Should regression calibration or multiple imputation be used when calibrating different devices in a longitudinal study?

In longitudinal studies, the devices used to measure exposures can change from visit to visit. Calibration studies, wherein a subset of participants is measured using both devices at follow-up, may be used to assess between-device differences (i.e., errors). Then, statistical methods are needed to adjust for between-device differences and the missing measurement data that often appear in calibration studies. Regression calibration and multiple imputation are two possible methods. We compared both methods in linear regression with a simulation study, considering various real-world scenarios for a longitudinal study of pulse wave velocity. Regression calibration and multiple imputation were both essentially unbiased, but correctly estimating the standard errors posed challenges. Multiple imputation with predicted mean matching produced close agreement with the empirical standard error. Fully stochastic multiple imputation underestimated the standard error by up to 50%, and regression calibration with bootstrapped standard errors performed slightly better than fully stochastic multiple imputation. Regression calibration was slightly more efficient than either multiple imputation method. The results suggest use of multiple imputation with predictive mean matching over fully stochastic imputation or regression calibration in longitudinal studies where a new device at follow-up might be error-prone compared to the device used at baseline.

Liver integrity and the risk of Alzheimer's disease and related dementias.

INTRODUCTION: We examined midlife (1990-1992, mean age 57) and late-life (2011-2013, mean age 75) nonalcoholic fatty liver disease (NAFLD) and aminotransferase with incident dementia risk through 2019 in the Atherosclerosis Risk in Communities (ARIC) Study. METHODS: We characterized NAFLD using the fatty liver index and fibrosis-4, and we categorized aminotransferase using the optimal equal-hazard ratio (HR) approach. We estimated HRs for incident dementia ascertained from multiple data sources. RESULTS: Adjusted for demographics, alcohol consumption, and kidney function, individuals with low, intermediate, and high liver fibrosis in midlife (HRs: 1.45, 1.40, and 2.25, respectively), but not at older age, had higher dementia risks than individuals without fatty liver. A U-shaped association was observed for alanine aminotransferase with dementia risk, which was more pronounced in late-life assessment. DISCUSSION: Our findings highlight dementia burden in high-prevalent NAFLD and the important feature of late-life aminotransaminase as a surrogate biomarker linking liver hypometabolism to dementia. Highlights Although evidence of liver involvement in dementia development has been documented in animal studies, the evidence in humans is limited. Midlife NAFLD raised dementia risk proportionate to severity. Late-life NAFLD was not associated with a high risk of dementia. Low alanine aminotransferase was associated with an elevated dementia risk, especially when measured in late life.

Ex vivo biomechanical evaluation of an adhered fiberglass and polymethyl methacrylate sole-hoof wall cast on stabilization of type III distal phalanx fractures under simulated physiologic midstance loads.

OBJECTIVE: To evaluate the effect of the application of a novel fiberglass-glue cast (FGC) on the fracture gap width in experimentally created type III distal phalanx fractures in cadaveric specimens under simulated physiologic loads. STUDY DESIGN: Ex vivo biomechanical laboratory study. ANIMALS: Nine unilateral adult equine cadaver forelimbs. METHODS: Type III distal phalanx fractures were created in forelimb specimens, which maintained distal components of the passive stay apparatus. The fracture gap was measured at 5%, 20%, 25%, 50%, 75%, and 95% of fracture length (palmar articular border to solar margin) using D65Pr-PaDiO radiographs. The limb was axially loaded (700, 3600, 4600, and 6700 N) before, during, and after removal of a woven fiberglass cloth and polymethyl methacrylate cast that encompassed the sole and distal portion of the hoof wall (FGC). Fracture gap widths were compared among loads and treatments using a mixed model ANOVA. RESULTS: On average, under simulated physiological midstance loads, the fracture gap width was 0.2 mm smaller after FGC application, with the greatest decrease (0.5 mm) near the articular surface. On average, it was 0.3 mm smaller than after FGC removal. Fracture gap width was 0.1 mm greater when midstance loads transitioned from standing load to walking, trotting, and gallop loads. The fracture gap width increased by 1.3 mm with increasing distance from the articular surface. CONCLUSION: The FGC reduced the fracture gap width and prevented the fracture gap widening that occurred after FGC removal. CLINICAL SIGNIFICANCE: The findings support consideration of FGC use in the treatment of horses with type III distal phalangeal fractures.

