with Bernoulli and Poisson models are commonly used for geographical disease surveillance and cluster detection. These models, suitable for count data, were not designed for data with continuous outcomes. We propose a spatial scan statistic based on an exponential model to handle either uncensored or censored continuous survival data. The power and sensitivity of the developed model are investigated through intensive simulations. The method performs well for different survival distribution functions including the exponential, gamma, and log-normal distributions. We also present a method to adjust the analysis for covariates. The cluster detection method is illustrated using survival data for men diagnosed with prostate cancer in Connecticut from 1984 to 1995. [source]

    Joint Models for Multivariate Longitudinal and Multivariate Survival Data

    BIOMETRICS, Issue 2 2006
    Yueh-Yun Chi
    Summary Joint modeling of longitudinal and survival data is becoming increasingly essential in most cancer and AIDS clinical trials. We propose a likelihood approach to extend both longitudinal and survival components to be multidimensional. A multivariate mixed effects model is presented to explicitly capture two different sources of dependence among longitudinal measures over time as well as dependence between different variables. For the survival component of the joint model, we introduce a shared frailty, which is assumed to have a positive stable distribution, to induce correlation between failure times. The proposed marginal univariate survival model, which accommodates both zero and nonzero cure fractions for the time to event, is then applied to each marginal survival function. The proposed multivariate survival model has a proportional hazards structure for the population hazard, conditionally as well as marginally, when the baseline covariates are specified through a specific mechanism. In addition, the model is capable of dealing with survival functions with different cure rate structures. The methodology is specifically applied to the International Breast Cancer Study Group (IBCSG) trial to investigate the relationship between quality of life, disease-free survival, and overall survival. [source]

    A Bayesian Semiparametric Joint Hierarchical Model for Longitudinal and Survival Data

    BIOMETRICS, Issue 2 2003
    Elizabeth R. Brown
    Summary This article proposes a new semiparametric Bayesian hierarchical model for the joint modeling of longitudinal and survival data. We relax the distributional assumptions for the longitudinal model using Dirichlet process priors on the parameters defining the longitudinal model. The resulting posterior distribution of the longitudinal parameters is free of parametric constraints, resulting in more robust estimates. This type of approach is becoming increasingly essential in many applications, such as HIV and cancer vaccine trials, where patients' responses are highly diverse and may not be easily modeled with known distributions. An example will be presented from a clinical trial of a cancer vaccine where the survival outcome is time to recurrence of a tumor. Immunologic measures believed to be predictive of tumor recurrence were taken repeatedly during follow-up. We will present an analysis of this data using our new semiparametric Bayesian hierarchical joint modeling methodology to determine the association of these longitudinal immunologic measures with time to tumor recurrence. [source]

    Analysis of Survival Data from Case,Control Family Studies

    BIOMETRICS, Issue 3 2002
    Joanna H. Shih
    Summary. In case,control family studies with survival endpoint, age of onset of diseases can be used to assess the familial aggregation of the disease and the relationship between the disease and genetic or environmental risk factors. Because of the retrospective nature of the case-control study, methods for analyzing prospectively collected correlated failure time data do not apply directly. In this article, we propose a semiparametric quasi-partial-likelihood approach to simultaneously estimate the effect of covariates on the age of onset and the association of ages of onset among family members that does not require specification of the baseline marginal distribution. We conducted a simulation study to evaluate the performance of the proposed approach and compare it with the existing semiparametric ones. Simulation results demonstrate that the proposed approach has better performance in terms of consistency and efficiency. We illustrate the methodology using a subset of data from the Washington Ashkenazi Study. [source]

    Nonparametric Rank-Based Methods for Group Sequential Monitoring of Paired Censored Survival Data

    BIOMETRICS, Issue 4 2000
    Susan Murray
    Summary. This research gives methods for nonparametric sequential monitoring of paired censored survival data in the two-sample problem using paired weighted log-rank statistics with adjustments for dependence in survival and censoring outcomes. The joint asymptotic closed-form distribution of these sequentially monitored statistics has a dependent increments structure. Simulations validating operating characteristics of the proposed methods highlight power and size consequences of ignoring even mildly correlated data. A motivating example is presented via the Early Treatment Diabetic Retinopathy Study. [source]

    Tests of Proportional Hazards and Proportional Odds Models for Grouped Survival Data

    BIOMETRICS, Issue 4 2000
    Enrico A. Colosimo
    Summary. In this paper, we derive score test statistics to discriminate between proportional hazards and proportional odds models for grouped survival data. These models are embedded within a power family transformation in order to obtain the score tests. In simple cases, some small-sample results are obtained for the score statistics using Monte Carlo simulations. Score statistics have distributions well approximated by the chi-squared distribution. Real examples illustrate the proposed tests. [source]

