State Laws That Require Coprescribing Opioids and Naloxone and Codispensing Practices

INTRODUCTION

Coprescribing naloxone with opioids could reduce the risk of overdose. By the end of 2020, 8 U.S. states implemented coprescribing laws requiring the prescription of naloxone alongside certain opioid prescriptions. This study examined the impacts of state laws that require coprescribing opioids and naloxone on codispensing practices.

METHODS

Data included opioid prescriptions for commercially insured adults between 2014 and 2020. Augmented synthetic control analyses were used to examine the impacts of 8 coprescribing requirement laws implemented between 2017 and 2020 on the proportion of opioid prescription fills with a naloxone coprescription fill. Analyses were completed in spring 2023.

RESULTS

Changes in the proportion of opioid prescription fills with a naloxone coprescription fill attributable to the laws varied across states. In 4 states (New Jersey, New Mexico, Rhodes Island, and Virginia), laws were associated with 0.8 (95% CI=0.3, 1.3) to 4.4 (95% CI=3.4, 5.4) percentage point increases in the proportion of opioid prescriptions with a naloxone coprescription fill (p<0.05). There were no statistically significant changes attributable to the other state laws (Arizona, Florida, Vermont, Washington).

CONCLUSIONS

Laws requiring coprescribing naloxone with certain opioid prescriptions are associated with small-in-magnitude increases in codispensing in some states. Broadening the categories of opioid prescriptions covered in naloxone coprescribing requirement laws and implementing health system strategies to encourage providers to coprescribe naloxone could help to magnify the impacts of these laws.

Effects of Opioid Prescribing Cap Laws on Opioid and Other Pain Treatments Among Persons with Chronic Pain

BACKGROUND

Many states have adopted laws that limit the amount or duration of opioid prescriptions. These limits often focus on prescriptions for acute pain, but there may be unintended consequences for those diagnosed with chronic pain, including reduced opioid prescribing without substitution of appropriate non-opioid treatments.

OBJECTIVE

To evaluate the effects of state opioid prescribing cap laws on opioid and non-opioid treatment among those diagnosed with chronic pain.

DESIGN

We used a difference-in-differences approach that accounts for staggered policy adoption. Treated states included 32 states that implemented a prescribing cap law between 2017 and 2019.

POPULATION

A total of 480,856 adults in the USA who were continuously enrolled in medical and pharmacy coverage from 2013 to 2019 and diagnosed with a chronic pain condition between 2013 and 2016.

MAIN MEASURES

Among individuals with chronic pain in each state: proportion with at least one opioid prescription and with prescriptions of a specific duration or dose, average number of opioid prescriptions, average opioid prescription duration and dose, proportion with at least one non-opioid chronic pain prescription, average number of such prescriptions, proportion with at least one chronic pain procedure, and average number of such procedures.

KEY RESULTS

State laws limiting opioid prescriptions were not associated with changes in opioid prescribing, non-opioid medication prescribing, or non-opioid chronic pain procedures among patients with chronic pain diagnoses.

CONCLUSIONS

These findings do not support an association between state opioid prescribing cap laws and changes in the treatment of chronic non-cancer pain.

Causal mediation analysis: From simple to more robust strategies for estimation of marginal natural (in)direct effects

This paper aims to provide practitioners of causal mediation analysis with a better understanding of estimation options. We take as inputs two familiar strategies (weighting and model-based prediction) and a simple way of combining them (weighted models), and show how a range of estimators can be generated, with different modeling requirements and robustness properties. The primary goal is to help build intuitive appreciation for robust estimation that is conducive to sound practice. We do this by visualizing the target estimand and the estimation strategies. A second goal is to provide a "menu" of estimators that practitioners can choose from for the estimation of marginal natural (in)direct effects. The estimators generated from this exercise include some that coincide or are similar to existing estimators and others that have not previously appeared in the literature. We note several different ways to estimate the weights for cross-world weighting based on three expressions of the weighting function, including one that is novel; and show how to check the resulting covariate and mediator balance. We use a random continuous weights bootstrap to obtain confidence intervals, and also derive general asymptotic variance formulas for the estimators. The estimators are illustrated using data from an adolescent alcohol use prevention study. R-code is provided.

Causal and Associational Language in Observational Health Research: A Systematic Evaluation

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers' ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.

State prescribing cap laws' association with opioid analgesic prescribing and opioid overdose

INTRODUCTION

In response to the role of opioid prescribing in the U.S. opioid crisis, states have enacted laws intended to curb high risk opioid prescribing practices. This study assessed the effects of state prescribing cap laws that limit the dose and/or duration of dispensed opioid prescriptions on opioid prescribing patterns and opioid overdose.

