scholarly journals Growth mixture models: a case example of the longitudinal analysis of patient‐reported outcomes data captured by a clinical registry

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jae-Yung Kwon ◽  
Richard Sawatzky ◽  
Jennifer Baumbusch ◽  
Sandra Lauck ◽  
Pamela A. Ratner
Keyword(s):  
Atrial Fibrillation ◽  
Longitudinal Analysis ◽  
Model Building ◽  
Population Based ◽  
Patient Reported Outcome ◽  
Latent Classes ◽  
Clinical Registry ◽  
Growth Mixture ◽  
Growth Mixture Modelling ◽  
Patient Reported

Abstract Background An assumption in many analyses of longitudinal patient-reported outcome (PRO) data is that there is a single population following a single health trajectory. One approach that may help researchers move beyond this traditional assumption, with its inherent limitations, is growth mixture modelling (GMM), which can identify and assess multiple unobserved trajectories of patients’ health outcomes. We describe the process that was undertaken for a GMM analysis of longitudinal PRO data captured by a clinical registry for outpatients with atrial fibrillation (AF). Methods This expository paper describes the modelling approach and some methodological issues that require particular attention, including (a) determining the metric of time, (b) specifying the GMMs, and (c) including predictors of membership in the identified latent classes (groups or subtypes of patients with distinct trajectories). An example is provided of a longitudinal analysis of PRO data (patients’ responses to the Atrial Fibrillation Effect on QualiTy-of-Life (AFEQT) Questionnaire) collected between 2008 and 2016 for a population-based cardiac registry and deterministically linked with administrative health data. Results In determining the metric of time, multiple processes were required to ensure that “time” accounted for both the frequency and timing of the measurement occurrences in light of the variability in both the number of measures taken and the intervals between those measures. In specifying the GMM, convergence issues, a common problem that results in unreliable model estimates, required constrained parameter exploration techniques. For the identification of predictors of the latent classes, the 3-step (stepwise) approach was selected such that the addition of predictor variables did not change class membership itself. Conclusions GMM can be a valuable tool for classifying multiple unique PRO trajectories that have previously been unobserved in real-world applications; however, their use requires substantial transparency regarding the processes underlying model building as they can directly affect the results and therefore their interpretation.

scholarly journals O17 Modelling longitudinal patient-reported outcome measures in JDM

Rheumatology ◽  
2020 ◽  
Vol 59 (Supplement_2) ◽  
Author(s):  
Paris J Baptiste ◽  
Lucy R Wedderburn ◽  
Claire T Deakin ◽  
Bianca L. De Stavola ◽  
Edmund Njeru Njagi ◽  
...  
Keyword(s):  
Disease Activity ◽  
Mixture Models ◽  
Patient Reported Outcome ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Latent Classes ◽  
Growth Mixture Models ◽  
Growth Mixture ◽  
Gastrointestinal Problems ◽  
Patient Reported