    Time-Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker

    BIOMETRICS, Issue 2 2000
    Patrick J. Heagerty
    Summary. ROC curves are a popular method for displaying sensitivity and specificity of a continuous marker, X, for a binary disease variable, D. However, many disease outcomes are time dependent, D(t, and ROC curves that vary as a function of time may be mire appropriate. A common examples of a time-dependent variable is vital status, where D(t) = 1 if a patient has died prior to time t and zero otherwise. We propose summarizing the discrimination potential of a marker X, measured at baseline (t= 0), by calculating ROC Curves for cumulative disease or death incidence by time t, which we denote as ROC(t). A typical complexity with survival data is that observations may be censored. Two ROC curve estimators are proposed that can accommodate censored data. A simple estimator is based on using the Kaplan-Meier estimated for each possible subset X > c. However, this estimator does not guarantee the necessary condition that sensitivity and specificity are monotone in X. An alternative estimator that does guarantee monotonicity is based on a nearest neighbor estimator for the bivariate distribution function of (X, T), where T represents survival time (Akritas, M. J., 1994, Annals of Statistics22, 1299,1327). We present an example where ROC(t) is used to compare a standard and a modified flow cytometry measurement for predicting survival after detection of breast cancer and an example where the ROC(t) curve displays the impact of modifying eligibility criteria for sample size and power in HIV prevention trials. [source]

    Immediate and 5-year cumulative outcome after paediatric intensive care in Sweden

    Background: Little has been reported about intensive care of children in Sweden. The aims of this study are to (I) assess the number of admissions, types of diagnoses and length-of-stay (LOS) for all Swedish children admitted to intensive care during the years 1998,2001, and compare paediatric intensive care units (PICUs) with other intensive care units (adult ICUs) (II) assess immediate (ICU) and cumulative 5-year mortality and (III) determine the actual consumption of paediatric intensive care for the defined age group in Sweden. Methods: Children between 6 months and 16 years of age admitted to intensive care in Sweden were included in a national multicentre, ambidirectional cohort study. In PICUs, data were also collected for infants aged 1,6 months. Survival data were retrieved from the National Files of Registration, 5 years after admission. Results: Eight-thousand sixty-three admissions for a total of 6661 patients were identified, corresponding to an admission rate of 1.59/1000 children per year. Median LOS was 1 day. ICU mortality was 2.1% and cumulative 5-year mortality rate was 5.6%. Forty-four per cent of all admissions were to a PICU. Conclusions: This study has shown that Sweden has a low immediate ICU mortality, similar in adult ICU and PICU. Patients discharged alive from an ICU had a 20-fold increased mortality risk, compared with a control cohort for the 5-year period. Less than half of the paediatric patients admitted for intensive care in Sweden were cared for in a PICU. Studies are needed to evaluate whether a centralization of paediatric intensive care in Sweden would be beneficial to the paediatric population. [source]

    Outcome following surgery for squamous cell carcinoma of the oesophagus

    ANZ JOURNAL OF SURGERY, Issue 10 2009
    En Loon C. Yong
    Abstract Introduction:, This study was undertaken to determine the outcomes of patients treated for squamous cell carcinoma (SCC) of the oesophagus. Methods:, The study group consisted of 61 patients (median age: 64 years) with invasive SCC of the oesophagus who underwent resection between 1987 and 2007 in Adelaide, South Australia. Thirty-two (52%) were female. Survival data were available for all patients. The log rank test was performed to identify prognostic factors for survival. Results:, The 5-year overall survival rate was 33% (median: 24 months). Of 61 patients, 42 (69%) received neoadjuvant therapy prior to surgery. The overall resection rate was 95%. Significant post-operative morbidity occurred in 47%, and the in-hospital mortality was 5% (30-day mortality: 3%). No overall survival benefit was seen in patients undergoing neoadjuvant therapy prior to surgical resection. However, patients who had a complete pathological response to neoadjuvant therapy had a better 5-year survival than patients who did not receive neoadjuvant therapy: 47% versus 30%, respectively. Conclusions:, Oesophagectomy following neoadjuvant therapy for SCC of the oesophagus can be performed with low perioperative mortality. A complete response to neoadjuvant therapy was followed by an improved survival outcome. [source]

