Statistical inference problems in sequential parallel comparison design.

The sequential parallel comparison designhas recently been considered to solve the problem with high placebo response and the required sample size in the psychiatric clinical trials. One feature with this design is that a difference between the placebo group and the drug group may also arise in the variance-covariance structure of the clinical outcome. Provided the heterogeneity of the second moment, the treatment effect estimation at the second stage can be biased for the entire randomized patient population that includes patient responders. Our work presented here aims at how the coverage probability of the interval estimation of treatment effect performs under the unstructured variance-covariance matrix. The interaction between the truncation after the first stage and the heterogeneity of the second moment causes a substantial coverage probability problem. The type I error probability may not be controlled under the weak null due to this bias. This bias can also cause spurious power evaluation under an alternative hypothesis. The coverage probability of the ordinary least square statistic is shown in different scenarios.

Rejoinder to "Statistical inference problems in sequential parallel comparison designs".

In this rejoinder the authors stipulate further for two challenging issues. First, if placebo non-responders are selected simply by their response meeting a threshold, this selection may have misclassification error and consequently the treatment effect estimate may be biased, regardless of whether the estimand at the second stage is the treatment effect in the entire population or placebo non-responders. Secondly, the weak null hypothesis considered in our article Statistical Inference Problems in Sequential Parallel Comparison Design (2019) is that the expected treatment effects in placebo non-responders and in the entire set of patients entering the trial are both zero, in contrast to the strong null hypothesis that the statistical distribution of the response variable is equal in the compared treatments. The impact of violating the assumption of equal moments other than the mean parameter on statistical operating characteristics in estimation and testing of treatment effect can be substantial. As an example, the ordinary least squares based test detects a treatment difference even if the expected treatment effects in placebo non-responders and the entire population are both zero.

Design of sequentially randomized trials for testing adaptive treatment strategies.

An adaptive treatment strategy (ATS) is an outcome-guided algorithm that allows personalized treatment of complex diseases based on patients' disease status and treatment history. Conditions such as AIDS, depression, and cancer usually require several stages of treatment because of the chronic, multifactorial nature of illness progression and management. Sequential multiple assignment randomized (SMAR) designs permit simultaneous inference about multiple ATSs, where patients are sequentially randomized to treatments at different stages depending upon response status. The purpose of the article is to develop a sample size formula to ensure adequate power for comparing two or more ATSs. Based on a Wald-type statistic for comparing multiple ATSs with a continuous endpoint, we develop a sample size formula and test it through simulation studies. We show via simulation that the proposed sample size formula maintains the nominal power. The proposed sample size formula is not applicable to designs with time-to-event endpoints but the formula will be useful for practitioners while designing SMAR trials to compare adaptive treatment strategies.

Course of cognitive impairment following attempted suicide in older adults.

OBJECTIVE: Cognitive impairment has been associated with late-life suicidal behavior. Without longitudinal data it is unclear whether these are transient features of a depressive state or stable impairments. We examined longitudinally the course of cognitive impairment in older adults with depression and a history of suicide attempt. METHODS: We investigated the persistence of cognitive impairment over time in 198 depressed older adults (age >60); 91 suicide attempters, 39 depressed individuals with suicidal ideation (ideators), and 68 non-suicidal depressed adults assessed over a 2-year period at four time points. We used linear mixed effects modeling to examine group differences in trajectories of cognitive decline over 2 years, using the Mini-Mental State Examination (MMSE), Mattis Dementia Rating Scale (DRS), and Executive Interview (EXIT). RESULTS: Over the 2-year period, suicide attempters performed significantly worse than both suicide ideators and non-suicidal depressed older adults on the MMSE (mean difference: from ideators: -0.88, p = 0.02; from non-suicidal depressed: -1.52, p < 0.01), while on the EXIT and DRS, suicide attempters performed significantly worse than non-suicidal depressed older adults (mean difference: in EXIT: -1.75, p = 0.01; in DRS: 3.04, p < 0.01; in MMSE: 1.15, p < 0.01). Cognitive impairment in suicide attempters partly resolved, as indicated by a group × time interaction on the DRS (p = 0.039), but not the EXIT (p = 0.58) or the MMSE (p = 0.08). CONCLUSIONS: Cognitive impairment in late-life suicidal behavior appears to involve both a stable and a state-related component.

A hidden Markov modeling approach combining objective measure of activity and subjective measure of self-reported sleep to estimate the sleep-wake cycle.

