Search

Aims: Spinal muscular atrophy (SMA) is a progressive neuromuscular disease associated with the degeneration of motor neurons in the brainstem and spinal cord. Studies examining the epidemiology and economic impact of SMA are limited in Canada. This study aimed to estimate the epidemiology as well as healthcare resource utilization (HRU) and healthcare costs for children with SMA in Alberta, Canada.Materials and Methods: We conducted a retrospective study using anonymized data from administrative healthcare databases provided by Alberta Health. Data from 1 April 2010 to 31 March 2018, were extracted for patients <18 years of age identified with SMA. Five-year incidence and prevalence were calculated for cases identified between 1 April 2012 and 31 March 2017. HRU and healthcare costs were assessed one year after SMA diagnosis, including hospitalizations, physician visits, ambulatory care visits and long-term care admissions.Results: The five-year incidence and prevalence of pediatric onset SMA were 1.03 per 100,000 person-years and 9.97 per 100,000 persons, respectively. General practitioner, specialist, and ambulatory care visits were common among children with SMA in the first-year post-diagnosis. The mean (SD) total annual direct cost per patient in the first-year post-diagnosis was $29,774 ($38,407); hospitalizations accounted for 41.7% of these costs ($12,412 [$21,170]), followed by practitioner visits at 32.3% ($9,615 [$13,054]), and ambulatory care visits at 26.0% ($7,746 [$9,988]).Conclusions: Children with SMA experience substantial HRU, particularly for hospitalizations and practitioner visits, following diagnosis. Given the high costs of SMA, timely access to effective treatment strategies, such as the novel survival motor neuron (SMN)-restoring treatments recently approved for use, are needed to improve health outcomes and HRU. [ABSTRACT FROM AUTHOR]

Abstract Background Computer simulation models are used increasingly to support public health research and policy, but questions about their quality persist. The purpose of this article is to review the principles and methods for validation of population-based disease simulation models. Methods We developed a comprehensive framework for validating population-based chronic disease simulation models and used this framework in a review of published model validation guidelines. Based on the review, we formulated a set of recommendations for gathering evidence of model credibility. Results Evidence of model credibility derives from examining: 1) the process of model development, 2) the performance of a model, and 3) the quality of decisions based on the model. Many important issues in model validation are insufficiently addressed by current guidelines. These issues include a detailed evaluation of different data sources, graphical representation of models, computer programming, model calibration, between-model comparisons, sensitivity analysis, and predictive validity. The role of external data in model validation depends on the purpose of the model (e.g., decision analysis versus prediction). More research is needed on the methods of comparing the quality of decisions based on different models. Conclusion As the role of simulation modeling in population health is increasing and models are becoming more complex, there is a need for further improvements in model validation methodology and common standards for evaluating model credibility.

Background: Influenza vaccine immunogenicity is diminished in patients living with HIV/AIDS. We evaluated the costeffectiveness and expected value of perfect information (EVPI) of three alternative influenza vaccine dosing strategies intended to increase immunogenicity in those patients. Methods: A randomized, multi-centered, controlled, vaccine trial was conducted at 12 CIHR Canadian HIV Trials Network sites. Three dosing strategies with seasonal, inactivated trivalent, non-adjuvanted intramuscular vaccine were used in HIV infected adults: two standard doses over 28 days (Strategy A), two double doses over 28 days (Strategy B) and a single standard dose of influenza vaccine (Strategy C), administered prior to the 2008 influenza season. The comparator in our analysis was practice in the previous year, in which 82.8% of HIV/AIDS received standard-dose vaccination (Strategy D). A Markov cohort model was developed to estimate the monthly probability of Influenza-like Illness (ILI) over one influenza season. Costs and quality-adjusted life years, extrapolated to the lifetime of the hypothetical study cohorts, were estimated in calculating incremental cost-effectiveness ratios (ICER) and EVPI in conducting further research. Results: 298 patients with median CD4 of 470 cells/μl and 76% with viral load suppression were randomized. Strategy C was the most cost-effective strategy for the overall trial population and for suppressed and unsuppressed individuals. Mean ICERs for Strategy A for unsuppressed patients could also be considered cost-effective. The level of uncertainty regarding the decision to implement strategy A versus C for unsuppressed individuals was high. The maximum acceptable cost of reducing decision uncertainty in implementing strategy A for individuals with unsuppressed pVL was $418,000 - below the cost of conducting a larger-scale trial. Conclusion: Our results do not support a policy to implement increased antigen dose or booster dosing strategies with seasonal, inactivated trivalent, non-adjuvanted intramuscular vaccine for individuals with HIV in Canada. [ABSTRACT FROM AUTHOR]

