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Introduction: While randomized controlled trials remain the reference standard for evaluating treatment efficacy, there is an increased interest in the use of external control arms (ECA), namely in oncology, using real-world data (RWD). Challenges related to measurement of real-world oncology endpoints, like progression-free survival (PFS), are one factor limiting the use and acceptance of ECAs as comparators to trial populations. Differences in how and when disease assessments occur in the real-world may introduce measurement error and limit the comparability of real-world PFS (rwPFS) to trial progression-free survival. While measurement error is a known challenge when conducting an externally-controlled trial with real-world data, there is limited literature describing key contributing factors, particularly in the context of multiple myeloma (MM).Methods: We distinguish between biases attributed to how endpoints are derived or ascertained (misclassification bias) and when outcomes are observed or assessed (surveillance bias). We further describe how misclassification of progression events (i.e., false positives, false negatives) and irregular assessment frequencies in multiple myeloma RWD can contribute to these biases, respectively. We conduct a simulation study to illustrate how these biases may behave, both individually and together.Results: We observe in simulation that certain types of measurement error may have more substantial impacts on comparability between mismeasured median PFS (mPFS) and true mPFS than others. For instance, when the observed progression events are misclassified as either false positives or false negatives, mismeasured mPFS may be biased towards earlier (mPFS bias = −6.4 months) or later times (mPFS bias = 13 months), respectively. However, when events are correctly classified but assessment frequencies are irregular, mismeasured mPFS is more similar to the true mPFS (mPFS bias = 0.67 months).Discussion: When misclassified progression events and irregular assessment times occur simultaneously, they may generate bias that is greater than the sum of their parts. Improved understanding of endpoint measurement error and how resulting biases manifest in RWD is important to the robust construction of ECAs in oncology and beyond. Simulations that quantify the impact of measurement error can help when planning for ECA studies and can contextualize results in the presence of endpoint measurement differences.

The prevalence of multiple age-related cardiovascular disease (CVD) risk factors is high among individuals living in low- and middle-income countries. We described receipt of healthcare services for and management of hypertension and diabetes among individuals living with these conditions using individual-level data from 55 nationally representative population-based surveys (2009-2019) with measured blood pressure (BP) and diabetes biomarker. We restricted our analysis to non-pregnant individuals aged 40-69 years and defined three mutually exclusive groups (i.e., hypertension only, diabetes only, and both hypertension-diabetes) to compare individuals living with concurrent hypertension and diabetes to individuals with each condition separately. We included 90,086 individuals who lived with hypertension only, 11,975 with diabetes only, and 16,228 with hypertension-diabetes. We estimated the percentage of individuals who were aware of their diagnosis, used pharmacological therapy, or achieved appropriate hypertension and diabetes management. A greater percentage of individuals with hypertension-diabetes were fully diagnosed (64.1% [95% CI: 61.8-66.4]) than those with hypertension only (47.4% [45.3-49.6]) or diabetes only (46.7% [44.1-49.2]). Among the hypertension-diabetes group, pharmacological treatment was higher for individual conditions (38.3% [95% CI: 34.8-41.8] using antihypertensive and 42.3% [95% CI: 39.4-45.2] using glucose-lowering medications) than for both conditions jointly (24.6% [95% CI: 22.1-27.2]).The percentage of individuals achieving appropriate management was highest in the hypertension group (17.6% [16.4-18.8]), followed by diabetes (13.3% [10.7-15.8]) and hypertension-diabetes (6.6% [5.4-7.8]) groups. Although health systems in LMICs are reaching a larger share of individuals living with both hypertension and diabetes than those living with just one of these conditions, only seven percent achieved both BP and blood glucose treatment targets. Implementation of cost-effective population-level interventions that shift clinical care paradigm from disease-specific to comprehensive CVD care are urgently needed for all three groups, especially for those with multiple CVD risk factors.