METHODS

We identified 1,414,908 adults from a large U.S. administrative insurance claims database. Treatment states included 32 states that implemented a prescribing cap law between 2017 and 2019. Comparison states included 16 states and DC without a prescribing cap law by 2019. A difference-in-differences approach with staggered policy adoption was used to assess effects of these laws on opioid analgesic prescribing and opioid overdose.

RESULTS

State opioid prescribing cap laws were not associated with changes in the proportion of people receiving opioid analgesic prescriptions, the dose or duration of opioid prescriptions, or opioid overdose. States with laws that imposed days' supply limits only versus days' supply and dosage limits, as well as with specific law provisions also showed no association with opioid prescribing or opioid overdose outcomes.

CONCLUSIONS

State opioid prescribing cap laws did not appear to impact outcomes related to opioid analgesic prescribing or opioid overdose. These findings are potentially due to the limited scope of these laws, which often apply only to a subset of opioid prescriptions and include professional judgment exemptions.

Effects of state opioid prescribing cap laws on opioid prescribing after surgery

OBJECTIVE

To evaluate the effects of state opioid prescribing cap laws on opioid prescribing after surgery.

DATA SOURCES

OptumLabs Data Warehouse administrative claims data covering all 50 states from July 2012 through June 2019.

STUDY DESIGN

We included individuals from 20 states that had implemented prescribing cap laws without exemptions for postsurgical pain by June 2019 and individuals from 16 control states plus the District of Columbia. We used a difference-in-differences approach accounting for differential timing in law implementation across states to estimate the effects of state prescribing cap laws on postsurgical prescribing of opioids. Outcome measures included filling an opioid prescription within 30 days after surgery; filling opioid prescriptions of specific doses or durations; and the number, days' supply, daily dose, and pill quantity of opioid prescriptions. To assess the validity of the parallel counterfactual trends assumption, we examined differences in outcome trends between law-implementing and control states in the years preceding law implementation using an equivalence testing framework.

DATA COLLECTION/EXTRACTION METHODS

We included the first surgery in the study period for opioid-naïve individuals undergoing one of eight common surgical procedures.

PRINCIPAL FINDINGS

State prescribing cap laws were associated with 0.109 lower days' supply of postsurgical opioids on the log scale (95% Confidence Interval [CI]: -0.139, -0.080) but were not associated with the number (Average treatment effect on the treated [ATT]: -0.011; 95% CI: -0.043, 0.021) or daily dose of postsurgical opioid prescriptions (ATT: -0.013; 95% CI: -0.030, 0.005). The negative association observed between prescribing cap laws and the probability of filling a postsurgical opioid prescription (ATT: -0.041; 95% CI: -0.054, -0.028) was likely spurious, given differences between law-implementing and control states in the pre-law period.

CONCLUSIONS

Prescribing cap laws appear to have minimal effects on postsurgical opioid prescribing.

Scaling Interventions to Manage Chronic Disease: Innovative Methods at the Intersection of Health Policy Research and Implementation Science

Policy implementation is a key component of scaling effective chronic disease prevention and management interventions. Policy can support scale-up by mandating or incentivizing intervention adoption, but enacting a policy is only the first step. Fully implementing a policy designed to facilitate implementation of health interventions often requires a range of accompanying implementation structures, like health IT systems, and implementation strategies, like training. Decision makers need to know what policies can support intervention adoption and how to implement those policies, but to date research on policy implementation is limited and innovative methodological approaches are needed. In December 2021, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness and the Johns Hopkins Center for Mental Health and Addiction Policy convened a forum of research experts to discuss approaches for studying policy implementation. In this report, we summarize the ideas that came out of the forum. First, we describe a motivating example focused on an Affordable Care Act Medicaid health home waiver policy used by some US states to support scale-up of an evidence-based integrated care model shown in clinical trials to improve cardiovascular care for people with serious mental illness. Second, we define key policy implementation components including structures, strategies, and outcomes. Third, we provide an overview of descriptive, predictive and associational, and causal approaches that can be used to study policy implementation. We conclude with discussion of priorities for methodological innovations in policy implementation research, with three key areas identified by forum experts: effect modification methods for making causal inferences about how policies' effects on outcomes vary based on implementation structures/strategies; causal mediation approaches for studying policy implementation mechanisms; and characterizing uncertainty in systems science models. We conclude with discussion of overarching methods considerations for studying policy implementation, including measurement of policy implementation, strategies for studying the role of context in policy implementation, and the importance of considering when establishing causality is the goal of policy implementation research.

