Psychological as well as illness factors influence acceptance of non-invasive ventilation (NIV) and gastrostomy in amyotrophic lateral sclerosis (ALS): a prospective population study.

Our objective was to identify factors associated with acceptance of non-invasive ventilation (NIV) and gastrostomy in an exploratory population-based study. Seventy-eight people with ALS at least six months post-diagnosis, and 50 caregivers, were recruited from the South-East ALS Register. Baseline physical, cognitive and psychological measures were obtained. Three-monthly follow-ups monitored whether patients had accepted or refused NIV or gastrostomy. Following an intervention decision, post-decision interviews repeated baseline measures and included further intervention-specific questionnaires. Results showed that 32 people with ALS made at least one intervention decision and of these 10 decided about both NIV and gastrostomy. While illness factors predicted those needing to make an intervention decision, cognitive and education status, and level of executive dysfunction were associated with decision-making and acceptance or refusal of interventions. Patients' understanding of their illness, their early approach to considering interventions and carer-related factors were also associated with treatment decisions. In conclusion, our findings highlight the complexity of decision-making and provide a platform for designing further studies. Cognitive and psychosocial factors may assume a greater role in palliative care decisions for people with ALS than has been explicitly recognized. Future work must clarify how to ensure patients are not inadvertently being denied suitable interventions.

Prognostic categories for amyotrophic lateral sclerosis.

Our objective was to generate a prognostic classification method for amyotrophic lateral sclerosis (ALS) from a prognostic model built using clinical variables from a population register. We carried out a retrospective multivariate analysis of 713 patients with ALS over a 20-year period from the South-East England Amyotrophic Lateral Sclerosis (SEALS) population register. Patients were randomly allocated to 'discovery' or 'test' cohorts. A prognostic score was calculated using the discovery cohort and then used to predict survival in the test cohort. The score was used as a predictor variable to split the test cohort in four prognostic categories (good, moderate, average, poor). The accuracy of the score in predicting survival was tested by checking whether the predicted survival fell within the actual survival tertile which that patient was in. A prognostic score generated from one cohort of patients predicted survival for a second cohort of patients (r(2) = 0.72). Six variables were included in the survival model: age at onset, diagnostic delay, El Escorial category, use of riluzole, gender and site of onset. Cox regression demonstrated a strong relationship between these variables and survival (χ(2) 80.8, df 1, p < 0.0001, n = 343) in the test cohort. Kaplan-Meier analysis demonstrated a significant difference in survival between clinical categories (log rank 161.932, df 3, p < 0.001), and the prognostic score generated for the test cohort accurately predicted survival in 64% of the patients. In conclusion, it is possible to correctly classify patients into prognostic categories using clinical data easily available at time of diagnosis.

The association between ALS and population density: A population based study.

We aimed to assess whether rural residence is associated with amyotrophic lateral sclerosis in the south-east of England using a population based register. Previous studies in different populations have produced contradictory findings. Residence defined by London borough or non-metropolitan district at time of diagnosis was recorded for each incident case in the South-East England ALS Register between 1995 and 2005. Each of the 26 boroughs or districts of the catchment area of the register was classified according to population density. Age- and sex-adjusted incidence of ALS was calculated for each region and the relationship with population density tested by linear regression, thereby controlling for the underlying population structure. We found that population density in region of residence at diagnosis explained 25% of the variance in ALS rates (r = 0.5, p < 0.01). Thus, in this cohort in the south-east of England, people with ALS were more likely to be resident in areas of high population density at diagnosis.

The sex ratio in amyotrophic lateral sclerosis: A population based study.

Replicable risk factors for ALS include increasing age, family history and being male. The male: female ratio has been reported as being between 1 and 3. We tested the hypothesis that the sex ratio changes with age in a population register covering the south-east of England. The sex ratio before and after the age of 51 years was compared using a Z-test for proportions. Kendall's tau was used to assess the relationship between age group and sex ratio using incidence and prevalence data. Publicly available data from Italian and Irish population registers were compared with results. There was a significant difference in the proportion of females with ALS between those in the younger group (30.11%) and those in the older group (43.66%) (p = 0.013). The adjusted male: female ratio dropped from 2.5 in the younger group to 1.4 in the older group using prevalence data (Kendall's tau = -0.73, p = 0.039). Similar ratios were found in the Italian but not the Irish registry. We concluded that sex ratios in ALS may change with age. Over-representation of younger patients in clinic registers may explain the variation in sex ratios between studies. Menopause may also play a role.