    Efficacy of repeat hepatic resection for recurrent hepatocellular carcinomas

    ANZ JOURNAL OF SURGERY, Issue 10 2009
    Yasuhiko Nagano
    Abstract Background:, This study evaluated the efficacy of repeat hepatic resection for recurrent hepatocellular carcinoma (HCC) and the clinicopathological factors influencing overall survival after resection. Methods:, From 1992 to 2005, 231 patients underwent curative hepatic resection for HCC at Yokohama City University, Japan. Of these, 105 patients developed intrahepatic recurrence, and 24 repeat hepatectomies were performed for recurrent HCC. Survival data were analysed, and prognostic factors for repeat hepatic resection were determined. Results:, The overall cumulative 1-, 3- and 5-year survival rates and the median survival time of the patients after initial hepatic resection (n= 231) did not differ from those of the patients after repeat hepatic resection (n= 24), with values of 91.3, 70.2 and 49.1%, and 57 months, versus 91.7, 73.1 and 50.9%, and 61.5 months, respectively (P= 0.875). The operative time and blood loss in patients who underwent repeat hepatic resection did not differ from those who underwent primary resection. Multivariate analysis identified portal invasion at the first hepatic resection and a disease-free interval of ,1.5 years after primary hepatic resection as independent risk factors for survival after repeat hepatic resection. The 12 patients who did not show either of the two prognostic factors had 3- and 5-year survival rates of 91.7 and 68.8%, respectively, after repeat hepatic resection. Conclusions:, Our findings suggest repeat hepatic resection as the treatment of choice for recurrent HCC patients without portal invasion at the first resection whose recurrence develops after a disease-free interval of >1.5 years since the previous surgery. [source]


    S. K. Thompson
    Purpose Controversy exists over the 2nd edition of the TNM staging system introduced by the American Joint Committee in Cancer in 1988, and revised in 2002. Prognostic pathological factors such as the number of positive lymph nodes and any extracapsular lymph node invasion may refine this current staging system and optimize patient treatment. Methodology All patients who underwent surgical resection for oesophageal cancer were identified in a prospectively-maintained database. Patients without invasive adenocarcinoma or squamous cell cancer were excluded. Pathology slides were reviewed by a single pathologist. Survival data was calculated using Kaplan-Meier curves, and prognostic factors were examined using the log rank test. Results 235 surgical specimens met inclusion criteria, and 95 specimens have been reviewed so far. The 5-yr overall survival rate was 43% (median 31.4 months). Subdividing pN-stage into 1,2 positive nodes and >2 positive nodes showed significant differences in 5-yr survival between both groups: 41% vs. 6.0%, respectively (P = 0.0003). Similarly, including absence and presence of extracapsular lymph node invasion into our pathology review showed significant differences in 5-yr survival: 40% vs. 7.8%, respectively (P < 0.01). A negative circumferential margin, and the absence of both vascular and perineural invasion were also found to significantly improve survival rates. Conclusions The number and characteristics of metastatic invasion of lymph nodes should be included in current oesophageal cancer staging systems. Clinicians will then have more accurate prognostic information, and treatment can be better tailored to patients' needs. [source]


    ANZ JOURNAL OF SURGERY, Issue 1-2 2007
    Mark Omundsen
    Background: Carcinoma of the oesophagus is a rare but a highly lethal malignancy. The incidence of adenocarcinoma in particular is increasing in the Western world. Despite improvements in staging, perioperative care and the use of adjuvant/neoadjuvant regimen the prognosis remains poor. Methods: All patients who had biopsy-proven oesophageal carcinoma between the years 1992 and 2004 in the Wellington region, New Zealand, were retrospectively reviewed. The personal and tumour characteristics, operation details, complications and the details of hospital stay of patients who had had a resection were recorded in a database . Survival data were recovered from the notes, hospital database or general practitioner records and were available for all patients who had surgery. Survival analyses were calculated using Kaplan,Meier estimates. Results: One hundred and ninety-one patients were diagnosed with oesophageal carcinoma during the study period (59% adenocarcinoma, 32% squamous cell carcinoma). Only 35% (n = 67) had a resection (81% adenocarcinoma, 13% squamous cell carcinoma). Fifty-one (77%) had an Ivor Lewis procedure, 9 (14%) had only a laparotomy and 6 (9%) had a laparotomy, right thoracotomy and cervical incision. Forty-six (70%) tumours were in the distal third of the oesophagus and 13 (20%) were at the oesophagogastric junction. Perioperative mortality was 10% (n = 7) and anastomotic leak rate 9% (n = 6). Five-year survival was 23%. Conclusion: Results from our institution for the resection of oesophageal cancer compare favourably with those in the published work. Staging with computed tomography and laparoscopy has resulted in acceptable resection and survival rates. Survival for this disease is still largely stage dependent and earlier diagnosis probably holds the key to improved prognosis. [source]

    Maintenance therapy and 3-year outcome of opioid-dependent prisoners: a prospective study in France (2003,06)

