Summary

Pattern mixture modeling is a popular approach for handling incomplete longitudinal data. Such models are not identifiable by construction. Identifying restrictions are one approach to mixture model identification (Little, 1995; Little and Wang, 1996; Thijs et al., 2002; Kenward et al., 2003; Daniels and Hogan, 2008) and are a natural starting point for missing not at random sensitivity analysis (Thijs et al., 2002; Daniels and Hogan, 2008). However, when the pattern specific models are multivariate normal, identifying restrictions corresponding to missing at random may not exist. Furthermore, identification strategies can be problematic in models with covariates (e.g. baseline covariates with time-invariant coefficients). In this paper, we explore conditions necessary for identifying restrictions that result in missing at random (MAR) to exist under a multivariate normality assumption and strategies for identifying sensitivity parameters for sensitivity analysis or for a fully Bayesian analysis with informative priors. In addition, we propose alternative modeling and sensitivity analysis strategies under a less restrictive assumption for the distribution of the observed response data. We adopt the deviance information criterion for model comparison and perform a simulation study to evaluate the performances of the different modeling approaches. We also apply the methods to a longitudinal clinical trial. Problems caused by baseline covariates with time-invariant coefficients are investigated and an alternative identifying restriction based on residuals is proposed as a solution.

Summary

Acute lung injury (ALI) is a condition characterized by acute onset of severe hypoxemia and bilateral pulmonary infiltrates. ALI patients typically require mechanical ventilation in an intensive care unit. Low tidal volume ventilation (LTVV), a time-varying dynamic treatment regime, has been recommended as an effective ventilation strategy. This recommendation was based on the results of the ARMA study, a randomized clinical trial designed to compare low vs. high tidal volume strategies (The Acute Respiratory Distress Syndrome Network, 2000) . After publication of the trial, some critics focused on the high non-adherence rates in the LTVV arm suggesting that non-adherence occurred because treating physicians felt that deviating from the prescribed regime would improve patient outcomes. In this paper, we seek to address this controversy by estimating the survival distribution in the counterfactual setting where all patients assigned to LTVV followed the regime. Inference is based on a fully Bayesian implementation of Robins’ (1986) G-computation formula. In addition to re-analyzing data from the ARMA trial, we also apply our methodology to data from a subsequent trial (ALVEOLI), which implemented the LTVV regime in both of its study arms and also suffered from non-adherence.

Missing phenotype data can be a major hurdle to mapping quantitative trait loci (QTL). Though in many cases experiments may be designed to minimize the occurrence of missing data, it is often unavoidable in practice; thus, statistical methods to account for missing data are needed. In this paper we describe an approach for conjoining multiple imputation and QTL mapping. Methods are applied to map genes associated with increased breathing effort in mice after lung inflammation due to allergen challenge in developing lines of the Collaborative Cross, a new mouse genetics resource. Missing data poses a particular challenge in this study because the desired phenotype summary to be mapped is a function of incompletely observed dose-response curves. Comparison of the multiple imputation approach to two naive approaches for handling missing data suggest that these simpler methods may yield poor results: ignoring missing data through a complete case analysis may lead to incorrect conclusions, while using a last observation carried forward procedure, which does not account for uncertainty in the imputed values, may lead to anti-conservative inference. The proposed approach is widely applicable to other studies with missing phenotype data.

Abstract

Obese older adults are particularly susceptible to sarcopenia and have a higher prevalence of disability than their peers of normal weight. Interventions to improve body composition in late life are crucial to maintaining independence. The main mechanisms underlying sarcopenia have not been determined conclusively, but chronic inflammation, apoptosis, and impaired mitochondrial function are believed to play important roles. It has yet to be determined whether impaired cellular quality control mechanisms contribute to this process. The objective of this study was to assess the effects of a 6-month weight loss program combined with moderate-intensity exercise on the cellular quality control mechanisms autophagy and ubiquitin-proteasome, as well as on inflammation, apoptosis, and mitochondrial function, in the skeletal muscle of older obese women. The intervention resulted in significant weight loss (8.0 ± 3.9 % vs. 0.4 ± 3.1% of baseline weight, p = 0.002) and improvements in walking speed (reduced time to walk 400 meters, − 20.4 ± 16% vs. − 2.5 ± 12%, p = 0.03). In the intervention group, we observed a three-fold increase in messenger RNA (mRNA) levels of the autophagy regulators LC3B, Atg7, and lysosome-associated membrane protein-2 (LAMP-2) compared to controls. Changes in mRNA levels of FoxO3A and its targets MuRF1, MAFBx, and BNIP3 were on average seven-fold higher in the intervention group compared to controls, but these differences were not statistically significant. Tumor necrosis factor-α (TNF-α) mRNA levels were elevated after the intervention, but we did not detect significant changes in the downstream apoptosis markers caspase 8 and 3. Mitochondrial biogenesis markers (PGC1α and TFAm) were increased by the intervention, but this was not accompanied by significant changes in mitochondrial complex content and activity. In conclusion, although exploratory in nature, this study is among the first to report the stimulation of cellular quality control mechanisms elicited by a weight loss and exercise program in older obese women.

Background:

Obesity and a sedentary lifestyle are associated with physical impairments and biologic changes in older adults. Weight loss combined with exercise may reduce inflammation and improve physical functioning in overweight, sedentary, older adults. This study tested whether a weight loss program combined with moderate exercise could improve physical function in obese, older adult women.

Methods:

Participants (N = 34) were generally healthy, obese, older adult women (age range 55–79 years) with mild to moderate physical impairments (ie, functional limitations). Participants were randomly assigned to one of two groups for 24 weeks: (i) weight loss plus exercise (WL+E; n = 17; mean age = 63.7 years [4.5]) or (ii) educational control (n = 17; mean age = 63.7 [6.7]). In the WL+E group, participants attended a group-based weight management session plus three supervised exercise sessions within their community each week. During exercise sessions, participants engaged in brisk walking and lower-body resistance training of moderate intensity. Participants in the educational control group attended monthly health education lectures on topics relevant to older adults. Outcomes were: (i) body weight, (ii) walking speed (assessed by 400-meter walk test), (iii) the Short Physical Performance Battery (SPPB), and (iv) knee extension isokinetic strength.

Results:

Participants randomized to the WL+E group lost significantly more weight than participants in the educational control group (5.95 [0.992] vs 0.23 [0.99] kg; P < 0.01). Additionally, the walking speed of participants in the WL+E group significantly increased compared with that of the control group (reduction in time on the 400-meter walk test = 44 seconds; P < 0.05). Scores on the SPPB improved in both the intervention and educational control groups from pre- to post-test (P < 0.05), with significant differences between groups (P = 0.02). Knee extension strength was maintained in both groups.

Conclusion:

Our findings suggest that a lifestyle-based weight loss program consisting of moderate caloric restriction plus moderate exercise can produce significant weight loss and improve physical function while maintaining muscle strength in obese, older adult women with mild to moderate physical impairments.