PurposeMissing data is a key methodological consideration in longitudinal studies of aging. We described missing data challenges and potential methodological solutions using a case example describing five-year frailty state transitions in a cohort of older adults.MethodsWe used longitudinal data from the National Health and Aging Trends Study, a nationally-representative cohort of Medicare beneficiaries. We assessed the five components of the Fried frailty phenotype and classified frailty based on their number of components (robust: 0, prefrail: 1-2, frail: 3-5). One-, two-, and five-year frailty state transitions were defined as movements between frailty states or death. Missing frailty components were imputed using hot deck imputation. Inverse probability weights were used to account for potentially informative loss-to-follow-up. We conducted scenario analyses to test a range of assumptions related to missing data.ResultsMissing data were common for frailty components measured using physical assessments (walking speed, grip strength). At five years, 36% of individuals were lost-to-follow-up, differentially with respect to baseline frailty status. Assumptions for missing data mechanisms impacted inference regarding individuals improving or worsening in frailty.ConclusionsMissing data and loss-to-follow-up are common in longitudinal studies of aging. Robust epidemiologic methods can improve the rigor and interpretability of aging-related research.

Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies.

Background Randomized trials demonstrate the cardioprotective effects of sodium‐glucose cotransporter 2 inhibitors (SGLT2i) and glucagon‐like peptide‐1 receptor agonists (GLP‐1RA). We evaluated their relative cardiovascular effectiveness in routine care populations with a broad spectrum of atherosclerotic cardiovascular diseases (CVDs) or heart failure (HF). Methods and Results We identified Medicare beneficiaries from 2013 to 2017, aged >65 years, initiating SGLT2i (n=24 747) or GLP‐1RA (n=22 596) after a 1‐year baseline. On the basis of diagnoses during baseline, we classified patients into: (1) no HF or CVD, (2) HF but no CVD, (3) no HF but CVD, and (4) both HF and CVD. We identified hospitalized HF and atherosclerotic CVD outcomes from drug initiation until treatment changes, death, or disenrollment. We estimated propensity score–weighted 2‐year risk ratios (RRs) and risk differences, accounting for measured confounding, informative censoring, and competing risk. In patients with no CVD or HF, SGLT2i reduced the hospitalized HF risk compared with GLP‐1RA (propensity score–weighted RR, 0.65; 95% CI, 0.43–0.96). The association was strongest in those who had HF but no CVD (RR, 0.48; 95% CI, 0.25–0.85). The combined myocardial infarction, stroke, and mortality outcome risk was slightly higher for SGLT2i compared with GLP‐1RA in those without CVD or HF (RR, 1.31; 95% CI, 1.09–1.56). The association was favorable toward SGLT2i in subgroups with a history of HF. Conclusions SGLT2i reduced the cardiovascular risk versus GLP‐1RA in patients with a history of HF but no CVD. Atherosclerotic CVD events were less frequent with GLP‐1RA in those without prior CVD or HF.

BackgroundWhile vaccination is the most important way to combat the SARS-CoV-2 pandemic, there may still be a need for early outpatient treatment that is safe, inexpensive, and currently widely available in parts of the world that do not have access to the vaccine. There are in-silico, in-vitro, and in-tissue data suggesting that metformin inhibits the viral life cycle, as well as observational data suggesting that metformin use before infection with SARS-CoV2 is associated with less severe COVID-19. Previous observational analyses from single-center cohorts have been limited by size.MethodsConducted a retrospective cohort analysis in adults with type 2 diabetes (T2DM) for associations between metformin use and COVID-19 outcomes with an active comparator design of prevalent users of therapeutically equivalent diabetes monotherapy: metformin versus dipeptidyl-peptidase-4-inhibitors (DPP4i) and sulfonylureas (SU). This took place in the National COVID Cohort Collaborative (N3C) longitudinal U.S. cohort of adults with +SARS-CoV-2 result between January 1 2020 to June 1 2021. Findings included hospitalization or ventilation or mortality from COVID-19. Back pain was assessed as a negative control outcome.Results6,626 adults with T2DM and +SARS-CoV-2 from 36 sites. Mean age was 60.7 +/- 12.0 years; 48.7% male; 56.7% White, 21.9% Black, 3.5% Asian, and 16.7% Latinx. Mean BMI was 34.1 +/- 7.8kg/m2. Overall 14.5% of the sample was hospitalized; 1.5% received mechanical ventilation; and 1.8% died. In adjusted outcomes, compared to DPP4i, metformin had non-significant associations with reduced need for ventilation (RR 0.68, 0.32-1.44), and mortality (RR 0.82, 0.41-1.64). Compared to SU, metformin was associated with a lower risk of ventilation (RR 0.5, 95% CI 0.28-0.98, p = 0.044) and mortality (RR 0.56, 95%CI 0.33-0.97, p = 0.037). There was no difference in unadjusted or adjusted results of the negative control.ConclusionsThere were clinically significant associations between metformin use and less severe COVID-19 compared to SU, but not compared to DPP4i. New-user studies and randomized trials are needed to assess early outpatient treatment and post-exposure prophylaxis with therapeutics that are safe in adults, children, pregnancy and available worldwide.