Associations between avocado intake and measures of glucose and insulin homeostasis in Hispanic individuals with and without type 2 diabetes: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

BACKGROUND AND AIMS: To investigate associations between avocado intake and glycemia in adults with Hispanic/Latino ancestry. METHODS AND RESULTS: The associations of avocado intake with measures of insulin and glucose homeostasis were evaluated in a cross-sectional analysis of up to 14,591 Hispanic/Latino adults, using measures of: average glucose levels (hemoglobin A1c; HbA1c), fasting glucose and insulin, glucose and insulin levels after an oral glucose tolerance test (OGTT), and calculated measures of insulin resistance (HOMA-IR, and HOMA-%ß), and insulinogenic index. Associations were assessed using multivariable linear regression models, which controlled for sociodemographic factors and health behaviors, and which were stratified by dysglycemia status. In those with normoglycemia, avocado intake was associated with a higher insulinogenic index (ß = 0.17 ± 0.07, P = 0.02). In those with T2D (treated and untreated), avocado intake was associated with lower hemoglobin A1c (HbA1c; ß = -0.36 ± 0.21, P = 0.02), and lower fasting glucose (ß = -0.27 ± 0.12, P = 0.02). In the those with untreated T2D, avocado intake was additionally associated with HOMA-%ß (ß = 0.39 ± 0.19, P = 0.04), higher insulin values 2-h after an oral glucose load (ß = 0.62 ± 0.23, P = 0.01), and a higher insulinogenic index (ß = 0.42 ± 0.18, P = 0.02). No associations were observed in participants with prediabetes. CONCLUSIONS: We observed an association of avocado intake with better glucose/insulin homeostasis, especially in those with T2D.

Biomechanical Performance of Biodegradable Screw Fixation in Mandibular Distraction Osteogenesis.

Internal distraction devices are commonly used in congenital micrognathia. The eventual need for device and screw removal can be challenging, requiring extensive dissection and disturbance of bone regenerate. Bioabsorbable poly-L-lactide (PLLA) screws, compared to traditional titanium screws, simplify device removal. Previous in vivo studies have found that the maximal compressive force generated by mandibular distraction is 69.4N. We hypothesized that PLLA screws could support these compressive/distraction forces. Ten mandibles were obtained from 5 canine cadavers. Paired mandibles from the same cadaver were each fixated to a mandibular distractor with eight screws (either titanium or PLLA). Devices were each set to 15 and 30 mm of distraction distance. Compression force of 80 N was then generated parallel to the axis of the distraction device. Distractor displacement was measured to detect any mechanical failure during this pre-set load. Finally, if no failure was observed at 80 N, a load-to-failure compression test was done in the PLLA group to determine the mechanical failure point. All distractors in both the titanium and PLLA screw groups withstood 80 N of compression without failure. When the load-to-failure test was performed in the PLLA group, the average device failure point was 172.8 N (range 148-196 N). Review of high-frame-rate video demonstrated that all failures occurred due to the PLLA screws breaking or falling out. Bioabsorbable PLLA screws can withstand compressive forces more than double that of the maximal in vivo forces needed during mandibular distraction. These screws may be an acceptable alternative for the fixation of internal mandibular distractors.

Plasma metabolites associated with cognitive function across race/ethnicities affirming the importance of healthy nutrition.

INTRODUCTION: We studied the replication and generalization of previously identified metabolites potentially associated with global cognitive function in multiple race/ethnicities and assessed the contribution of diet to these associations. METHODS: We tested metabolite-cognitive function associations in U.S.A. Hispanic/Latino adults (n = 2222) from the Community Health Study/ Study of Latinos (HCHS/SOL) and in European (n = 1365) and African (n = 478) Americans from the Atherosclerosis Risk In Communities (ARIC) Study. We applied Mendelian Randomization (MR) analyses to assess causal associations between the metabolites and cognitive function and between Mediterranean diet and cognitive function. RESULTS: Six metabolites were consistently associated with lower global cognitive function across all studies. Of these, four were sugar-related (e.g., ribitol). MR analyses provided weak evidence for a potential causal effect of ribitol on cognitive function and bi-directional effects of cognitive performance on diet. DISCUSSION: Several diet-related metabolites were associated with global cognitive function across studies with different race/ethnicities. HIGHLIGHTS: Metabolites associated with cognitive function in Puerto Rican adults were recently identified. We demonstrate the generalizability of these associations across diverse race/ethnicities. Most identified metabolites are related to sugars. Mendelian Randomization (MR) provides weak evidence for a causal effect of ribitol on cognitive function. Beta-cryptoxanthin and other metabolites highlight the importance of a healthy diet.

