Association Between Direct-to-Consumer Advertising and Testosterone Testing and Initiation in the United States, 2009-2013

Testosterone initiation increased substantially in the United States from 2000 to 2013, especially among men without clear indications. Direct-to-consumer advertising (DTCA) also increased during this time

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

Design and microfabrication of a high-aspect-ratio PDMS microbeam array for parallel nanonewton force measurement and protein printing

Journal of Micromechanics and Microengineering, 17(3): pp. 623-632.Cell and protein mechanics has applications ranging from cellular development to tissue engineering. Techniques such as magnetic tweezers, optic tweezers, and atomic force microscopy have been used to measure cell deformation forces on the order of piconewtons to nanonewtons. In this study, an array of polymeric polydimethylsiloxane (PDMS) microbeams with diameters of 10-40μm and lengths of 118μm was fabricated from Sylgard® with curing agent concentrations ranging from 5% to 20%. Resulting spring constants were 100-300nN/μm. The elastic modulus of PDMS was determined experimentally at different curing agent concentrations and found to be 346kPa to 704kPa in a millimeter-scale array and ~1MPa in a microbeam array. Additionally, the microbeam array was used to print laminin for the purpose of cell adhesion. Linear and non-linear finite element analyses are presented and compared to the closed-from solution. Conclusion: The highly compliant, transparent, biocompatible PDMS may offer a method for more rapid throughput in cell and protein mechanics force measurement experiments with sensitivities necessary for highly compliant structures such as axons

Propensity Score Methods for Confounding Control in Nonexperimental Research

Nonexperimental studies are increasingly used to investigate the safety and effectiveness of medical products as they are used in routine care. One of the primary challenges of such studies is confounding, systematic differences in prognosis between patients exposed to an intervention of interest and the selected comparator group. In the presence of uncontrolled confounding, any observed difference in outcome risk between the groups cannot be attributed solely to a causal effect of the exposure on the outcome. Confounding in studies of medical products can arise from a variety of different sociomedical processes.1 The most common form of confounding arises from good medical practice, physicians prescribing medications and performing procedures on patients who are most likely to benefit from them. This leads to a bias known as confounding by indication, which can cause medical interventions to appear to cause events that they prevent.2,3 Conversely, patients who are perceived by a physician to be near the end of life may be less likely to receive preventive medications, leading to confounding by frailty or comorbidity.4–6 Additional sources of confounding bias can result from patients’ health-related behaviors. For example, patients who initiate a preventive medication may be more likely than other patients to engage in other healthy, prevention-oriented behaviors leading to bias known as the healthy user/adherer effect.7–9 Many statistical approaches can be used to remove the confounding effects of such factors if they are captured in the data. The most common statistical approaches for confounding control are based on multivariable regression models of the outcome. To yield unbiased estimates of treatment effects, these approaches require that the researcher correctly models the effect of the treatment and covariates on the outcome. However, correct specification of an outcome model can be challenging, particularly in studies

Observational Research Using Propensity Scores

In most observational studies, treatments or other "exposures" (in an epidemiologic sense) do not occur at random. Instead, treatments or other such interventions depend on several patient-related and patient-independent characteristics. Such factors, associated with the receipt vs nonreceipt of treatment, may also be-independently-associated with outcomes. Thus, confounding exists making it difficult to ascertain the true association between treatments and outcomes. Propensity scores (PS) represent an intuitive set of approaches to reduce the influence of such "confounding" factors. PS is a computed probability of treatment, a value that is estimated for each patient in an observational study and then applied (in a variety of ways such as matching, stratification, weighting, etc.) to reduce distortion in the true nature of the association between treatment (or any similar exposure) and outcomes. Despite several advantages, PS-based methods cannot account for unmeasured confounding, ie, for factors that are not being included in the computation of PS

Statin initiation and acute kidney injury following elective cardiovascular surgery: a population cohort study in Denmark

OBJECTIVES: Acute kidney injury (AKI) is a serious complication of cardiac surgery. Statins may prevent post-surgical AKI, yet methodological concerns about existing studies raise questions about the magnitude of a protective effect. We sought to determine the effect of initiating a statin prior to elective cardiac surgery on post-surgical AKI in a regional Danish surgical cohort. METHODS: We identified adults who underwent cardiac surgery during 2006-11 using the Western Denmark Heart Registry. Presurgical medication use, pre- and post-surgical serum creatinine (sCr) measures, and other patient characteristics were obtained from Danish population-based registries. Post-surgical AKI was assessed using sCr measures within 5 days of surgery. The adjusted risk ratio (RR) of AKI and 95% confidence interval (CI) were estimated for patients who initiated a statin within 100 days prior to surgery compared with patients without prior statin use; long-term statin users were excluded to reduce healthy-user bias. Subanalyses were stratified by surgery type: coronary artery bypass grafting (CABG) and non-CABG surgeries. RESULTS: We identified 1929 CABG and 1775 non-CABG patients. AKI occurred in 25% of CABG and 28% of non-CABG surgeries, and in 29% of the non-users and 21% of the statin initiators. Half of CABG patients and 9% of non-CABG patients initiated a statin prior to surgery. The adjusted RRs for the effect of statin initiation on AKI were as follows: all surgeries combined, RR = 0.86 (95% CI: 0.74, 0.98); CABG, RR = 0.88 (0.74, 1.05); non-CABG RR = 0.87 (0.68, 1.11). CONCLUSIONS: Presurgical statin initiation is associated with a reduction in AKI risk after cardiac surgery

