Power Analysis for the Likelihood-Ratio Test in Latent Markov Models: Shortcutting the Bootstrap p-Value-Based Method.

The latent Markov (LM) model is a popular method for identifying distinct unobserved states and transitions between these states over time in longitudinally observed responses. The bootstrap likelihood-ratio (BLR) test yields the most rigorous test for determining the number of latent states, yet little is known about power analysis for this test. Power could be computed as the proportion of the bootstrap p values (PBP) for which the null hypothesis is rejected. This requires performing the full bootstrap procedure for a large number of samples generated from the model under the alternative hypothesis, which is computationally infeasible in most situations. This article presents a computationally feasible shortcut method for power computation for the BLR test. The shortcut method involves the following simple steps: (1) obtaining the parameters of the model under the null hypothesis, (2) constructing the empirical distributions of the likelihood ratio under the null and alternative hypotheses via Monte Carlo simulations, and (3) using these empirical distributions to compute the power. We evaluate the performance of the shortcut method by comparing it to the PBP method and, moreover, show how the shortcut method can be used for sample-size determination.

Pregnancy rate after vasectomy reversal in a contemporary series: influence of smoking, semen quality and post-surgical use of assisted reproductive techniques.

UNLABELLED: Study Type - Outcomes (cohort series). Level of Evidence 2b What's known on the subject? and What does the study add? Microsurgical vasectomy reversal is an effective and cost-effective method of reinstating fertility in a man who has previously had a vasectomy. The current literature indicates that the success rate (i.e. potency and pregnancy rates) are dependent primarily on the time elapsed since vasectomy and the age of the female partner. Using a multivariate Cox regression model, evaluation of the influence of preoperative data (including smoking) and semen parameters indicates a significant influence of post-surgical sperm motility only, on time to first pregnancy. The use of assisted reproductive techniques, when natural pregnancy failed, was successful in ≈50% of couples who attempted this procedure and accounted for an absolute increase in pregnancy rate of 14%. OBJECTIVE: • To determine the influence of smoking, postoperative semen characteristics and the use of an assisted reproductive technique (ART) on pregnancy rate in a contemporary series of men undergoing vasectomy reversal. PATIENTS AND METHODS: • Between January 2002 and January 2009, 186 vasectomy reversals were performed. Of the 171 patients who could be contacted for follow-up, 162 attempted pregnancy and constitute the study group. • Semen analysis was performed 3 months after the procedure and at subsequent 3-monthly intervals. • Patient characteristics and surgical information were obtained from a computerized database, and follow-up data were collected by telephone interview. • A multivariate Cox regression model was used to discern possible prognosticators with respect to pregnancy outcome. RESULTS: • The overall patency rate was 91.4%, with a natural pregnancy rate of 44.4% and a subsequent 14.2% of patients conceiving using a ARTs resulting in a total pregnancy rate of 58.6%. Multiple pregnancies were obtained by 20.4% of couples. • Smoking of the male or female partner did not influence the probability of conception. • In a multivariate model that included, among other factors, time since vasectomy, female age and semen characteristics, only sperm motility was significantly related to natural pregnancy outcome. • The probability of obtaining a natural pregnancy within 2 years after surgery is 53% for men with sperm motility >20% (WHO a+b) compared to 19% for men with sperm motility <5% (P= 0.003). CONCLUSIONS: • A clear and significant association between sperm motility and the probability of conception was found, whereas smoking, female age and time since vasectomy appeared to have no influence on pregnancy outcome in this patient cohort. • The use of ARTs accounted for an absolute increase in pregnancy rate of 14.2%.

Prognostic importance of distressed (Type D) personality and shocks in patients with an implantable cardioverter defibrillator.

BACKGROUND: Clinical trials have shown the benefit of implantable cardioverter defibrillator (ICD) treatment. In this study, we examined the importance of chronic psychological distress and device shocks among ICD patients seen in clinical practice. METHODS: This prospective follow-up study included 589 patients with an ICD (mean age=62.6 ± 10.1 years; 81% men). At baseline, vulnerability for chronic psychological distress was measured by the 14-item Type D (distressed) personality scale. Cox regression models of all-cause and cardiac death were used to examine the importance of risk markers. RESULTS: After a median follow-up of 3.2 years, 94 patients (16%) had died (67 cardiac death), 61 patients (10%) had experienced an appropriate shock and 28 (5%) an inappropriate shock. Inappropriate shocks were not associated with all-cause (p=0.52) or cardiac (p=0.99) death. However, appropriate shocks (HR=2.60, 95% CI 1.47-5.58, p=0.001) and Type D personality (HR=1.85, 95% CI 1.12-3.05, p=0.015) were independent predictors of all-cause mortality, adjusting for age, sex, left ventricular ejection fraction, cardiac resynchronization therapy (CRT), secondary indication, history of coronary artery disease, medication and diabetes. Type D personality and appropriate shocks also independently predicted an increased risk of cardiac death. Other independent predictors of poor prognosis were older age, treatment with CRT and diabetes. CONCLUSION: Vulnerability to chronic psychological distress, as defined by the Type D construct, had incremental prognostic value above and beyond clinical characteristics and ICD shocks. Physicians should be aware of chronic psychological distress and device shocks as markers of an increased mortality risk in ICD patients seen in daily clinical practice.

