Joint latent class model: Simulation study of model properties and application to amyotrophic lateral sclerosis disease

Kyheng, Maéva; Babykina, Génia; Ternynck, Camille; Devos, David; Labreuche, Julien; Duhamel, Alain

doi:10.1186/s12874-021-01377-9

Cited by 2 publications

(1 citation statement)

References 29 publications

(35 reference statements)

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“…A limited number of studies have used the joint model for the prediction of risk of mortality using SOFA scores in the adult ICU population (21)(22)(23). In addition, this approach has been used to predict a wide range of events in other clinical settings (24)(25)(26)(27)(28)(29)(30). The…”

Section: Discussionmentioning

confidence: 99%

Dynamic Prediction of Mortality Using Longitudinally Measured Pediatric Sequential Organ Failure Assessment Scores: A Joint Modeling Approach*

Akhondi-Asl,

Geva,

Burns

et al. 2024

Pediatric Critical Care Medicine

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OBJECTIVES: The pediatric Sequential Organ Failure Assessment (pSOFA) score was designed to track illness severity and predict mortality in critically ill children. Most commonly, pSOFA at a point in time is used to assess a static patient condition. However, this approach has a significant drawback because it fails to consider any changes in a patients’ condition during their PICU stay and, especially, their response to initial critical care treatment. We aimed to evaluate the performance of longitudinal pSOFA scores for predicting mortality. DESIGN: Single-center, retrospective cohort study. SETTING: Quaternary 40-bed PICU. PATIENTS: All patients admitted to the PICU between 2015 and 2021 with at least 24 hours of ICU stay. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We calculated daily pSOFA scores up to 30 days, or until death or discharge from the PICU, if earlier. We used the joint longitudinal and time-to-event data model for the dynamic prediction of 30-day in-hospital mortality. The dataset, which included 9146 patients with a 30-day in-hospital mortality of 2.6%, was divided randomly into training (75%) and validation (25%) subsets, and subjected to 40 repeated stratified cross-validations. We used dynamic area under the curve (AUC) to evaluate the discriminative performance of the model. Compared with the admission-day pSOFA score, AUC for predicting mortality between days 5 and 30 was improved on average by 6.4% (95% CI, 6.3–6.6%) using longitudinal pSOFA scores from the first 3 days and 9.2% (95% CI, 9.0–9.5%) using scores from the first 5 days. CONCLUSIONS: Compared with admission-day pSOFA score, longitudinal pSOFA scores improved the accuracy of mortality prediction in PICU patients at a single center. The pSOFA score has the potential to be used dynamically for the evaluation of patient conditions.

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Section: Discussionmentioning

confidence: 99%

Dynamic Prediction of Mortality Using Longitudinally Measured Pediatric Sequential Organ Failure Assessment Scores: A Joint Modeling Approach*

Akhondi-Asl,

Geva,

Burns

et al. 2024

Pediatric Critical Care Medicine

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Circulating thrombospondin-2 level for identifying individuals with rapidly declining kidney function trajectory in type 2 diabetes: a prospective study of the Hong Kong West Diabetes Registry

Lee

Lui

Cheung

et al. 2023

Nephrology Dialysis Transplantation

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Background Thrombospondin-2 (TSP2) is a matricellular protein with tissue expression induced by hyperglycaemia. TSP2 has been implicated in non-diabetic renal injury in preclinical studies and high circulating levels were associated with worse kidney function in cross-sectional clinical studies. Therefore, we investigated the prospective associations of circulating TSP2 level with kidney function decline and the trajectories of estimated glomerular filtration rate (eGFR) in type 2 diabetes. Methods Baseline serum TSP2 level was measured in 5471 patients with type 2 diabetes to evaluate its association with incident eGFR decline, defined as ≥ 40% sustained eGFR decline, using multivariable Cox regression analysis. Among participants with relatively preserved kidney function (Baseline eGFR ≥ 60 ml/min/1.73m2), joint latent class modelling was employed to identify three different eGFR trajectories. Their associations with baseline serum TSP2 was evaluated using multinomial logistic regression analysis. The predictive performance of serum TSP2 level was examined using time-dependent c-statistics and calibration statistics. Results Over a median follow-up of 8.8 years, 1083 patients (19.8%) developed eGFR decline. Baseline serum TSP2 level was independently associated with incident eGFR decline (HR 1.21, 95%CI 1.07–1.37, P = 0.002). With internal validation, incorporating serum TSP2 to a model of clinical risk factors including albuminuria led to significant improvement in c-statistics from 83.9 to 84.4 (P < 0.001). Among patients with eGFR ≥ 60 ml/min/1.73m2, baseline serum TSP2 level was independently associated with a rapidly declining eGFR trajectory (HR 1.63, 95%CI 1.26–2.10, P < 0.001). Conclusion Serum TSP2 level was independently associated with incident eGFR decline, particularly a rapidly declining trajectory, in type 2 diabetes.

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Joint latent class model: Simulation study of model properties and application to amyotrophic lateral sclerosis disease

Cited by 2 publications

References 29 publications

Dynamic Prediction of Mortality Using Longitudinally Measured Pediatric Sequential Organ Failure Assessment Scores: A Joint Modeling Approach*

Dynamic Prediction of Mortality Using Longitudinally Measured Pediatric Sequential Organ Failure Assessment Scores: A Joint Modeling Approach*

Circulating thrombospondin-2 level for identifying individuals with rapidly declining kidney function trajectory in type 2 diabetes: a prospective study of the Hong Kong West Diabetes Registry

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