Causal inference based on counterfactuals

BACKGROUND: The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. DISCUSSION: This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. SUMMARY: Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century's work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery

Integrated multiple mediation analysis: A robustness–specificity trade-off in causal structure

Recent methodological developments in causal mediation analysis have addressed several issues regarding multiple mediators. However, these developed methods differ in their definitions of causal parameters, assumptions for identification, and interpretations of causal effects, making it unclear which method ought to be selected when investigating a given causal effect. Thus, in this study, we construct an integrated framework, which unifies all existing methodologies, as a standard for mediation analysis with multiple mediators. To clarify the relationship between existing methods, we propose four strategies for effect decomposition: two-way, partially forward, partially backward, and complete decompositions. This study reveals how the direct and indirect effects of each strategy are explicitly and correctly interpreted as path-specific effects under different causal mediation structures. In the integrated framework, we further verify the utility of the interventional analogues of direct and indirect effects, especially when natural direct and indirect effects cannot be identified or when cross-world exchangeability is invalid. Consequently, this study yields a robustness–specificity trade-off in the choice of strategies. Inverse probability weighting is considered for estimation. The four strategies are further applied to a simulation study for performance evaluation and for analyzing the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer data set from Taiwan to investigate the causal effect of hepatitis C virus infection on mortality

Age and Ethnicity among Hospitalized Alcoholics: A Nationwide Study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65651/1/j.1530-0277.1992.tb00694.x.pd

Pneumococcal carriage in sub-Saharan Africa--a systematic review.

BACKGROUND: Pneumococcal epidemiology varies geographically and few data are available from the African continent. We assess pneumococcal carriage from studies conducted in sub-Saharan Africa (sSA) before and after the pneumococcal conjugate vaccine (PCV) era. METHODS: A search for pneumococcal carriage studies published before 2012 was conducted to describe carriage in sSA. The review also describes pneumococcal serotypes and assesses the impact of vaccination on carriage in this region. RESULTS: Fifty-seven studies were included in this review with the majority (40.3%) from South Africa. There was considerable variability in the prevalence of carriage between studies (I-squared statistic = 99%). Carriage was higher in children and decreased with increasing age, 63.2% (95% CI: 55.6-70.8) in children less than 5 years, 42.6% (95% CI: 29.9-55.4) in children 5-15 years and 28.0% (95% CI: 19.0-37.0) in adults older than 15 years. There was no difference in the prevalence of carriage between males and females in 9/11 studies. Serotypes 19F, 6B, 6A, 14 and 23F were the five most common isolates. A meta-analysis of four randomized trials of PCV vaccination in children aged 9-24 months showed that carriage of vaccine type (VT) serotypes decreased with PCV vaccination; however, overall carriage remained the same because of a concomitant increase in non-vaccine type (NVT) serotypes. CONCLUSION: Pneumococcal carriage is generally high in the African continent, particularly in young children. The five most common serotypes in sSA are among the top seven serotypes that cause invasive pneumococcal disease in children globally. These serotypes are covered by the two PCVs recommended for routine childhood immunization by the WHO. The distribution of serotypes found in the nasopharynx is altered by PCV vaccination

Admission to acute care hospitals for adolescent substance abuse: a national descriptive analysis

BACKGROUND: Use of alcohol and illicit drugs by adolescents remains a problem in the U.S. Case identification and early treatment can occur within a broad variety of healthcare and non-healthcare settings, including acute care hospitals. The objective of this study is to describe the extent and nature of adolescent admissions to the acute inpatient setting for substance abuse (SA). We use the Agency for Healthcare Research and Quality (AHRQ) 2000 Healthcare Cost and Utilization Project Kids Inpatient Database (HCUP-KID) which includes over 2.5 million admissions for youth age 20 and under to 2,784 hospitals in 27 states in the year 2000. Specifically, this analysis estimates national number of admissions, mean total charges, and mean lengths of stay for adolescents between the ages of 12 and 17 admitted to an acute care hospital for the following diagnostic categories from the AHRQ's Clinical Classifications Software categories: "alcohol-related mental disorders" and "substance-related mental disorders". Frequency and percentage of total admissions were calculated for demographic variables of age, gender and income and for hospital characteristic variables of urban/rural designation and children's hospital designation. RESULTS: SA admissions represented 1.25 percent of adolescent admissions to acute care hospitals. Nearly 90 percent of the admission occurred in non-Children's hospitals. Most were for drug dependence (38%) or non-dependent use of alcohol or drugs (35%). Costs were highest for drug dependence admissions. Nearly half of admissions had comorbid mental health diagnoses. Higher rates of admission were seen in boys, in older adolescents, and in "self-pay" patients. Alcohol and drug rehabilitation/detoxification, alone or in combination with psychological and psychiatric evaluation and therapy, was documented for 38 percent of admissions. Over 50 percent of cases had no documentation of treatment specific to substance use behavior. CONCLUSION: General acute care hospitals have a significant and important opportunity to recognize, treat, and refer adolescents with substance abuse problems. These results suggest that inpatient facilities should develop and implement policies and processes to ensure that adolescent substance abusers admitted to their institutions receive appropriate care during the admission and appropriate referral to community care resources

Generalized linear model for interval mapping of quantitative trait loci

We developed a generalized linear model of QTL mapping for discrete traits in line crossing experiments. Parameter estimation was achieved using two different algorithms, a mixture model-based EM (expectation–maximization) algorithm and a GEE (generalized estimating equation) algorithm under a heterogeneous residual variance model. The methods were developed using ordinal data, binary data, binomial data and Poisson data as examples. Applications of the methods to simulated as well as real data are presented. The two different algorithms were compared in the data analyses. In most situations, the two algorithms were indistinguishable, but when large QTL are located in large marker intervals, the mixture model-based EM algorithm can fail to converge to the correct solutions. Both algorithms were coded in C++ and interfaced with SAS as a user-defined SAS procedure called PROC QTL

A New Calibrated Bayesian Internal Goodness-of-Fit Method: Sampled Posterior p-Values as Simple and General p-Values That Allow Double Use of the Data

Background: Recent approaches mixing frequentist principles with Bayesian inference propose internal goodness-of-fit (GOF) p-values that might be valuable for critical analysis of Bayesian statistical models. However, GOF p-values developed to date only have known probability distributions under restrictive conditions. As a result, no known GOF p-value has a known probability distribution for any discrepancy function. Methodology/Principal Findings: We show mathematically that a new GOF p-value, called the sampled posterior p-value (SPP), asymptotically has a uniform probability distribution whatever the discrepancy function. In a moderate finite sample context, simulations also showed that the SPP appears stable to relatively uninformative misspecifications of the prior distribution. Conclusions/Significance: These reasons, together with its numerical simplicity, make the SPP a better canonical GOF p-value than existing GOF p-values