Statistical approaches for the integration of external controls in a cystic fibrosis clinical trial: a simulation and an application.

Development of new therapeutics for a rare disease such as cystic fibrosis (CF) is hindered by challenges in accruing enough patients for clinical trials. Using external controls from well-matched historical trials can reduce prospective trial sizes, and this approach has supported regulatory approval of new interventions for other rare diseases. We consider three statistical methods that incorporate external controls into a hypothetical clinical trial of a new treatment to reduce pulmonary exacerbations in CF patients: 1) inverse probability weighting, 2) Bayesian modeling with propensity score-based power priors, and 3) hierarchical Bayesian modeling with commensurate priors. We compare the methods via simulation study and in a real clinical trial data setting. Simulations showed that bias in the treatment effect was <4% using any of the methods, with type 1 error (or in the Bayesian cases, posterior probability of the null hypothesis) usually <5%. Inverse probability weighting was sensitive to similarity in prevalence of the covariates between historical and prospective trial populations. The commensurate prior method performed best with real clinical trial data. Using external controls to reduce trial size in future clinical trials holds promise and can advance the therapeutic pipeline for rare diseases.

Traumatic brain injury in the prodromal period of Parkinson's disease: A large epidemiological study using medicare data.

OBJECTIVE: Studies suggest a greater risk of Parkinson's disease (PD) after traumatic brain injury (TBI), but it is possible that the risk of TBI is greater in the prodromal period of PD. We aimed to examine the time-to-TBI in PD patients in their prodromal period compared to population-based controls. METHODS: We identified 89,790 incident PD cases and 118,095 comparable controls aged > 65 years in 2009 using Medicare claims data. Using data from the preceding 5 years, we compared time-to-TBI in PD patients in their prodromal period to controls. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for TBI in a Cox regression, while adjusting for age, sex, race/ethnicity, modified Charlson comorbidity index, smoking, and alcohol use. RESULTS: Risk of TBI was greater in PD patients in their prodromal period across all age and sex groups, with HRs consistently increasing with proximity to PD diagnosis. HRs ranged from 1.64 (95% CI, 1.52, 1.77) 5 years preceding diagnosis to 3.93 (95% CI, 3.74, 4.13) in the year before. The interaction between PD, TBI, and time was primarily observed for TBI attributed to falls. Motor dysfunction and cognitive impairment, suggested by corresponding International Classification of Diseases, Ninth Revision codes, partially mediated the PD-TBI association. INTERPRETATION: There is a strong association between PD and a recent TBI in the prodromal period of PD. This association strengthens as PD diagnosis approaches and may be a result of undetected nonmotor and motor symptoms, but confirmation will be required. Ann Neurol 2017;82:744-754.

A predictive algorithm to identify ever smoking in medical claims-based epidemiologic studies.

PURPOSE: To develop and validate an algorithm to estimate probability of ever smoking using administrative claims. METHODS: Using population-based samples of Medicare-aged individuals (121,278 Behavioral Risk Factor Surveillance System survey respondents and 207,885 Medicare beneficiaries), we developed a logistic regression model to predict probability of ever smoking from demographic and claims data. We applied the model in 1,657,266 additional Medicare beneficiaries and calculated area under the receiver operating characteristic curve (AUC) using presence or absence of a tobacco-specific diagnosis or procedure code as our "gold standard." We used these "gold standard" and lung/laryngeal cancer codes to over-ride predicted probability as 100%. We calculated Spearman's rho between probability from this full algorithm and smoking assessed in prior Parkinson disease studies, by substituting our observed and prior ("true") smoking-Parkinson disease odds ratios into the attenuation equation. RESULTS: The predictive model contained 23 variables, including basic demographics, high alcohol consumption, asthma, cardiovascular disease and associated risk factors, selected cancers, and indicators of routine medical usage. The AUC was 67.6% (95% confidence interval 67.5%-67.7%) comparing smoking probability to tobacco-specific diagnosis or procedure codes. Spearman's rho for the full algorithm was 0.82. CONCLUSIONS: Ever smoking might be approximated in administrative data for use as a continuous, probabilistic variable in epidemiologic analyses.