Biomechanical comparison of compact versus standard flute drill bits, and interlocking versus buttress thread self-tapping cortical bone screws in cadaveric equine third metacarpal condyle.

OBJECTIVES: To compare (1) performance of compact versus standard flute drill bits, (2) screw insertion properties and (3) pullout variables between interlocking thread (ITS) and buttress thread (BTS) self-tapping screws in third metacarpi. STUDY DESIGN: In vitro experimental study. SAMPLE POPULATION: Paired third metacarpi from 11 Thoroughbreds aged 2-4 years. METHODS: Screws were inserted into the lateral condylar fossae following bone preparation using the respective drill bit for each screw type. Screw pullout was achieved using a mechanical testing system. Density and porosity of bone surrounding screw holes was measured with microcomputed tomography following each pullout test. Drilling, screw insertion and pullout variables were compared between drill bit and screw types using repeated measures ANOVA. Linear regression analyses were used to characterize relationships between bone tissue properties and drill bit and screw outcomes. RESULTS: Maximum torque power spectral density (PSD) was lower for compact flute drill bits. Insertion torque was 50% higher for ITS. BTS had 33% greater preyield stiffness and 7% greater mean yield force. Bone tissue properties affected measured variables similarly for both screw and drill bit types. CONCLUSIONS: Lower torque PSD may increase durability of the compact flute drill bit. ITS had greater insertional torque, which may reflect greater bone engagement. BTS had greater resistance to axial pullout forces. CLINICAL SIGNIFICANCE: Metacarpal bone provides a simple model for comparison of drill bit and screw designs. Use of ITS to repair equine fractures subject to predominantly tensile forces is not justified based on the results of this study.

Stifle joint osteoarthritis in small-breed and medium-breed dogs is more severe after cranial cruciate ligament injury than medial patellar luxation.

This retrospective observational study aimed to characterize the severity and distribution of OA in the stifle joints of small and medium dogs with CCL injury and/or MPL. Radiographs of the stifle joints from 218 dogs from 10 small and medium breeds were included; 127 joints had CCL injury, 76 joints had MPL, and 73 joints had CCL injury and MPL. OA was graded at 33 sites within the joint. The mean ± SD OA score was 20.3 ± 9.9. For all joints, OA was more severe in heavier than lighter dogs (P = 0.003). Joints with MPL (14.9 ± 8.2) had lower OA scores than joints with CCL injury (22.2 ± 10.0, P = 0.003) or CCL injury and MPL (22.6 ± 9.4, P < 0.001). OA scores were higher in joints with MPL for older dogs (r = 0.408, P < 0.001) but did not change with age in joints with CCL injury. The pattern of OA did not differ among joints with CCL injury or MPL. The retrospective nature of the study limited findings to associations but did not allow conclusions regarding factors causing OA or enhancing its progression. We concluded that, in small- and medium-breed dogs, the patterns of stifle OA joint after CCL injury and MPL are similar. Radiographic OA after CCL injury is more severe than MPL. An increase in age leads to an increase in OA at the time of presentation at a referral hospital in stifle joints with MPL and without CCL injury.

Dynamic landmark prediction for mixture data.

In kin-cohort studies, clinicians want to provide their patients with the most current cumulative risk of death arising from a rare deleterious mutation. Estimating the cumulative risk is difficult when the genetic mutation status is unknown and only estimated probabilities of a patient having the mutation are available. We estimate the cumulative risk for this scenario using a novel nonparametric estimator that incorporates covariate information and dynamic landmark prediction. Our estimator has improved prediction accuracy over existing estimators that ignore covariate information. It is built within a dynamic landmark prediction framework whereby we can obtain personalized dynamic predictions over time. Compared to current standards, a simple transformation of our estimator provides more efficient estimates of marginal distribution functions in settings where patient-specific predictions are not the main goal. We show our estimator is unbiased and has more predictive accuracy compared to methods that ignore covariate information and landmarking. Applying our method to a Huntington disease study of mortality, we develop dynamic survival prediction curves incorporating gender and familial genetic information.

Estimating disease onset from change points of markers measured with error.