Emotional distress, positive affect, and mortality in patients with an implantable cardioverter defibrillator.

BACKGROUND: Little is known about the relationship between emotional distress and mortality in patients with an implantable cardioverter defibrillator (ICD). Our aim was to examine the predictive value of general negative and positive affect, and depressive symptoms (including its components somatic symptoms and cognitive-affective symptoms) for mortality. METHODS: ICD patients (N=591, 81% male, mean age=62.7 ± 10.1 years) completed the Global Mood Scale to measure the independent dimensions negative and positive mood, and the Beck Depression Inventory to measure depressive symptoms. Covariates consisted of demographic and clinical variables. RESULTS: During the median follow-up of 3.2 years, 96 (16.2%) patients died. After controlling for covariates, negative affect was significantly related to all-cause mortality (HR=1.034, p=0.002), whereas positive affect was not (HR=1.007, p=0.61). Depressive symptoms were also independently associated with an increased mortality risk (HR=1.031, p=0.030) and somatic symptoms of depression in particular (HR=1.130, p=0.003), but cognitive-affective symptoms were not associated with mortality (HR=0.968, p=0.29). When entering both significant psychological predictors in a covariate-adjusted model, negative mood remained significant (HR=1.039, p=0.009), but somatic symptoms of depression did not (HR=0.988, p=0.78). Similar results were found for cardiac-related death. Of covariates, increased age, CRT, appropriate shocks were positively related to death. CONCLUSIONS: Negative affect in general was related to mortality, but reduced positive affect was not. Depression, particularly its somatic symptoms, was also related to mortality, while cognitive-affective symptoms were not. Future research may further focus on the differential predictive value of emotional distress factors, as well as on mechanisms that relate emotional distress factors to mortality.

Age-related differences in the effect of psychological distress on mortality: Type D personality in younger versus older patients with cardiac arrhythmias.

BACKGROUND: Mixed findings in biobehavioral research on heart disease may partly be attributed to age-related differences in the prognostic value of psychological distress. This study sought to test the hypothesis that Type D (distressed) personality contributes to an increased mortality risk following implantable cardioverter defibrillator (ICD) treatment in younger patients but not in older patients. METHODS: The Type D Scale (DS14) was used to assess general psychological distress in 455 younger (≤70 y, m = 59.1) and 134 older (>70 y, m = 74.3) ICD patients. End points were all-cause mortality and cardiac death after a median follow-up of 3.2 years. RESULTS: Older patients had more advanced heart failure and a higher mortality rate (n = 34/25%) than younger patients (n = 60/13%), P = 0.001. Cardiac resynchronization therapy (CRT), but not Type D personality, was associated with increased mortality in older patients. Among younger patients, however, Type D personality was associated with an adjusted hazard ratio = 1.91 (95% CI 1.09-3.34) and 2.26 (95% CI 1.16-4.41) for all-cause and cardiac mortality; other predictors were increasing age, CRT, appropriate shocks, ACE-inhibitors, and smoking. CONCLUSION: Type D personality was independently associated with all-cause and cardiac mortality in younger ICD patients but not in older patients. Cardiovascular research needs to further explore age-related differences in psychosocial risk.

Shock and patient preimplantation type D personality are associated with poor health status in patients with implantable cardioverter-defibrillator.

BACKGROUND: Implantable cardioverter-defibrillator (ICD) shock is a critical event to patients associated with well-being after implantation, although other factors may play an equally important role. We compared the association of shock and the patient's preimplantation personality with health status, using a prospective study design. METHODS AND RESULTS: Consecutively implanted ICD patients (n=383; 79% men) completed the Type D Scale at baseline and the Short-Form Health Survey 36 (SF-36) at baseline and 3, 6, and 12 months. Of all patients, 23.5% had a Type D personality and 13.8% received a shock during follow-up. Shocked patients reported significantly poorer health status, as did Type D patients. Health status patterns were poorest in patients with combined Type D personality and shock during follow-up. Shock during follow-up was a significant independent associate of poorer health status for 4 of 8 subscales of the SF-36 and the Mental Component Summary (all P<.05), with shocked patients scoring between 2.60 to 13.30 points lower than nonshocked patients. Type D personality was an independent associate of poor postimplantation health status for 6 of 8 of the SF-36 subscales and the Mental Component Summary, with Type D patients scoring between 2.12 to 8.02 points lower, adjusting for demographic and clinical characteristics. CONCLUSIONS: ICD shock and the patient's preimplantation personality disposition were equally important associates of health status 12 months after implantation. Identification of the patient's personality profile before ICD implantation may help identify subsets of patients who may need additional care, for example, with a psychosocial component.

