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PubMed1991

Adjustment for cofactors in pediatric research.

Behavioral and developmental pediatric research often seeks to form causal inferences from associations between variables obtained in nonrandomized studies. To do this it is necessary to distinguish the effects of the independent variable of interest from other factors with which it is correlated. We review statistical adjustment procedures for assessing the effects of the independent variable after controlling for other variables, called cofactors. We present guidelines for cofactor adjustment for different patterns of causal relationships occurring in the developmental pediatric literature. We also review procedures for selecting a subset of cofactors from a larger array of candidate variables. Finally, we examine common methodological complications related to cofactor adjustment, including the presence of measurement error in the independent variable and/or the cofactors.

Child↗

PubMed2000

Survival analysis in clinical trials: past developments and future directions.

The field of survival analysis emerged in the 20th century and experienced tremendous growth during the latter half of the century. The developments in this field that have had the most profound impact on clinical trials are the Kaplan-Meier (1958, Journal of the American Statistical Association 53, 457-481) method for estimating the survival function, the log-rank statistic (Mantel, 1966, Cancer Chemotherapy Report 50, 163-170) for comparing two survival distributions, and the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-220) proportional hazards model for quantifying the effects of covariates on the survival time. The counting-process martingale theory pioneered by Aalen (1975, Statistical inference for a family of counting processes, Ph.D. dissertation, University of California, Berkeley) provides a unified framework for studying the small- and large-sample properties of survival analysis statistics. Significant progress has been achieved and further developments are expected in many other areas, including the accelerated failure time model, multivariate failure time data, interval-censored data, dependent censoring, dynamic treatment regimes and causal inference, joint modeling of failure time and longitudinal data, and Baysian methods.

Biometry↗

PubMed2003

Semiparametric estimation of treatment effect in a pretest-posttest study.

Inference on treatment effects in a pretest-posttest study is a routine objective in medicine, public health, and other fields. A number of approaches have been advocated. We take a semiparametric perspective, making no assumptions about the distributions of baseline and posttest responses. By representing the situation in terms of counterfactual random variables, we exploit recent developments in the literature on missing data and causal inference, to derive the class of all consistent treatment effect estimators, identify the most efficient such estimator, and outline strategies for implementation of estimators that may improve on popular methods. We demonstrate the methods and their properties via simulation and by application to a data set from an HIV clinical trial.

Antiviral Agents↗

PubMed2003

Migration of objects and inferences across episodes.

Participants viewed episodes in the form of a series of photographs portraying ordinary routines (e.g., eating at a restaurant) and later received a recognition test. In Experiment 1, it was shown that objects (e.g., a vase of flowers, a pewter lantern) that appeared in a single episode during the study phase migrated between memories of episodes described by the same abstract schema (e.g., from Restaurant Episode A at study to Restaurant Episode B at test), and not between episodes anchored by different schemas. In Experiment 2, it was demonstrated that backward causal inferences from one study episode influenced memories of other episodes described by the same schema, and that high-schema-relevant items viewed in one episode were sometimes remembered as having occurred in another episode of the same schematic type.

Humans↗

PubMed1995

Ecologic studies in epidemiology: concepts, principles, and methods.

An ecologic study focuses on the comparison of groups, rather than individuals; thus, individual-level data are missing on the joint distribution of variables within groups. Variables in an ecologic analysis may be aggregate measures, environmental measures, or global measures. The purpose of an ecologic analysis may be to make biologic inferences about effects on individual risks or to make ecologic inferences about effects on group rates. Ecologic study designs may be classified on two dimensions: (a) whether the primary group is measured (exploratory vs analytic study); and (b) whether subjects are grouped by place (multiple-group study), by time (time-trend study), or by place and time (mixed study). Despite several practical advantages of ecologic studies, there are many methodologic problems that severely limit causal inference, including ecologic and cross-level bias, problems of confounder control, within-group misclassification, lack of adequate data, temporal ambiguity, collinearity, and migration across groups.

Data Interpretation, Statistical↗

PubMedDate not supplied

The effects of stress on wound healing and leg ulceration.

Stress is a universal phenomenon, which has been the focus of much investigation over the past five decades. Much has been discovered about the physiological responses to stress. This review examines the concept of stress in relation to its effect on wound healing. An online literature search was carried out using the databases Medline, Cinahl and Pubmed and the key words stress and wound healing, and stress and leg ulceration. The rationale for specifically examining leg ulceration resulted from the author's interest in this wound type and also the volume of associated literature on the topic published to date. Stress has been demonstrated to have an adverse effect on a variety of natural resistance responses and specific immunological modifications in animal and man alike, causing, for example, reduced inflammatory response, susceptibility to infection and decreased cytokine production (Cohen et al, 1988; Sheridan et al, 1991). Stress and its effects on growth factor regulation have led theorists to examine whether stress adversely affects wound healing (Glaser et al, 1999). Much of the research as examined acute wounds, although causal inferences may be drawn from the wealth of qualitative research examining the effects of venous ulceration. To date, very little has been conducted in the relatively new area of stress and wound healing. Further investigations are required to prove that stress elicits an immunological response affecting the biological markers of wound healing and thus validates the theory that stress may have a negative impact on healing itself. Causal relationships may be postulated between stress and healing in leg ulceration.

