Purna Mukhopadhyay

An intraductal human-in-mouse transplantation model mimics the subtypes of ductal carcinoma in situ.

IntroductionHuman models of noninvasive breast tumors are limited, and the existing in vivo models do not mimic inter- and intratumoral heterogeneity. Ductal carcinoma in situ (DCIS) is the most common type (80%) of noninvasive breast lesions. The aim of this study was to develop an in vivo model whereby the natural progression of human DCIS might be reproduced and studied. To accomplish this goal, the intraductal human-in-mouse (HIM) transplantation model was developed. The resulting models, which mimicked some of the diversity of human noninvasive breast cancers in vivo, were used to show whether subtypes of human DCIS might contain distinct subpopulations of tumor-initiating cells.MethodsThe intraductal models were established by injection of human DCIS cell lines (MCF10DCIS.COM and SUM-225), as well as cells derived from a primary human DCIS (FSK-H7), directly into the primary mouse mammary ducts via cleaved nipple. Six to eight weeks after injections, whole-mount, hematoxylin and eosin, and immunofluorescence staining were performed to evaluate the type and extent of growth of the DCIS-like lesions. To identify tumor-initiating cells, putative human breast stem/progenitor subpopulations were sorted from MCF10DCIS.COM and SUM-225 with flow cytometry, and their in vivo growth fractions were compared with the Fishers Exact test.ResultsHuman DCIS cells initially grew within the mammary ducts, followed by progression to invasion in some cases into the stroma. The lesions were histologically almost identical to those of clinical human DCIS. This method was successful for growing DCIS cell lines (MCF10DCIS.COM and SUM-225) as well as a primary human DCIS (FSK-H7). MCF10DCIS.COM represented a basal-like DCIS model, whereas SUM-225 and FSK-H7 cells were models for HER-2+ DCIS. With this approach, we showed that various subtypes of human DCIS appeared to contain distinct subpopulations of tumor-initiating cells.ConclusionsThe intraductal HIM transplantation model provides an invaluable tool that mimics human breast heterogeneity at the noninvasive stages and allows the study of the distinct molecular and cellular mechanisms of breast cancer progression.

The prevalence of and factors associated with chronic atrial fibrillation in Medicare/Medicaid-eligible dialysis patients

Atrial fibrillation is an important comorbidity with substantial therapeutic implications in dialysis patients but its prevalence varies in different studies. We used a database that includes patients in the United States on hemodialysis who were eligible for government assistance with prescription drugs. We then used ICD-9 codes from billing claims in this database to identify patients with chronic atrial fibrillation. Multivariable logistic regression was used to determine adjusted prevalence odds ratios for associated factors. Of 63,884 individuals, the prevalence of chronic atrial fibrillation was 7%. The factors of age over 60 years, male, Caucasian, body mass index over 25 kg/m(2), coronary artery disease, and heart failure were all significantly associated with chronic atrial fibrillation. Prevalence rates, particularly in younger patients, were far higher than those reported in an age group-matched nondialysis population. Thus, given its clinical impact, future efforts are needed to examine risk factors for adverse outcomes in chronic atrial fibrillation, and to identify appropriate management strategies for this disorder, as well as opportunities for quality improvement in this vulnerable population.

Geographic Variation in Cardioprotective Antihypertensive Medication Usage in Dialysis Patients

BACKGROUND Despite their high risk of adverse cardiac outcomes, persons on long-term dialysis therapy have had lower use of antihypertensive medications with cardioprotective properties, such as angiotensin-converting enzyme (ACE) inhibitors/angiotensin receptor blockers (ARBs), β-blockers, and calcium channel blockers, than might be expected. We constructed a novel database that permits detailed exploration into the demographic, clinical, and geographic factors associated with the use of these agents in hypertensive long-term dialysis patients. STUDY DESIGN National cross-sectional retrospective analysis linking Medicaid prescription drug claims with US Renal Data System core data. SETTING & PARTICIPANTS 48,882 hypertensive long-term dialysis patients who were dually eligible for Medicaid and Medicare services in 2005. FACTORS Demographics, comorbid conditions, functional status, and state of residence. OUTCOMES Prevalence of cardioprotective antihypertensive agents in Medicaid pharmacy claims and state-specific observed to expected ORs of medication exposure. MEASUREMENTS Factors associated with medication use were modeled using multilevel logistic regression models. RESULTS In multivariable analyses, cardioprotective antihypertensive medication exposure was associated significantly with younger age, female sex, nonwhite race, intact functional status, and use of in-center hemodialysis. Diabetes was associated with a statistically significant 28% higher odds of ACE-inhibitor/ARB use, but congestive heart failure was associated with only a 9% increase in the odds of β-blocker use and no increase in ACE-inhibitor/ARB use. There was substantial state-by-state variation in the use of all classes of agents, with a greater than 2.9-fold difference in adjusted-rate ORs between the highest and lowest prescribing states for ACE inhibitors/ARBs and a 3.6-fold difference for β-blockers. LIMITATIONS Limited generalizability beyond study population. CONCLUSIONS In publicly insured long-term dialysis patients with hypertension, there were marked differences in use rates by state, potentially due in part to differences in Medicaid benefits. However, geographic characteristics also were associated with exposure, suggesting clinical uncertainty about the utility of these medications.