    ADDICTION, Issue 7 2009
    Jean-NoŽl Marzo
    ABSTRACT Aims To describe the profile of imprisoned opioid-dependent patients, prescriptions of maintenance therapy at imprisonment and 3-year outcome in terms of re-incarceration and mortality. Design Prospective, observational study (France, 2003,06). Setting Health units of 47 remand prisons. Participants A total of 507 opioid-dependent patients included within the first week of imprisonment between June 2003 and September 2004, inclusive. Measurements Physicians collected socio-demographic data, penal history, history of addiction, maintenance therapy and psychoactive agent use, general health status and comorbidities. Prescriptions at imprisonment were recorded by the prison pharmacist. Re-incarceration data were retrieved from the National Register of Inmates, survival data and causes of death from the National Registers of vital status and death causes. Findings Prison maintenance therapy was delivered at imprisonment to 394/507 (77.7%) patients. These patients had poorer health status, heavier opioid use and prison history and were less socially integrated than the remaining 113 patients. Over 3 years, 238/478 patients were re-incarcerated [51.3 re-incarcerations per 100 patient-years, 95% confidence interval (CI) 46.4,56.2]. Factors associated independently with re-incarceration were prior imprisonment and benzodiazepine use. After adjustment for confounders, maintenance therapy was not associated with a reduced rate of re-incarceration (adjusted relative risk 1.28, 95% CI 0.89,1.85). The all-cause mortality rate was eight per 1000 patient-years (n = 10, 95% CI 4,13). Conclusions Prescription of maintenance therapy has increased sharply in French prisons since its introduction in the mid-1990s. However, the risk of re-imprisonment or death remains high among opioid-dependent prisoners. Substantial efforts are needed to implement more effective preventive policies. [source]

    The importance of independent risk-factors for long-term mortality prediction after cardiac surgery

    I. K. Toumpoulis
    Abstract Background, The purpose of the present study was to determine independent predictors for long-term mortality after cardiac surgery. The European System for Cardiac Operative Risk Evaluation (EuroSCORE) was developed to score in-hospital mortality and recent studies have shown its ability to predict long-term mortality as well. We compared forecasts based on EuroSCORE with other models based on independent predictors. Methods, Medical records of patients with cardiac surgery who were discharged alive (n = 4852) were retrospectively reviewed. Their operative surgical risks were calculated according to EuroSCORE. Patients were randomly divided into two groups: training dataset (n = 3233) and validation dataset (n = 1619). Long-term survival data (mean follow-up 5∑1 years) were obtained from the National Death Index. We compared four models: standard EuroSCORE (M1); logistic EuroSCORE (M2); M2 and other preoperative, intra-operative and post-operative selected variables (M3); and selected variables only (M4). M3 and M4 were determined with multivariable Cox regression analysis using the training dataset. Results, The estimated five-year survival rates of the quartiles in compared models in the validation dataset were: 94∑5%, 87∑8%, 77∑1%, 64∑9% for M1; 95∑1%, 88∑0%, 80∑5%, 64∑4% for M2; 93∑4%, 89∑4%, 80∑8%, 64∑1% for M3; and 95∑8%, 90∑9%, 81∑0%, 59∑9% for M4. In the four models, the odds of death in the highest-risk quartile was 8∑4-, 8∑5-, 9∑4- and 15∑6-fold higher, respectively, than the odds of death in the lowest-risk quartile (P < 0∑0001 for all). Conclusions, EuroSCORE is a good predictor of long-term mortality after cardiac surgery. We developed and validated a model using selected preoperative, intra-operative and post-operative variables that has better discriminatory ability. [source]

    Ecological processes influencing mortality of juvenile pink salmon (Oncorhynchus gorbuscha) in Prince William Sound, Alaska

    T. M. Willette
    Abstract Our collaborative work focused on understanding the system of mechanisms influencing the mortality of juvenile pink salmon (Oncorhynchus gorbuscha) in Prince William Sound, Alaska. Coordinated field studies, data analysis and numerical modelling projects were used to identify and explain the mechanisms and their roles in juvenile mortality. In particular, project studies addressed the identification of major fish and bird predators consuming juvenile salmon and the evaluation of three hypotheses linking these losses to (i) alternative prey for predators (prey-switching hypothesis); (ii) salmon foraging behaviour (refuge-dispersion hypothesis); and (iii) salmon size and growth (size-refuge hypothesis). Two facultative planktivorous fishes, Pacific herring (Clupea pallasi) and walleye pollock (Theragra chalcogramma), probably consumed the most juvenile pink salmon each year, although other gadids were also important. Our prey-switching hypothesis was supported by data indicating that herring and pollock switched to alternative nekton prey, including juvenile salmon, when the biomass of large copepods declined below about 0.2 g m,3. Model simulations were consistent with these findings, but simulations suggested that a June pteropod bloom also sheltered juvenile salmon from predation. Our refuge-dispersion hypothesis was supported by data indicating a five-fold increase in predation losses of juvenile salmon when salmon dispersed from nearshore habitats as the biomass of large copepods declined. Our size-refuge hypothesis was supported by data indicating that size- and growth-dependent vulnerabilities of salmon to predators were a function of predator and prey sizes and the timing of predation events. Our model simulations offered support for the efficacy of representing ecological processes affecting juvenile fishes as systems of coupled evolution equations representing both spatial distribution and physiological status. Simulations wherein model dimensionality was limited through construction of composite trophic groups reproduced the dominant patterns in salmon survival data. In our study, these composite trophic groups were six key zooplankton taxonomic groups, two categories of adult pelagic fishes, and from six to 12 groups for tagged hatchery-reared juvenile salmon. Model simulations also suggested the importance of salmon density and predator size as important factors modifying the predation process. [source]