Humans↗

PubMed1991

Alcohol and breast cancer risk--putting the current controversy into perspective.

The potential association of alcohol intake with breast cancer risk is currently being debated in the literature and a clear consensus of opinion has not emerged. Clarification of the issues surrounding this controversy would be helpful in developing recommendations for the general public regarding alcohol use. A review of the available evidence regarding the association of alcohol with breast cancer is presented followed by an application of the Bradford Hill criteria for causal inference to this data to examine the existence and nature of the association of alcohol with breast cancer risk. Results of published studies demonstrated a weak association of alcohol with breast cancer risk that was consistent only for relatively high levels of intake (more than 1 or 2 drinks daily). Increasing daily intake was associated with increased risk, but the association was not linear. Criteria relating to temporality and analogy to other causal associations were satisfied while inconsistent evidence was available for those relating to epidemiologic and biologic sense. The criterion for specificity was not satisfied and no experimental evidence was available. It is concluded that insufficient evidence exists to support a causal association of alcohol consumption with breast cancer risk. Further research is recommended to resolve conflicting evidence and to provide additional evidence where needed. In the meantime, recommendations that women should reduce their consumption of alcohol beyond existing guidelines to modify breast cancer risk are probably premature.

Alcohol Drinking↗

PubMed1996

Nutrition and pancreatic cancer.

Epidemiologic evidence on the relation between nutrition and pancreatic cancer is reviewed. A number of epidemiologic studies of diet and cancer of the pancreas have been reported including descriptive, case-control, and cohort studies. Overall, fairly consistent patterns of positive associations with the intake of meat, carbohydrates, and dietary cholesterol have been observed. Consistent inverse relationships with fruit and vegetable intakes and, in particular, with two markers of such foods, namely fiber and vitamin C, also have been noted. However, the methodologic limitations of these studies, particularly the descriptive and case-control studies, are such that causal inferences regarding these empirical associations currently are not warranted. Future follow-up of existing dietary cohorts should enable more precise assessment of the possible role of diet in the etiology of cancer of the pancreas.

Animals↗

PubMed2006

The magnitude of bias in a cross-sectional study on lifestyle factors in relation to Type 2 diabetes.

AIM: In cross-sectional studies it may be difficult to ascertain the temporal order of exposure and disease, which may have consequences for causal inference. The authors aimed to illustrate the possible magnitude of this potential bias using data from a cross-sectional study on coffee consumption and work stress in relation to type 2 diabetes. METHODS: By a series of computer simulations the authors examined to what extent the observed negative association between type 2 diabetes and high coffee consumption and positive association between type 2 diabetes and high work stress could be due to reverse causality, by assuming that cases changed their exposures in response to development of the disease. RESULTS: If the negative association between coffee and type 2 diabetes was a consequence of reversed causality, 30-40% of the cases would have to decrease their coffee consumption from 5 cups of coffee per day to 3-4 cups per day and from 3-4 cups per day to 2 cups of coffee per day. Moreover, approximately 60% of the cases would have to increase their work stress from low to medium work stress and from medium to high work stress, in order to produce the positive association with diabetes that was observed. CONCLUSION: Even if the type 2 diabetic patients to some extent may have changed their exposure in response to disease development, it seems unlikely that the associations observed between type 2 diabetes, coffee consumption, and work stress are due to this bias.

Adult↗

PubMed1997

The effects of stressful life events on depression.

This chapter reviews recent research on the relationship between stressful life experiences and depression. A distinction is made between aggregate studies of overall stress effects and focused studies of particular events and difficulties. A distinction is also made between effects of life stress on first onset of depression and on the subsequent course of depression. Although the available evidence suggests that acute stressful life events can lead to the recurrence of episodes of major depression, a series of methodological problems compromise our ability to make clear causal inferences about the effects of life events on first onset of major depression or about the effects of chronic stress on either onset or recurrence of depression. The main problems of this sort are discussed, and recommendations made for ways of addressing these problems in future studies.

Adaptation, Psychological↗

PubMed2004

Precaution, prevention, and public health ethics.

