Causes and outcomes of emergency presentation of rectal cancer.

Emergency presentation of rectal cancer carries a relatively poor prognosis, but the roles and interactions of causative factors remain unclear. We describe an innovative statistical approach which distinguishes between direct and indirect effects of a number of contextual, patient and tumour factors on emergency presentation and outcome of rectal cancer. All patients diagnosed with rectal cancer in Ireland 2004-2008 were included. Registry information, linked to hospital discharge data, provided data on patient demographics, comorbidity and health insurance; population density and deprivation of area of residence; tumour type, site, grade and stage; treatment type and optimality; and emergency presentation and hospital caseload. Data were modelled using a structural equation model with a discrete-time survival outcome, allowing us to estimate direct and mediated effects of the above factors on hazard, and their inter-relationships. Two thousand seven hundred and fifty patients were included in the analysis. Around 12% had emergency presentations, which increased hazard by 80%. Affluence, private patient status and being married reduced hazard indirectly by reducing emergency presentation. Older patients had more emergency presentations, while married patients, private patients or those living in less deprived areas had fewer than expected. Patients presenting as an emergency were less likely to receive optimal treatment or to have this in a high caseload hospital. Apart from stage, emergency admission was the strongest determinant of poor survival. The factors contributing to emergency admission in this study are similar to those associated with diagnostic delay. The socio-economic gradient found suggests that patient education and earlier access to endoscopic investigation for public patients could reduce emergency presentation.

Mechanisms and mediation in survival analysis: towards an integrated analytical framework.

BACKGROUND: A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare. METHODS: The authors begin by summarising debates on causal inference, mediated effects and statistical models, showing that these three strands of research have powerful synergies. They review a range of approaches which seek to extend existing survival models to obtain valid estimates of mediation effects. They then argue for an alternative strategy, which involves integrating survival outcomes within Structural Equation Models via the discrete-time survival model. This approach can provide an integrated framework for studying mediation effects in relation to survival outcomes, an issue of great relevance in applied health research. The authors provide an example of how these techniques can be used to explore whether the social class position of patients has a significant indirect effect on the hazard of death from colon cancer. RESULTS: The results suggest that the indirect effects of social class on survival are substantial and negative (-0.23 overall). In addition to the substantial direct effect of this variable (-0.60), its indirect effects account for more than one quarter of the total effect. The two main pathways for this indirect effect, via emergency admission (-0.12), on the one hand, and hospital caseload, on the other, (-0.10) are of similar size. CONCLUSIONS: The discrete-time survival model provides an attractive way of integrating time-to-event data within the field of Structural Equation Modelling. The authors demonstrate the efficacy of this approach in identifying complex causal pathways that mediate the effects of a socio-economic baseline covariate on the hazard of death from colon cancer. The results show that this approach has the potential to shed light on a class of research questions which is of particular relevance in health research.

Influence of socioeconomic status on allograft and patient survival following kidney transplantation.

AIM: Whether socioeconomic status confers worse outcomes after kidney transplantation is unknown. Its influence on allograft and patient survival following kidney transplantation in Ireland was examined. METHODS: A retrospective, observational cohort study of adult deceased-donor first kidney transplant recipients from 1990 to 2009 was performed. Those with a valid Irish postal address were assigned a socioeconomic status score based on the Pobal Hasse-Pratschke deprivation index and compared in quartiles. Cox proportional hazards models and Kaplan-Meier survival analysis were used to investigate any significant association of socioeconomic status with patient and allograft outcomes. RESULTS: A total of 1944 eligible kidney transplant recipients were identified. The median follow-up time was 8.2 years (interquartile range 4.4-13.3 years). Socioeconomic status was not associated with uncensored or death-censored allograft survival (hazard ratio (HR) 1.0, 95% confidence interval (CI) 0.99-1.00, P = 0.33 and HR 1.0, 95% CI 0.99-1.00, P = 0.37, respectively). Patient survival was not associated with socioeconomic status quartile (HR 1.0, 95% CI 0.93-1.08, P = 0.88). There was no significant difference among quartiles for uncensored or death-censored allograft survival at 5 and 10 years. CONCLUSION: There was no socioeconomic disparity in allograft or patient outcomes following kidney transplantation, which may be partly attributable to the Irish healthcare model. This may give further impetus to calls in other jurisdictions for universal healthcare and medication coverage for kidney transplant recipients.

Determinants of care outcomes for patients who die in hospital in Ireland: a retrospective study.

