Use of medical care biases associations between Parkinson disease and other medical conditions

Fine Particulate Matter and Parkinson Disease Risk Among Medicare Beneficiaries

BACKGROUND AND OBJECTIVES

Numerous studies suggest that environmental exposures play a critical role in Parkinson disease (PD) pathogenesis, and large, population-based studies have the potential to advance substantially the identification of novel PD risk factors. We sought to study the nationwide geographic relationship between PD and air pollution, specifically PM2.5 (particulate matter with a diameter <2.5 micrometers), using population-based US Medicare data.

METHODS

We conducted a population-based geographic study of Medicare beneficiaries aged 66-90 years geocoded to US counties and zip+4. We used integrated nested Laplace approximation to create age, sex, race, smoking, and health care utilization-adjusted relative risk (RR) at the county level for geographic analyses with PM2.5 as the primary exposure of interest. We also performed an individual-level analysis using logistic regression with cases and controls with zip+4 centroid PM2.5. We adjusted a priori for the same covariates and verified no confounding by indicators of socioeconomic status or neurologist density.

RESULTS

Among 21,639,190 Medicare beneficiaries, 89,390 had incident PD in 2009. There was a nationwide association between average annual PM2.5 and PD risk whereby the RR of PD was 56% (95% CI 47%-66%) greater for those exposed to the median level of PM2.5 compared with those with the lowest level of PM2.5. This association was linear up to 13 μg/m3 corresponding to a 4.2% (95% CI 3.7%-4.8%) greater risk of PD for each additional μg/m3 of PM2.5 (p trend < 0.0001). We identified a region with high PD risk in the Mississippi-Ohio River Valley, where the risk of PD was 19% greater compared with the rest of the nation. The strongest association between PM2.5 and PD was found in a region with low PD risk in the Rocky Mountains. PM2.5 was also associated with PD in the Mississippi-Ohio River Valley where the association was relatively weaker, due to a possible ceiling effect at average annual PM2.5 levels of ∼13 μg/m3.

DISCUSSION

State-of-the-art geographic analytic techniques revealed an association between PM2.5 and PD that varied in strength by region. A deeper investigation into the specific subfractions of PM2.5 may provide additional insight into regional variability in the PM2.5-PD association.

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.

Protective Effects of Lovastatin in a Population-Based ALS Study and Mouse Model

OBJECTIVE

The objective of this study was to use a novel combined pharmacoepidemiologic and amyotrophic lateral sclerosis (ALS) mouse model approach to identify potential motor neuron protective medications.

METHODS

We constructed a large, population-based case-control study to investigate motor neuron disease (MND) among US Medicare beneficiaries aged 66 to 90 in 2009. We included 1,128 incident MND cases and 56,400 age, sex, race, and ethnicity matched controls. We calculated MND relative risk for >1,000 active ingredients represented in Part D (pharmacy) claims in 2006 to 2007 (>1 year before diagnosis/reference). We then applied a comprehensive screening approach to select medications for testing in SOD1^G93A mice: sulfasalazine, telmisartan, and lovastatin. We treated mice with the human dose equivalent of the medication or vehicle via subcutaneous osmotic pump before onset of weakness. We then assessed weight, gait, and survival. In additional mice, we conducted histological studies.

RESULTS

We observed previously established medical associations for MND and an inverse dose-response association between lovastatin and MND, with 28% reduced risk at 40 mg/day. In SOD1^G93A mouse studies, sulfasalazine and telmisartan conferred no benefit, whereas lovastatin treatment delayed onset and prolonged survival. Lovastatin treated mice also had less microgliosis, misfolded SOD1, and spinal motor neuron loss in the ventral horn.

INTERPRETATION

Lovastatin reduced the risk of ALS in humans, which was confirmed in an ALS mouse model by delayed symptom onset, prolonged survival, and preservation of motor neurons. Although further studies to understand the mechanism are required, lovastatin may represent a potential neuroprotective therapy for patients with ALS. These data demonstrate the utility of a combined pharmacoepidemiologic and mouse model approach. ANN NEUROL 2023.