A new path for CF clinical trials through the use of historical controls.

BACKGROUND: Given future challenges in conducting large randomized, placebo controlled trials for future CF therapeutics development, we evaluated the potential for using external historical controls to either enrich or replace traditional concurrent placebo groups in CF trials. METHODS: The study included data from sequentially completed, randomized, controlled clinical trials, EPIC and OPTIMIZE respectively, evaluating optimal antibiotic therapy to reduce the risk of pulmonary exacerbation in children with early Pseudomonas aeruginosa infection. The primary treatment effect in OPTIMIZE, the risk of pulmonary exacerbation associated with azithromycin, was re-estimated in alternative designs incorporating varying numbers of participants from the earlier trial (EPIC) as historical controls. Bias and precision of these estimates were characterized. Propensity scores were derived to adjust for baseline differences across study populations, and both Poisson and Cox regression were used to estimate treatment efficacy. RESULTS: Replacing 86 OPTIMIZE placebo participants with 304 controls from EPIC to mimic a fully historically controlled trial resulted an 8% reduction in risk of pulmonary exacerbations (Hazard ratio (HR):0.92 95% CI 0.61, 1.34) when not adjusting for key baseline differences between study populations. After adjustment, a 37% decrease in risk of exacerbation (HR:0.63, 95% CI 0.50, 0.80) was estimated, comparable to the estimate from the original trial comparing the 86 placebo participants to 77 azithromycin participants on azithromycin (45%, HR:0.55, 95% CI: 0.34, 0.86). Other adjusted approaches provided similar estimates for the efficacy of azithromycin in reducing exacerbation risk: pooling all controls from both studies provided a HR of 0.60 (95% x`CI 0.46, 0.77) and augmenting half the OPTIMIZE placebo participants with EPIC controls gave a HR 0.63 (95% CI 0.48, 0.82). CONCLUSIONS: The potential exists for future CF trials to utilize historical control data. Careful consideration of both the comparability of controls and of optimal methods can reduce the potential for biased estimation of treatment effects.

A comparison of prediction approaches for identifying prodromal Parkinson disease.

Identifying people with Parkinson disease during the prodromal period, including via algorithms in administrative claims data, is an important research and clinical priority. We sought to improve upon an existing penalized logistic regression model, based on diagnosis and procedure codes, by adding prescription medication data or using machine learning. Using Medicare Part D beneficiaries age 66-90 from a population-based case-control study of incident Parkinson disease, we fit a penalized logistic regression both with and without Part D data. We also built a predictive algorithm using a random forest classifier for comparison. In a combined approach, we introduced the probability of Parkinson disease from the random forest, as a predictor in the penalized regression model. We calculated the receiver operator characteristic area under the curve (AUC) for each model. All models performed well, with AUCs ranging from 0.824 (simplest model) to 0.835 (combined approach). We conclude that medication data and random forests improve Parkinson disease prediction, but are not essential.

Solvent exposed occupations and risk of Parkinson disease in Finland.

INTRODUCTION: Epidemiologic and toxicology studies suggest that exposure to various solvents, especially chlorinated hydrocarbon solvents, might increase Parkinson disease (PD) risk. METHODS: In a population-based case-control study in Finland, we examined whether occupations with potential for solvent exposures were associated with PD. We identified newly diagnosed cases age 45-84 from a nationwide medication reimbursement register in 1995-2014. From the population register, we randomly selected non-PD controls matched on sex, along with birth and diagnosis years (age). We included 11,757 cases and 23,236 controls with an occupation in the 1990 census, corresponding to age 40-60. We focused on 28 occupations with ≥ 5% probability of solvent exposure according to the Finnish Job Exposure Matrix. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) by logistic regression modeling, adjusting for age, sex, socioeconomic status, and smoking probability. RESULTS: Similar proportions of cases (5.5%) and controls (5.6%) had an occupation with potential exposure to any solvents. However, all occupations with a point estimate above one, and all significantly or marginally significantly associated with PD (electronic/telecommunications worker [OR = 1.63, 95% CI 1.05-2.50], laboratory assistant [OR = 1.40, 95% CI 0.98-1.99], and machine/engine mechanic [OR = 1.23, 95% CI 0.99-1.52]) entailed potential for exposure to chlorinated hydrocarbon solvents, specifically. Secondary analyses indicated exposure to polycyclic aromatic hydrocarbons and some metals might contribute to the association for mechanics. CONCLUSION: PD risk might be slightly increased in occupations with potential exposure to chlorinated hydrocarbon solvents. Confirmation is required in additional studies that adjust for other occupational exposures and smoking.

