Multivariable analysis of predictors of excess mortality using Poisson regression.

<p>Reference categories – a. First year of follow up; b. Female. c. Non-Indigenous d. Age group 15-44 years. e. Charlson comorbidity index = 0; f. Non-severe sepsis patients; g. Non-bacteraemic patients.</p><p>Multivariable analysis of predictors of excess mortality using Poisson regression.</p

Long Term Outcomes Following Hospital Admission for Sepsis Using Relative Survival Analysis: A Prospective Cohort Study of 1,092 Patients with 5 Year Follow Up - Figure 1

<p>a. Kaplan-Meier crude survival estimates by age group for all sepsis patients (n = 1,028). b. Kaplan-Meier crude survival estimates by age group for severe sepsis patients (n = 228).</p

Demographics, comorbidities, characteristics of infection and disease severity in those who died compared with those who were alive at the end of follow up.

<p>Data are given as n(%) unless stated otherwise.</p><p>Parameters are grouped according to PIRO classification <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112224#pone.0112224-Rubulotta1" target="_blank">[39]</a>.</p>a<p>P-value comparing those alive at end of follow up period compared with those who were not.</p>b<p>Mean (SD).</p>c<p>Data were not available for all patients regarding alcohol use and smoking.</p>d<p>Median (IQR).</p><p>Demographics, comorbidities, characteristics of infection and disease severity in those who died compared with those who were alive at the end of follow up.</p

Five-year relative survival (with 95% confidence interval) by age group, sex and Indigenous status.

<p>Five-year relative survival (with 95% confidence interval) by age group, sex and Indigenous status.</p

Interval specific relative survival by age category (severe sepsis patients).

<p>Interval specific relative survival by age category (severe sepsis patients).</p

Demographics characteristics and HBsAg, anti-HBc and anti-HBs positive results, NT residents tested for HBV in 2007–2011, by Indigenous status and sex.

<p>Demographics characteristics and HBsAg, anti-HBc and anti-HBs positive results, NT residents tested for HBV in 2007–2011, by Indigenous status and sex.</p

Interrupted time series analysis looking at HBsAg prevalence trends for (A) Indigenous, (B) non-Indigenous and (C) total population pre and post 1990 by birth cohort.

<p>Interrupted time series analysis looking at HBsAg prevalence trends for (A) Indigenous, (B) non-Indigenous and (C) total population pre and post 1990 by birth cohort.</p

Numbers of people who had one or more hepatitis B serology markers tested between 2007 and 2011 inclusive and the proportion of the NT population they represent detailed by Indigenous status and age group at the time of testing.

<p>Numbers of people who had one or more hepatitis B serology markers tested between 2007 and 2011 inclusive and the proportion of the NT population they represent detailed by Indigenous status and age group at the time of testing.</p

Comorbidity and cervical cancer survival of Indigenous and non-Indigenous Australian women: A semi-national registry-based cohort study (2003-2012)

<div><p>Background</p><p>Little is known about the impact of comorbidity on cervical cancer survival in Australian women, including whether Indigenous women’s higher prevalence of comorbidity contributes to their lower survival compared to non-Indigenous women.</p><p>Methods</p><p>Data for cervical cancers diagnosed in 2003–2012 were extracted from six Australian state-based cancer registries and linked to hospital inpatient records to identify comorbidity diagnoses. Five-year cause-specific and all-cause survival probabilities were estimated using the Kaplan-Meier method. Flexible parametric models were used to estimate excess cause-specific mortality by Charlson comorbidity index score (0,1,2+), for Indigenous women compared to non-Indigenous women.</p><p>Results</p><p>Of 4,467 women, Indigenous women (4.4%) compared to non-Indigenous women had more comorbidity at diagnosis (score ≥1: 24.2% vs. 10.0%) and lower five-year cause-specific survival (60.2% vs. 76.6%). Comorbidity was associated with increased cervical cancer mortality for non-Indigenous women, but there was no evidence of such a relationship for Indigenous women. There was an 18% reduction in the Indigenous: non-Indigenous hazard ratio (excess mortality) when comorbidity was included in the model, yet this reduction was not statistically significant. The excess mortality for Indigenous women was only evident among those without comorbidity (Indigenous: non-Indigenous HR 2.5, 95%CI 1.9–3.4), indicating that factors other than those measured in this study are contributing to the differential. In a subgroup of New South Wales women, comorbidity was associated with advanced-stage cancer, which in turn was associated with elevated cervical cancer mortality.</p><p>Conclusions</p><p>Survival was lowest for women with comorbidity. However, there wasn’t a clear comorbidity-survival gradient for Indigenous women. Further investigation of potential drivers of the cervical cancer survival differentials is warranted.</p><p>Impact</p><p>The results highlight the need for cancer care guidelines and multidisciplinary care that can meet the needs of complex patients. Also, primary and acute care services may need to pay more attention to Indigenous Australian women who may not obviously need it (i.e. those without comorbidity).</p></div

Cause-specific survival for NSW women (n = 1,069) by Charlson Comorbidity Index score, stratified by cancer stage, adjusted for age at diagnosis and Indigenous status.

<p>Cause-specific survival for NSW women (n = 1,069) by Charlson Comorbidity Index score, stratified by cancer stage, adjusted for age at diagnosis and Indigenous status.</p