Biologic targets of prescription medications and risk of neurodegenerative disease in United States Medicare beneficiaries

OBJECTIVE

To identify prescription medications associated with a lower risk of three neurodegenerative diseases: Parkinson disease, Alzheimer disease, and amyotrophic lateral sclerosis.

METHODS

We conducted a population-based, case-control study of U.S. Medicare beneficiaries in 2009 (42,885 incident neurodegenerative disease cases, 334,387 randomly selected controls). Using medication data from 2006-2007, we categorized all filled medications according to their biological targets and mechanisms of action on those targets. We used multinomial logistic regression models, while accounting for demographics, indicators of smoking, and health care utilization, to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for 141 target-action pairs and each neurodegenerative disease. For target-action pairs inversely associated with all three diseases, we attempted replication in a cohort study that included an active comparator group. We constructed the cohort by following controls forward for incident neurodegenerative disease from the beginning of 2010 until death or end of 2014, i.e., up to five years after the two-year exposure lag. We used Cox proportional hazards regression while accounting for the same covariates.

RESULTS

The most consistent inverse association across both studies and all three neurodegenerative diseases was for xanthine dehydrogenase/oxidase blockers, represented by the gout medication, allopurinol. Allopurinol was associated with a 13-34% lower risk for each neurodegenerative disease group in multinomial regression, and a mean reduction of 23% overall, as compared to individuals who did not use allopurinol. In the replication cohort we observed a significant 23% reduction for neurodegenerative disease in the fifth year of follow-up, when comparing allopurinol users to non-users, and more marked associations with an active comparator group. We observed parallel associations for a related target-action pair unique to carvedilol.

DISCUSSION/CONCLUSION

Xanthine dehydrogenase/oxidase blockade might reduce risk of neurodegenerative disease. However, further research will be necessary to confirm that the associations related to this pathway are causal or to examine whether this mechanism slows progression.

The economic burden of Parkinson disease among Medicare beneficiaries

BACKGROUND: The progressive nature of Parkinson disease (PD), together with a lack of curative treatments, contributes to its economic burden. OBJECTIVE: To estimate the longitudinal incremental costs attributable to PD among Medicare beneficiaries. METHODS: In this retrospective cohort study, we used data from the Chronic Conditions Data Warehouse to identify Medicare beneficiaries with and without PD-related claims identified from 2006 to 2014 with follow-up until 2015. We grouped PD cases and controls based on their survival profiles using a grouping algorithm that used the following baseline measures: age, race, sex, and comorbidity. We identified 3 survival groups and used them to stratify the descriptive annual cost estimates in the 9 years after the index date. We estimated the incremental 1-, 3-, and 5-year costs of PD using generalized linear models (GLM) that controlled for baseline factors. RESULTS: We identified 27,394 cases and controls who were grouped into 3 survival groups. The mean age of the full study sample was 73 years. No material differences were found in the incremental cost of PD across the survival groups. Based on the multivariable GLM, the 1-year incremental cost of PD was $9,625 (95% CI, $9,054-$10,197). The 3-year incremental cost of PD was $20,832 (95% CI, $19,390-$22,274). The 5-year incremental cost of PD was $27,466 (95% CI, 25,088-$29,844). CONCLUSIONS: Among Medicare beneficiaries, PD is associated with excess costs compared with controls. We did not identify substantial differences in the incremental cost of PD across the survival groups. DISCLOSURES:This study was funded by Pfizer Inc. The funding agreement did not impact the authors' independence in designing the study, collecting the data, interpreting the data, writing the manuscript, and submitting the manuscript for publication. Dr Onukwugha reports grants from Pfizer Inc for the conduct of this study and is an employee of University of Maryland, Baltimore, which received financial support from Pfizer Inc in connection with the development of this manuscript; Dr Shulman reports research funding from Pfizer Inc related to the current work, is an employee of University of Maryland, Baltimore, which received financial support from Pfizer Inc in connection with the development of this manuscript, and reports research funding from the NIH, The Rosalyn Newman Foundation, and the Eugenia and Michael Brin family unrelated to the current work and royalties from Oxford University Press and Johns Hopkins University Press; Ms Myers and Dr Alvir are employees and stockholders of Pfizer Inc; Dr Gray was an employee and stockholder of Pfizer Inc at the time of analysis.