Background: Computer simulation models are used increasingly to support public health research and policy, but questions about their quality persist. The purpose of this article is to review the principles and methods for validation of population-based disease simulation models. Methods: We developed a comprehensive framework for validating population-based chronic disease simulation models and used this framework in a review of published model validation guidelines. Based on the review, we formulated a set of recommendations for gathering evidence of model credibility. Results: Evidence of model credibility derives from examining: 1) the process of model development, 2) the performance of a model, and 3) the quality of decisions based on the model. Many important issues in model validation are insufficiently addressed by current guidelines. These issues include a detailed evaluation of different data sources, graphical representation of models, computer programming, model calibration, between-model comparisons, sensitivity analysis, and predictive validity. The role of external data in model validation depends on the purpose of the model (e.g., decision analysis versus prediction). More research is needed on the methods of comparing the quality of decisions based on different models. Conclusion: As the role of simulation modeling in population health is increasing and models are becoming more complex, there is a need for further improvements in model validation methodology and common standards for evaluating model credibility. [ABSTRACT FROM AUTHOR]

Aim: Insufficient adherence to colorectal cancer (CRC) screening impedes individual and population health benefits, with about one-third of individuals non-adherent to available screening options. The impact of poor adherence is inadequately considered in most health economics models, limiting the evaluation of real-world population-level screening outcomes. This study introduces the CAN-SCREEN (Colorectal cANcer SCReening Economics and adherENce) model, utilizing real-world adherence scenarios to assess the effectiveness of a blood-based test (BBT) compared to existing strategies., Materials and Methods: The CAN-SCREEN model evaluates various CRC screening strategies per 1,000 screened individuals for ages 45-75. Adherence is modeled in two ways: (1) full adherence and (2) longitudinally declining adherence. BBT performance is based on recent pivotal trial data while existing strategies are informed using literature. The full adherence model is calibrated using previously published Cancer Intervention and Surveillance Modeling Network (CISNET) models. Outcomes, including life-years gained (LYG), CRC cases averted, CRC deaths averted, and colonoscopies, are compared to no screening., Results: Longitudinal adherence modeling reveals differences in the relative ordering of health outcomes and resource utilization, as measured by the number of colonoscopies performed per 1,000, between screening modalities. BBT outperforms the fecal immunochemical test (FIT) and the multitarget stool DNA (mtsDNA) test with more CRC deaths averted (13) compared to FIT and mtsDNA (7, 11), more CRC cases averted (27 vs. 16, 22) and higher LYG (214 vs. 157, 199). BBT yields fewer CRC deaths averted compared to colonoscopy (13, 15) but requires fewer colonoscopies (1,053 vs. 1,928)., Limitations: Due to limited data, the CAN-SCREEN model with longitudinal adherence leverages evidence-informed assumptions for the natural history and real-world longitudinal adherence to screening., Conclusions: The CAN-SCREEN model demonstrates that amongst non-invasive CRC screening strategies, those with higher adherence yield more favorable health outcomes as measured by CRC deaths averted, CRC cases averted, and LYG.

Objectives: To evaluate the association between percent body fat (%BF) and body mass index (BMI) among BMI-defined non-obese individuals between 40 and 69 years of age using a population-based Canadian sample., Data and Methods: Cross-sectional data from the Canadian Health Measures Survey (2007 and 2009) was used to select all middle-aged individuals with BMI &lt; 30 kg/m2 (n = 2,656). %BF was determined from anthropometric skinfolds and categorized according to sex-specific equations. Association of other anthropometry measures and metabolic markers were evaluated across different %BF categories. Significance of proportions was evaluated using chi-squared and Bonferroni-adjusted Wald test. Diagnostic performance measures of BMI-defined overweight categories compared to those defined by %BF were reported., Results: The majority (69%) of the sample was %BF-defined overweight/obese, while 55% were BMI-defined overweight. BMI category was not concordant with %BF classification for 30% of the population. The greatest discordance between %BF and BMI was observed among %BF-defined overweight/obese women (32%). Sensitivity and specificity of BMI-defined overweight compared to %BF-defined overweight/obese were (58%, 94%) among females and (82%, 59%) among males respectively. According to the estimated negative predictive value, if an individual is categorized as BMI-defined non-obese, he/she has a 52% chance of being in the %BF-defined overweight/obese category., Conclusion: Middle-aged individuals classified as normal by BMI may be overweight/obese based on measures of %BF. These individuals may be at risk for chronic diseases, but would not be identified as such based on their BMI classification. Quantifying %BF in this group could inform targeted strategies for disease prevention.