Abstract Background Juvenile dermatomyositis (JDM) is a rare autoimmune disease known to primarily cause rash and muscle weakness. The evolution of the disease is still unclear, in particular disease activity based on patient-reported outcomes. A cohort of 493 patients with 3,625 visits up to 5 years since diagnosis was used to explore disease trajectories based on the patient-reported outcome, patient/parent visual analogue scale (VAS), completed by the appropriate person depending on the child’s age. Age at diagnosis, sex, ethnicity and baseline physician's global assessment (PGA) measurements were considered as predictors of disease activity. In addition to this 8 baseline clinical/medical history variables were also considered as potentially predictive: ulcerations, Gottron’s papules, myalgia, fever, fatigue, dysphagia, respiration and gastrointestinal problems. Methods A mixed effects model was fitted to the data to identify the strongest predictors of disease activity accounting for correlations of patient/parent VAS measurements within patients. Growth mixture models were used to identify subgroups of patients that shared similar trajectories (latent classes) and logistic regression was used to predict the probability of belonging to the subgroup that had more severe disease activity. The identified latent classes of disease activity, based on the patient-reported outcome of patient/parent VAS, were compared with previously identified latent classes derived from PGA as the outcome measure. Results The results from fitting a mixed effects model showed that disease activity had a cubic relationship with time since diagnosis. Being non-white and having a history of myalgia and gastrointestinal problems was shown to predict higher disease activity across the whole follow-up time. The results from fitting growth mixture models led to identifying two classes: the first showed an improvement in condition after the first year, which correlated with results from the mixed effects model, the second, more severe class, was on average higher and showed little improvement across the 5 years. In addition to the predictors identified in the mixed effects model, skin ulceration and older than the mean age (8.3 years) at diagnosis were shown to be associated with the probability of belonging to the more severe class. Conclusion Comparing these results to those previously found in analyses of PGA data collected on the same patients, we found that the patterns of activity were similar although on average higher, indicating that reports of disease activity by patients/parents were worse than those collected from physicians. This could be due to factors influencing patient’s experiences that are not measured by physicians. Discussions with clinicians suggest that this could be due to symptoms that are difficult to measure and that are unaffected by treatment, for example, symptoms causing damage. These are often overlooked in physician’s assessments, despite being an important factor for patients. Disclosures P.J. Baptiste None. L.R. Wedderburn None. C.T. Deakin None. B.L. De Stavola None. E. Njagi None.

scholarly journals Antiarrhythmic drug therapy after catheter ablation for atrial fibrillation has no impact on recurrences, cardiovascular events and mortality – insights from the German Ablation Registry

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
R Schleberger ◽  
A Metzner ◽  
K H Kuck ◽  
D Andresen ◽  
S Willems ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Drug Therapy ◽  
Catheter Ablation ◽  
Antiarrhythmic Drug ◽  
Treatment Satisfaction ◽  
Cardiovascular Events ◽  
Patient Reported Outcome ◽  
Antiarrhythmic Drug Therapy ◽  
Funding Sources ◽  
Patient Reported

Abstract Background Data on the optimal treatment strategy for antiarrhythmic drug therapy (AAD) after atrial fibrillation (AF) catheter ablation are inconsistent. While AAD potentially stabilizes sinus rhythm, it also increases the patients' treatment burden. Methods Patients from the prospective German Ablation Registry (n=3275) discharged with or without AAD after AF catheter ablation were compared regarding long-term success, cardiovascular events and patient reported outcome. Results In patients with paroxysmal AF (n=2138) recurrence and rehospitalization rates did not differ when discharged with (n=1051) or without (n=1087) AAD (recurrence: adjusted odds ratio (OR) 1.13, 95% confidence interval (CI) [0.95–1.35]; rehospitalization: OR 1.08, 95% CI [0.90–1.30]). The reablation rate was higher and reduced treatment satisfaction was reported more often in those discharged with AAD (reablation: OR 1.30, 95% CI [1.05–1.61]; reduced treatment satisfaction: OR 1.76, 95% CI [1.20–2.58]). Similar rates of recurrences, rehospitalisations, reablations and treatment satisfaction were found in patients with persistent AF (n=1137) discharged with (n=641) or without (n=496) AAD (recurrence: OR 1.22, 95% CI [0.95–1.56]; rehospitalization: OR 1.16, 95% CI [0.90–1.50]; reablation: OR 1.21, 95% CI [0.91–1.61]; treatment satisfaction: OR 1.24, 95% CI [0.74–2.08]). The incidence of cardiovascular events and mortality did not differ at follow-up in paroxysmal and persistent AF patients discharged with or without AAD. Conclusion The rates of recurrences, cardiovascular events and mortality did not differ between patients discharged with or without AAD after AF catheter ablation. However, AAD should be considered carefully in patients with paroxysmal AF, in whom it was associated with a higher reablation rate and reduced treatment satisfaction. FUNDunding Acknowledgement Type of funding sources: None.

scholarly journals Minimal important difference and patient acceptable symptom state for PFDI-20 and POPDI-6 in POP surgery