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.

Parkinson's disease and cancer: a systematic review and meta-analysis of over 17 million participants

OBJECTIVE

To systematically review and qualitatively evaluate epidemiological evidence on associations between Parkinson's disease (PD) and cancer via meta-analysis.

DATA SOURCES

MEDLINE via PubMed, Web of Science and EMBASE, until March 2021.

STUDY SELECTION

Included were publications that (1) were original epidemiological studies on PD and cancer; (2) reported risk estimates; (3) were in English. Exclusion criteria included: (1) review/comments; (2) biological studies; (3) case report/autopsy studies; (4) irrelevant exposure/outcome; (5) treated cases; (6) no measure of risk estimates; (7) no confidence intervals/exact p values and (8) duplicates.

DATA EXTRACTION AND SYNTHESIS

PRISMA and MOOSE guidelines were followed in data extraction. Two-step screening was performed by two authors blinded to each other. A random-effects model was used to calculate pooled relative risk (RR).

MAIN OUTCOMES AND MEASURES

We included publications that assessed the risk of PD in individuals with vs without cancer and the risk of cancer in individuals with vs without PD.

RESULTS

A total of 63 studies and 17 994 584 participants were included. Meta-analysis generated a pooled RR of 0.82 (n=33; 95% CI 0.76 to 0.88; p<0.001) for association between PD and total cancer, 0.76 (n=21; 95% CI 0.67 to 0.85; p<0.001) for PD and smoking-related cancer and 0.92 (n=19; 95% CI 0.84 to 0.99; p=0.03) for non-smoking-related cancer. PD was associated with an increased risk of melanoma (n=29; pooled RR=1.75; 95% CI 1.43 to 2.14; p<0.001) but not for other skin cancers (n=17; pooled RR=0.90; 95% CI 0.60 to 1.34; p=0.60).

CONCLUSIONS

PD and total cancer were inversely associated. This inverse association persisted for both smoking-related and non-smoking-related cancers. PD was positively associated with melanoma. These results provide evidence for further investigations for possible mechanistic associations between PD and cancer.

PROSPERO REGISTRATION NUMBER

CRD42020162103.

Herpesvirus Infections and Risk of Parkinson's Disease

INTRODUCTION

Herpesviruses might play a role in the pathogenesis of neurodegenerative disorders. We sought to examine a possible association between alpha herpesvirus infections and Parkinson's disease.

METHODS

We conducted a population-based case-control study of incident Parkinson's disease in 2009 Medicare beneficiaries age 66-90 years (89,790 cases, 118,095 randomly selected comparable controls). We classified beneficiaries with any diagnosis code for "herpes simplex" and/or "herpes zoster" in the previous 5 years as having had the respective alpha herpesviruses. In beneficiaries with Part D prescription coverage, we also identified those prescribed anti-herpetic medications. We calculated odds ratios (OR) and 95% CI between alpha herpesvirus diagnosis/treatment and Parkinson's disease with logistic regression, with adjustment for age, sex, race/ethnicity, smoking, and use of medical care.

RESULTS

Parkinson's disease risk was inversely associated with herpes simplex (OR 0.79, 95% CI 0.74-0.84), herpes zoster (OR 0.88, 95% CI 0.85-0.91), and anti-herpetic medications (OR 0.87, 95% CI 0.80-0.96).

CONCLUSION

Herpesvirus infection or treatment might reduce risk of Parkinson's disease, but future studies will be required to explore whether this inverse association is causal.