Association Between State Opioid Prescribing Cap Laws and Receipt of Opioid Prescriptions Among Children and Adolescents

Importance

High-dose and long-duration opioid prescriptions remain relatively common among children and adolescents, but there is insufficient research on the association of state laws limiting the dose and/or duration of opioid prescriptions (referred to as opioid prescribing cap laws) with opioid prescribing for this group.

Objective

To examine the association between state opioid prescribing cap laws and the receipt of opioid prescriptions among children and adolescents.

Design Setting and Participants

This repeated cross-sectional study used a difference-in-differences approach accounting for staggered policy adoption to assess the association of state opioid prescribing cap laws in the US from January 1, 2013, to December 31, 2019, with receipt of opioid prescriptions among children and adolescents. Analyses were conducted between March 22 and December 15, 2021. Data were obtained from the OptumLabs Data Warehouse, a national commercial insurance claims database. The analysis included 482 118 commercially insured children and adolescents aged 0 to 17 years with full calendar-year continuous insurance enrollment between 2013 and 2019. Individuals were included for every year in which they were continuously enrolled; they did not need to be enrolled for the entire 7-year study period. Those with any cancer diagnosis were excluded from analysis.

Exposure

Implementation of a state opioid prescribing cap law between January 1, 2017, and July 1, 2019. This date range allowed analysis of the same number years for both pre-cap and post-cap data.

Main Outcomes and Measures

Outcomes of interest included receipt of any opioid prescription and, among those with at least 1 opioid prescription, the mean number of opioid prescriptions, mean morphine milligram equivalents (MMEs) per day, and mean days' supply.

Results

Among 482 118 children and adolescents (754 368 person-years of data aggregated to the state-year level), 245 178 (50.9%) were male, with a mean (SD) age of 9.8 (4.8) years at the first year included in the sample (data on race and ethnicity were not collected as part of this data set, which was obtained from insurance billing claims). Overall, 10 659 children and adolescents (2.2%) received at least 1 opioid prescription during the study period. Among those with at least 1 prescription, the mean (SD) number of filled opioid prescriptions was 1.2 (0.8) per person per year. No statistically significant association was found between state opioid prescribing cap laws and any outcome. After opioid prescribing cap laws were implemented, a -0.001 (95% CI, -0.005 to 0.002) percentage point decrease in the proportion of youths receiving any opioid prescription was observed. In addition, percentage point decreases of -0.01 (95% CI, -0.10 to 0.09) in high-dose opioid prescriptions (>50 MMEs per day) and -0.02 (95% CI, -0.12 to 0.08) in long-duration opioid prescriptions (>7 days' supply) were found after cap laws were implemented.

Conclusions and Relevance

In this cross-sectional study, no association was observed between state opioid prescribing cap laws and the receipt of opioid prescriptions among children and adolescents. Alternative strategies, such as opioid prescribing guidelines tailored to youths, are needed.

Factors associated with county-level mental health during the COVID-19 pandemic

The objective of this study is to determine county-level factors associated with anxiety, depression, and isolation during the coronavirus disease 2019 (COVID-19) pandemic. This study used daily data from 23,592,355 respondents of a nationwide Facebook-based survey from April 2020 to July 2021, aggregated to the week-county level to yield 212,581 observations. Mental distress prevalences were modeled using weighted linear mixed-effects models with a county random effect. These models revealed that weekly percentages of mental distress were higher in counties with higher unemployment rates, populations, and education levels; higher percentages of females, young adults, individuals with a medical condition, and individuals very worried about their finances and COVID-19; and lower percentages of individuals who were working outside the home, living with children, without health insurance, and Black. Anxiety peaked in April 2020, depression in October 2020, and isolation in December 2020. Therefore, United States counties experienced the mental health effects of the pandemic differently dependent upon their characteristics, and mental distress prevalence varied across time.

Trends in cannabis use among U.S. adults amid the COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic has had an impact on mental health and alcohol use in the US, however there is little research on its impacts on cannabis use. Considering the role of cannabis as a coping strategy or self-medicating behavior, there is a need to understand how individuals who use cannabis have adapted their use amid the pandemic. Therefore, this study examined changes in self-reported cannabis use among US adults in the context of COVID-19 pandemic by (1) describing trends of use during the first 8 months of the pandemic among adults who used cannabis in this period; and (2) characterizing trends of use within sociodemographic subgroups and by state cannabis policy status.

METHODS

The sample consisted of 1,761 US adults who used cannabis at least once during the 8-month study period from the nationally representative Understanding America Study. Linear mixed-effect models were used to model changes in the number of days of past-week cannabis use across 16 waves from March 10, 2020, to November 11, 2020.