The precautionary principle brings a special challenge to the practice of evidence-based public health decision-making, suggesting changes in the interpretative methods of public health used to identify causes of disease. In this paper, precautionary changes to these methods are examined: including discounting contrary evidence, reducing the number of causal criteria, weakening the rules of evidence assigned to the criteria, and altering thresholds for statistical significance. All such changes reflect the precautionary goal of earlier primary preventive intervention, i.e. acting on insufficient evidence, the least amount, or minimum level, of evidence for causation. Evaluating the impact of these changes will be difficult without a careful study of how well the current methods of causal inference work, their theoretical foundations, and the ethical implications of their applications. That research program will be most productive if it is jointly developed by public health professionals trained in the ethics and philosophy and by bioethicists and philosophers trained in the theories, methods, and practice of public health.

Bioethical Issues↗

PubMed2026

NLCD: A method to discover nonlinear causal relations among genes.

Distinguishing correlation from causation is a fundamental challenge in many scientific fields, including biology, especially when interventions like randomized controlled trials are infeasible and only observational data are available. Methods based on statistical tests of conditional independence within the Mendelian Randomization framework can detect causality between two observed variables that are each associated with a third instrumental variable. However, these methods for detecting causal relationships between traits (e.g., two gene expression or clinical traits associated with a genetic variant, all observed in the same population) often assume a linear relationship, thereby hindering the discovery of causal gene networks from genomics data. We have developed NLCD, a method for NonLinear Causal Discovery from genomics data based on nonlinear regression modeling and conditional feature importance scoring. NLCD uses these techniques to extend the statistical tests in an existing linear causal discovery method called the Causal Inference Test (CIT). We benchmarked NLCD against current state-of-the-art methods: CIT, Findr, and MRPC. On simulated datasets, NLCD performs comparably to most methods in detecting linear relations (Average AUPRC (Area Under the Precision-Recall Curve) of NLCD = 0.94, CIT = 0.94, Findr = 0.94, and MRPC = 0.99), and outperforms them in detecting nonlinear (sine and sawtooth type) relations between two genes (Average AUPRC of NLCD = 0.76, CIT = 0.60, Findr = 0.56, and MRPC = 0.73). When tested on a nonlinear subset of a yeast genomic dataset to recover known causal relations involving transcription factors, NLCD and CIT performed comparable to each other and slightly better than Findr and MRPC (Average AUPRC of NLCD = 0.82, CIT = 0.81, Findr = 0.71, and MRPC = 0.54). On application to a human genomic dataset, NLCD revealed active causal gene pairs (IRF1 → PSME1 and HLA-C → HLA-T) in the muscle tissue, and clarified the promises and challenges in discovering causal gene networks in tissues under in vivo human settings.

Humans↗

PubMed2006

Trichloroethylene cancer epidemiology: a consideration of select issues.

A large body of epidemiologic evidence exists for exploring causal associations between cancer and trichloroethylene (TCE) exposure. The U.S. Environmental Protection Agency 2001 draft TCE health risk assessment concluded that epidemiologic studies, on the whole, support associations between TCE exposure and excess risk of kidney cancer, liver cancer, and lymphomas, and, to a lesser extent, cervical cancer and prostate cancer. As part of a mini-monograph on key issues in the health risk assessment of TCE, this article reviews recently published scientific literature examining cancer and TCE exposure and identifies four issues that are key to interpreting the larger body of epidemiologic evidence: a) relative sensitivity of cancer incidence and mortality data ; b) different classifications of lymphomas, including non-Hodgkin lymphoma ; c) differences in data and methods for assigning TCE exposure status ; and d) different methods employed for causal inferences, including statistical or meta-analysis approaches. The recent epidemiologic studies substantially expand the epidemiologic database, with seven new studies available on kidney cancer and somewhat fewer studies available that examine possible associations at other sites. Overall, recently published studies appear to provide further support for the kidney, liver, and lymphatic systems as targets of TCE toxicity, suggesting, as do previous studies, modestly elevated (typically 1.5-2.0) site-specific relative risks, given exposure conditions in these studies. However, a number of challenging issues need to be considered before drawing causal conclusions about TCE exposure and cancer from these data.

Animals↗

PubMed1992

Covariation in natural causal induction.

The covariation component of everyday causal inference has been depicted, in both cognitive and social psychology as well as in philosophy, as heterogeneous and prone to biases. The models and biases discussed in these domains are analyzed with respect to focal sets: contextually determined sets of events over which covariation is computed. Moreover, these models are compared to our probabilistic contrast model, which specifies causes as first and higher order contrasts computed over events in a focal set. Contrary to the previous depiction of covariation computation, the present assessment indicates that a single normative mechanism--the computation of probabilistic contrasts--underlies this essential component of natural causal induction both in everyday and in scientific situations.

