Longitudinal Data Analysis for Discrete and Continuous Outcomes

Zeger, Scott L.; Liang, Kung‐Yee

doi:10.2307/2531248

Cited by 7,070 publications

(4,372 citation statements)

References 23 publications

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“…Additionally, Generalized Estimating Equation (GEE) models (Zeger & Liang, 1986;Twisk, 2004) were used to estimate the mean differences between treatment groups and the confidence intervals (CIs) at each assessment point for both primary and secondary continuous outcomes; odds ratios with 95% CIs were given for dichotomous outcomes and differences in means for continuous outcomes. Since our GEE models yields odds ratios as the effect measure instead of risk ratios, effect-sizes are not presented.…”

Section: Resultsmentioning

confidence: 99%

The clinical effectiveness of concise cognitive behavioral therapy with or without pharmacotherapy for depressive and anxiety disorders; a pragmatic randomized controlled equivalence trial in clinical practice

Meuldijk

Carlier

Vliet

et al. 2016

Contemporary Clinical Trials

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. (2016). The clinical effectiveness of concise cognitive behavioral therapy with or without pharmacotherapy for depressive and anxiety disorders; a pragmatic randomized controlled equivalence trial in clinical practice. Contemporary Clinical Trials, 47 131-138. See next page for additional authorsThe clinical effectiveness of concise cognitive behavioral therapy with or without pharmacotherapy for depressive and anxiety disorders; a pragmatic randomized controlled equivalence trial in clinical practice Abstract Background: Depressive and anxiety disorders contribute to a high disease burden. This paper investigates whether concise formats of cognitive behavioral-and/or pharmacotherapy are equivalent with longer standard care in the treatment of depressive and/or anxiety disorders in secondary mental health care. Methods: A pragmatic randomized controlled equivalence trial was conducted at five Dutch outpatient Mental Healthcare Centers (MHCs) of the Regional Mental Health Provider (RMHP) 'Rivierduinen'. Patients (aged 18-65 years) with a mild to moderate anxiety and/or depressive disorder, were randomly allocated to concise or standard care. Data were collected at baseline, 3, 6 and 12 months by Routine Outcome Monitoring (ROM). Primary outcomes were the Brief Symptom Inventory (BSI) and the Web Screening Questionnaire (WSQ). We used Generalized Estimating Equations (GEE) to assess outcomes. Results: Between March 2010 and December 2012, 182 patients, were enrolled (n = 89 standard care; n = 93 concise care). Both intention-to-treat and per-protocol analyses demonstrated equivalence of concise care and standard care at all time points. Severity of illness reduced, and both treatments improved patient's general health status and subdomains of quality of life. Moreover, in concise care, the beneficial effects started earlier. Discussion: Concise care has the potential to be a feasible and promising alternative to longer standard secondary mental health care in the treatment of outpatients with a mild to moderate depressive and/or anxiety disorder. For future research, we recommend adhering more strictly to the concise treatment protocols to further explore the beneficial effects of the concise treatment. Moreover, in concise care, the beneficial effects started earlier.

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Section: Resultsmentioning

confidence: 99%

The clinical effectiveness of concise cognitive behavioral therapy with or without pharmacotherapy for depressive and anxiety disorders; a pragmatic randomized controlled equivalence trial in clinical practice

Meuldijk

Carlier

Vliet

et al. 2016

Contemporary Clinical Trials

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“…To identify multilevel correlates of medication adherence, we first predicted nonadherence via simple logistic regression analyses, invoking generalized estimating equations to account for possible within‐center subject correlations 40. Variables whose odds ratios (ORs) suggested associations (ie confidence intervals [CIs] not including 1.00) were subjected to multiple logistic regression analysis.…”

Section: Methodsmentioning

confidence: 99%

Multilevel factors are associated with immunosuppressant nonadherence in heart transplant recipients: The international BRIGHT study