Principal Component Analysis of Striatal and Extrastriatal D2 Dopamine Receptor Positron Emission Tomography in Manganese-Exposed Workers.

The relationships between the neurotoxicant manganese (Mn), dopaminergic pathology, and parkinsonism remain unclear. Therefore, we used [11C](N-methyl)benperidol (NMB) positron emission tomography to investigate the associations between Mn exposure, striatal and extrastriatal D2 dopamine receptors (D2R), and motor function in 54 workers with a range of Mn exposure. Cumulative Mn exposure was estimated from work histories, and all workers were examined by a movement specialist and completed a Grooved Pegboard test (GPT). NMB D2R nondisplaceable binding potentials (BPND) were calculated for brain regions of interest. We identified 2 principal components (PCs) in a PC analysis which explained 66.8% of the regional NMB BPND variance (PC1 = 55.4%; PC2 = 11.4%). PC1 was positively correlated with NMB binding in all regions and inversely correlated with age. PC2 was driven by NMB binding in 7 brain regions (all p < .05), positively in the substantia nigra, thalamus, amygdala, and medial orbital frontal gyrus and negatively in the nucleus accumbens, anterior putamen, and caudate. PC2 was associated with both Mn exposure status and exposure duration (years). In addition, PC2 was associated with higher Unified Parkinson's Disease Rating Scale motor subsection 3 (UPDRS3) scores and slower GPT performance. We conclude Mn exposure is associated with both striatal and extrastriatal D2R binding. Multifocal alterations in D2R expression are also associated with motor dysfunction as measured by both the GPT and UPDRS3, demonstrating a link between Mn exposure, striatal and extrastriatal D2R expression, and clinical neurotoxicity.

Fractures in the prodromal period of Parkinson disease.

OBJECTIVE: To examine the association between fractures and Parkinson disease (PD) during the 5-year prodromal phase as compared to controls. METHODS: We performed a population-based case-control study of Medicare beneficiaries in the United States from 2004 to 2009. We identified 89,632 incident PD cases and 117,760 comparable controls 66-90 years of age in 2009. PD case status was the outcome, and noncranial fracture the independent variable. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for association between fracture and PD in yearly time intervals prior to PD diagnosis/control reference date, after adjusting for covariates. RESULTS: There were 39,606 total fractures (25.4% cases, 14.3% controls) over the 5 years prior to the PD diagnosis/control reference date. PD was positively associated with fractures even after adjusting for age, sex, race/ethnicity, Charlson comorbidity index, alcohol use, tobacco use, and osteoporosis. The association between PD and fracture was evident at yearly time windows prior to PD diagnosis/control reference date. The association between PD and each type of fracture strengthened as the PD diagnosis/control reference date approached (all time interaction p values ≤0.02). Among beneficiaries with a mechanism of injury, the majority were attributed to falls (74.6% cases, 72.8% controls). CONCLUSION: Fractures occur more commonly during the prodromal period of PD compared to controls, especially as diagnosis date approached, suggesting that patients with PD may experience unrecognized motor and nonmotor symptoms.

[11C]dihydrotetrabenazine Positron Emission Tomography in Manganese-Exposed Workers.