Cognition↗

PubMed1993

Perspective on the content of worker notifications.

The concept of worker notification has evolved over the years to a prevailing view that workers should be notified of all epidemiologic studies that make use of their medical information. To adequately communicate health information to workers, epidemiologists must consider the intended audience along with its need for risk information that is scientifically valid and clearly outlines areas of uncertainty. This goal is facilitated by full disclosure to workers of information pertinent to the planning, conduct, and interpretation of research efforts. Subjectivity in choosing unanticipated research findings for inclusion in worker notifications may permit bias toward a personal viewpoint, but this can be minimized by prestudy agreement on appropriate criteria for selecting which research findings to communicate. Epidemiologic theory and principles of causal inference should guide the development of appropriate criteria. The timeliness of worker communications has received limited attention, and workers have often been the "last to know" about important studies. This may influence workers' receptivity to the risk message. Sponsoring organizations should ensure that an acceptable communications plan is included in research protocols and that the plan accords priority to notifying workers about study results.

Causality↗

PubMed2006

Systematically describing gross lesions in corals.

Many coral diseases are characterized based on gross descriptions and, given the lack or difficulty of applying existing laboratory tools to understanding causes of coral diseases, most new diseases will continued to be described based on appearance in the field. Unfortunately, many existing descriptions of coral disease are ambiguous or open to subjective interpretation, making comparisons between oceans problematic. One reason for this is that the process of describing lesions is often confused with that of assigning causality for the lesion. However, causality is usually something not obtained in the field and requires additional laboratory tests. Because a concise and objective morphologic description provides the foundation for a case definition of any disease, there is a need for a consistent and standardized process to describe lesions of corals that focuses on morphology. We provide a framework to systematically describe and name diseases in corals involving 4 steps: (1) naming the disease, (2) describing the lesion, (3) formulating a morphologic diagnosis and (4) formulating an etiologic diagnosis. This process focuses field investigators on describing what they see and separates the process of describing a lesion from that of inferring causality, the latter being more appropriately done using laboratory techniques.

Animals↗

PubMed2002

Clustered encouragement designs with individual noncompliance: bayesian inference with randomization, and application to advance directive forms.

In many studies comparing a new 'target treatment' with a control target treatment, the received treatment does not always agree with assigned treatment-that is, the compliance is imperfect. An obvious example arises when ethical or practical constraints prevent even the randomized assignment of receipt of the new target treatment but allow the randomized assignment of the encouragement to receive this treatment. In fact, many randomized experiments where compliance is not enforced by the experimenter (e.g. with non-blinded assignment) may be more accurately thought of as randomized encouragement designs. Moreover, often the assignment of encouragement is at the level of clusters (e.g. doctors) where the compliance with the assignment varies across the units (e.g. patients) within clusters. We refer to such studies as 'clustered encouragement designs' (CEDs) and they arise relatively frequently (e.g. Sommer and Zeger, 1991; McDonald et al., 1992; Dexter et al., 1998) Here, we propose Bayesian methodology for causal inference for the effect of the new target treatment versus the control target treatment in the randomized CED with all-or-none compliance at the unit level, which generalizes the approach of Hirano et al. (2000) in important and surprisingly subtle ways, to account for the clustering, which is necessary for statistical validity. We illustrate our methods using data from a recent study exploring the role of physician consulting in increasing patients' completion of Advance Directive forms.

Journal Article↗

PubMed1995

The risk of childhood cancer from intrauterine and preconceptional exposure to ionizing radiation.

The findings of studies investigating whether exposures to ionizing radiation before birth, either pre- or post-conception, increase the risk of childhood cancer have provoked much scientific controversy. An epidemiological association between the abdominal exposure of pregnant women to diagnostic X-rays and childhood cancer was first reported in the 1950s, while an association between the recorded dose of radiation received occupationally by fathers before the conception of their offspring and childhood leukemia was reported only recently in 1990. The scientific interpretation of these particular statistical associations is by no means straightforward, but the latest analyses of intrauterine irradiation and childhood cancer indicate that a causal inference is likely. Scientific committees have adopted risk coefficients for the intrauterine exposure of somatic tissues, which for childhood leukemia are comparable to those accepted for exposure in infancy, although questions remain about the level of risk of childhood solid tumors imparted by exposure to radiation in utero and shortly after birth. In contrast, the association between paternal preconceptional radiation dose and childhood leukemia has not been confirmed by studies using objectively determined doses. The original association has been found to be restricted to children born in one village, it does not extend to cancers other than leukemia, and it is markedly inconsistent with the established body of knowledge on radiation-induced hereditary disease. A causal interpretation of this association has effectively been abandoned by scientific authorities.

Case-Control Studies↗