    Tests for genetic association using family data

    Mei-Chiung Shih
    Abstract We use likelihood-based score statistics to test for association between a disease and a diallelic polymorphism, based on data from arbitrary types of nuclear families. The Nonfounder statistic extends the transmission disequilibrium test (TDT) to accommodate affected and unaffected offspring, missing parental genotypes, phenotypes more general than qualitative traits, such as censored survival data and quantitative traits, and residual correlation of phenotypes within families. The Founder statistic compares observed or inferred parental genotypes to those expected in the general population. Here the genotypes of affected parents and those with many affected offspring are weighted more heavily than unaffected parents and those with few affected offspring. We illustrate the tests by applying them to data on a polymorphism of the SRD5A2 gene in nuclear families with multiple cases of prostate cancer. We also use simulations to compare the power of these family-based statistics to that of the score statistic based on Cox's partial likelihood for censored survival data, and find that the family-based statistics have considerably more power when there are many untyped parents. The software program FGAP for computing test statistics is available at Genet. Epidemiol. 22:128,145, 2002. © 2002 Wiley-Liss, Inc. [source]

    Lagged effects of North Atlantic Oscillation on spittlebug Philaenus spumarius (Homoptera) abundance and survival

    GLOBAL CHANGE BIOLOGY, Issue 12 2006
    Abstract The North Atlantic Oscillation (NAO) is a large-scale pattern of climate variability that has been shown to have important ecological effects on a wide spectrum of taxa. Studies on terrestrial invertebrates are, however, lacking. We studied climate-connected causes of changes in population sizes in island populations of the spittlebug Philaenus spumarius (L.) (Homoptera). Three populations living in meadows on small Baltic Sea islands were investigated during the years 1970,2005 in Tvšrminne archipelago, southern Finland. A separate analysis was done on the effects of NAO and local climate variables on spittlebug survival in 1969,1978, for which survival data existed for two islands. We studied survival at two stages of the life cycle: growth rate from females to next year's instars (probably mostly related to overwintering egg survival), and survival from third instar stage to adult. The latter is connected to mortality caused by desiccation of plants and spittle masses. Higher winter NAO values were consistently associated with smaller population sizes on all three islands. Local climate variables entering the most parsimonious autoregressive models of population abundance were April and May mean temperature, May precipitation, an index of May humidity, and mean temperature of the coldest month of the previous winter. High winter NAO values had a clear negative effect on late instar survival in 1969,1978. Even May,June humidity and mean temperature of the coldest month were associated with late instar survival. The climate variables studied (including NAO) had no effect on the growth rate from females to next year's instars. NAO probably affected the populations primarily in late spring. Cold and snowy winters contribute to later snow melt and greater spring humidity in the meadows. We show that winter NAO has a considerable lagged effect on April and May temperature; even this second lagged effect contributes to differences in humidity. The lagged effect of the winter NAO to spring temperatures covers a large area in northern Europe and has been relatively stationary for 100 years at least in the Baltic area. [source]

    Out-of-hospital Cardiac Arrest in Denver, Colorado: Epidemiology and Outcomes

    Jason S. Haukoos MD
    Abstract Objectives:, The annual incidence of out-of-hospital cardiac arrest (OOHCA) in the United States is approximately 6 per 10,000 population and survival remains low. Relatively little is known about the performance characteristics of a two-tiered emergency medical services (EMS) system split between fire-based basic life support (BLS) dispersed from fixed locations and hospital-based advanced life support (ALS) dispersed from nonfixed locations. The objectives of this study were to describe the incidence of OOHCA in Denver, Colorado, and to define the prevalence of survival with good neurologic function in the context of this particular EMS system. Methods:, This was a retrospective cohort study using standardized abstraction methodology. A two-tiered hospital-based EMS system for the County of Denver and 10 receiving hospitals were studied. Consecutive adult patients who experienced nontraumatic OOHCA from January 1, 2003, through December 31, 2004, were enrolled. Demographic, prehospital arrest characteristics, treatment data, and survival data using the Utstein template were collected. Good neurologic survival was defined by a Cerebral Performance Categories (CPC) score of 1 or 2. Results:, During the study period, 1,985 arrests occurred. Of these, 715 (36%) had attempted resuscitation by paramedics and constitute our study sample. The median age was 65 years (interquartile range = 52,78 years), 69% were male, 41% had witnessed arrest, 25% had bystander cardiopulmonary resuscitation (CPR) performed, and 30% had ventricular fibrillation (VF) or pulseless ventricular tachycardia (VT) as their initial rhythm. Of the 715 patients, 545 (76%) were transported to a hospital, 223 (31%) had return of spontaneous circulation (ROSC), 175 (25%) survived to hospital admission, 58 (8%) survived to hospital discharge, and 42 (6%, 95% confidence interval [CI] = 4% to 8%) had a good neurologic outcome. Conclusions:, Out-of-hospital cardiac arrest survival in Denver, Colorado, is similar to that of other United States communities. This finding provides the basis for future epidemiologic and health services research in the out-of-hospital and ED settings in our community. ACADEMIC EMERGENCY MEDICINE,2010; 17:391,398 © 2010 by the Society for Academic Emergency Medicine [source]

