Exploring the relationship between North Star Ambulatory Assessment and Health Utilities Index scores in Duchenne muscular dystrophy.

BACKGROUND: The North Star Ambulatory Assessment (NSAA) documents motor performance in ambulatory individuals with Duchenne muscular dystrophy (DMD). Health Utilities Index (HUI) scores, reflecting preferences for health-related quality-of-life (HRQoL) implications of health states, are commonly estimated within trials. This study sought to characterize the relationship between the NSAA score and utility in DMD. METHODS: Family members serving as proxy respondents for placebo-treated ambulatory individuals with DMD (NCT01254019; BioMarin Pharmaceuticals Inc) completed the HUI and the NSAA (score range, 0-34). Mean change over time on these measures was estimated, and the correlation between changes in NSAA score and a) HUI utility; b) HUI3 ambulation and HUI2 mobility attribute scores, over 48 weeks was calculated. RESULTS: Baseline mean (range) age was 8.0 years (5-16; n = 61) and mean (standard deviation [SD]) scores were 0.87 (0.13; HUI2), 0.82 (0.19; HUI3), and 21.0 (8.1; NSAA). Mean (SD) change over 48 weeks was -0.05 (0.14; HUI2), -0.06 (0.19; HUI3), and -2.9 (4.7; NSAA). Weak positive correlations were observed between baseline NSAA score and HUI utility (HUI2: r = 0.29; HUI3: r = 0.17) and for change over 48 weeks (HUI2: r = 0.16; HUI3: r = 0.15). Stronger correlations were observed between change in NSAA score and the HUI3 ambulation (r = 0.41) and HUI2 mobility (r = 0.41) attributes. CONCLUSIONS: Among ambulatory individuals with DMD, NSAA score is weakly correlated with HUI utility, suggesting that motor performance alone does not fully explain HRQoL. Stronger relationships were observed between HUI ambulation and mobility attributes, and NSAA. Although unidimensional measures like the NSAA are informative for documenting disease-specific health impacts, they may not correlate well with measures of overall health status; requiring use in conjunction with other patient-reported and preference-based outcomes.

An Epidemiological Model to Estimate the Prevalence of Diffuse Large B-Cell Lymphoma in the United States.

BACKGROUND: Prevalence is reflective of disease incidence and survival, and defined as the number of patients living with active disease. In diseases such as diffuse large B-cell lymphoma (DLBCL) with treatments with curative potential, a proportion of patients are cured, leading to a need for accurate, contemporary estimates of DLBCL prevalence to gauge the impact of the rapidly emerging treatment landscape. METHODS: Data from Surveillance, Epidemiology, and End Results (SEER) from 2000-2018 were utilized to develop an epidemiological model of incidence, survival, and cure, to estimate the current prevalent DLBCL population requiring active management in the United States (US). A variety of estimates were explored regarding cure rate and timing, based on a companion analysis of MarketScan data for treatment patterns and survival in incident DLBCL patients, and conditional survival analysis of SEER data. RESULTS: Across scenarios, with estimated cure ranging from 52.8% and 68.9%, and timing of cure ranging from 1 and 20 years post diagnosis, the estimated prevalence ranged from 63,883 to 142,889. With an assumption of no cure, estimated prevalence was 179,475. DISCUSSION: Prevalence estimates of DLBCL varied almost 3-fold, depending on specific cure adjustments made. Further understanding of DLBCL prevalence, for newly diagnosed and relapsed and/or refractory disease, is important to characterize the impact of emerging treatment options and related health care burden.

Short interpregnancy interval and pregnancy outcomes: How important is the timing of confounding variable ascertainment?

BACKGROUND: Estimation of causal effects of short interpregnancy interval on pregnancy outcomes may be confounded by time-varying factors. These confounders should be ascertained at or before delivery of the first ("index") pregnancy, but are often only measured at the subsequent pregnancy. OBJECTIVES: To quantify bias induced by adjusting for time-varying confounders ascertained at the subsequent (rather than the index) pregnancy in estimated effects of short interpregnancy interval on pregnancy outcomes. METHODS: We analysed linked records for births in British Columbia, Canada, 2004-2014, to women with ≥2 singleton pregnancies (n = 121 151). We used log binomial regression to compare short (<6, 6-11, 12-17 months) to 18-23-month reference intervals for 5 outcomes: perinatal mortality (stillbirth and neonatal death); small for gestational age (SGA) birth and preterm delivery (all, early, spontaneous). We calculated per cent differences between adjusted risk ratios (aRR) from two models with maternal age, low socio-economic status, body mass index, and smoking ascertained in the index pregnancy and the subsequent pregnancy. We considered relative per cent differences <5% minimal, 5%-9% modest, and ≥10% substantial. RESULTS: Adjustment for confounders measured at the subsequent pregnancy introduced modest bias towards the null for perinatal mortality aRRs for <6-month interpregnancy intervals [-9.7%, 95% confidence interval [CI] -15.3, -6.2). SGA aRRs were minimally biased towards the null (-1.1%, 95% CI -2.6, 0.8) for <6-month intervals. While early preterm delivery aRRs were substantially biased towards the null (-10.4%, 95% CI -14.0, -6.6) for <6-month interpregnancy intervals, bias was minimal for <6-month intervals for all preterm deliveries (-0.6%, 95% CI -2.0, 0.8) and spontaneous preterm deliveries (-1.3%, 95% CI -3.1, 0.1). For all outcomes, bias was attenuated and minimal for 6-11-month and 12-17-month interpregnancy intervals. CONCLUSION: These findings suggest that maternally linked pregnancy data may not be needed for appropriate confounder adjustment when studying the effects of short interpregnancy interval on pregnancy outcomes.

Income-related disparities in private prescription drug coverage in Canada.

BACKGROUND: Canada does not have universal public coverage for prescription drugs, which leaves an important role for private insurance plans. However, we do not have recent data on the characteristics of Canadians who report holding such coverage, particularly differences based on household income. We performed a study to examine the relation between household income and private drug insurance coverage in Canada. METHODS: We used data from the 2015-2016 cycle of the Canadian Community Health Survey to investigate the relation between household income and holding private drug insurance. We constructed modified multivariate Poisson regression models with robust error variances, including several potential confounders. RESULTS: Overall, 59.4% of respondents reported having private drug insurance. We found a strong dose-response relation between household income level and private drug insurance coverage: 19.8% of those with a household income less than $20 000 reported private coverage, compared to 76.2% of those with a household income of $80 000 or more. INTERPRETATION: Higher-income households are much more likely to hold private drug insurance coverage in Canada. This likely contributes to differential access to medicines and health outcomes by different income groups.