Denhaerynck

Berben

Dobbels

et al. 2018

American Journal of Transplantation

100

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Factors at the level of family/healthcare worker, organization, and system are neglected in medication nonadherence research in heart transplantation (HTx). The 4‐continent, 11‐country cross‐sectional Building Research Initiative Group: Chronic Illness Management and Adherence in Transplantation (BRIGHT) study used multistaged sampling to examine 36 HTx centers, including 36 HTx directors, 100 clinicians, and 1397 patients. Nonadherence to immunosuppressants—defined as any deviation in taking or timing adherence and/or dose reduction—was assessed using the Basel Assessment of Adherence to Immunosuppressive Medications Scale© (BAASIS ©) interview. Guided by the Integrative Model of Behavioral Prediction and Bronfenbrenner's ecological model, we analyzed factors at these multiple levels using sequential logistic regression analysis (6 blocks). The nonadherence prevalence was 34.1%. Six multilevel factors were associated independently (either positively or negatively) with nonadherence: patient level: barriers to taking immunosuppressants (odds ratio [OR]: 11.48); smoking (OR: 2.19); family/healthcare provider level: frequency of having someone to help patients read health‐related materials (OR: 0.85); organization level: clinicians reporting nonadherent patients were targeted with adherence interventions (OR: 0.66); pickup of medications at physician's office (OR: 2.31); and policy level: monthly out‐of‐pocket costs for medication (OR: 1.16). Factors associated with nonadherence are evident at multiple levels. Improving medication nonadherence requires addressing not only the patient, but also family/healthcare provider, organization, and policy levels.

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“…The generalized estimating equation method with an exchangeable working correlation structure was used to account for within‐site clustering of patients (ie, within‐site correlation for response) 11. Multivariable logistic regression models were used to estimate the marginal effect of FI separately by MI type (NSTEMI and STEMI) after adjusting for age, sex, and covariates previously identified as significantly associated with in‐hospital mortality among patients with MI 12.…”

Section: Methodsmentioning

confidence: 99%

Frailty and Outcomes After Myocardial Infarction: Insights From the CONCORDANCE Registry

Patel

Goodman

Yan

et al. 2018

JAHA

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BackgroundLittle is known about the prognostic implications of frailty, a state of susceptibility to stressors and poor recovery to homeostasis in older people, after myocardial infarction (MI).Methods and ResultsWe studied 3944 MI patients aged ≥65 years treated at 41 Australian hospitals from 2009 to 2016 in the CONCORDANCE (Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events) registry. Frailty index (FI) was determined using the health deficit accumulation method. All‐cause and cardiac‐specific mortality at 6 months were compared between frail (FI >0.25) and nonfrail (FI ≤0.25) patients. Among 1275 patients with ST‐segment–elevation MI (STEMI), 192 (15%) were frail, and among 2669 non‐STEMI (NSTEMI) patients, 902 (34%) were frail. Compared with nonfrail counterparts, frail STEMI patients received 30% less reperfusion therapy and 22% less revascularization during index hospitalization; frail NSTEMI patients received 30% less diagnostic angiography and 39% less revascularization. Unadjusted 6‐month all‐cause mortality (STEMI: 13% versus 3%; NSTEMI: 13% versus 4%) and cardiac‐specific mortality (STEMI: 6% versus 1.4%, NSTEMI: 3.2% versus 1.2%) were higher among frail patients. After adjustment for known prognosticators, FI was significantly associated with higher 6‐month all‐cause (STEMI: odds ratio: 1.74 per 0.1 FI [95% confidence interval, 1.37–2.22], P<0.001; NSTEMI: odds ratio: 1.62 per 0.1 FI [95% confidence interval, 1.40–1.87], P<0.001) but not cardiac‐specific mortality (STEMI: P=0.99; NSTEMI: P=0.93).ConclusionsFrail patients receive lower rates of invasive cardiac care during MI hospitalization. Increased frailty was independently associated with increased postdischarge all‐cause mortality but not cardiac‐specific mortality. These findings inform identification of frailty during MI hospitalization as a potential opportunity to address competing risks for mortality in this high‐risk population.

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Longitudinal Data Analysis for Discrete and Continuous Outcomes

Cited by 7,070 publications

References 23 publications

The clinical effectiveness of concise cognitive behavioral therapy with or without pharmacotherapy for depressive and anxiety disorders; a pragmatic randomized controlled equivalence trial in clinical practice

The clinical effectiveness of concise cognitive behavioral therapy with or without pharmacotherapy for depressive and anxiety disorders; a pragmatic randomized controlled equivalence trial in clinical practice

Multilevel factors are associated with immunosuppressant nonadherence in heart transplant recipients: The international BRIGHT study

Frailty and Outcomes After Myocardial Infarction: Insights From the CONCORDANCE Registry

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