Introduction Increasingly in pharmacoepidemiology, linking is required to enrich analytic data to more accurately define study populations, enable adjustment for confounding, and improve capture of health outcomes. When creating such novel linked datasets, researchers should consider their suitability to meet research objectives, assess source data completeness and population coverage, and ensure well-defined data governance standards and protections exist. Additionally, while the RECORD-PE guidelines assist in the reporting of studies using observational health data specific to pharmacoepidemiology, they do not address the unique requirements for transparent evaluation and reporting of the data linkage process. Objectives and Approach We aimed to 1) provide guidance on data linkage appropriateness and feasibility to plan purposeful and sustainable new linkages that advance pharmacoepidemiological research and 2) generate a checklist with specific recommendations to assist researchers in providing clear and transparent assessment of the linkage process. To develop these guidelines, a working group comprised of members of the International Society of harmacoepidemiology was formed. Recommendations were open for comment by Society members and endorsed by the Society. Results Guidance for feasibility assessment was categorized into five domains: (1) research objectives and justification; (2) data quality and completeness; (3) the linkage process; (4) data ownership and governance; and (5) overall value added by linkage. A checklist for evaluation and reporting of data-linkage processes covered five domains including; (1) data sources; (2) linkage variables; (3) linkage methods; (4) linkage results; and (5) linkage evaluation, including validation and verification of the resulting linked data. Conclusion/Implications Our guidelines for data linkage feasibility assessment and reporting can be used to inform the design of sustainable linked data resources and for transparent communication of linkage processes. Together, these guidelines will help various stakeholders to critically assess the potential for bias in research based on linked data and help generate actionable evidence.

BackgroundSodium-glucose cotransporter-2 inhibitors (SGLT2i) have been associated with increased occurrence of Fournier’s gangrene (FG), a rare but serious form of necrotizing fasciitis, leading to a warning from the Food and Drug Administration. Real-world evidence on FG is needed to validate this warning.MethodsWe used data from IBM MarketScan (2013–2017) to compare the incidence of FG among adult patients who initiated either SGLT2i, a dipeptidyl peptidase-4 inhibitor (DPP4i), or any non-SGLT2i antihyperglycemic medication. FG was defined using inpatient International Classification of Diseases, Ninth Edition and Tenth Edition diagnosis codes 608.83 and N49.3, respectively, combined with procedure codes for debridement, surgery, or systemic antibiotics. We estimated crude incidence rates (IRs) using Poisson regression, and crude and adjusted HRs (aHR) and 95% CIs using standardized mortality ratio-weighted Cox proportional hazards models. Sensitivity analyses examined the impact of alternative outcome definitions.ResultsWe identified 211 671 initiators of SGLT2i (n=93 197) and DPP4i (n=118 474), and 305 329 initiators of SGLT2i (n=32 868) and non-SGLT2i (n=272 461). Crude FG IR ranged from 3.2 to 3.8 cases per 100 000 person-years during a median follow-up of 0.51–0.58 years. Compared with DPP4i, SGLT2i initiation was not associated with increased risk of FG for any outcome definition, with aHR estimates ranging from 0.25 (0.04–1.74) to 1.14 (0.86–1.51). In the non-SGLT2i comparison, we observed an increased risk of FG for SGLT2i initiators when using FG diagnosis codes alone, using all diagnosis settings (aHR 1.80; 0.53–6.11) and inpatient diagnoses only (aHR 4.58; 0.99–21.21).ConclusionsNo evidence of increased risk of FG associated with SGLT2i was observed compared with DPP4i, arguably the most relevant clinical comparison. However, uncertainty remains based on potentially higher risk in the broader comparison with all non-SGLT2i antihyperglycemic agents and the rarity of FG.Trial registration numberEUPAS Register Number 30018.