RESULTS

Compared to early March, the number of days cannabis was used per week was significantly higher at the start of April (β=0.11, 95% CI=0.03, 0.18) and May (β=0.21,95% CI=0.05, 0.36). In subsequent months (June - November), the number of days of cannabis use attenuated to levels comparable to March. Trends of cannabis use across the study period generally did not differ across sociodemographic characteristics and state cannabis policy status.

CONCLUSION

Though increases in use were marginal among many groups, the evolving pandemic and the growing concern for the mental health of segments of the U.S. population warrant close monitoring of coping behaviors, including substance use.

Assumptions Not Often Assessed or Satisfied in Published Mediation Analyses in Psychology and Psychiatry

Mediation analysis aims to investigate the mechanisms of action behind the effects of interventions or treatments. Given the history and common use of mediation in mental health research, we conducted this review to understand how mediation analysis is implemented in psychology and psychiatry and whether analyses adhere to, address, or justify the key underlying assumptions of their approaches. All articles (n = 206) were from top academic psychiatry or psychology journals in the PsycInfo database and were published in English from 2013 to 2018. Information extracted from each article related to study design, covariates adjusted for in the analysis, temporal ordering of variables, and the specific method used to perform the mediation analysis. In most studies, underlying assumptions were not adhered to. Only approximately 20% of articles had full temporal ordering of exposure, mediator, and outcome. Confounding of the exposure-mediator and/or mediator-outcome relationships was controlled for in fewer than half of the studies. In almost none of the articles were the underlying assumptions of their approaches discussed or causal mediation methods used. These results provide insights to how methodologists should aim to communicate methods, and motivation for more outreach to the research community on best practices for mediation analysis.

Problems with evidence assessment in COVID-19 health policy impact evaluation: a systematic review of study design and evidence strength

INTRODUCTION

Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment.

METHODS

We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on 26 November 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation.

RESULTS

After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-sectional), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.

DISCUSSION

The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigour to be actionable by policy-makers. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.

Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength

Introduction:

Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.

Methods:

We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.

Results:

After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.

Discussion:

The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policymakers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.

Generalizability of Subgroup Effects

Generalizability methods are increasingly used to make inferences about the effect of interventions in target populations using a study sample. Most existing methods to generalize effects from sample to population rely on the assumption that subgroup-specific effects generalize directly. However, researchers may be concerned that in fact subgroup-specific effects differ between sample and population. In this brief report, we explore the generalizability of subgroup effects. First, we derive the bias in the sample average treatment effect estimator as an estimate of the population average treatment effect when subgroup effects in the sample do not directly generalize. Next, we present a Monte Carlo simulation to explore bias due to unmeasured heterogeneity of subgroup effects across sample and population. Finally, we examine the potential for bias in an illustrative data example. Understanding the generalizability of subgroup effects may lead to increased use of these methods for making externally valid inferences of treatment effects using a study sample.

Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn

The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements-effect definitions with causal interpretation, clarification of assumptions required for effect identification, and an expanding array of options for effect estimation. However, the literature on these results is fast-growing and complex, which may be confusing to researchers unfamiliar with causal inference or unfamiliar with mediation. The goal of this article is to help ease the understanding and adoption of causal mediation analysis. It starts by highlighting a key difference between the causal inference and traditional approaches to mediation analysis and making a case for the need for explicit causal thinking and the causal inference approach in mediation analysis. It then explains in as-plain-as-possible language existing effect types, paying special attention to motivating these effects with different types of research questions, and using concrete examples for illustration. This presentation differentiates 2 perspectives (or purposes of analysis): the explanatory perspective (aiming to explain the total effect) and the interventional perspective (asking questions about hypothetical interventions on the exposure and mediator, or hypothetically modified exposures). For the latter perspective, the article proposes tapping into a general class of interventional effects that contains as special cases most of the usual effect types-interventional direct and indirect effects, controlled direct effects and also a generalized interventional direct effect type, as well as the total effect and overall effect. This general class allows flexible effect definitions which better match many research questions than the standard interventional direct and indirect effects. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Comparing the performance of statistical methods that generalize effect estimates from randomized controlled trials to much larger target populations

Policymakers use results from randomized controlled trials to inform decisions about whether to implement treatments in target populations. Various methods - including inverse probability weighting, outcome modeling, and Targeted Maximum Likelihood Estimation - that use baseline data available in both the trial and target population have been proposed to generalize the trial treatment effect estimate to the target population. Often the target population is significantly larger than the trial sample, which can cause estimation challenges. We conduct simulations to compare the performance of these methods in this setting. We vary the size of the target population, the proportion of the target population selected into the trial, and the complexity of the true selection and outcome models. All methods performed poorly when the trial size was only 2% of the target population size or the target population included only 1,000 units. When the target population or the proportion of units selected into the trial was larger, some methods, such as outcome modeling using Bayesian Additive Regression Trees, performed well. We caution against generalizing using these existing approaches when the target population is much larger than the trial sample and advocate future research strives to improve methods for generalizing to large target populations.