OBJECTIVE: To understand the neurotoxic effects of manganese (Mn) exposure on monoaminergic function, utilizing [C]dihydrotetrabenazine (DTBZ) positron emission tomography (PET) to measure vesicular monoamine transporter 2 (VMAT2). METHODS: Basal ganglia and thalamic DTBZ binding potentials (BPND) were calculated on 56 PETs from 41 Mn-exposed workers. Associations between cumulative Mn exposure, regional BPND, and parkinsonism were examined by mixed linear regression. RESULTS: Thalamic DTBZ BPND was inversely associated with exposure in workers with less than 3 mg Mn/m-yrs, but subsequently remained stable. Pallidal DTBZ binding increased in workers with less than 2 mg Mn/m-yrs of exposure, but decreased thereafter. Thalamic DTBZ binding was inversely associated with parkinsonism (P = 0.003). CONCLUSION: Mn-dose-dependent associations with thalamic and pallidal DTBZ binding indicate direct effects on monoaminergic VMAT2. Thalamic DTBZ binding was also associated with parkinsonism, suggesting potential as an early biomarker of Mn neurotoxicity.

MRI Signal Intensity and Parkinsonism in Manganese-Exposed Workers.

OBJECTIVE: T1-weighted brain magnetic resonance imaging (MRI) of the basal ganglia provides a noninvasive measure of manganese (Mn) exposure, and may also represent a biomarker for clinical neurotoxicity. METHODS: We acquired T1-weighted MRI scans in 27 Mn-exposed welders, 12 other Mn-exposed workers, and 29 nonexposed participants. T1-weighted intensity indices were calculated for four basal ganglia regions. Cumulative Mn exposure was estimated from work history data. Participants were examined using the Unified Parkinson's Disease Rating Scale motor subsection 3 (UPDRS3). RESULTS: We observed a positive dose-response association between cumulative Mn exposure and the pallidal index (PI) (ß = 2.33; 95% confidence interval [CI], 0.93 to 3.74). There was a positive relationship between the PI and UPDRS3 (ß = 0.15; 95% CI, 0.03 to 0.27). CONCLUSION: The T1-weighted pallidal signal is associated with occupational Mn exposure and severity of parkinsonism.

Selective D2 receptor PET in manganese-exposed workers.

OBJECTIVE: To investigate the associations between manganese (Mn) exposure, D2 dopamine receptors (D2Rs), and parkinsonism using [11C](N-methyl)benperidol (NMB) PET. METHODS: We used NMB PET to evaluate 50 workers with a range of Mn exposure: 22 Mn-exposed welders, 15 Mn-exposed workers, and 13 nonexposed workers. Cumulative Mn exposure was estimated from work histories, and movement disorder specialists examined all workers. We calculated NMB D2R nondisplaceable binding potential (BPND) for the striatum, globus pallidus, thalamus, and substantia nigra (SN). Multivariate analysis of covariance with post hoc descriptive discriminate analysis identified regional differences by exposure group. We used linear regression to examine the association among Mn exposure, Unified Parkinson's Disease Rating Scale motor subsection 3 (UPDRS3) score, and regional D2R BPND. RESULTS: D2R BPND in the SN had the greatest discriminant power among exposure groups (p < 0.01). Age-adjusted SN D2R BPND was 0.073 (95% confidence interval [CI] 0.022-0.124) greater in Mn-exposed welders and 0.068 (95% CI 0.013-0.124) greater in Mn-exposed workers compared to nonexposed workers. After adjustment for age, SN D2R BPND was 0.0021 (95% CI 0.0005-0.0042) higher for each year of Mn exposure. Each 0.10 increase in SN D2R BPND was associated with a 2.65 (95% CI 0.56-4.75) increase in UPDRS3 score. CONCLUSIONS AND RELEVANCE: Nigral D2R BPND increased with Mn exposure and clinical parkinsonism, indicating dose-dependent dopaminergic dysfunction of the SN in Mn neurotoxicity.

[18F]FDOPA positron emission tomography in manganese-exposed workers.