Huntington disease is an autosomal dominant, neurodegenerative disease without clearly identified biomarkers for when motor-onset occurs. Current standards to determine motor-onset rely on a clinician's subjective judgment that a patient's extrapyramidal signs are unequivocally associated with Huntington disease. This subjectivity can lead to error which could be overcome using an objective, data-driven metric that determines motor-onset. Recent studies of motor-sign decline-the longitudinal degeneration of motor-ability in patients-have revealed that motor-onset is closely related to an inflection point in its longitudinal trajectory. We propose a nonlinear location-shift marker model that captures this motor-sign decline and assesses how its inflection point is linked to other markers of Huntington disease progression. We propose two estimating procedures to estimate this model and its inflection point: one is a parametric method using nonlinear mixed effects model and the other one is a multi-stage nonparametric approach, which we developed. In an empirical study, the parametric approach was sensitive to correct specification of the mean structure of the longitudinal data. In contrast, our multi-stage nonparametric procedure consistently produced unbiased estimates regardless of the true mean structure. Applying our multi-stage nonparametric estimator to Neurobiological Predictors of Huntington Disease, a large observational study of Huntington disease, leads to earlier prediction of motor-onset compared to the clinician's subjective judgment.

Robust methods to correct for measurement error when evaluating a surrogate marker.

The identification of valid surrogate markers of disease or disease progression has the potential to decrease the length and costs of future studies. Most available methods that assess the value of a surrogate marker ignore the fact that surrogates are often measured with error. Failing to adjust for measurement error can erroneously identify a useful surrogate marker as not useful or vice versa. We investigate and propose robust methods to correct for the effect of measurement error when evaluating a surrogate marker using multiple estimators developed for parametric and nonparametric estimates of the proportion of treatment effect explained by the surrogate marker. In addition, we quantify the attenuation bias induced by measurement error and develop inference procedures to allow for variance and confidence interval estimation. Through a simulation study, we show that our proposed estimators correct for measurement error in the surrogate marker and that our inference procedures perform well in finite samples. We illustrate these methods by examining a potential surrogate marker that is measured with error, hemoglobin A1c, using data from the Diabetes Prevention Program clinical trial.

Correcting conditional mean imputation for censored covariates and improving usability.

Missing data are often overcome using imputation, which leverages the entire dataset to replace missing values with informed placeholders. This method can be modified for censored data by also incorporating partial information from censored values. One such modification proposed by Atem et al. (2017, 2019a, 2019b) is conditional mean imputation where censored covariates are replaced by their conditional means given other fully observed information. These methods are robust to additional parametric assumptions on the censored covariate and utilize all available data, which is appealing. However, in implementing these methods, we discovered that these three articles provide nonequivalent formulas and, in fact, none is the correct formula for the conditional mean. Herein, we derive the correct form of the conditional mean and discuss the bias incurred when using the incorrect formulas. Furthermore, we note that even the correct formula can perform poorly for log hazard ratios far from 0${\mathbf {0}}$ . We also provide user-friendly R software, the imputeCensoRd package, to enable future researchers to tackle censored covariates correctly.

svReg: Structural varying-coefficient regression to differentiate how regional brain atrophy affects motor impairment for Huntington disease severity groups.

For Huntington disease, identification of brain regions related to motor impairment can be useful for developing interventions to alleviate the motor symptom, the major symptom of the disease. However, the effects from the brain regions to motor impairment may vary for different groups of patients. Hence, our interest is not only to identify the brain regions but also to understand how their effects on motor impairment differ by patient groups. This can be cast as a model selection problem for a varying-coefficient regression. However, this is challenging when there is a pre-specified group structure among variables. We propose a novel variable selection method for a varying-coefficient regression with such structured variables and provide a publicly available R package svreg for implementation of our method. Our method is empirically shown to select relevant variables consistently. Also, our method screens irrelevant variables better than existing methods. Hence, our method leads to a model with higher sensitivity, lower false discovery rate and higher prediction accuracy than the existing methods. Finally, we found that the effects from the brain regions to motor impairment differ by disease severity of the patients. To the best of our knowledge, our study is the first to identify such interaction effects between the disease severity and brain regions, which indicates the need for customized intervention by disease severity.

Evaluation of depth gauge accuracy in a canine tibial plateau leveling osteotomy model.

