63 research outputs found
Effects of aggregation of drug and diagnostic codes on the performance of the high-dimensional propensity score algorithm: an empirical example
BACKGROUND: The High-Dimensional Propensity Score (hd-PS) algorithm can select and adjust for baseline confounders of treatment-outcome associations in pharmacoepidemiologic studies that use healthcare claims data. How hd-PS performance is affected by aggregating medications or medical diagnoses has not been assessed. METHODS: We evaluated the effects of aggregating medications or diagnoses on hd-PS performance in an empirical example using resampled cohorts with small sample size, rare outcome incidence, or low exposure prevalence. In a cohort study comparing the risk of upper gastrointestinal complications in celecoxib or traditional NSAIDs (diclofenac, ibuprofen) initiators with rheumatoid arthritis and osteoarthritis, we (1) aggregated medications and International Classification of Diseases-9 (ICD-9) diagnoses into hierarchies of the Anatomical Therapeutic Chemical classification (ATC) and the Clinical Classification Software (CCS), respectively, and (2) sampled the full cohort using techniques validated by simulations to create 9,600 samples to compare 16 aggregation scenarios across 50% and 20% samples with varying outcome incidence and exposure prevalence. We applied hd-PS to estimate relative risks (RR) using 5 dimensions, predefined confounders, ≤ 500 hd-PS covariates, and propensity score deciles. For each scenario, we calculated: (1) the geometric mean RR; (2) the difference between the scenario mean ln(RR) and the ln(RR) from published randomized controlled trials (RCT); and (3) the proportional difference in the degree of estimated confounding between that scenario and the base scenario (no aggregation). RESULTS: Compared with the base scenario, aggregations of medications into ATC level 4 alone or in combination with aggregation of diagnoses into CCS level 1 improved the hd-PS confounding adjustment in most scenarios, reducing residual confounding compared with the RCT findings by up to 19%. CONCLUSIONS: Aggregation of codes using hierarchical coding systems may improve the performance of the hd-PS to control for confounders. The balance of advantages and disadvantages of aggregation is likely to vary across research settings
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Current and Projected Water Use in the Texas Mining and Oil and Gas Industry
In the middle of 2009, we undertook a study of water use in the mining industry in Texas, both current and projected for the next 50 years. The study concerned the upstream segment of the oil and gas industry (that is, water used to extract the commodity until it leaves the wellhead), the aggregate industry (sand and gravel and crushed rock operations, washing included but no further processing), the coal industry (mostly pit dewatering and aquifer depressurizing), and other substances mined in a fashion very similar to that of aggregates (industrial sand, lime, etc.), as well as through solution mining. In general, we followed the definition of mining according to SIC/NAICS codes. It follows that cement facilities, despite their large quarries, are considered to belong to the manufacturing, not mining, category. The objective of the study, essentially prompted by the sudden increase in shale-gas production, was to assist in the next cycle of water planning by the state agency in charge of such planning, the Texas Water Development Board (TWDB).
The approach to the study is twofold:
1. To collect water-use data and auxiliary information by contacting actual mining facilities.
2. To interview experts and other knowledgeable individuals in their respective fields to fill in the gaps in water-use data and to understand future development/contraction of water use in the different segments of the mining industry.
We surveyed the industry either through formal questionnaires sent to the membership of trade associations (TACA for aggregates; TMRA for aggregate, coal, and uranium; TXOGA and others for oil and gas), through surveys sent to water providers/observers such as GCDs, or through survey results from other organizations (MSHA, RRC, TCEQ, TWDB, USGS), and especially private vendors of the oil and gas industry. We contacted and had in-depth interviews with multiple representatives of every major segment of the mining industry to help us understand how the water is used, how much is recycled, what its source is (groundwater, surface water, or something else), whether it is fresh or brackish (saline water use is not tallied in this study), how much is rejected outside of the mining facility, etc.
