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Imputation of Ordinal Outcomes: A Comparison of Approaches in Traumatic Brain Injury.

ABSTRACT: Loss to follow-up and missing outcomes data are important issues for longitudinal observational studies and clinical trials in traumatic brain injury. One popular solution to missing 6-month outcomes has been to use the last observation carried forward (LOCF). The purpose of the current study was to compare the performance of model-based single-imputation methods with that of the LOCF approach. We hypothesized that model-based methods would perform better as they potentially make better use of available outcome data. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (n?=?4509) included longitudinal outcome collection at 2 weeks, 3 months, 6 months, and 12 months post-injury; a total of 8185 Glasgow Outcome Scale extended (GOSe) observations were included in the database. We compared single imputation of 6-month outcomes using LOCF, a multiple imputation (MI) panel imputation, a mixed-effect model, a Gaussian process regression, and a multi-state model. Model performance was assessed via cross-validation on the subset of individuals with a valid GOSe value within 180?±?14 days post-injury (n?=?1083). All models were fit on the entire available data after removing the 180?±?14 days post-injury observations from the respective test fold. The LOCF method showed lower accuracy (i.e., poorer agreement between imputed and observed values) than model-based methods of imputation, and showed a strong negative bias (i.e., it imputed lower than observed outcomes). Accuracy and bias for the model-based approaches were similar to one another, with the multi-state model having the best overall performance. All methods of imputation showed variation across different outcome categories, with better performance for more frequent outcomes. We conclude that model-based methods of single imputation have substantial performance advantages over LOCF, in addition to providing more complete outcome data.

SUBMITTER: Kunzmann K

PROVIDER: S-EPMC7875604 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Imputation of Ordinal Outcomes: A Comparison of Approaches in Traumatic Brain Injury.

Kunzmann Kevin K Wernisch Lorenz L Richardson Sylvia S Steyerberg Ewout W EW Lingsma Hester H Ercole Ari A Maas Andrew I R AIR Menon David D Wilson Lindsay L

Journal of neurotrauma 20201113 4

Loss to follow-up and missing outcomes data are important issues for longitudinal observational studies and clinical trials in traumatic brain injury. One popular solution to missing 6-month outcomes has been to use the last observation carried forward (LOCF). The purpose of the current study was to compare the performance of model-based single-imputation methods with that of the LOCF approach. We hypothesized that model-based methods would perform better as they potentially make better use of a ...[more]

PMID: 33108942

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Project description:ImportanceTraumatic brain injury (TBI) affects millions of people in the US each year. Most patients with TBI seen in emergency departments (EDs) have a Glasgow Coma Scale (GCS) score of 15 and a head computed tomography (CT) scan showing no acute intracranial traumatic injury (negative head CT scan), yet the short-term and long-term functional outcomes of this subset of patients remain unclear.ObjectiveTo describe the 2-week and 6-month recovery outcomes in a cohort of patients with mild TBI with a GCS score of 15 and a negative head CT scan.Design, setting, and participantsThis cohort study analyzed participants who were enrolled from January 1, 2014, to December 31, 2018, in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study, a prospective, observational cohort study of patients with TBI that was conducted in EDs of 18 level I trauma centers in urban areas. Of the total 2697 participants in the TRACK-TBI study, 991 had a GCS score of 15 and negative head CT scan and were eligible for inclusion in this analysis. Data were analyzed from September 1, 2021, to May 30, 2022.Main outcomes and measuresThe primary outcome was the Glasgow Outcome Scale-Extended (GOS-E) score, which was stratified according to functional recovery (GOS-E score, 8) vs incomplete recovery (GOS-E score, <8), at 2 weeks and 6 months after the injury. The secondary outcome was severity of mild TBI-related symptoms assessed by the Rivermead Post Concussion Symptoms Questionnaire (RPQ) total score.ResultsA total of 991 participants (mean [SD] age, 38.5 [15.8] years; 631 male individuals [64%]) were included. Of these participants, 751 (76%) were followed up at 2 weeks after the injury: 204 (27%) had a GOS-E score of 8 (functional recovery), and 547 (73%) had a GOS-E scores less than 8 (incomplete recovery). Of 659 participants (66%) followed up at 6 months after the injury, 287 (44%) had functional recovery and 372 (56%) had incomplete recovery. Most participants with incomplete recovery reported that they had not returned to baseline or preinjury life (88% [479 of 546]; 95% CI, 85%-90%). Mean RPQ score was 16 (95% CI, 14-18; P < .001) points lower at 2 weeks (7 vs 23) and 18 (95% CI, 16-20; P < .001) points lower at 6 months (4 vs 22) in participants with a GOS-E score of 8 compared with those with a GOS-E score less than 8.Conclusions and relevanceThis study found that most participants with a GCS score of 15 and negative head CT scan reported incomplete recovery at 2 weeks and 6 months after their injury. The findings suggest that emergency department clinicians should recommend 2-week follow-up visits for these patients to identify those with incomplete recovery and to facilitate their rehabilitation.

Project description:When a patient is admitted to the intensive care unit (ICU) after a traumatic brain injury (TBI), an early prognosis is essential for baseline risk adjustment and shared decision making. TBI outcomes are commonly categorised by the Glasgow Outcome Scale-Extended (GOSE) into eight, ordered levels of functional recovery at 6 months after injury. Existing ICU prognostic models predict binary outcomes at a certain threshold of GOSE (e.g., prediction of survival [GOSE > 1]). We aimed to develop ordinal prediction models that concurrently predict probabilities of each GOSE score. From a prospective cohort (n = 1,550, 65 centres) in the ICU stratum of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) patient dataset, we extracted all clinical information within 24 hours of ICU admission (1,151 predictors) and 6-month GOSE scores. We analysed the effect of two design elements on ordinal model performance: (1) the baseline predictor set, ranging from a concise set of ten validated predictors to a token-embedded representation of all possible predictors, and (2) the modelling strategy, from ordinal logistic regression to multinomial deep learning. With repeated k-fold cross-validation, we found that expanding the baseline predictor set significantly improved ordinal prediction performance while increasing analytical complexity did not. Half of these gains could be achieved with the addition of eight high-impact predictors to the concise set. At best, ordinal models achieved 0.76 (95% CI: 0.74-0.77) ordinal discrimination ability (ordinal c-index) and 57% (95% CI: 54%- 60%) explanation of ordinal variation in 6-month GOSE (Somers' Dxy). Model performance and the effect of expanding the predictor set decreased at higher GOSE thresholds, indicating the difficulty of predicting better functional outcomes shortly after ICU admission. Our results motivate the search for informative predictors that improve confidence in prognosis of higher GOSE and the development of ordinal dynamic prediction models.

Dataset Information

Imputation of Ordinal Outcomes: A Comparison of Approaches in Traumatic Brain Injury.

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Imputation of Ordinal Outcomes: A Comparison of Approaches in Traumatic Brain Injury.

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