Validation of a Parkinson Disease Predictive Model in a Population-Based Study

Parkinson disease (PD) has a relatively long prodromal period that may permit early identification to reduce diagnostic testing for other conditions when patients are simply presenting with early PD symptoms, as well as to reduce morbidity from fall-related trauma. Earlier identification also could prove critical to the development of neuroprotective therapies. We previously developed a PD predictive model using demographic and Medicare claims data in a population-based case-control study. The area under the receiver-operating characteristic curve (AUC) indicated good performance. We sought to further validate this PD predictive model. In a randomly selected, population-based cohort of 115,492 Medicare beneficiaries aged 66-90 and without PD in 2009, we applied the predictive model to claims data from the prior five years to estimate the probability of future PD diagnosis. During five years of follow-up, we used 2010-2014 Medicare data to determine PD and vital status and then Cox regression to investigate whether PD probability at baseline was associated with time to PD diagnosis. Within a nested case-control sample, we calculated the AUC, sensitivity, and specificity. A total of 2,326 beneficiaries developed PD. Probability of PD was associated with time to PD diagnosis (p < 0.001, hazard ratio = 13.5, 95% confidence interval (CI) 10.6-17.3 for the highest vs. lowest decile of probability). The AUC was 83.3% (95% CI 82.5%-84.1%). At the cut point that balanced sensitivity and specificity, sensitivity was 76.7% and specificity was 76.2%. In an independent sample of additional Medicare beneficiaries, we again applied the model and observed good performance (AUC = 82.2%, 95% CI 81.1%-83.3%). Administrative claims data can facilitate PD identification within Medicare and Medicare-aged samples.

Overlapping genetic architecture between Parkinson disease and melanoma

Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here, we apply polygenic, linkage disequilibrium-informed methods to the largest available case-control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10-0.24; P = 4.09 × 10-06) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 × 10-04) and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression.

Well Water and Parkinson's Disease in Medicare Beneficiaries: A Nationwide Case-Control Study

BACKGROUND

Well water frequently is considered a risk factor for Parkinson's disease (PD), but few studies were designed appropriately to test whether geographic factors affect PD risk.

OBJECTIVE

To determine the risk of PD in relation to residential use of private well water.

METHODS

In a nationwide, population-based case-control study, we identified all incident PD cases (N = 89,790) and all comparable controls (N = 21,549,400) age 66-90 who solely relied on Medicare coverage in the U.S. in 2009. We estimated the probability of use of private well water using zip code of residence at diagnosis/reference and U.S. Census data on household water source. We modeled this exposure linearly in logistic regression to calculate the odds ratio (OR) and 95% confidence interval (CI) of PD risk in relation to well water use. We adjusted for age, sex and race/ethnicity, and verified that smoking and use of medical care did not confound results. We repeated analyses with a 2-year exposure lag and separately within each U.S. state.

RESULTS

Use of well water was inversely associated with PD risk (OR = 0.87, 95% CI 0.85-0.89). We confirmed this association in a Cox survival analysis in which we followed controls for 5 years, death or PD diagnosis. There was little evidence that well water use increased risk of PD in any individual state.

CONCLUSIONS

Although it remains possible that exposures in well water in more narrow geographic regions increase PD risk, in general these results suggest that exposures more common in urban/suburban areas might also be relevant.

Transplant and risk of Parkinson disease

INTRODUCTION

The pathophysiology of Parkinson's disease (PD) remains unclear, but growing evidence supports a role of neuroinflammation. The purpose of this study was to investigate the association between tissue transplantation and PD risk, given the importance of immunosuppressants in post-transplant management.

METHODS

We performed a case-control study among Medicare beneficiaries age 66-90 using claims from 2004 to 2009. We used International Classification of Diseases, Ninth Edition (ICD-9) and Current Procedural Terminology (CPT) codes to identify PD (89,790 incident cases, 118,095 population-based controls) and history of tissue transplant (kidney, heart, liver, lung, and bone marrow). We investigated risk of PD in relation to tissue transplant in logistic regression models, adjusting for age, sex, race, smoking, and overall use of medical care.