Results from the surveys were useful but not as extensive as needed to fully assemble a representative sample of the hundreds of mining facilities in the state, with the exception of the coal industry and the uranium industry. We were also able to gather relatively accurate data from the stimulation stage when a well is being readied for production (that is, the fracking process), but we are more uncertain about water use for drilling wells and waterfloods. Results of current water use for the aggregate industry relied on previous information somewhat calibrated and updated by survey results. Overall, in 2008 (latest year with complete information), we estimate that the state used approximately 160 thousand acre-feet (AF) in the mining industry (Figure ES1), including 35.8 thousand AF for fracking wells (mostly in the Barnett Shale/Fort Worth area) and approximately 21.0 thousand AF for other purposes in the oil and gas industry, although more spread out across the state, with a higher demand in the Permian Basin area in West Texas. The coal industry used 20.0 thousand AF along the lignite belt from Central to East Texas. The 71.6 thousand AF used by the aggregate industry is distributed over most of the state, but with a clear concentration around major metropolitan areas. The remainder amounts to 11.0 thousand AF and is dominated by industrial sand production (approximately 80% of total).Bureau of Economic Geolog
A Retrospective Database Analysis of Neonatal Morbidities to Evaluate a Composite Endpoint for Use in Preterm Labor Clinical Trials
Objective To propose and assess a composite endpoint (CE) of neonatal benefit based on neonatal mortality and morbidities by gestational age (GA) for use in preterm labor clinical trials. Study Design A descriptive, retrospective analysis of the Medical University of South Carolina Perinatal Information System database was conducted. Neonatal morbidities were assessed for inclusion in the CE based on clinical significance/risk of childhood neurodevelopmental impairment, frequency, and association with GA in a mother– neonate linked cohort, comprising women with uncomplicated singleton pregnancies delivered at !24 weeks’ GA.
Results Among 17,912 mother–neonate pairs, neonates were at a risk of numerous severe but infrequent morbidities. Clinically important, predominantly rare events were combined into a CE comprising neonatal mortality and morbidities, which decreased in frequency with increasing GA. The highest CE frequency occurred at \u3c31 weeks. High frequency of respiratory distress syndrome, bronchopulmonary dysplasia, and sepsis drove the CE. Median length of hospital stay was longer at all GAs in those with the CE compared with those without.
Conclusions Descriptive epidemiological assessment and clinical input were used to develop a CE to measure neonatal benefit, comprising clinically meaningful outcomes. These empirical data and CE allowed trials investigating tocolytics to be sized appropriately
Investigating variation in replicability
Although replication is a central tenet of science, direct replications are rare in psychology. This research tested variation in the replicability of 13 classic and contemporary effects across 36 independent samples totaling 6,344 participants. In the aggregate, 10 effects replicated consistently. One effect – imagined contact reducing prejudice – showed weak support for replicability. And two effects – flag priming influencing conservatism and currency priming influencing system justification – did not replicate. We compared whether the conditions such as lab versus online or US versus international sample predicted effect magnitudes. By and large they did not. The results of this small sample of effects suggest that replicability is more dependent on the effect itself than on the sample and setting used to investigate the effect
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Common genetic variants in the CLDN2 and PRSS1-PRSS2 loci alter risk for alcohol-related and sporadic pancreatitis
Pancreatitis is a complex, progressively destructive inflammatory disorder. Alcohol was long thought to be the primary causative agent, but genetic contributions have been of interest since the discovery that rare PRSS1, CFTR, and SPINK1 variants were associated with pancreatitis risk. We now report two significant genome-wide associations identified and replicated at PRSS1-PRSS2 (1×10-12) and x-linked CLDN2 (p < 1×10-21) through a two-stage genome-wide study (Stage 1, 676 cases and 4507 controls; Stage 2, 910 cases and 4170 controls). The PRSS1 variant affects susceptibility by altering expression of the primary trypsinogen gene. The CLDN2 risk allele is associated with atypical localization of claudin-2 in pancreatic acinar cells. The homozygous (or hemizygous male) CLDN2 genotype confers the greatest risk, and its alleles interact with alcohol consumption to amplify risk. These results could partially explain the high frequency of alcohol-related pancreatitis in men – male hemizygous frequency is 0.26, female homozygote is 0.07
Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease
We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development
Effects of aggregation of drug and diagnostic codes on the performance of the high-dimensional propensity score algorithm: an empirical example
A novel Alzheimer disease locus located near the gene encoding tau protein
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordAPOE ε4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ε4+ (10 352 cases and 9207 controls) and APOE ε4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ε4 status. Suggestive associations (P<1 × 10-4) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ε4+: 1250 cases and 536 controls; APOE ε4-: 718 cases and 1699 controls). Among APOE ε4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10-9). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ε4+ subjects (CR1 and CLU) or APOE ε4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10-7) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P≤1.3 × 10-8), frontal cortex (P≤1.3 × 10-9) and temporal cortex (P≤1.2 × 10-11). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10-6) and temporal cortex (P=2.6 × 10-6). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ε4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted
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