Nimotuzumab and radiotherapy for treatment of newly diagnosed diffuse intrinsic pontine glioma (DIPG): a phase III clinical study

BACKGROUND

Diffuse intrinsic pontine glioma (DIPG) is a devastating cancer of childhood and adolescence.

METHODS

The study included patients between 3 and 20 years with clinically and radiologically confirmed DIPG. Primary endpoint was 6-month progression-free survival (PFS) following administration of nimotuzumab in combination with external beam radiotherapy (RT). Nimotuzumab was administered intravenously at 150 mg/m² weekly for 12 weeks. Radiotherapy at total dose of 54 Gy was delivered between week 3 and week 9. Response was evaluated based on clinical features and MRI findings according to RECIST criteria at week 12. Thereafter, patients continued to receive nimotuzumab every alternate week until disease progression/unmanageable toxicity. Adverse events (AE) were evaluated according to Common Terminology Criteria for Adverse Events (CTC-AE) Version 3.0 (CTC-AE3).

RESULTS

All 42 patients received at least one dose of nimotuzumab in outpatient settings. Two patients had partial response (4.8%), 27 had stable disease (64.3%), 10 had progressive disease (23.8%) and 3 patients (7.1%) could not be evaluated. The objective response rate (ORR) was 4.8%. Median PFS was 5.8 months and median overall survival (OS) was 9.4 months. Most common drug-related AEs were alopecia (14.3%), vomiting, headache and radiation skin injury (7.1% each). Therapy-related serious adverse events (SAEs) were intra-tumoral bleeding and acute respiratory failure, which were difficult to distinguish from effects of tumor progression.

CONCLUSIONS

Concomitant treatment with RT and nimotuzumab was feasible in an outpatient setting. The PFS and OS were comparable to results achieved with RT and intensive chemotherapy in hospitalized setting.

Sensitivity analyses for effect modifiers not observed in the target population when generalizing treatment effects from a randomized controlled trial: Assumptions, models, effect scales, data scenarios, and implementation details

Background

Randomized controlled trials are often used to inform policy and practice for broad populations. The average treatment effect (ATE) for a target population, however, may be different from the ATE observed in a trial if there are effect modifiers whose distribution in the target population is different that from that in the trial. Methods exist to use trial data to estimate the target population ATE, provided the distributions of treatment effect modifiers are observed in both the trial and target population—an assumption that may not hold in practice.

Methods

The proposed sensitivity analyses address the situation where a treatment effect modifier is observed in the trial but not the target population. These methods are based on an outcome model or the combination of such a model and weighting adjustment for observed differences between the trial sample and target population. They accommodate several types of outcome models: linear models (including single time outcome and pre- and post-treatment outcomes) for additive effects, and models with log or logit link for multiplicative effects. We clarify the methods’ assumptions and provide detailed implementation instructions.

Illustration

We illustrate the methods using an example generalizing the effects of an HIV treatment regimen from a randomized trial to a relevant target population.

Conclusion

These methods allow researchers and decision-makers to have more appropriate confidence when drawing conclusions about target population effects.

Propensity Scores in Pharmacoepidemiology: Beyond the Horizon

Purpose of review

Propensity score methods have become commonplace in pharmacoepidemiology over the past decade. Their adoption has confronted formidable obstacles that arise from pharmacoepidemiology's reliance on large healthcare databases of considerable heterogeneity and complexity. These include identifying clinically meaningful samples, defining treatment comparisons, and measuring covariates in ways that respect sound epidemiologic study design. Additional complexities involve correctly modeling treatment decisions in the face of variation in healthcare practice, and dealing with missing information and unmeasured confounding. In this review, we examine the application of propensity score methods in pharmacoepidemiology with particular attention to these and other issues, with an eye towards standards of practice, recent methodological advances, and opportunities for future progress.

Recent findings

Propensity score methods have matured in ways that can advance comparative effectiveness and safety research in pharmacoepidemiology. These include natural extensions for categorical treatments, matching algorithms that can optimize sample size given design constraints, weighting estimators that asymptotically target matched and overlap samples, and the incorporation of machine learning to aid in covariate selection and model building.

Summary

These recent and encouraging advances should be further evaluated through simulation and empirical studies, but nonetheless represent a bright path ahead for the observational study of treatment benefits and harms.