Measuring chronic care management experience of patients with diabetes: PACIC and PACIC+ validation.

BACKGROUND: The patient assessment of chronic illness care (PACIC) is a promising instrument to evaluate the chronic care experiences of patients, yet additional validation is needed to improve its usefulness. METHODS: A total of 1941 patients with diabetes completed the questionnaire. Reliability coefficients and factor analyses were used to psychometrically test the PACIC and PACIC+ (i.e. PACIC extended with six additional multidisciplinary team functioning items to improve content validity). Intra-class correlations were computed to identify the extent to which variation in scores can be attributed to GP practices. RESULTS: The PACIC and PACIC+ showed a good psychometric quality (Cronbach's alpha's >0.9). Explorative factor analyses showed inconclusive results. Confirmative factor analysis showed that none of the factor structures had an acceptable fit (RMSEA>0.10). In addition, 5.1 to 5.4% of the total variation was identified at the GP practice level. CONCLUSION: The PACIC and PACIC+ are reliable instruments to measure the chronic care management experiences of patients. The PACIC+ is preferred because it also includes multidisciplinary coordination and cooperation-one of the central pillars of chronic care management-with good psychometric quality. Previously identified subscales should be used with caution. Both PACIC instruments are useful in identifying GP practice variation.

Too many cohorts and repeated measurements are a waste of resources.

OBJECTIVE: Researchers in Health Sciences and Medicine often use cohort designs to study treatment effects and changes of outcome variables over time period. The costs of these studies can be reduced by choosing an optimal number of repeated measurements over time and by selecting cohorts of subjects more efficiently with optimal design procedures. The objective of this study is to provide evidence on how to design large-scale cohort studies with budget constraints as efficiently as possible. STUDY DESIGN AND SETTING: A linear cost function for repeated measurements is proposed, and this cost function is used in the optimization procedure. For a given budget/cost, different designs for linear mixed-effects models are compared by means of their efficiency. RESULTS: We found that adding more repeated measures is only beneficiary if the costs of selecting and measuring a new subject are much higher than the costs of obtaining an additional measurement for an already recruited subject. However, this gain in efficiency and power is not very large. CONCLUSION: Adding more cohorts or repeated measurements do not necessarily lead to a gain in efficiency of the estimated model parameters. A general guideline for the optimal choice of a cohort design in practice is required and we offer this guideline.

Interactive computer program for optimal designs of longitudinal cohort studies.

Many large scale longitudinal cohort studies have been carried out or are ongoing in different fields of science. Such studies need a careful planning to obtain the desired quality of results with the available resources. In the past, a number of researches have been performed on optimal designs for longitudinal studies. However, there was no computer program yet available to help researchers to plan their longitudinal cohort design in an optimal way. A new interactive computer program for the optimization of designs of longitudinal cohort studies is therefore presented. The computer program helps users to identify the optimal cohort design with an optimal number of repeated measurements per subject and an optimal allocations of time points within a given study period. Further, users can compute the loss in relative efficiencies of any other alternative design compared to the optimal one. The computer program is described and illustrated using a practical example.

D-optimal cohort designs for linear mixed-effects models.

The D-optimality criterion is used to construct optimal designs for different numbers of independent cohorts, which constitute a number of repeated measurements per subject over time. A cost function for longitudinal data is proposed, and the optimality criterion is optimized taking into account the cost of the study. First, an optimal number of design points for a given number of cohorts and cost was identified. Then, an optimal number of cohorts is identified by comparing the relative efficiencies (REs). A numerical study shows that for models describing the trend of a continuous outcome over time by polynomials, the most efficient number of repeated measurements is equal to the sum of the total number of cohorts and the degree of the polynomial in the model. REs of a purely longitudinal cohort design with only one cohort, and mixed longitudinal and cross-sectional cohort designs with more cohorts are compared. The results show that a purely longitudinal cohort design with only one cohort of subjects measured at the optimal time points is the most efficient design. The findings in this paper show that one can obtain a highly efficient design for parameter estimation with only a few repeated measurements. The results of this study will reduce the cost of data collection and ease the logistical burdens in cohort studies.