Introduction: In older patients with axis fractures, the survival benefit from surgery is unclear due to high baseline mortality. Comparative effectiveness research can provide evidence from population level cohorts. Propensity weighting is the preferred methodology for reducing bias when analyzing national administrative cohort data for these purposes but has not yet been utilized for this important surgical conundrum. We estimate the effect of surgery on mortality after isolated acute traumatic axis fracture in older adults. Materials and Methods: We used a retrospective population-based cohort of Medicare patients and generated a propensity score-weighted nonsurgical cohort and compared mortality with and without surgery. This balanced the comorbid conditions of the treatment groups. Incident fractures were defined using a predetermined algorithm based on enrollment, code timing, and billing location. The primary outcome was adjusted all-cause 1-year mortality. Results: From 12 372 beneficiaries with 1-year continuous enrollment and a coded axis fracture, 2676 patients met final inclusion/exclusion criteria. Estimated incidence was 16.5 per 100 000 person-years overall in 2014 (95% confidence interval [CI]: 15.0-18.0) and was stable from 2008 through 2014. Patients with axis fracture had a mean age of 82.8 years, 30.2% were male, and 91.9% were Caucasian. Mortality was 3.8 times higher (CI 3.6-4.1) compared with the general population of older US adults. Propensity-weighted mortality at 1 year for nonsurgical patients was 26.7 of 100 (CI: 24.5-29.0). Mortality for surgical patients was significantly lower (19.7/100; CI 14.5-25.0). Risk difference was 7.0 fewer surgical deaths per 100 patients (CI: 1.3-12.7). Surgical patients aged 65 to 74 years had the largest difference in mortality with 11.2 fewer deaths per 100 (CI: 1.1-21.3). Discussion: Patients with axis fractures are predominantly older Caucasian women and have a higher mortality rate than the general population. Propensity-weighted mortality at 1-year was lower in the surgical patients with the largest risk difference occurring in patients 65 to 74 years old. Conclusions: Surgery may provide an independent survival benefit in patients aged 65 to 75 years, and the mortality difference diminishes thereafter.

Abstract Background Research suggests antihypertensive medications are associated with fractures in older adults, however results are inconsistent and few have examined how the association varies over time. We sought to examine the association between antihypertensive class and incident non-vertebral fractures among older adults initiating monotherapy according to time since initiation. Methods We used a new-user cohort design to identify Medicare beneficiaries (≥ 65 years of age) initiating antihypertensive monotherapy during 2008–2011 using a 20% random sample of Fee-For-Service Medicare beneficiaries enrolled in parts A (inpatient services), B (outpatient services), and D (prescription medication) coverage. Starting the day after the initial antihypertensive prescription, we followed beneficiaries for incident non-vertebral fractures. We used multinomial logistic regression models to estimate propensity scores for initiating each antihypertensive drug class. Using these propensity scores, we weighted beneficiaries to achieve the same baseline covariate distribution as beneficiaries initiating with angiotensin-converting enzyme inhibitors. Lastly, we used weighted Cox proportional hazard models to estimate hazard ratios (HRs) of having an incident fractures according to antihypertensive class and time since initiation. Results During 2008–2011, 122,629 Medicare beneficiaries initiated antihypertensive monotherapy (mean age 75, 61% women, 86% White). Fracture rates varied according to days since initiation and antihypertensive class. Beneficiaries initiating with thiazides had the highest fracture rate in the first 14 days following initiation (438 per 10,000 person-years, 95% confidence interval (CI): 294–628; HR: 1.40, 0.78–2.52). However, beneficiaries initiating with calcium channel blockers had the highest fracture rate during the 15–365 days after initiation (435 per 10,000 person-years, 95% CI: 404–468; HR: 1.11, 1.00–1.24). Beneficiaries initiating with angiotensin-receptor blockers had the lowest fracture rates during the initial 14 days (333 per 10,000 person-years, 190–546, HR: 0.92, 0.49–1.75) and during 15–365 days after initiation (321 per 10,000 person-years, 287–358, HR: 0.96, 0.84–1.09). Conclusion The association between antihypertensives and fractures varied according to class and time since initiation. Results suggest that when deciding upon antihypertensive therapy, clinicians may want to consider possible fracture risks when choosing between antihypertensive drug classes.