BACKGROUND: More people die in hospital than in any other setting which is why it is important to study the outcomes of hospital care at end of life. This study analyses what influenced outcomes in a sample of patients who died in hospital in Ireland in 2008/9. The study was undertaken as part of the Irish Hospice Foundation's Hospice Friendly Hospitals Programme (2007-2012). METHODS: Outcomes of care were assessed by nurses, doctors and relatives who cared for the patient during the last week of life. Multi-level modelling was used to analyse how care outcomes were influenced by care inputs. RESULTS: The sample of 999 patients represents 10% of acute hospital deaths and 29% of community hospital deaths in Ireland in 2008/9. Five care outcomes were assessed for each patient: symptom experience, symptom management, patient care, acceptability of the way patient died, family support. Care outcomes during the last week of life tended to be better when: the patient had cancer; admission to hospital was planned rather than emergency; death occurred in a single room or where privacy, dignity and environment of the ward was better; team meetings were held; there was good communication with patients and relatives; relatives were facilitated to stay overnight and were present at the time of death; nursing staff were experienced and had training in end-of-life care; the hospital had specific objectives for developing end-of-life care in its service plan. CONCLUSIONS: The study shows significant differences in how care outcomes, including pain, were assessed by nurses, doctors and relatives. Care inputs operate in a mutually reinforcing manner to generate care outcomes which implies that improvements in one area are likely to have spill-over effects in others. Building on these findings, the Irish Hospice Foundation has developed an audit and review system to support quality improvement in all care settings where people die.

Affluence and Private Health Insurance Influence Treatment and Survival in Non-Hodgkin's Lymphoma.

BACKGROUND: The aim of this study was to investigate inequalities in survival for non-Hodgkin's lymphoma (NHL), distinguishing between direct and indirect effects of patient, social and process-of-care factors. METHODS: All cases of NHL diagnosed in Ireland in 2004-2008 were included. Variables describing patient, cancer, stage and process of care were included in a discrete-time model of survival using Structural Equation Modelling software. RESULTS: Emergency admissions were more common in patients with co-morbid conditions or with more aggressive cancers, and less frequent for patients from more affluent areas. Aggressive morphology, female sex, emergency admission, increasing age, comorbidity, treatment in a high caseload hospital and late stage were associated with increased hazard of mortality. Private patients had a reduced hazard of mortality, mediated by systemic therapy, admission to high caseload hospitals and fewer emergency admissions. DISCUSSION: The higher rate of emergency presentation, and consequent poorer survival, of uninsured patients, suggests they face barriers to early presentation. Social, educational and cultural factors may also discourage disadvantaged patients from consulting with early symptoms of NHL. Non-insured patients, who present later and have more emergency admissions would benefit from better access to diagnostic services. Older patients remain disadvantaged by sub-optimal treatment, treatment in non-specialist centres and emergency admission.

The influence of socioeconomic status on patient survival on chronic dialysis.

Socioeconomic status (SES) has been linked to worse end-stage kidney disease survival. The effect of SES on survival on chronic dialysis, including the impact of transplantation, was examined. A retrospective, observational study investigated the association of SES with dialysis patient survival, with censoring at time of transplantation. Adult patients commencing dialysis from 1990 to 2009 in an Irish tertiary center received a spatial SES score using the 2011 Pobal Haase-Pratschke Deprivation Index and were compared by quartile. Cox proportional hazard models and Kaplan-Meier survival analysis examined any association of SES with survival. The 1794 patients included had a median follow-up of 3.8 years. Patients in the lowest SES area quartile were significantly younger than the highest, mean age 56.7 vs. 59 years, P = 0.006, respectively. There was no association between SES area score and survival in an unadjusted model (hazard ratio [HR] 1.00, 95% confidence interval [CI] 0.99-1.01). Survival in the highest SES area quartile was superior to the lowest SES in a multivariable adjusted model including age, gender, and dialysis modality (HR 0.83, 95% CI 0.70-0.99, P = 0.04). These results were only mildly attenuated by censoring at time of transplantation (highest SES area quartile deprived vs. lowest SES area quartile, HR 0.85, 95% CI 0.70-1.03, P = 0.09). Superior patient survival was identified in the highest SES areas compared with the lowest following age-adjusted analyses, despite the older population in the most affluent areas. Further research should focus on identifying modifiable targets for intervention that account for this socioeconomic-related survival advantage.