A human immunodeficiency syndrome caused by mutations in CARMIL2

Human T-cell function is dependent on T-cell antigen receptor (TCR) and co-signalling as evidenced by immunodeficiencies affecting TCR-dependent signalling pathways. Here, we show four human patients with EBV⁺ disseminated smooth muscle tumours that carry two homozygous loss-of-function mutations in the CARMIL2 (RLTPR) gene encoding the capping protein regulator and myosin 1 linker 2. These patients lack regulatory T cells without evidence of organ-specific autoimmunity, and have defective CD28 co-signalling associated with impaired T-cell activation, differentiation and function, as well as perturbed cytoskeletal organization associated with T-cell polarity and migration disorders. Human CARMIL2-deficiency is therefore an autosomal recessive primary immunodeficiency disorder associated with defective CD28-mediated TCR co-signalling and impaired cytoskeletal dynamics.

CARMIL2 (Rltpr) is involved in T-cell function. Here, the authors identify human CARMIL2-deficiency as an autosomal recessive primary immunodeficiency disorder characterized by EBV⁺ smooth muscle tumours, CD28 co-signalling deficiency and impaired cytoskeletal dynamics.

Laparoscopic Adrenalectomy is Feasible for Suspected Adrenal Tumors in Children Younger than 24 Months of Age - But is it Always Justified?

INTRODUCTION

Tumors of the adrenal gland are rare in children younger than 24 months of age. While neuroblastomas are most important in this age group, adrenal hemorrhage and other tumors are sometimes difficult to distinguish. Harvesting biopsies is mandatory in these young patients to obtain information on molecular markers, namely, MYCN and 1p deletion.

PATIENTS

Between 03/2012 and 10/2013, 11 patients younger than 24 months of age with suspicious adrenal tumors were operated on laparoscopically.

METHODS

The diagnostic workup was coordinated by our pediatric oncologists according to the terms of the NB2004 trial protocol.

RESULTS

9 out of 11 had a diagnosis of neuroblastoma, the others were adenoma respective complete necrosis of the adrenal gland. All of the neuroblastomas were negative for both MYCN amplification and 1p deletion. A complete resection was successful in 9 out of 11 cases. 3 complications occurred, 1 major and 2 minor.

DISCUSSION AND CONCLUSION

Behind the recognition that laparoscopic adrenalectomy is technically feasible, the fact that all neuroblastomas were negative for MYCN amplification and 1p deletion raises the issue of whether biopsy is mandatory for risk stratification in this age group.

Free asymmetric dimethylarginine (ADMA) is low in children and adolescents with classical phenylketonuria (PKU)

INTRODUCTION

Free asymmetric dimethylarginine (ADMA) is a competitive inhibitor of the nitric oxide synthases (NOS). Suppression of nitric oxide (NO) synthesis increases the risk of atherosclerosis. Nevertheless, in the condition of oxidative stress, NOS blockade by ADMA may exert protective effects. Protein metabolism is altered in patients with phenylketonuria (PKU) on dietary treatment and as shown recently, oxidative stress is high in PKU. Since free ADMA concentrations are determined by both protein metabolism and oxidative stress we hypothesized, that free ADMA levels may be elevated in PKU patients.

DESIGN

Sixteen patientswith PKU on dietary treatment (mean age 10.1 ± 5.2 yrs), and 91 healthy children (mean age 11.6 ± 3.7 yrs) participated in a cross sectional study.

RESULTS

ADMA, total homocysteine (tHcy) and blood glucose were lower and the L-arginine/ADMA ratio was higher in PKU patients compared to controls. No significant correlation was present between phenylalanine (Phe) concentrations, protein intake, and lipid profile, history of cardiovascular disease or ADMA.

DISCUSSION

In contrast to our hypothesis, ADMAwas lower and the L-arginine/ADMA ratio was higher in PKU patients. Therefore, in PKU patients, the regulating function of ADMA on NO synthesis is altered and may thus contribute to oxidative stress.

Favorable outcome in infants with AML after intensive first- and second-line treatment: an AML-BFM study group report

Infants <1 year of age have a high prevalence of prognostically unfavorable leukemias and a presumed susceptibility to treatment-related toxicities. A total of 125 infants with acute myeloid leukemia (AML) were treated in studies AML-BFM-98 (n = 59) and -2004 (n = 66). Treatment regimens of both studies were comparable, consisting of intensive induction followed by four courses (mainly high-dose cytarabine and anthracyclines). Allogeneic-hematopoietic stem-cell-transplantation (allo-HSCT) in 1st remission was optional for high-risk (HR) patients. Most infants (120/125=96%) were HR patients according to morphological, cytogenetic/molecular genetic and response criteria. Five-year overall survival was 66 ± 4%, and improved from 61 ± 6% in study-98 to 75 ± 6% in study-2004 (P(logrank) 0.14) and event-free survival rates were 44 ± 6% and 51 ± 6% (P(logrank) 0.66), respectively. Results in HR infants were similar to those of older HR children (1-<2- or 2-<10-year olds, P(logrank) 0.90 for survival). Survival rates of HSCT in 1st remission, initial partial response and after relapse were high (13/14, 2/8 and 20/30 patients, respectively). The latter contributes to excellent 5-year survival after relapse (50±8%). Despite more severe infections and pulmonary toxicities in infants, treatment-related death rate was identical to that of older children (3%). Our data indicate that intensive frontline and relapse AML treatment is feasible in infants, toxicities are manageable, and outcome is favorable.