OBJECTIVE:To evaluate trends and identify predictors of treatment initiation of oral anti-diabetic drugs (OAD) in youth. PATIENTS AND METHODS:We identified a select population of children, ages 8-18 years, with at least 13 months of continuous health plan coverage within the years 2001-2012 in a large US commercial insurance claims database. New use of an OAD was defined as the first claim for an outpatient dispensing following a 12-month wash out period. Treatment incidence was estimated monthly over the study period, and stratified by age, gender, geographic region, and provider specialty. RESULTS:The median size of the source population during the study period was 2.2 million children. A total of 13,824 initiators (mean monthly incidence of 4.6 (95% CI = 3.6, 5.5) per 100,000 youths) were identified. Initiators were more likely to be females, age 15-18, from the southern region, and have visited a family practitioner (versus a general pediatrician) prior to initiation. Time trends demonstrate a 43% increase in initiation from 2002-2012, with a gradual decrease starting from early 2008. CONCLUSION:Incidence of filled OAD medications in youth increased over time, especially for patients treated by family practitioners. Additional research is needed into factors influencing prescribing by family practitioners and pediatricians.

Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD.

Recent studies suggested that insulin glargine use could be associated with increased risk of cancer. We compared the incidence of cancer in new users of glargine versus new users of NPH in a longitudinal clinical cohort with diabetes for up to 6 years.From all patients who had been regularly followed at Massachusetts General Hospital from 1/01/2005 to 12/31/2010, 3,680 patients who had a medication record for glargine or NPH usage were obtained from the electronic medical record (EMR). From those we selected 539 new glargine users (age: 60.1±13.6 years, BMI: 32.7±7.5 kg/m2) and 343 new NPH users (61.5±14.1 years, 32.7±8.3 kg/m2) who had no prevalent cancer during 19 months prior to glargine or NPH initiation. All incident cancer cases were ascertained from the EMR requiring at least 2 ICD-9 codes within a 2 month period. Insulin exposure time and cumulative dose were validated. The statistical analysis compared the rates of cancer in new glargine vs. new NPH users while on treatment, adjusted for the propensity to receive one or the other insulin. There were 26 and 28 new cancer cases in new glargine and new NPH users for 1559 and 1126 person-years follow-up, respectively. There were no differences in the propensity-adjusted clinical characteristics between groups. The adjusted hazard ratio for the cancer incidence comparing glargine vs. NPH use was 0.65 (95% CI: 0.36-1.19).Insulin glargine is not associated with development of cancers when compared with NPH in this longitudinal and carefully retrieved EMR data.

Channeling occurs when a medication and its potential comparators are selectively prescribed based on differences in underlying patient characteristics. Drug safety advisories can provide new information regarding the relative safety or effectiveness of a drug product which might increase selective prescribing. In particular, when reported adverse effects vary among drugs within a therapeutic class, clinicians may channel patients toward or away from a drug based on the patient's underlying risk for an adverse outcome. If channeling is not identified and appropriately managed it might lead to confounding in observational comparative effectiveness studies.To demonstrate channeling among new users of second generation antipsychotics following a Food and Drug Administration safety advisory and to evaluate the impact of channeling on cardiovascular risk estimates over time.Florida Medicaid data from 2001-2006.Retrospective cohort of adults initiating second generation antipsychotics. We used propensity scores to match olanzapine initiators with other second generation antipsychotic initiators. To evaluate channeling away from olanzapine following an FDA safety advisory, we estimated calendar time-specific propensity scores. We compare the performance of these calendar time-specific propensity scores with conventionally-estimated propensity scores on estimates of cardiovascular risk.Increased channeling away from olanzapine was evident for some, but not all, cardiovascular risk factors and corresponded with the timing of the FDA advisory. Covariate balance was optimized within period and across all periods when using the calendar time-specific propensity score. Hazard ratio estimates for cardiovascular outcomes did not differ across models (Conventional PS: 0.97, 95%CI: 0.81-3.18 versus calendar time-specific PS: 0.93, 95%CI: 0.77-3.04).Changes in channeling over time was evident for several covariates but had limited impact on cardiovascular risk estimates, possibly due to unmeasured confounding. Although calendar time-specific propensity scores appear to improve covariate balance, the impact on comparative effectiveness results is limited in this setting.

