Cost-effectiveness of early intervention in psychosis in low- and middle-income countries: economic evaluation from São Paulo, Brazil

AIMS

The effectiveness and cost-effectiveness of early intervention for psychosis (EIP) services are well established in high-income countries but not in low- and middle-income countries (LMICs). Despite the scarcity of local evidence, several EIP services have been implemented in LMICs. Local evaluations are warranted before adopting speciality models of care in LMICs. We aimed to estimate the cost-effectiveness of implementing EIP services in Brazil.

METHODS

A model-based economic evaluation of EIP services was conducted from the Brazilian healthcare system perspective. A Markov model was developed using a cohort study conducted in São Paulo. Cost data were retrieved from local sources. The outcome of interest was the incremental cost-effectiveness ratio (ICER) measured as the incremental costs over the incremental quality-adjusted life-years (QALYs). Sensitivity analyses were performed to test the robustness of the results.

RESULTS

The study included 357 participants (38% female), with a mean (SD) age of 26 (7.38) years. According to the model, implementing EIP services in Brazil would result in a mean incremental cost of 4,478 Brazilian reals (R$) and a mean incremental benefit of 0.29 QALYs. The resulting ICER of R$ 15,495 (US dollar [USD] 7,640 adjusted for purchase power parity [PPP]) per QALY can be considered cost-effective at a willingness-to-pay threshold of 1 Gross domestic product (GDP) per capita (R$ 18,254; USD 9,000 PPP adjusted). The model results were robust to sensitivity analyses.

CONCLUSIONS

This study supports the economic advantages of implementing EIP services in Brazil. Although cultural adaptations are required, these data suggest EIP services might be cost-effective even in less-resourced countries.

Depression and physical multimorbidity during the adulthood. Cross-sectional associations

Introduction

The prevalence of depression and physical multimorbidity (pMM) might vary over the life course in a non-random fashion. The aims of our study were to: 1) assess the prevalence of depression and pMM over the life course; and 2) estimate changes in their pattern of association at different ages.

Methods

Data from 13,736 participants aged 26, 30, 34, 38, 42 and 46 years old of the British Child Study cohort was used. Individuals with information on current self-reported depression were selected as study sample. pMM (yes/no) caseness was defined as the coexistence of 2 or more self-reported physical conditions (e.g. asthma, diabetes, epilepsy). The prevalence of depression and pMM was calculated for each wave. To assess their relationship, prevalence ratios (PR) adjusted by gender, socioeconomic (e.g. educational level) and health-related variables (e.g. BMI and smoking status) and their 95% Confidence Intervals (95%CI) were obtained at each wave from multivariable Poisson models.

Results

Prevalence of depression varied with age (10.0% at age 26, 7.8% at age 38 and 18.3% at age 46) as did prevalence of pMM (37% at age 26, 15.6% at age 34, and 20.2% at age 46). A non-linear trend in the prevalence both of depression and pMM was observed with a decrease from age 26 to age 38 (34 for pMM) followed by a consistent increment to age 46. In all ages depression was significantly associated with pMM the magnitude ranging from PR: 1.52 (95%CI 1.41-1.65) at age 26 to PR: 1.96 (95%CI 1.72-2.23) at age 38.

Conclusions

There is consistent association between the prevalence of depression and pMM over different ages during adulthood. The non-linear pattern suggests differences in the type of conditions contributing to pMM at different ages (non-chronic in young adulthood vs chronic from middle adulthood). Further research on clusters and trajectories of different conditions over life course might be valuable to understand the association between depression and pMM.

Key messages

There is consistent association between the prevalence of depression and pMM over different ages during adulthood. They could be differences in the type of conditions contributing to depression related pMM at different ages (non-chronic in young adulthood vs chronic from middle adulthood).

Stability of clinically relevant depression symptoms in old-age across 11 cohorts: a multi-state study

AIMS

To study the temporal dynamics of depression symptom episodes in old-age and the related influence of risk factors.

METHODS

Data from 41 362 old adults (54.61% women; mean age = 75.30, SD = 6.20) from the Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project were used. Depressive symptoms were followed over an 18-year period. A multi-state model, comprising three statuses (no depression, new clinically relevant episode of symptoms and episode persistence), was fitted. Multinomial regression was used to study the role of risk factors in status transition.

RESULTS

Almost 85% of participants showed no depression, but prevalence became lower over time (B = -0.25, P < 0.001). New episode point prevalence was over 5.30% with a significant probability of moving to persistence status (transition probability = 0.27). Episode persistence became evident in 9.86% of episode status transitions, with increasing rate over time (B = 0.54, P < 0.01). Loneliness was proven to be the strongest predictor of episode emergence (OR = 17.76) and persistence (OR = 5.93).

CONCLUSIONS

The course of depression tends to become chronic and unremitting in old-age. This study may help to plan interventions to tackle symptom escalation and risk factor influence.

Evaluation of most frequent errors in daily compilation and use of a radiation treatment chart

Between 1 March and 30 April (1994) we recorded the errors detected by the physician, the radiographer or the physicist during prescription, preparation and execution phases of 227 treatment plans. The radiation treatment modalities used were the following: (i) single or opposed fields, moulded or not; and (ii) multiple fields or kinetic techniques. The total number of sessions performed is 1613 with the cobalt unit and 2131 with the linear accelerator (total, 3744). The total number of wrong data is 155, consisting of 24/227 (10.5%) in compilation, 22/3744 (0.58%) in execution and 109/3744 (2.9%) in registration phases. The number of missing data is 140, consisting of 10/227 (4.4%) in compilation, 9/3744 (0.2%) in execution and 121/3744 (3.2%) in registration phases. Wrong data of compilation, even if in high rate (10.5%), were all found during the same compilation phase or at the first treatment, so that they did not alter the exactness of the treatment plan. Wrong and missing data, found in the registration phase (2.9% and 3.2%, respectively), depend on the repetition of daily treatment and on the registration of data on the chart after having digitized them on the display.