Considering health insurance: how do dialysis initiates with Medicaid coverage differ from persons without Medicaid coverage?

BACKGROUND Type of health insurance is an important mediator of medical outcomes in the United States. Medicaid, a jointly sponsored Federal/State programme, is designed to serve medically needy individuals. How these patients differ from non-Medicaid-enrolled incident dialysis patients and how these differences have changed over time have not been systematically examined. METHODS Using data from the United States Renal Data System, we identified individuals initiating dialysis from 1995 to 2004 and categorized their health insurance status. Longitudinal trends in demographic, risk behaviour, functional, comorbidity, laboratory and dialysis modality factors, as reported on the Medical Evidence Form (CMS-2728), were examined in all insurance groups. Polychotomous logistic regression was used to estimate adjusted generalized ratios (AGRs) for these factors by insurance status, with Medicaid as the referent insurance group. RESULTS Overall, males constitute a growing percentage of both Medicaid and non-Medicaid patients, but in contrast to other insurance groups, Medicaid has a higher proportion of females. Non-Caucasians also constitute a higher proportion of Medicaid patients than non-Medicaid patients. Body mass index increased in all groups over time, and all groups witnessed a significant decrease in initiation on peritoneal dialysis. Polychotomous regression showed generally lower AGRs for minorities, risk behaviours and functional status, and higher AGRs for males, employment and self-care dialysis, for non-Medicaid insurance relative to Medicaid. CONCLUSIONS While many broad parallel trends are evident in both Medicaid and non-Medicaid incident dialysis patients, many important differences between these groups exist. These findings could have important implications for policy planners, providers and payers.

Has Dialysis Payment Reform Led to Initial Racial Disparities in Anemia and Mineral Metabolism Management

Implementation of the Medicare ESRD prospective payment system (PPS) and changes to dosing guidelines for erythropoiesis-stimulating agents (ESAs) in 2011 appear to have influenced use of injectable medications among dialysis patients. Given historically higher ESA and vitamin D use among black patients, we assessed the effect of these policy changes on racial disparities in the management of anemia and mineral metabolism. Analyses used cross-sectional monthly cohorts for a period-prevalent sample of 7384 maintenance hemodialysis patients at 132 facilities from the Dialysis Outcomes and Practice Patterns Study (DOPPS) Practice Monitor. Linear splines with knots at each policy change were used in survey-weighted regressions to estimate time trends in hemoglobin (Hgb), erythropoietin (EPO) dose, intravenous (IV) iron dose, ferritin, transferrin saturation (TSAT) concentration, parathyroid hormone (PTH), IV vitamin D dose, cinacalcet use, and phosphate binder use. From August 2010 to December 2011, mean Hgb declined from 11.5 to 11.0 g/dl (P<0.001), mean EPO dose declined from 20,506 to 14,777 U/wk (P<0.001), and mean serum PTH increased from 340 to 435 pg/ml (P<0.001). No meaningful differences by race were observed regarding the rates of change of management practices or laboratory measures (all P>0.21). Mean EPO and vitamin D dose and serum PTH levels remained higher in blacks. Despite evidence that anemia and mineral metabolism management practices have changed significantly over time, there was no immediate indication of racial disparities resulting from implementation of the PPS or ESA label change. Further studies are needed to examine effects among patient and facility subgroups.

Association of Race with Cumulative Exposure to Statins in Dialysis

Background: Patients on dialysis have high rates of cardiovascular disease and are frequently treated with HMG-CoA reductase inhibitors. Given that these patients have insurance coverage for medications as well as regular contact with health care providers, differences by race in exposure to statins over time should be minimal among patients who are candidates for the drug. Methods: We created a cohort of incident dialysis patients who were dually eligible for Medicare and Medicaid services. We determined the proportion of days covered (or PDC, a marker of cumulative medication exposure) by a statin prescription over a mean of 2.0 ± 1.4 years. Ordinary least squares regression was used to determine the factors associated with cumulative drug exposure. Results: Of the 18,727 patients who filled at least one prescription for a statin, mean PDC was 0.57 ± 0.32. The unadjusted PDC was higher for Caucasians (0.63 ± 0.31) than for African-Americans (0.51 ± 0.32), Hispanics (0.54 ± 0.31), and individuals of other race/ethnicity (0.58 ± 0.32). In multivariable modeling, Caucasian race was independently associated with greater exposure to statins. Relative to Caucasians, the adjusted odds ratios for the PDC for African-Americans was 0.47 (95% confidence interval, CI, 0.43–0.50), for Hispanics 0.52 (0.48–0.56) and for others, 0.72 (0.64–0.81). Conclusions: Despite insurance coverage, regular contact with health care providers, and at least one prescription for a statin, there are large differences by race in statin exposure over time. The provider- and patient-associated factors related to this phenomenon should be further examined.