OBJECTIVE: To evaluate the accuracy of six depth gauges used in three tibial plateau leveling osteotomy (TPLO) plate holes. STUDY DESIGN: Ex vivo experimental study. ANIMALS AND SAMPLE POPULATION: Cadaveric canine limbs (n = 10), one 25-mm-thick wood board, and one 33.8-mm-diameter polyvinyl chloride (PVC) pipe. METHODS: A TPLO was performed on 10 canine cadaveric pelvic limbs. Three 3.5-mm plate holes were filled with screws. The remaining three plate holes: a compression hole, a combination compression-locking hole, and a stacked combination compression-locking hole were measured by three observers using six commercial depth gauges and using a micrometer as gold standard. The process was repeated on one wood board and one PVC pipe. RESULTS: Bone measurements collected using two depth gauges with base diameter < 5 mm were smaller than measurements collected using the four depth gauges with base diameter > 5.5 mm (p ranging from < .001 to .038). Mean depth gauge measurements were smaller than micrometer measurements by 2.20 mm for the compression hole, 0.82 mm for the combination hole, and 3.57 mm for the stacked combination hole. Measurement differences among depth gauges were also present for wood board and PVC pipe measurements. Bone measurement variability between depth gauges was less for the combination and compression holes than for the stacked combination hole. CONCLUSION: Depth gauges lacked accuracy. Measurements differed among gauges and measurement variability varied based on plate hole geometry. CLINICAL RELEVANCE: Depth gauge measurement accuracy varies based on measuring devices and on 3.5-mm plate hole geometry.

Comparison of needle arthroscopy, traditional arthroscopy, and computed tomography for the evaluation of medial coronoid disease in the canine elbow.

OBJECTIVE: To evaluate the diagnostic value of still images of needle arthroscopy (SNAR), still images of traditional arthroscopy (STAR), and computed tomography (CT) to diagnose medial coronoid process (MCP) pathology. STUDY DESIGN: Prospective clinical trial. ANIMALS: Dogs (n = 17) presented for evaluation of elbow dysplasia. METHODS: For each case, two SNAR and STAR images of the MCP were reviewed independently and in random order by three board-certified surgeons. Computed tomographic images were reviewed by one board-certified radiologist. Reviewers were blinded to surgical and clinical findings. Surgical findings from real-time TAR with palpation were used as the gold standard. Receiver operating characteristic (ROC) curves and concordance statistics tests for the diagnostic accuracy of MCP fissure, MCP fragment, medial compartment condition, and cartilage score were calculated. RESULTS: Images of 27 elbows joints were reviewed. For MCP fissure detection, areas under the ROC curves for CT (0.84), STAR (0.73), and SNAR (0.57) did not differ. For the detection of MCP fragment, STAR had a larger area under the ROC curve (0.93) compared with SNAR (0.74, P = .015) and CT (0.54, P < .001). Still images of TAR and SNAR had comparable concordance for cartilage score (0.80 and 0.77, respectively) and medial compartment pathology (0.80 and 0.73, respectively). CONCLUSION: Still images of NAR, STAR, and CT had similar diagnostic value to identify MCP fissures. Still images of TAR was superior to SNAR and CT to identify MCP fragments. CLINICAL SIGNIFICANCE: The diagnostic accuracy of SNAR varied on the basis of the coronoid lesion being evaluated.

Influence of interlocking thread screws to repair simulated adult canine humeral condylar fractures.

OBJECTIVE: To determine the influence of interlocking screw threads on the biomechanical properties of repaired canine humeral condylar fractures. STUDY DESIGN: Ex vivo biomechanical study. SAMPLE POPULATION: Thirty-six humeral condyles. METHODS: Simulated fractures of the lateral aspect of the humeral condyle were stabilized by a 3.5 mm interlocking thread screw (ITS) or 3.5 mm buttress thread screw placed in lag (BTS-L) or positional fashion (BTS-P) and axially loaded at a walk, trot, 2-mm displacement, and failure cycles. Compact flute drill bits (CFBs) were used for ITS constructs and standard flute drill bits (SFB) for BTS constructs. The effects of bit type on drilling parameters and screw type on screw insertion properties and fragment stability were assessed. RESULTS: CFB produced a 6°C greater temperature increase (p = .042) and required 20 N higher torque (p = .003) than SFB. Insertional torque was greater for ITS than BTS-P (p = .001) and BTS-L (p = .001). Condylar fragment rotation at failure was lower in ITS (lsmean ± SE, 8.3° ± 1.9°) than BTS-L constructs (14.5° ± 2.3°, p = .011). ITS resisted greater loads (1503 ± 105 N) than BTS-P (1189 ± 99 N, p = .038) but not BTS-L (1249 ± 123 N, p = .121) constructs. CONCLUSION: Biomechanical performance of constructs was improved with ITS rather than BTS fixation. CLINICAL SIGNIFICANCE: ITS can be considered for stabilization of humeral condylar fractures in adult dogs.