    Clinical relevance of three subtypes of primary sinonasal lymphoma characterized by immunophenotypic analysis

    Gwi Eon Kim MD
    Abstract Background. The purpose of this study was to investigate the clinical relevance of subtypes categorized by immunophenotypic analysis in primary sinonasal lymphomas. Methods. Eighty patients with localized non-Hodgkin's lymphoma involving the nasal cavity and/or paranasal sinuses were divided into three subtypes on the basis of their immunohistochemical findings: (A) B-cell lymphoma (n = 19), (B) T-cell lymphoma (n = 27), and (C) natural killer (NK)/T-cell lymphoma (n = 34). The clinicopathologic profiles, immunophenotypic data, patterns of treatment failure, and survival data among the three patient groups were retrospectively compared. Results. The nasal cavity was the predominant site of involvement in T-cell and NK/T-cell lymphoma, whereas sinus involvement without nasal disease was common in B-cell lymphoma. Systemic B symptoms were frequently observed in NK/T-cell lymphoma. Almost all patients with NK/T-cell lymphoma showed a strong association with the Epstein-Barr virus by in situ hybridization studies. Sixty-five patients (81%) patients achieved complete remission after initial treatment, but 36 (55%) of these subsequently experienced treatment failure. Although there were no significant differences in locoregional failure rates among the patients of the three groups, distant failure was far more common in B-cell or NK/T-cell lymphoma than in T-cell lymphoma (p = .005). Most B-cell lymphoma cases showed a predilection for sites of systemic failure in the nodal and extranodal sites below the diaphragm, such as the paraaortic lymph nodes or the gastrointestinal (GI) tract, whereas patients with NK/T-cell lymphoma showed an increased risk of systemic dissemination to the skin, testes, or GI tract, including the development of hemophagocytic syndrome. The 5-year actuarial and disease-free survival rates for all patients were 57% and 51%, respectively. Of the three subtypes of primary sinonasal lymphomas, T-cell lymphoma seemed to carry the most favorable prognosis and NK/T-cell lymphoma the worst. (The 5-year actuarial survival rate was 57% for B-cell lymphoma, 80% for T-cell lymphoma, 37% for NK/T-cell lymphoma; p = .02, log-rank.) By univariate and multivariate analyses, immunophenotype was identified as the most important prognostic factor. Conclusions. Our data indicate that the three subtypes of primary sinonasal lymphomas classified by immunohistochemical studies exhibit different clinical profiles, different patterns of failure, and different treatment outcomes. Given these observations, it is concluded that the recognition of these distinct subsets, diagnosed on the basis of immunophenotypic study, is very important and clinically relevant in predicting their potential behavior and prognosis. © 2004 Wiley Periodicals, Inc. Head Neck26: 584,593, 2004 [source]

    Epoetin alfa corrects anemia and improves quality of life in patients with hematologic malignancies receiving non-platinum chemotherapy

    Timothy J. Littlewood
    Abstract Anemia, a commonly occurring morbidity in patients with cancer, often leads to diminished quality of life (QOL). Numerous clinical trials have shown that epoetin alfa treatment improves hematologic and QOL variables in cancer patients. The clinical trial analysis reported here was performed to assess response to epoetin alfa in patients with hematologic malignancies. Cancer patients with anemia undergoing non-platinum-based chemotherapy who were enrolled in a multinational, randomized (2:1), double-blind, placebo-controlled trial were prospectively stratified by tumor type (hematologic, solid). Efficacy endpoints included proportion of patients transfused after day 28; change in hemoglobin (Hb) level from baseline to last assessment; proportion of treatment responders (increase in Hb ,2,g/dl unrelated to transfusion) and correctors (patients whose Hb levels reached ,12,g/dl during the study); and QOL. The protocol was amended before unblinding to prospectively collect and assess survival data 12 months after the last patient completed the study, and survival for the full study cohort was estimated using Kaplan,Meier techniques. Efficacy analyses of hematologic and QOL variables, as well as Kaplan,Meier estimates of survival, were performed post hoc for the hematologic tumor stratum. Among patients with hematologic malignancies, the mean increase in Hb levels was greater with epoetin alfa than with placebo treatment (2.2 vs. 0.3,g/dl). Transfusion requirements were lower in patients who received epoetin alfa versus placebo (25.2 vs. 43.1%), and the proportion of responders and correctors was higher with epoetin alfa than with placebo (75.2 vs. 16.7% and 72.6 vs. 14.8%, respectively). Patients who received epoetin alfa had improved QOL while patients who received placebo had decreased QOL. These results are similar to those seen in the full study cohort, where differences between epoetin alfa and placebo were significant (P<0.05) for all five primary cancer- and anemia-specific QOL domains evaluated. Although the study was not powered for survival, Kaplan,Meier estimates showed a trend in overall survival favoring epoetin alfa in both the full study cohort and the hematologic subgroup. Epoetin alfa treatment was well tolerated. Epoetin alfa therapy increased Hb levels, reduced transfusion requirements, and improved QOL in patients with anemia undergoing non-platinum chemotherapy for hematologic malignancies. Copyright © 2004 John Wiley & Sons, Ltd. [source]