Characterizing the sleep-wake cycle in adolescents is an important prerequisite to better understand the association of abnormal sleep patterns with subsequent clinical and behavioral outcomes. The aim of this research was to develop hidden Markov models (HMM) that incorporate both objective (actigraphy) and subjective (sleep log) measures to estimate the sleep-wake cycle using data from the NEXT longitudinal study, a large population-based cohort study. The model was estimated with a negative binomial distribution for the activity counts (1-minute epochs) to account for overdispersion relative to a Poisson process. Furthermore, self-reported measures were dichotomized (for each one-minute interval) and subject to misclassification. We assumed that the unobserved sleep-wake cycle follows a two-state Markov chain with transitional probabilities varying according to a circadian rhythm. Maximum-likelihood estimation using a backward-forward algorithm was applied to fit the longitudinal data on a subject by subject basis. The algorithm was used to reconstruct the sleep-wake cycle from sequences of self-reported sleep and activity data. Furthermore, we conduct simulations to examine the properties of this approach under different observational patterns including both complete and partially observed measurements on each individual.

Summer activity patterns among teenage girls: harmonic shape invariant modeling to estimate circadian cycles.

BACKGROUND: Physical activity as measured by activity counts over short time intervals across a 24 h period are often used to assess circadian variation. We are interested in characterizing circadian patterns in activity among adolescents and examining how these patterns vary by obesity status. New statistical approaches are needed to examine how factors affect different features of the circadian pattern and to make appropriate covariate adjustments when the outcomes are longitudinal count data. METHODS: We develop a statistical model for longitudinal or repeated activity count data that is used to examine differences in the overall activity level, amplitude (defined as the difference between the lowest and highest activity level over a 24 hour period), and phase shift. Using seven days of continuous activity monitoring, we characterize the circadian patterns and compare them between obese and non-obese adolescent girls. RESULTS: We find a statistically significant phase delay in adolescent girls who were obese compared with their non-obese counterparts. After the appropriate adjustment for measured potential confounders, we did not find differences in mean activity level between the two groups. CONCLUSION: New statistical methodology was developed to identify a phase delay in obese compared with non-obese adolescents. This new approach for analyzing longitudinal circadian rhythm count data provides a useful statistical technique to add to the repertoire for those analyzing circadian rhythm data.

Response to antidepressant medications in late-life depression across the spectrum of cognitive functioning.

OBJECTIVE: Late-life depression frequently co-occurs with cognitive impairment. To inform clinical management of these conditions, we examined the hypotheses that, relative to cognitively normal elders meeting DSM-IV criteria for major depressive disorder, those with cognitive impairment would require greater intensity of pharmacotherapy to reach criteria for antidepressant response and would take longer to respond. METHOD: Using data from the MTLD-3 study, we conducted a series of secondary analyses examining the implications of cognitive impairment for short-term, open-trial pharmacotherapy of late-life depression (major depressive disorder in individuals 65 years and older). The treatment algorithm consisted of 3 steps: initial treatment with a selective serotonin reuptake inhibitor (SSRI), a switch to a serotonin-norepinephrine reuptake inhibitor (SNRI) if the patient did not respond, and addition of an atypical antipsychotic if the patient did not respond to the SNRI. The first subject entered the protocol in April 2004, and the last subject exited in September 2009. We examined data for participants who completed the acute phase of MTLD-3 as responders and received a cognitive diagnosis (N = 153) based on National Alzheimer's Coordinating Center (NACC) Uniform Data Set criteria. We divided participants into 3 groups on the basis of NACC cognitive diagnosis: no cognitive disorder (n = 74), mild cognitive impairment (n = 60), and dementia (n = 19). For each group, we calculated the proportion of participants requiring first- (SSRI), second- (SNRI), or third-step (add-on atypical antipsychotic) treatment to meet criteria for response (17-Item Hamilton Depression Rating Scale score ≤ 10 for 3 consecutive weeks). We compared time to response across groups and correlates of nonresponse. RESULTS: The 3 groups did not differ in intensity of pharmacotherapy (P = .68) or time to response (P = .84). Nonresponse was more strongly correlated with longer major depressive episode duration (P = .0015), presence of recurrent depression (P = .002), and younger current age (P = .047), rather than cognitive status (P = .61). CONCLUSIONS: Cognitive status does not appear to impact short-term pharmacotherapy response variability in individuals whose depression responds to treatment with open-trial antidepressants delivered in a supportive, university-based medication clinic.

The SUCCESS program for smoking cessation for pregnant women.

The Association of Women's Health, Obstetric, and Neonatal Nurses (AWHONN) developed an evidence-based practice program, Setting Universal Cessation Counseling Education and Screening Standards (SUCCESS), to educate nurses and other health care practitioners about smoking cessation interventions, increase the number of practitioners providing smoking cessation interventions, and deliver a smoking cessation intervention program to childbearing women who smoke. The development, implementation, and outcomes of the SUCCESS program are described.