Acute kidney injury in statin initiators

Statins are widely used for preventing cardiovascular disease, yet recent reports suggest an increased risk of acute kidney injury (AKI). We estimated the one-year risk of AKI associated with statin initiation and determined the comparative safety of individual statin formulations

Effect of Statin Use on Acute Kidney Injury Risk Following Coronary Artery Bypass Grafting

Acute kidney injury (AKI) is a serious complication of cardiovascular surgery. While some non-experimental studies suggest statin use may reduce post-surgical AKI, methodological differences in study designs leave uncertainty regarding the reality or magnitude of the effect. We estimated the effect of pre-operative statin initiation on post-coronary artery bypass graft (CABG) AKI using an epidemiologic approach more closely simulating a randomized controlled trial in a large CABG patient population. We utilized healthcare claims from large, employer-based and Medicare insurance databases for the years 2000 – 2010. To minimize healthy user bias, we identified patients undergoing non-emergency CABG who either newly initiated a statin within 20 days prior to surgery or were unexposed for 200+ days prior to CABG. AKI was identified within 15 days following CABG. We calculated multivariable adjusted risk ratios (RR) and 95% confidence intervals (CI) with Poisson regression. Analyses were repeated using propensity score methods adjusted for clinical and healthcare utilization variables. We identified 17,077 CABG patients. Post-CABG AKI developed in 3.4% of statin initiators and 6.2% of non-initiators. After adjustment, we observed a protective effect of statin initiation on AKI (RR = 0.78, 95% CI 0.63, 0.96). This effect differed by age: ≥65 years, RR=0.91 (95% CI: 0.68, 1.20); <65 years, RR=0.62 (95% CI: 0.45, 0.86), although AKI was more common in the older age group (7.7 vs. 4.0%). In conclusion, statin initiation immediately prior to CABG may modestly reduce the risk of post-operative AKI, particularly in younger CABG patients

Sodium Phosphate Does Not Increase Risk for Acute Kidney Injury After Routine Colonoscopy, Compared With Polyethylene Glycol

Oral sodium phosphate (OSP) is a common bowel purgative administered before colonoscopy; the Food and Drug Administration has warned against its use because of concerns about acute kidney injury (AKI) from the absorbed phosphate and dystrophic calcification. However, it is not clear if OSP is associated with AKI in the general population or in high-risk subgroups undergoing colonoscopy. We estimated the risk of AKI among patients undergoing a screening colonoscopy using OSP vs polyethylene glycol (PEG) for bowel cleansing in a large, US-based claims database

Cognitive pharmacy services at a pediatric nephrology and hypertension clinic

Purpose: Pediatric patients require special attention from pediatric pharmacists. This is particularly true for pediatric patients with chronic kidney disease (CKD) as the number of their medications and the complexity of their treatment increase with disease progression. However, there is paucity of information describing pediatric cognitive pharmacy services in this setting. The objective of this study is to identify the potential roles of a clinical pharmacist as a provider in a pediatric nephrology and hypertension clinic. Methods: Pediatric patients (≤18 years of age) who chronically took at least one medication were consecutively enrolled at the University of North Carolina (UNC) Pediatric Nephrology and Hypertension Clinic from 1 August 2007 to 15 April 2008. Demographic information and the interventions performed during the clinic visit by a clinical pharmacist were examined. Results: Three hundred and seventy-four visits made in 283 participants were evaluated. The mean (SD) number of cognitive pharmacy interventions per patient was 2.3 (1.0) on the first visit, with medication counseling and verification of current medications comprising the most common activity (85). The mean (SD) number of medications per patient was 5.7 (4.8) and of medications counseled per visit was 4.0 (3.4). Medication adherence was investigated in 141 (38) visits. Pretransplant education on medications was performed in 3 of the patients. Discrepancies of medications were discovered in 12 of the 374 visits. Conclusion: Pediatric cognitive pharmacy services to patients at the UNC pediatric nephrology clinic were feasible, which improved the quality of services and promoted better outcomes for these complex patients