Impact of Race on Cumulative Exposure to Antihypertensive Medications in Dialysis

BACKGROUND Racial minorities typically have less exposure than non-minorities to antihypertensive medications across an array of cardiovascular conditions in the general population. However, cumulative exposure has not been investigated in dialysis patients. METHODS In a longitudinal analysis of 38,381 hypertensive dialysis patients, prescription drug data from Medicaid was linked to Medicare data contained in United States Renal Data System core data, creating a national cohort of dialysis patients dually eligible for Medicare and Medicaid services. The proportion of days covered (PDC) was calculated to determine cumulative exposure to angiotensin converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), β-blockers, and calcium-channel blockers (CCDs). The factors associated with use of these medications were modeled through weighted linear regression, with derivation of the adjusted odds ratios (AORs) for exposure. RESULTS Relative to non-Hispanic Caucasians, African-American, Hispanic, or Other race/ethnicity were significantly associated with less exposure to β-blockers (AOR 0.56-0.69, P < 0.001 in each case) and CCBs (AOR 0.84-0.85, P < 0.001 in each case); African-American race and Hispanic ethnicity had AORs of 0.78 and 0.73 for ACEIs and ARBs, respectively (P < 0.001 in both cases). Collectively, the odds of exposure to each class of medication for minorities was about three-quarters of that for Caucasians. CONCLUSIONS Given that dually Medicare-and-Medicaid-eligible dialysis patients have insurance coverage for prescription medications as well as regular contact with health care providers, differences by race in exposure to antihypertensive medications should with time be minimal among patients who are candidates for these drugs. The causes of differences by race in exposure to antihypertensive medications over the course of time should be further examined.

Geographic Variation in HMG-CoA Reductase Inhibitor Use in Dialysis Patients

BackgroundDespite uncertainty about their effectiveness in chronic dialysis patients, statin use has increased in recent years. Little is known about the demographic, clinical, and geographic factors associated with statin exposure in end-stage renal disease (ESRD) patients.ObjectiveTo analyze the demographic, clinical, and geographic factors associated with use of statins among chronic dialysis patients.DesignCross-sectional analysis.SettingPrevalent dialysis patients across the U.S.Participants55,573 chronic dialysis patients who were dually eligible for Medicaid and Medicare services during the last four months of 2005.MethodsUsing Medicaid prescription drug claims and United States Renal Data System core data, we examined demographics, comorbid conditions, and state of residence using hierarchical logistic regression models to determine their associations with statin use.InterventionPrescription for a statin.Outcome MeasuresFactors associated with a prescription for a statin.ResultsStatin exposure was significantly associated with older age, female sex, Caucasian (versus African-American) race, body mass index, use of self-care dialysis, diabetes, and comorbidity burden. Moreover, there was substantial state-by-state variation in statin use, with a greater than 2.3-fold difference in adjusted odds ratios between the highest- and lowest-prescribing states.ConclusionsAmong publicly insured chronic dialysis patients, there were marked differences between states in the use of HMG-CoA reductase inhibitors above and beyond patient characteristics. This suggests substantial clinical uncertainty about the utility of these medications. Understanding how such regional variations impact patient care in this high-risk population is an important focus for future work.

Obtaining Prediction Intervals for Farima Processes Using the Sieve Bootstrap

The sieve bootstrap (SB) prediction intervals for invertible autoregressive moving average (ARMA) processes are constructed using resamples of residuals obtained by fitting a finite degree autoregressive approximation to the time series. The advantage of this approach is that it does not require the knowledge of the orders, p and q, associated with the ARMA(p, q) model. Up until recently, the application of this method has been limited to ARMA processes whose autoregressive polynomials do not have fractional unit roots. The authors, in a 2012 publication, introduced a version of the SB suitable for fractionally integrated autoregressive moving average (FARIMA (p,d,q)) processes with 0<d<0.5 and established its asymptotic validity. Herein, we study the finite sample properties this new method and compare its performance against an older method introduced by Bisaglia and Grigoletto in 2001. The sieve bootstrap (SB) method is a numerically simpler alternative to the older method which requires the estimation of p, d, and q at every bootstrap step. Monte-Carlo simulation studies, carried out under the assumption of normal, mixture of normals, and exponential distributions for the innovations, show near nominal coverages for short-term and long-term SB prediction intervals under most situations. In addition, the sieve bootstrap method yields better coverage and narrower intervals compared to the Bisaglia–Grigoletto method in some situations, especially when the error distribution is a mixture of normals.

The Zero-Truncated Poisson With Right Censoring: An Application to Translational Breast Cancer Research

We propose to analyze positive count data with right censoring from Behbod et al. (2009) using the censored zero-truncated Poisson (CZTP) model. The comparison in truncated means across subgroups in each cell line is carried out through a log-linear model that links the untruncated Poisson parameter and regression covariates. We also perform simulation to evaluate the performance of the CZTP model in finite and large sample sizes. In general, the CZTP model provides accurate and precise estimates. However, for data with small means and small sample sizes, it may be more proper to make inference based on the mean counts rather than on the regression coefficients. For small sample sizes and moderate means, the likelihood ratio test is more reliable than the Wald test. We also demonstrate how power analysis can be used to justify and/or guide the choice of censoring thresholds in study design. A SAS macro is provided in the Appendix for readers’ reference.