Occupational manganese (Mn) exposure is associated with the development of parkinsonism; however, the mechanism of neurotoxicity is unknown. Brain positron emission tomography (PET) imaging provides a non-invasive method of assessing dopamineric neuronal function. 6-[18F]fluoro-L-DOPA (FDOPA) PET reflects in-vivo nigrostriatal function, but results in Mn exposure are conflicting. The objective of this study was to investigate the association between Mn exposure secondary to occupational welding, FDOPA striatal uptake, and clinical parkinsonism as measured by Unified Parkinson Disease Rating Scale motor subscore 3 (UPDRS3) scores. FDOPA PET scans were acquired on 72 subjects (27 Mn-exposed welders, 14 other Mn-exposed workers, and 31 non-exposed subjects). We estimated cumulative welding exposure from detailed work histories, and a movement disorders specialist examined all subjects. Striatal volumes of interest were identified on aligned magnetic resonance imaging (MRI) for each subject. Specific striatal FDOPA uptake was calculated with a graphical analysis method. We used linear regression while adjusting for age to assess the association between welding exposure and FDOPA uptake in the caudate, anterior putamen, and posterior putamen. Compared to the non-exposed subjects, mean caudate FDOPA uptake was 0.0014min-1 (95% confidence interval [CI] 0.0008, 0.0020) lower in Mn-exposed welders and 0.0012min-1 (95% CI 0.0005, 0.0019) lower in other Mn-exposed workers (both p≤0.001). There was no clear dose-response association between caudate FDOPA uptake and Mn exposure or UPDRS3 scores. Mn-exposed welders and workers demonstrated lower caudate FDOPA uptake, indicating pre-synaptic dopaminergic dysfunction in Mn-exposed subjects that was not associated with clinical parkinsonism.

A predictive model to identify Parkinson disease from administrative claims data.

OBJECTIVE: To use administrative medical claims data to identify patients with incident Parkinson disease (PD) prior to diagnosis. METHODS: Using a population-based case-control study of incident PD in 2009 among Medicare beneficiaries aged 66-90 years (89,790 cases, 118,095 controls) and the elastic net algorithm, we developed a cross-validated model for predicting PD using only demographic data and 2004-2009 Medicare claims data. We then compared this model to more basic models containing only demographic data and diagnosis codes for constipation, taste/smell disturbance, and REM sleep behavior disorder, using each model's receiver operator characteristic area under the curve (AUC). RESULTS: We observed all established associations between PD and age, sex, race/ethnicity, tobacco smoking, and the above medical conditions. A model with those predictors had an AUC of only 0.670 (95% confidence interval [CI] 0.668-0.673). In contrast, the AUC for a predictive model with 536 diagnosis and procedure codes was 0.857 (95% CI 0.855-0.859). At the optimal cut point, sensitivity was 73.5% and specificity was 83.2%. CONCLUSIONS: Using only demographic data and selected diagnosis and procedure codes readily available in administrative claims data, it is possible to identify individuals with a high probability of eventually being diagnosed with PD.

Dose-dependent progression of parkinsonism in manganese-exposed welders.

OBJECTIVE: To determine whether the parkinsonian phenotype prevalent in welders is progressive, and whether progression is related to degree of exposure to manganese (Mn)-containing welding fume. METHODS: This was a trade union-based longitudinal cohort study of 886 American welding-exposed workers with 1,492 examinations by a movement disorders specialist, including 398 workers with 606 follow-up examinations up to 9.9 years after baseline. We performed linear mixed model regression with cumulative Mn exposure as the independent variable and annual change in Unified Parkinson Disease Rating Scale motor subsection part 3 (UPDRS3) as the primary outcome, and subcategories of the UPDRS3 as secondary outcomes. The primary exposure metric was cumulative Mn exposure in mg Mn/m3-year estimated from detailed work histories. RESULTS: Progression of parkinsonism increased with cumulative Mn exposure. Specifically, we observed an annual change in UPDRS3 of 0.24 (95% confidence interval 0.10-0.38) for each mg Mn/m3-year of exposure. Exposure was most strongly associated with progression of upper limb bradykinesia, upper and lower limb rigidity, and impairment of speech and facial expression. The association between welding exposure and progression appeared particularly marked in welders who did flux core arc welding in a confined space or workers whose baseline examination was within 5 years of first welding exposure. CONCLUSIONS: Exposure to Mn-containing welding fume may cause a dose-dependent progression of parkinsonism, especially upper limb bradykinesia, limb rigidity, and impairment of speech and facial expression.