Rotavirus vaccines are highly effective at preventing gastroenteritis in young children and are now universally recommended for infants in the US. We studied patterns of use of rotavirus vaccines among US infants with commercial insurance. We identified a large cohort of infants in the MarketScan Research Databases, 2006-2010. The analysis was restricted to infants residing in states without state-funded rotavirus vaccination programs. We computed summary statistics and used multivariable regression to assess the association between patient-, provider-, and ecologic-level variables of rotavirus vaccine receipt and series completion. Approximately 69% of 594,117 eligible infants received at least one dose of rotavirus vaccine from 2006-2010. Most infants received the rotavirus vaccines at the recommended ages, but more infants completed the series for monovalent rotavirus vaccine than pentavalent rotavirus vaccine or a mix of the vaccines (87% versus 79% versus 73%, P

The Infectious Disease Society of America (IDSA) 2010 Clinical Practice Guidelines for the management of cryptococcosis outlined three key populations at risk of disease: (1) HIV-infected, (2) transplant recipient, and (3) HIV-negative/non-transplant. However, direct comparisons of management, severity and outcomes of these groups have not been conducted.Annual changes in frequency of cryptococcosis diagnoses, cryptococcosis-attributable mortality and mortality were captured. Differences examined between severe and non-severe disease within the context of the three groups included: demographics, symptoms, microbiology, clinical management and treatment. An average of nearly 15 patients per year presented at Duke University Medical Center (DUMC) with cryptococcosis. Out of 207 study patients, 86 (42%) were HIV-positive, 42 (20%) were transplant recipients, and 79 (38%) were HIV-negative/non-transplant. HIV-infected individuals had profound CD4 lymphocytopenia and a majority had elevated intracranial pressure. Transplant recipients commonly (38%) had renal dysfunction. Nearly one-quarter (24%) had their immunosuppressive regimens stopped or changed. The HIV-negative/non-transplant population reported longer duration of symptoms than HIV-positive or transplant recipients and 28% (22/79) had liver insufficiency or underlying hematological malignancies. HIV-positive and HIV-negative/non-transplant patients accounted for 89% of severe disease cryptococcosis-attributable deaths and 86% of all-cause mortality.In this single-center study, the frequency of cryptococcosis did not change in the last two decades, although the underlying case mix shifted (fewer HIV-positive cases, stable transplant cases, more cases with neither). Cryptococcosis had a relatively uniform and informed treatment strategy, but disease-attributable mortality was still common.

Controversy persists regarding the cardiovascular risks of treatment with selective cyclooxygenase 2 inhibitors (coxibs) and nonselective nonsteroidal antiinflammatory drugs (NSAIDs). This study was undertaken to examine, in a large group of new users of coxibs and NSAIDs, the rate of cardiovascular events, their time course, and whether baseline cardiovascular risk modified the rate ratios (RRs) for future events.This cohort study included Medicare beneficiaries who enrolled in a state‐run prescription drug plan that fully covered NSAIDs and coxibs without restriction. All study patients started use of a coxib or NSAID after January 1, 1999. The primary composite end point was a hospital admission for either myocardial infarction or ischemic stroke. Predefined exposure groups included the 3 coxibs available in the US during the study period (celecoxib, rofecoxib, and valdecoxib), as well as oral formulations of diclofenac, ibuprofen, naproxen, and a composite of all other NSAIDs. We compared the rate of cardiovascular events associated with each of these agents with that in a reference group of patients who did not use NSAIDs or coxibs, but started other medications unrelated to cardiovascular risk. Daily exposure to all study drugs was assessed based on filled prescription data. A Cox proportional hazards model stratified on calendar year that included other baseline cardiovascular risk factors constituted the primary analysis.We identified 74,838 users of NSAIDs or coxibs, and 23,532 comparable users of other drugs comprised the reference group. Adjusted models demonstrated a significant elevation in the event rate for rofecoxib (RR 1.15, 95% confidence interval [95% CI] 1.06–1.25) and a significant reduction in the rate for naproxen (RR 0.75, 95% CI 0.62–0.92). No other coxib or NSAID was associated with a significant increase or decrease in cardiovascular event rate. The increased rate associated with rofecoxib was seen in the first 60 days of use (adjusted RR 1.14, 95% CI 1.01–1.29) and thereafter (adjusted RR 1.14, 95% CI 1.02–1.28). Kaplan‐Meier event curves showed a similar pattern of risk (early and persistent separation of the event curves) among long‐term rofecoxib users at low or high baseline cardiovascular risk.We found an increased cardiovascular event rate among users of rofecoxib, and a decreased rate with naproxen use. Other coxibs and NSAIDs did not appear to be associated with a difference in event rate compared with users of other drugs. The increase in rate associated with rofecoxib was seen within the first 60 days and persisted. There was no important modification of the event rate based on the patient''s baseline cardiovascular risk. [ABSTRACT FROM AUTHOR]