2020 ◽  
Author(s):  
Päivi K. Karjalainen ◽  
Nina K. Mattsson ◽  
Jyrki T. Jalkanen ◽  
Kari Nieminen ◽  
Anna-Maija Tolppanen
Keyword(s):  
Pelvic Organ Prolapse ◽  
Roc Curve ◽  
Minimal Important Difference ◽  
Patient Reported Outcome Measures ◽  
Pelvic Organ ◽  
Population Based ◽  
Patient Reported Outcome ◽  
Pop Surgery ◽  
Patient Reported ◽  
Patient Acceptable Symptom State

Abstract Introduction and hypothesis Patient-reported outcome measures are fundamental tools when assessing effectiveness of treatments. The challenge lies in the interpretation: which magnitude of change in score is meaningful for the patients? The minimal important difference (MID) is defined as the smallest difference in score that patients perceive as important. The Patient Acceptable Symptom State (PASS) represents the value of score beyond which patients consider themselves well. We aimed to determine the MID and PASS for Pelvic Floor Distress Inventory-20 (PFDI-20) and Pelvic Organ Prolapse Distress Inventory-6 (POPDI-6) in pelvic organ prolapse (POP) surgery. Methods We used data from 2704 POP surgeries from a prospective, population-based cohort. MID was determined with three anchor-based and one distribution-based method. PASS was defined using two different methods. Medians of the estimates were identified. Results The MID estimates with (1) mean change, (2) receiver-operating characteristic (ROC) curve, (3) 75th percentile, and (4) distribution-based method varied between 22.9–25.0 (median 24.2) points for PFDI-20 and 9.0–12.5 (median 11.3) for POPDI-6. The PASS cutoffs with (1) 75th percentile and (2) ROC curve method varied between 57.7–62.5 (median 60.0) for PFDI-20 and 16.7–17.7 (median 17.2) for POPDI-6. Conclusion A mean difference of 24 points in the PFDI-20 or 11 points in the POPDI-6 can be used as a clinically relevant difference between groups. Postoperative scores ≤ 60 for PFDI-20 and ≤ 17 for POPDI-6 signify acceptable symptom state.

scholarly journals Review of the 2020 ESC Guidelines for the Diagnosis and Management of Atrial Fibrillation—What Has Changed and How Does This Affect Daily Practice

2021 ◽  
Vol 10 (17) ◽  
pp. 3922
Author(s):  
Johanna B. Tonko ◽  
Matthew J. Wright
Keyword(s):  
Atrial Fibrillation ◽  
Catheter Ablation ◽  
Health Care Cost ◽  
Daily Practice ◽  
Patient Reported Outcome ◽  
Systematic Assessment ◽  
Optimal Outcomes ◽  
Patient Reported ◽  
High Prevalence ◽  
Patient Values

The high prevalence of atrial fibrillation (AF) in the overall population and its association with substantial morbidity, increased mortality and health care cost has instigated significant basic and clinical research efforts over recent years. The publication of multiple new high-quality randomized multi-center trials in the area of AF management and the rapidly evolving technological progress in terms of diagnostic possibilities and catheter ablation in recent years demanded a revision of the previous ESC AF Guidelines from 2016. The 2020 guidelines provide up-to-date, evidence-based guidance for the management of AF. One of the most important innovations is the presentation of a new concept for structural characterization of AF (the “4S AF scheme”) replacing the traditional classification based on its temporal pattern alone (paroxysmal-persistent-permanent). The 4S-AF-scheme highlights the importance of systematic assessment of stroke risk, severity of symptoms, total AF burden and underlying substrate as the foundation for effective and individualized AF treatment for each and every patient. Further novelties relate to the presentation of an easy and intuitive management pathway (“ABC pathway”) and strengthening the recommendations for early rhythm control, in particular the role of first line catheter ablation in heart failure. Another core component of the guidelines is the focus on patient involvement to achieve optimal outcomes. Patient education, shared decision making and incorporation of patient values and patient reported outcome of treatment interventions as well as integrated care by a multidisciplinary team all have a central role in the proposed management pathway for AF.

