Longitudinal diffusion MRI as surrogate outcome measure for myelopathy in adrenoleukodystrophy

ObjectiveTo prospectively determine the potential of diffusion MRI (dMRI) of the cervical spinal cord and the corticospinal tracts in brain as surrogate outcome measure for progression of myelopathy in men with adrenoleukodystrophy, as better outcome measures to quantify progression of myelopathy would enable clinical trials with fewer patients and shorter follow-up.MethodsClinical assessment of myelopathy included Expanded Disability Status Scale (EDSS), Severity Scoring System for Progressive Myelopathy (SSPROM), Timed Up-and-Go, and 6-Minute Walk Test. Applied dMRI metrics included fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity.ResultsData were available for 33 controls and 52 patients. First, cross-sectionally, differences between groups (controls vs patients; controls vs asymptomatic patients vs symptomatic patients) were statistically significant for fractional anisotropy, mean diffusivity, and radial diffusivity in spinal cord and brain corticospinal tracts (effect size 0.31–0.68). Correlations between dMRI metrics and clinical measures were moderate to strong (correlation coefficient 0.35–0.60). Second, longitudinally (n = 36), change on clinical measures was significant after 2-year follow-up for EDSS, SSPROM, and Timed Up-and-Go (p ≤ 0.021, effect size ≤0.14). Change on brain fractional anisotropy and radial diffusivity was slightly larger (p ≤ 0.002, effect sizes 0.16–0.28). In addition, a statistically significant change was detectable in asymptomatic patients using brain dMRI and not using the clinical measures. Change on clinical measures did not correlate to change on dMRI metrics.ConclusionAlthough effect sizes were small, our prospective data illustrate the potential of dMRI as surrogate outcome measure for progression of myelopathy in men with adrenoleukodystrophy.

Silent brain infarcts on diffusion-weighted imaging after carotid revascularisation: A surrogate outcome measure for procedural stroke? A systematic review and meta-analysis

Aim To investigate whether lesions on diffusion-weighted imaging (DWI+) after carotid artery stenting (CAS) or endarterectomy (CEA) might provide a surrogate outcome measure for procedural stroke. Materials and Methods Systematic MedLine® database search with selection of all studies published up to the end of 2016 in which DWI scans were obtained before and within seven days after CAS or CEA. The correlation between the underlying log odds of stroke and of DWI+ across all treatment groups (i.e. CAS or CEA groups) from included studies was estimated using a bivariate random effects logistic regression model. Relative risks of DWI+ and stroke in studies comparing CAS vs. CEA were estimated using fixed-effect Mantel-Haenszel models. Results We included data of 4871 CAS and 2099 CEA procedures (85 studies). Across all treatment groups (CAS and CEA), the log odds for DWI+ was significantly associated with the log odds for clinically manifest stroke (correlation coefficient 0.61 (95% CI 0.27 to 0.87), p = 0.0012). Across all carotid artery stenting groups, the correlation coefficient was 0.19 (p = 0.074). There were too few CEA groups to reliably estimate a correlation coefficient in this subset alone. In 19 studies comparing CAS vs. CEA, the relative risks (95% confidence intervals) of DWI+ and stroke were 3.83 (3.17–4.63, p < 0.00001) and 2.38 (1.44–3.94, p = 0.0007), respectively. Discussion This systematic meta-analysis demonstrates a correlation between the occurrence of silent brain infarcts on diffusion-weighted imaging and the risk of clinically manifest stroke in carotid revascularisation procedures. Conclusion Our findings strengthen the evidence base for the use of DWI as a surrogate outcome measure for procedural stroke in carotid revascularisation procedures. Further randomised studies comparing treatment effects on DWI lesions and clinical stroke are needed to fully establish surrogacy.

Abstract 353: Performance of SOFA Score to Predict Mortality at Hospital Discharge After Cardiac Arrest

Introduction: Cardiac arrest (CA) outcomes, when dichotomized as survival/non-survival, limit statistical power of interventional studies and do not acknowledge hospital-level factors independent of post-CA sequelae. We explored the Sequential Organ Failure Assessment (SOFA) score at 72 hours post-CA as a surrogate outcome measure for mortality. We also assessed methods to account for death <72 hours post-CA in SOFA score computation. Methods: This was a single center retrospective study of post-CA patients from 1/08-12/17. SOFA score components were abstracted at baseline, 24, 48, and 72h post-CA. Thirteen ways of accounting for missing data were assessed. The outcome was mortality at hospital discharge. Model performance was assessed using area under the receiver-operator characteristic (AUC) curves and Hosmer-Lemeshow goodness of fit statistics. Results: Of 847 patients, 528 (62%) had complete baseline SOFA scores and 205 (24%) had complete scores at 72h. Death <72h occurred in 28%; 45% survived to hospital discharge. SOFA score at 72h without accounting for death had an AUC of 0.62. The best performing SOFA model at 72h with good calibration imputed a 20% increase over the last observed SOFA score in patients who expired <72h with an AUC of 0.79 (95% CI: 0.74-0.83). In terms of change in SOFA at 72h from baseline, the best performing model with good calibration imputed death <72h as the highest possible score (AUC: 0.88 [95% CI: 0.84-0.92]). These results were consistent when analyzing in- and out-of-hospital CA separately, although the change from baseline model was not well calibrated in in-hospital arrests. Conclusions: Without consideration of death, SOFA scores at 72 hours post-CA perform poorly. Imputing for early mortality improved the model. If this imputation structure is validated prospectively, SOFA could provide a scoring system to predict death at hospital discharge and serve as a surrogate outcome measure in interventional studies.

Defining Biomarker Performance and Clinical Validity

Defining Biomarker Performance and Clinical ValidityIn the evaluation of biomarkers three questions can be answered: what is the analytical validity of the marker, what is its clinical validity, and does the marker have clinical utility? In most cases, clinical validity will be expressed in terms of the marker's accuracy: the degree to which it can be used to correctly identify diseased patients or, more generally, patients with the target condition. Diagnostic accuracy is evaluated in studies in which the biomarker values are compared to the outcome of the clinical reference standard in the same patients. There are several ways in which the results of diagnostic accuracy studies can be summarized, reported, and interpreted. In this paper we summarize and present the available measures. We classify these as error-based measures, information-based measures, and measures of the strength of the association. Clinical validity is linked to clinical utility. If the target condition is well defined and associated with unequivocal downstream management decisions, clinical validity, when defined in comparative terms, may sometimes act as a surrogate outcome measure for clinical utility.