Successful long-term correction of autosomal recessive hyper-IgE syndrome due to DOCK8 deficiency by hematopoietic stem cell transplantation

Autosomal dominant hyper-IgE syndrome (AD-HIES), characterised by eczema, increased susceptibility to skin and lung infections, elevated IgE and skeletal abnormalities is associated with heterozygous STAT3 mutations. The autosomal recessive variant (AR-HIES) has similar immunological findings but mainly lacks extraimmune manifestations. Several AR-HIES patients have recently been shown to harbour mutations in the gene for dedicator of cytokinesis 8 (DOCK8). Here, we present the long-term outcome of a girl having received a hematopoietic stem cell graft for an at that time genetically undefined combined immunodeficiency associated with severe eczema, multiple food allergies, excessively elevated serum IgE levels and eosinophilia. She was recently found to carry a homozygous nonsense mutation in the DOCK8 gene. HSCT resulted in complete immunological correction, even though mixed donor chimerism occurred. Clinically, the outcome was characterised by disappearance of skin manifestations and severe infections, improvement of pulmonary function and constant decline of IgE levels. Outcome in untransplanted DOCK8 deficient patients is poor because of frequent life-threatening infections, CNS bleeding and infarction, and increased susceptibility to malignancy. This argues for early curative therapeutic approaches, supported by this report of successful long-term outcome after HSCT.

Exchange bias and domain evolution at 10 nm scales

For a fixed 2 μm×2 μm area of a Co/Pt-CoO perpendicular exchange bias system we image the ferromagnetic (FM) domains for various applied fields with 10-nm resolution by magnetic force microscopy (MFM). Using quantitative MFM we measure the local areal density of pinned uncompensated spins (pinUCS) in the antiferromagnetic (AFM) CoO layer and correlate the FM domain structure with the UCS density. Larger applied fields drive the receding domains to areas of proportionally higher pinUCS aligned antiparallel to FM moments. The data confirm that the evolution of the FM domains is determined by the pinUCS in the AFM layer, and also present examples of frustration in the system.

Modern nuclear medicine evaluation of neuroblastoma

The neuroblastoma is an embryonic tumor of the peripheral sympathetic nervous system, and is metastatic or otherwise high risk for relapse in nearly 50% of cases, with a long-term survival of <40%. Therefore, exact staging with radiological and nuclear medicine imaging methods is crucial for finding the adequate therapeutic choice. The tumor cells express the norepinephrine transporter, which makes metaiodobenzylguanidine (MIBG), an analogue of norepinephrine, an ideal tumor specific agent for imaging. On the other hand, MIBG imaging has several disadvantages as limited spatial resolution, limited sensitivity in small lesions, need for two or even more acquisition sessions, and a delay between the start of the examination and result. Most of these limitations can be overcome with positron emission tomography (PET) using different radiotracers. Furthermore, MIBG imaging is not sufficient for operative or biopsy planning. With this regard, a combination with morphological imaging methods is indispensable. This article will discuss the therapeutic strategy for primary and follow-up diagnosis in neuroblastoma using different nuclear medicine and radiological imaging methods as well as multimodality imaging.

Non-surgical oncology - Guidelines on Parenteral Nutrition, Chapter 19

Reduced nutritional state is associated with unfavourable outcomes and a lower quality of life in patients with malignancies. Patients with active tumour disease frequently have insufficient food intake. The resting energy expenditure in cancer patients can be increased, decreased, or remain unchanged compared to predicted values. Tumours may result in varying degrees of systemic pro-inflammatory processes with secondary effects on all significant metabolic pathways. Therapeutic objectives are to stabilise nutritional state with oral/enteral nutrition and parenteral nutrition (PN) and thus to prevent or reduce progressive weight loss. The maintenance or improvement of quality of life, and the increase in the effectiveness and a reduction in the side-effects of antitumor therapy are further objectives. Indications for PN in tumour patients are essentially identical to those in patients with benign illnesses, with preference given to oral or enteral nutrition when feasible. A combined nutritional concept is preferred if oral or enteral nutrition are possible but not sufficient. There are generally no accepted standards for ideal energy and nutrient intakes in oncological patients, particularly when exclusive artificial nutrition is administered. The use of PN as a general accompaniment to radiotherapy or chemotherapy is not indicated, but PN is indicated in chronic severe radiogenic enteritis or after allogenic transplantation with pronounced mucositis or GvH-related gastrointestinal damage for prolonged periods, with particular attention to increased risk of bleeding and infection. No PN is necessary in the terminal phase.

