Death or survival from invasive pneumococcal disease in Scotland: associations with serogroups and multilocus sequence types

We describe associations between death from invasive pneumococcal disease (IPD) and particular serogroups and sequence types (STs) determined by multilocus sequence typing (MLST) using data from Scotland. All IPD episodes where blood or cerebrospinal fluid (CSF) culture isolates were referred to the Scottish Haemophilus, Legionella, Meningococcal and Pneumococcal Reference Laboratory (SHLMPRL) from January 1992 to February 2007 were matched to death certification records by the General Register Office for Scotland. This represented 5959 patients. The median number of IPD cases in Scotland each year was 292. Deaths, from any cause, within 30 days of pneumococcal culture from blood or CSF were considered to have IPD as a contributing factor. Eight hundred and thirty-three patients died within 30 days of culture of Streptococcus pneumoniae from blood or CSF [13.95 %; 95 % confidence interval (13.10, 14.80)]. The highest death rates were in patients over the age of 75. Serotyping data exist for all years but MLST data were only available from 2001 onward. The risk ratio of dying from infection due to particular serogroups or STs compared to dying from IPD due to all other serogroups or STs was calculated. Fisher’s exact test with Bonferroni adjustment for multiple testing was used. Age adjustment was accomplished using the Cochran–Mantel–Haenszel test and 95 % confidence intervals were reported. Serogroups 3, 11 and 16 have increased probability of causing fatal IPD in Scotland while serogroup 1 IPD has a reduced probability of causing death. None of the 20 most common STs were significantly associated with death within 30 days of pneumococcal culture, after age adjustment. We conclude that there is a stronger association between a fatal outcome and pneumococcal capsular serogroup than there is between a fatal outcome and ST.

Climate change, multiple paternity and offspring survival in lizards

Recent work suggests that rising spring temperatures over recent decades have eliminated many lizard populations, and threaten many more worldwide. However, because ambient temperatures constrain activity times in ectotherms, warming conditions (as expected under global climate change scenarios) can increase the duration of seasonal opportunities for courtship and mating. Thus, in species where polyandry results in enhanced offspring viability, a warming climate may not necessarily impair long-term survival. Our nine-year study of a sand lizard (Lacerta agilis) population near the northern range limit in Sweden revealed consistently higher incidence of multiple paternity of clutches in warmer years, and higher viability of offspring from multiply-sired clutches (presumably reflecting the advantages of more intense sperm competition). Any trend to warmer spring temperatures likely will benefit offspring viability in this system, by increasing a female's opportunities to mate with additional males.

Survival analysis of time-to-event data in respiratory health research studies

This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes.

Modelling grouped survival times in toxicological studies using generalized additive models

A method for combining a proportional-hazards survival time model with a bioassay model where the log-hazard function is modelled as a linear or smoothing spline function of log-concentration combined with a smoothing spline function of time is described. The combined model is fitted to mortality numbers, resulting from survival times that are grouped due to a common set of observation times, using Generalized Additive Models (GAMs). The GAM fits mortalities as conditional binomials using an approximation to the log of the integral of the hazard function and is implemented using freely-available, general software for fitting GAMs. Extensions of the GAM are described to allow random effects to be fitted and to allow for time-varying concentrations by replacing time with a calibrated cumulative exposure variable with calibration parameter estimated using profile likelihood. The models are demonstrated using data from a studies of a marine and a, previously published, freshwater taxa. The marine study involved two replicate bioassays of the effect of zinc exposure on survival of an Antarctic amphipod, Orchomenella pinguides. The other example modelled survival of the daphnid, Daphnia magna, exposed to potassium dichromate and was fitted by both the GAM and the process-based DEBtox model. The GAM fitted with a cubic regression spline in time gave a 61 % improvement in fit to the daphnid data compared to DEBtox due to a non-monotonic hazard function. A simulation study using each of these hazard functions as operating models demonstrated that the GAM is overall more accurate in recovering lethal concentration values across the range of forms of the underlying hazard function compared to DEBtox and standard multiple endpoint probit analyses.

Determining the sensitivity of the Antarctic amphipod Orchomenella pinguides to metals using a joint model of survival response to exposure concentration and duration

Developing water quality guidelines for Antarctic marine environments requires understanding the sensitivity of local biota to contaminant exposure. Antarctic invertebrates have shown slower contaminant responses in previous experiments compared to temperate and tropical species in standard toxicity tests. Consequently, test methods which take into account environmental conditions and biological characteristics of cold climate species need to be developed. This study investigated the effects of five metals on the survival of a common Antarctic amphipod, Orchomenella pinguides. Multiple observations assessing mortality to metal exposure were made over the 30 days exposure period. Traditional toxicity tests with quantal data sets are analysed using methods such as maximum likelihood regression (probit analysis) and Spearman–Kärber which treat individual time period endpoints independently. A new statistical model was developed to integrate the time-series concentration–response data obtained in this study. Grouped survival data were modelled using a generalized additive mixed model (GAMM) which incorporates all the data obtained from multiple observation times to derive time integrated point estimates. The sensitivity of the amphipod, O. pinguides, to metals increased with increasing exposure time. Response times varied for different metals with amphipods responding faster to copper than to cadmium, lead or zinc. As indicated by 30 days lethal concentration (LC50) estimates, copper was the most toxic metal (31 µg/L), followed by cadmium (168 µg/L), lead (256 µg/L) and zinc (822 µg/L). Nickel exposure (up to 1.12 mg/L) did not affect amphipod survival. Using longer exposure durations and utilising the GAMM model provides an improved methodology for assessing sensitivities of slow responding Antarctic marine invertebrates to contaminants.

Disparities in pediatric leukemia early survival in Argentina: a population-based study

To identify disparities-using recursive partitioning (RP)-in early survival for children with leukemias treated in Argentina, and to depict the main characteristics of the most vulnerable groups.

Assessment of delay in age-appropriate vaccination using survival analysis

 Assessment of delay in age-appropriate vaccination provides more information about timeliness of vaccination than up-to-date vaccination coverage. The authors applied survival analysis methods to data from a vaccination coverage survey among children aged 13–59 months conducted in Argentina in 2002. By age 19 months, 43% of children (95% confidence interval (CI): 40, 46) were vaccinated with the fourth dose of diphtheria, tetanus, and pertussis (DTP4). By age 13 months, 55% of children (95% CI: 52, 57) were vaccinated with measles-containing vaccine. By age 7 months, 33% of children (95% CI: 27, 40) were vaccinated with the third dose of hepatitis B. Compared with firstborn children, third children were more likely to be delayed for DTP4 (relative risk (RR) = 1.41, 95% CI: 1.22, 1.62), measles-containing vaccine (RR = 1.54, 95% CI: 1.32, 1.78), and the third dose of hepatitis B (RR = 1.31, 95% CI: 1.03, 1.67). Children whose caregivers had completed secondary school were less likely to be delayed for DTP4 (RR = 0.68, 95% CI: 0.52, 0.90) compared with those whose caregivers had not completed primary school. Survival analysis methods were helpful in measuring vaccine uptake and should be considered in future surveys when assessing delay in age-appropriate vaccination. Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved.

A population-based study of retinoblastoma incidence and survival in Argentine children

An increased incidence of retinoblastoma in some developing countries has been reported but no conclusive data are available from population-based studies at national level.