RESULTS

Beneficiaries who had received a tissue transplant at least five years prior to PD diagnosis or reference had a lower risk of PD (odds ratio [OR] 0.63, 95% confidence interval [CI] 0.53, 0.75) than those without tissue transplant. This inverse association was observed for kidney (OR 0.63, 95% CI 0.47, 0.84), heart (OR 0.58, 95% CI 0.40, 0.83), lung (OR 0.41, 95% CI 0.21, 0.77), and bone marrow (OR 0.57, 95% 0.38, 0.85) transplants. Associations were attenuated, but remained, following adjustment for indications for the respective type of transplant. Liver transplant was not associated with PD risk.

CONCLUSIONS

Patients undergoing tissue transplant may have a lower risk of developing PD than the general population. Further studies are needed to determine if this association is causal and if immunosuppressants mediate this association.

β2-adrenoreceptor medications and risk of Parkinson disease

OBJECTIVE

A recent study observed a 2-fold greater risk of Parkinson disease (PD) in relation to the β2-adrenoreceptor antagonist propranolol and a markedly lower risk of PD for the β2-adrenoreceptor agonist salbutamol. We examined whether confounding by clinical indication for these medications, that is, tremor and smoking-related pulmonary conditions, explained these associations.

METHODS

In a large, population-based case-control study of United States Medicare beneficiaries in 2009 with diagnosis codes, procedure codes, and prescription data (48,295 incident PD cases, 52,324 controls), we examined the risk of PD in relation to use of selected β antagonists (propranolol, carvedilol, metoprolol), the β2 agonist salbutamol, and other medications used for the same clinical indications (primidone, inhaled corticosteroids). We adjusted for demographics, smoking, and overall use of medical care. We then examined the effect of also adjusting for clinical indication and applying medication exposure lagging.

RESULTS

Propranolol appeared to increase PD risk (odds ratio [OR] = 3.62, 95% confidence interval [CI] = 3.31-3.96). When we adjusted for tremor or abnormal involuntary movement prior to the PD diagnosis/reference date and lagged propranolol exposure, the association was 0.97 (95% CI = 0.80-1.18). Primidone, also used for tremor, was similarly sensitive to this adjustment and lagging. β Antagonists not indicated for tremor appeared to reduce PD risk (carvedilol: OR = 0.77, 95% CI = 0.73-0.81; metoprolol: OR = 0.94, 95% CI = 0.91-0.97) and were insensitive to adjustment for indications and lagging. Neither salbutamol nor inhaled corticosteroids were consistently associated with PD risk.

INTERPRETATION

β2-adrenoreceptor agonists and antagonists do not appear to alter PD risk. Ann Neurol 2018;84:691-701.

Co-occurrence of Asthma and the Inflammatory Bowel Diseases: A Systematic Review and Meta-analysis

Background

Inflammatory bowel diseases (IBD) and asthma share genetic and environmental risk factors. Consequently, several observational studies have explored an association between IBD and asthma. We systematically reviewed and summarized the literature on the co-occurrence of asthma and IBD.

Methods

MEDLINE and EMBASE (to April 2017) were searched to identify observational studies on the association between asthma and IBD. Relative risks (RR) were pooled using random effects models. Heterogeneity was assessed using the I² and Cochran Q statistics. Meta-regression based on study design, source of patients (population-based vs. tertiary-care center) and study location was conducted to explain between-study heterogeneity.

Results

Eighteen studies were identified (15 Crohn’s disease, 15 ulcerative colitis (UC)). Asthma was associated with both Crohn’s disease (pooled RR 1.30, 95% confidence interval (CI) 1.16–1.47, I² = 88%) and UC (RR 1.34, 95% CI 1.24–1.44, I² = 93%). The study design and source of patients and study location explained between-study heterogeneity in Crohn’s disease, but not UC.

Conclusion

Asthma is associated with both Crohn’s disease and UC. Additional research is needed to determine if one disease influences the risk of developing the other or if the frequent co-occurrence of these diseases result from shared genetic, environmental, and microbial risk factors.