scholarly journals Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry

2018 ◽  
Vol 27 (12) ◽  
pp. 3313-3324 ◽  
Author(s):  
Belle H. de Rooij ◽  
Nicole P. M. Ezendam ◽  
Floortje Mols ◽  
Pauline A. J. Vissers ◽  
Melissa S. Y. Thong ◽  
...  
Keyword(s):  
Cancer Survivors ◽  
Population Based ◽  
Patient Reported Outcome ◽  
Outcome Studies ◽  
Lower Survival ◽  
Patient Reported

scholarly journals Axial growth and refractive change in white European children and young adults: predictive factors for myopia

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sara McCullough ◽  
Gary Adamson ◽  
Karen M. M. Breslin ◽  
Julie F. McClelland ◽  
Lesley Doyle ◽  
...  
Keyword(s):  
Predictive Factors ◽  
Population Based ◽  
Growth Trajectories ◽  
Latent Growth ◽  
Growth Mixture ◽  
Growth Mixture Modelling ◽  
Spherical Equivalent Refraction ◽  
Refractive Change ◽  
Children And Young Adults ◽  
Axial Growth

Abstract This report describes development of spherical equivalent refraction (SER) and axial length (AL) in two population-based cohorts of white, European children. Predictive factors for myopic growth were explored. Participants were aged 6–7- (n = 390) and 12–13-years (n = 657) at baseline. SER and AL were assessed at baseline and 3, 6 and 9 years prospectively. Between 6 and 16 years: latent growth mixture modelling identified four SER classes (Persistent Emmetropes-PEMM, Persistent Moderate Hyperopes-PMHYP, Persistent High Hyperopes-PHHYP and Emerging Myopes-EMYO) as optimal to characterise refractive progression and two classes to characterise AL. Between 12 and 22-years: five SER classes (PHHYP, PMHYP, PEMM, Low Progressing Myopes-LPMYO and High Progressing Myopes-HPMYO) and four AL classes were identified. EMYO had significantly longer baseline AL (≥ 23.19 mm) (OR 2.5, CI 1.05–5.97) and at least one myopic parent (OR 6.28, CI 1.01–38.93). More myopic SER at 6–7 years (≤ + 0.19D) signalled risk for earlier myopia onset by 10-years in comparison to baseline SER of those who became myopic by 13 or 16 years (p ≤ 0.02). SER and AL progressed more slowly in myopes aged 12–22-years (− 0.16D, 0.15 mm) compared to 6–16-years (− 0.41D, 0.30 mm). These growth trajectories and risk criteria allow prediction of abnormal myopigenic growth and constitute an important resource for developing and testing anti-myopia interventions.

scholarly journals Education and Successful Aging Trajectories: A Longitudinal Population-Based Latent Variable Modelling Analysis

2017 ◽  
Vol 36 (4) ◽  
pp. 427-434 ◽  
Author(s):  
Theodore D. Cosco ◽  
Blossom C.M. Stephan ◽  
Carol Brayne ◽  
Graciela Muniz ◽  
Keyword(s):  
Successful Aging ◽  
Latent Variable ◽  
Occupational Status ◽  
Later Life ◽  
Population Based ◽  
Logistic Regression Models ◽  
Growth Mixture ◽  
Growth Mixture Modelling ◽  
Higher Educational Attainment ◽  
Life Education

ABSTRACTAs the population ages, interest is increasing in studying aging well. However, more refined means of examining predictors of biopsychosocial conceptualizations of successful aging (SA) are required. Existing evidence of the relationship between early-life education and later-life SA is unclear. The Successful Aging Index (SAI) was mapped onto the Cognitive Function and Aging Study (CFAS), a longitudinal population-based cohort (n = 1,141). SAI scores were examined using growth mixture modelling (GMM) to identify SA trajectories. Unadjusted and adjusted (age, sex, occupational status) ordinal logistic regressions were conducted to examine the association between trajectory membership and education level. GMM identified a three-class model, capturing high, moderate, and low functioning trajectories. Adjusted ordinal logistic regression models indicated that individuals in higher SAI classes were significantly more likely to have higher educational attainment than individuals in the lower SAI classes. These results provide evidence of a life course link between education and SA.

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