Time-varying proportional odds model for mega-analysis of clustered event times.

Mega-analysis, or the meta-analysis of individual data, enables pooling and comparing multiple studies to enhance estimation and power. A challenge in mega-analysis is estimating the distribution for clustered, potentially censored event times where the dependency structure can introduce bias if ignored. We propose a new proportional odds model with unknown, time-varying coefficients, and random effects. The model directly captures event dependencies, handles censoring using pseudo-values, and permits a simple estimation by transforming the model into an easily estimable additive logistic mixed effect model. Our method consistently estimates the distribution for clustered event times even under covariate-dependent censoring. Applied to three observational studies of Huntington's disease, our method provides, for the first time in the literature, evidence of similar conclusions about motor and cognitive impairments in all studies despite different recruitment criteria.

Percutaneous radiologically guided gastrostomy tubes: Procedural description and biomechanical comparison in a canine model.

OBJECTIVE: To describe the novel placement of percutaneous radiologically guided gastrostomy (PRG) tubes in a canine cadaveric model and to biomechanically compare PRG and percutaneous endoscopic gastrostomy (PEG) tube constructs. STUDY DESIGN: Descriptive and biomechanical experimental study. ANIMALS: Fifteen large breed (>25 kg) canine cadavers. METHODS: Percutaneous endoscopic gastrostomy tubes, low-profile PRG tubes, and standard PRG tubes were each placed in five canine cadavers. Body wall and stomach (with attached gastrostomy tube constructs) were harvested and biomechanically tested. Data regarding the maximal load to failure and procedure time were statistically analyzed. RESULTS: Percutaneous endoscopic gastrostomy and PRG tube placement was successful in all cadavers with no procedure-related complications. Gastrostomy tube placement time was longer for the PEG group vs the low-profile PRG (P = .005) and standard PRG (P = .037) groups. Peak construct strength was lower for the PEG group vs the low-profile PRG (P = .002) and standard PRG (P = .010) groups. The site of failure varied among groups. CONCLUSION: Percutaneous radiologically guided gastrostomy tubes were successfully placed in all cases with shorter placement time and greater peak construct strength compared with PEG tubes. CLINICAL SIGNIFICANCE: Due to the increased load to failure as well as decreased placement time recorded for PRG tubes relative to PEG tubes, PRG tubes may be considered as an alternative minimally invasive gastrostomy option in large breed canine patients. Further evaluation in clinical animals is required. Results of this work were presented at the 2019 American College of Veterinary Surgeons Surgery Summit; October 16-19, 2019; Las Vegas, Nevada.

A consistent estimator for logistic mixed effect models.

We propose a consistent and locally efficient estimator to estimate the model parameters for a logistic mixed effect model with random slopes. Our approach relaxes two typical assumptions: the random effects being normally distributed, and the covariates and random effects being independent of each other. Adhering to these assumptions is particularly difficult in health studies where in many cases we have limited resources to design experiments and gather data in long-term studies, while new findings from other fields might emerge, suggesting the violation of such assumptions. So it is crucial if we could have an estimator robust to such violations and then we could make better use of current data harvested using various valuable resources. Our method generalizes the framework presented in Garcia & Ma (2016) which also deals with a logistic mixed effect model but only considers a random intercept. A simulation study reveals that our proposed estimator remains consistent even when the independence and normality assumptions are violated. This contrasts from the traditional maximum likelihood estimator which is likely to be inconsistent when there is dependence between the covariates and random effects. Application of this work to a Huntington disease study reveals that disease diagnosis can be further improved using assessments of cognitive performance.

Statistical Approaches to Longitudinal Data Analysis in Neurodegenerative Diseases: Huntington's Disease as a Model.

Understanding the overall progression of neurodegenerative diseases is critical to the timing of therapeutic interventions and design of effective clinical trials. Disease progression can be assessed with longitudinal study designs in which outcomes are measured repeatedly over time and are assessed with respect to risk factors, either measured repeatedly or at baseline. Longitudinal data allows researchers to assess temporal disease aspects, but the analysis is complicated by complex correlation structures, irregularly spaced visits, missing data, and mixtures of time-varying and static covariate effects. We review modern statistical methods designed for these challenges. Among all methods, the mixed effect model most flexibly accommodates the challenges and is preferred by the FDA for observational and clinical studies. Examples from Huntington's disease studies are used for clarification, but the methods apply to neurodegenerative diseases in general, particularly as the identification of prodromal forms of neurodegenerative disease through sensitive biomarkers is increasing.