Intensity-modulated radiation therapy (IMRT), an innovative treatment option for prostate cancer, has rapidly diffused over the past decade. To inform our understanding of racial disparities in prostate cancer treatment and outcomes, this study compared diffusion of IMRT in African American (AA) and Caucasian American (CA) prostate cancer patients during the early years of IMRT diffusion using the Surveillance, Epidemiology and End Results (SEER)–Medicare linked database. A retrospective cohort of 947 AA and 10,028 CA patients diagnosed with localized prostate cancer from 2002 through 2006, who were treated with either IMRT or non-IMRT as primary treatment within 1 year of diagnoses was constructed. Logistic regression was used to examine potential differences in diffusion of IMRT in AA and CA patients, while adjusting for socioeconomic and clinical covariates. A significantly smaller proportion of AA compared with CA patients received IMRT for localized prostate cancer (45% vs. 53%, p < .0001). Racial differences were apparent in multivariable analysis though did not achieve statistical significance, as time and factors associated with race (socioeconomic, geographic, and tumor related factors) explained the preponderance of variance in use of IMRT. Further research examining improved access to innovative cancer treatment and technologies is essential to reducing racial disparities in cancer care.

A number of covariate-balancing methods, based on the propensity score, are widely used to estimate treatment effects in observational studies. If the treatment effect varies with the propensity score, however, different methods can give very different answers. The authors illustrate this effect by using data from a United Kingdom–based registry of subjects treated with anti–tumor necrosis factor drugs for rheumatoid arthritis. Estimates of the effect of these drugs on mortality varied from a relative risk of 0.4 (95% confidence interval: 0.16, 0.91) to a relative risk of 1.3 (95% confidence interval: 0.8, 2.25), depending on the balancing method chosen. The authors show that these differences were due to a combination of an interaction between propensity score and treatment effect and to differences in weighting subjects with different propensity scores. Thus, the methods are being used to calculate average treatment effects in populations with very different distributions of effect-modifying variables, resulting in different overall estimates. This phenomenon highlights the importance of careful selection of the covariate-balancing method so that the overall estimate has a meaningful interpretation. [ABSTRACT FROM AUTHOR]

Confounding can be a major source of bias in nonexperimental research. The authors recently introduced propensity score calibration (PSC), which combines propensity scores and regression calibration to address confounding by variables unobserved in the main study by using variables observed in a validation study. Here, the authors assess the performance of PSC using simulations in settings with and without violation of the key assumption of PSC: that the error-prone propensity score estimated in the main study is a surrogate for the gold-standard propensity score (i.e., it contains no additional information on the outcome). The assumption can be assessed if data on the outcome are available in the validation study. If data are simulated allowing for surrogacy to be violated, results depend largely on the extent of violation. If surrogacy holds, PSC leads to bias reduction between 32% and 106% (>100% representing overcorrection). If surrogacy is violated, PSC can lead to an increase in bias. Surrogacy is violated when the direction of confounding of the exposure-disease association caused by the unobserved variable(s) differs from that of the confounding due to observed variables. When surrogacy holds, PSC is a useful approach to adjust for unmeasured confounding using validation data. [ABSTRACT FROM AUTHOR]