    A Comparison of CV-Catheters (CV) Grafts (GR) and Fistulae (FI) in Quotidian Hemodialysis

    C Kjellstrand
    We studied longevity and complications from CV, GR, and FI in 23 patients on quotidian hemodialysis. There were a total of 409 patient months, mean 18,10 months observation and a total of 9209 dialyses. There were 14 FI, 5 GR and 4 CV. 1, 1 and 2 replacements were necessary during a total observation time of 254, 105 and 50 patient months, respectively. For fistulae there were 0.02 replacements/year vs. 0.30 for GR and 0.41 for CV. P = 0.042 FI vs. other. The cumulative survival at 15 months was 100% for FI, 80% for GR and 20% for CV. P = 0.041. The cumulative survival at 3 years were 80% for fistulae and grafts, no CV lasted beyond 15 months. P = 0.013. There were 27 events requiring hospitalization or outpatient intervention. FI: 0.42/patient year, GR 1.22/patient year and CV 1.36/patient year. P = 0.080, FI vs. Other. Patients reported more problems between dialysis for FI, 3.2% of the days and least on GR (0.2%), CV (0.4%). P < 0.0001. Of the problems 85% were pain and redness. To the contrary there were more problems during dialysis with CV, 9.1% vs. FI 2.7%, and GR 0.9%. P < 0.0001. The complications and survival data are similar to those reported by others for quotidian hemodialysis and no different from reports on conventional 3 times per week dialyses. Conclusion: Daily hemodialysis does not adversely affect the different types of blood access. The survival and intervention need of accesses is best for fistulae, worst for CV, but GR, when functioning, have fewer problems between and during dialyses. [source]

    Adjuvant lipiodol I-131 after curative resection/ablation of hepatocellular carcinoma

    HPB, Issue 6 2008
    K. M. Ng
    Abstract Aim. A total of 329 patients with hepatocellular carcinoma have been treated at our unit since 1990. Following the randomized controlled trial in Hong Kong by Lau et al. in 1999, patients have been offered adjuvant lipiodol I-131. The aim of this study was to determine the effectiveness of adjuvant lipiodol I-131, following potentially curative surgery with resection and/or ablation, on overall and disease-free survival rates. Material and methods. The prospectively updated hepatocellular carcinoma database was analysed retrospectively. A total of 34 patients were identified to have received adjuvant lipiodol I-131 post-curative treatment with surgical resection and/or ablation. Patient demographics, clinical, surgical, pathology, and survival data were collected and analysed. Results. Three patients received ablation alone, 24 resection, and 7 resection and ablation. Of the 34 patients treated, there were 2 possible cases of treatment-related fatality (pneumonitis and liver failure). Potential prognostic factors studied for effect on survival included age, gender, serum AFP concentration, Child-Pugh score, cirrhosis, tumor size, portal vein tumor thrombus, tumor rupture, and vascular and margin involvement. The median follow-up duration was 23.3 months. The overall median survival was 40.1 months, while the overall survival rates at 1, 2, 3, and 4 years were 87.1%, 71.7%, 60.7%, and 49.6%, respectively. Median duration to recurrence was 22.3 months. Conclusion. Administration of adjuvant lipiodol I-131 is associated with good overall survival. [source]

    Up-to-date cancer survival: Period analysis and beyond

    Hermann Brenner
    Abstract Since its introduction in 1996, period analysis has been shown to be useful for deriving more up-to-date cancer survival estimates, and the method is now increasingly used for that purpose in national and international cancer survival studies. However, period analysis, like other commonly employed methods, is just a special case from a broad class of design options in the analysis of cancer survival data. Here, we explore a broader range of design options, including 2 model-based approaches, for deriving up-to-date estimates of 5- and 10-year relative survival for patients diagnosed in the most recent 5-year interval for which data are available. The performance of the various designs is evaluated empirically for 20 common forms of cancer using more than 50-year long time series of data from the Finnish Cancer Registry. Period analysis as well as the 2 model-based approaches, one using a "cohort-type model" and another using a "period-type model", all performed better than traditional cohort or complete analysis. Compared with "standard period analysis", the cohort-type model further increased up-to-dateness of survival estimates, whereas the period-type model increased their precision. While our analysis confirms advantages of period analysis over traditional methods in terms of up-to-dateness of cancer survival data, further improvements are possible by flexible use of model-based approaches. © 2008 Wiley-Liss, Inc. [source]