A novel FIP1L1-PDGFRA mutant destabilizing the inactive conformation of the kinase domain in chronic eosinophilic leukemia/hypereosinophilic syndrome

BACKGROUND

The Fip1-like-1-platelet-derived growth factor receptor alpha (FIP1L1-PDGFRA) gene fusion is a common cause of chronic eosinophilic leukemia (CEL)/hypereosinophilic syndrome (HES), and patients suffering from this particular subgroup of CEL/HES respond to low-dose imatinib therapy. However, some patients may develop imatinib resistance because of an acquired T674I mutation, which is believed to prevent drug binding through steric hindrance.

METHODS

In an imatinib resistant FIP1L1-PDGFRA positive patient, we analyzed the molecular structure of the fusion gene and analyzed the effect of several kinase inhibitors on FIP1L1-PDGFRA-mediated proliferative responses in vitro.

RESULTS

Sequencing of the FIP1L1-PDGFRA fusion gene revealed the occurrence of a S601P mutation, which is located within the nucleotide binding loop. In agreement with the clinical observations, imatinib did not inhibit the proliferation of S601P mutant FIP1L1-PDGFRA-transduced Ba/F3 cells. Moreover, sorafenib, which has been described to inhibit T674I mutant FIP1L1-PDGFRA, failed to block S601P mutant FIP1L1-PDGFRA. Structural modeling revealed that the newly identified S601P mutated form of PDGFRA destabilizes the inactive conformation of the kinase domain that is necessary to bind imatinib as well as sorafenib.

CONCLUSIONS

We identified a novel mutation in FIP1L1-PDGFRA resulting in both imatinib and sorafenib resistance. The identification of novel drug-resistant FIP1L1-PDGFRA variants may help to develop the next generation of target-directed compounds for CEL/HES and other leukemias.

Testing the efficiency of aerosol containment during cell sorting

Production of droplets and microdroplets (aerosols) is part of the normal operation of a cell sorter. These aerosols may contain toxic, carcinogenic, or teratogenic fluorophores or known or unknown pathogens from viable biological specimens. Most newer models of commercially available instruments incorporate features designed to reduce the production of aerosols and prevent their release into the room. This unit presents two protocols for assessment of aerosol containment on jet-in-air flow sorters. In both procedures, lytic T4 bacteriophage is run through the instrument at high concentrations to tag aerosol droplets. The instrument is tested in normal operating mode and in simulated failure mode. Aerosols are detected by plaque formation on susceptible E. coli lawns. With the continuing increase in the sorting of viable human cells, it is vital for cytometrists to be aware of the potential dangers.

Preparation of cells and reagents for flow cytometry

Flow cytometry is widely used for analyzing the expression of cell surface and intracellular molecules (on a per cell basis), characterizing and defining different cell types in heterogeneous populations, assessing the purity of isolated subpopulations, and analyzing cell size and volume. This technique is predominantly used to measure fluorescence intensity produced by fluorescent-labeled antibodies or ligands that bind to specific cell-associated molecules. A procedure for direct and indirect staining of single-cell suspensions of lymphoid tissue or peripheral blood lymphocytes to detect cell surface membrane antigens is presented. In addition, support protocols present methods for fluorescence labeling of purified antibodies. A protocol for flow cytometric analysis of intracellular antigens in single-cell suspensions is also included. Alternate protocols describe intracellular staining of unfixed cells in the presence of a detergent and staining of nonviable cells to facilitate discrimination of dead cells in fixed or permeabilized cell preparations.

[Sepsis after pharyngitis]

We report about a 36-year-old patient, who developped 4 days after a pharyngitis a sepsis with high temperature und recurrent vomiting. The chest radiograph showed multiple pulmonary abcesses and in the computed tomography additionally a thrombosis was detected in a communicans vein between the right jugularis anterior and the jugularis interna. This disease is commonly known as Lemierre Syndrom. The most common pathogen is the Fusobacterium necrophorum, but other bacteria of the normal oropharyngeal flora can also be the causative organisms. Given an adequate antibiotic therapy and supportive care, the prognosis is favourable.