    Effect of NSAIDs on the recurrence of nonmelanoma skin cancer

    Maria V. Grau
    Experimental studies have consistently shown a protective effect of nonsteroidal antiinflammatory drugs (NSAIDs) against nonmelanoma skin cancers (NMSC). However, little human epidemiological research has been done in this regard. We used data from the Skin Cancer Chemoprevention Study to explore the association of NSAID use and with the risk of basal-cell carcinoma (BCC) and squamous-cell carcinoma (SCC). 1,805 subjects with a recent history of NMSC were randomized to placebo or 50 mg of daily ,-carotene. Participants were asked about their use of over-the-counter and prescription medications at baseline and every 4 months during the trial. Skin follow-up examinations were scheduled annually with a study dermatologist; confirmed lesions were the endpoints in the study. We used a risk set approach to the analysis of grouped times survival data and unconditional logistic regression to compute odds ratios [ORs] for various exposures to NSAIDs. The use of NSAIDs was reported in over 50% of questionnaires. For BCC, NSAIDs exhibited a weak protective effect in crude analyses, which attenuated markedly after adjustment. For SCC, the use of NSAIDs in the year previous to diagnosis reduced the odds by almost 30% (adjusted OR= 0.71, 95% CI 0.48,1.04). When we accounted for frequency of use, results for BCC were not striking, and there were inconsistent suggestions of an inverse association with SCC. There were some indications of a modest, nonsignificant reduction on the number of BCCs and SCCs with NSAID use. Our data suggest a weak and inconsistent chemopreventive effect of NSAIDs on BCC and SCC. © 2006 Wiley-Liss, Inc. [source]

    Silencing of APAF-1 in B-CLL results in poor prognosis in the case of concomitant p53 mutation

    Isrid Sturm
    Abstract Apoptosis protease-activating factor 1 (APAF-1), a transcriptional target of p53, is a cytosolic adaptor protein that links the mitochondrial apoptosis pathway to the caspase cascade. Here, we aimed to study the impact of APAF-1 expression levels on cell death induced by anticancer drugs or ionizing irradiation (IR) and disease prognosis in B-type chronic lymphocytic leukemia (B-CLL) patients. Samples from 138 patients with B-CLL were investigated for APAF-1 expression and p53 mutations. The results were related to survival data, in vitro cytotoxicity of various cytotoxic drugs and IR and clinico-pathological data. Variable APAF-1 expression was observed in all investigated B-CLL samples. Reduction in APAF-1 expression was observed at both mRNA and protein level indicating transcriptional silencing whereas mutation of p53 or the immunoglobulin heavy chain variable genes (IgHV) had no impact on APAF-1 expression. Surprisingly, APAF-1 loss did not result in resistance to cytotoxic therapies. Likewise, APAF-1 downregulation on its own showed no impact on disease prognosis. Nevertheless, a poor prognosis was observed in patients with loss of APAF-1 expression and additional p53 mutation. Thus, loss of APAF-1 may become relevant when additional core apoptosis signaling components are disrupted. © 2005 Wiley-Liss, Inc. [source]

    Comparison of models for genetic evaluation of survival traits in dairy cattle: a simulation study

    J. Jamrozik
    Summary Three models for the analysis of functional survival data in dairy cattle were compared using stochastic simulation. The simulated phenotype for survival was defined as a month after the first calving (from 1 to 100) in which a cow was involuntarily removed from the herd. Parameters for simulation were based on survival data of the Canadian Jersey population. Three different levels of heritability of survival (0.100, 0.050 and 0.025) and two levels of numbers of females per generation (2000 or 4000) were considered in the simulation. Twenty generations of random mating and selection (on a second trait, uncorrelated with survival) with 20 replicates were simulated for each scenario. Sires were evaluated for survival of their daughters by three models: proportional hazard (PH), linear multiple-trait (MT), and random regression (RR) animal models. Different models gave different ranking of sires with respect to survival of their daughters. Correlations between true and estimated breeding values for survival to five different points in a cow's lifetime after the first calving (120 and 240 days in milk after first, second, third and fourth calving) favoured the PH model, followed by the RR model evaluations. Rankings of models were independent of the heritability level, female population size and sire progeny group size (20 or 100). The RR model, however, showed a slight superiority over MT and PH models in predicting the proportion of sire's daughters that survived to the five different end-points after the first calving. [source]