Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations.

BACKGROUND: Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research to inform recommendations for improving their transparency and utility in future research. METHODS: Original health research articles published during 1999-2017 mentioning 'directed acyclic graphs' (or similar) or citing DAGitty were identified from Scopus, Web of Science, Medline and Embase. Data were extracted on the reporting of: estimands, DAGs and adjustment sets, alongside the characteristics of each article's largest DAG. RESULTS: A total of 234 articles were identified that reported using DAGs. A fifth (n = 48, 21%) reported their target estimand(s) and half (n = 115, 48%) reported the adjustment set(s) implied by their DAG(s). Two-thirds of the articles (n = 144, 62%) made at least one DAG available. DAGs varied in size but averaged 12 nodes [interquartile range (IQR): 9-16, range: 3-28] and 29 arcs (IQR: 19-42, range: 3-99). The median saturation (i.e. percentage of total possible arcs) was 46% (IQR: 31-67, range: 12-100). 37% (n = 53) of the DAGs included unobserved variables, 17% (n = 25) included 'super-nodes' (i.e. nodes containing more than one variable) and 34% (n = 49) were visually arranged so that the constituent arcs flowed in the same direction (e.g. top-to-bottom). CONCLUSION: There is substantial variation in the use and reporting of DAGs in applied health research. Although this partly reflects their flexibility, it also highlights some potential areas for improvement. This review hence offers several recommendations to improve the reporting and use of DAGs in future research.

DAG-informed regression modelling, agent-based modelling and microsimulation modelling: a critical comparison of methods for causal inference.

The current paradigm for causal inference in epidemiology relies primarily on the evaluation of counterfactual contrasts via statistical regression models informed by graphical causal models (often in the form of directed acyclic graphs, or DAGs) and their underlying mathematical theory. However, there have been growing calls for supplementary methods, and one such method that has been proposed is agent-based modelling due to its potential for simulating counterfactuals. However, within the epidemiological literature, there currently exists a general lack of clarity regarding what exactly agent-based modelling is (and is not) and, importantly, how it differs from microsimulation modelling-perhaps its closest methodological comparator. We clarify this distinction by briefly reviewing the history of each method, which provides a context for their similarities and differences, and casts light on the types of research questions that they have evolved (and thus are well suited) to answering; we do the same for DAG-informed regression methods. The distinct historical evolutions of DAG-informed regression modelling, microsimulation modelling and agent-based modelling have given rise to distinct features of the methods themselves, and provide a foundation for critical comparison. Not only are the three methods well suited to addressing different types of causal questions, but, in doing so, they place differing levels of emphasis on fixed and random effects, and also tend to operate on different timescales and in different timeframes.

Duct Stenting Versus Modified Blalock-Taussig Shunt in Neonates With Duct-Dependent Pulmonary Blood Flow: Associations With Clinical Outcomes in a Multicenter National Study.

BACKGROUND: Infants born with cardiac abnormalities causing dependence on the arterial duct for pulmonary blood flow are often palliated with a shunt usually between the subclavian artery and either pulmonary artery. A so-called modified Blalock-Taussig shunt allows progress through early life to an age and weight at which repair or further more stable palliation can be safely achieved. Modified Blalock-Taussig shunts continue to present concern for postprocedural instability and early mortality such that other alternatives continue to be explored. Duct stenting (DS) is emerging as one such alternative with potential for greater early stability and improved survival. METHODS: The purpose of this study was to compare postprocedural outcomes and survival to next-stage palliative or reparative surgery between patients undergoing a modified Blalock-Taussig shunt or a DS in infants with duct-dependent pulmonary blood flow. All patients undergoing cardiac surgery and congenital interventions in the United Kingdom are prospectively recruited to an externally validated national outcome audit. From this audit, participating UK centers identified infants <30 days of age undergoing either a Blalock-Taussig shunt or a DS for cardiac conditions with duct-dependent pulmonary blood flow between January 2012 and December 31, 2015. One hundred seventy-one patients underwent a modified Blalock-Taussig shunt, and in 83 patients, DS was attempted. Primary and secondary outcomes of survival and need for extracorporeal support were analyzed with multivariable logistic regression. Longer-term mortality before repair and reintervention were analyzed with Cox proportional hazards regression. All multivariable analyses accommodated a propensity score to balance patient characteristics between the groups. RESULTS: There was an early (to discharge) survival advantage for infants before next-stage surgery in the DS group (odds ratio, 4.24; 95% confidence interval, 1.37-13.14; P=0.012). There was also a difference in the need for postprocedural extracorporeal support in favor of the DS group (odds ratio, 0.22; 95% confidence interval, 0.05-1.05; P=0.058). Longer-term survival outcomes showed a reduced risk of death before repair in the DS group (hazard ratio, 0.25; 95% confidence interval, 0.07-0.85; P=0.026) but a slightly increased risk of reintervention (hazard ratio, 1.50; 95% confidence interval, 0.85-2.64; P=0.165). CONCLUSIONS: DS is emerging as a preferred alternative to a surgical shunt for neonatal palliation with evidence for greater postprocedural stability and improved patient survival to destination surgical treatment.

Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix.

BACKGROUND: Using routinely collected patient data we explore the utility of multilevel latent class (MLLC) models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs). METHODS: Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640). Patient age, sex, stage-at-diagnosis (Dukes), and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. RESULTS: Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years), and one with better prognosis (39.3% died within 3 years). In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. CONCLUSIONS: A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments) and factors associated with the processes of healthcare delivery (e.g. delays). Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.

Latent class modelling of the association between socioeconomic background and breast cancer survival status at 5 years incorporating stage of disease.

BACKGROUND: Stage of disease and socioeconomic background (SEB) are often used to 'explain' differences in breast cancer outcomes. There are challenges for all types of analysis (eg, survival analysis, logistic regression), including missing data, measurement error and the 'reversal paradox'. This study investigates the association between SEB and survival status within 5 years of breast cancer diagnosis using (1) logistic regression with and without adjustment for stage and (2) logistic latent class analysis (LCA) excluding stage as a covariate but with and without stage as a latent class predictor. METHODS: Women diagnosed with invasive breast cancer between 1998 and 2000 in one UK region were identified (n=11 781). Multilevel logistic regression was performed using standard regression and LCA. Models included SEB (2001 Townsend Index), age and stage ('missing' stage (8.0%) modelled as a separate category). The association of SEB with stage was also assessed. RESULTS: Using standard regression, there was a substantial association between SEB and death within 5 years, with and without adjustment for stage. Using LCA, patients were assigned to a large good prognosis group and a small poor prognosis group. The association between SEB and survival was substantive in both classes for the model without stage, but only in the larger class for the model with stage. Increasing deprivation was associated with more advanced stage at diagnosis. CONCLUSIONS: LCA categorises patients into prognostic groups according to patient and tumour characteristics, providing an alternative strategy to the usual statistical adjustment for stage.

Rietveld refinement of Sr(5)(AsO(4))(3)Cl from high-resolution synchrotron data.

The apatite-type compound, penta-strontium tris-[arsenate(V)] chloride, Sr(5)(AsO(4))(3)Cl, has been synthesized by ion exchange at high temperature from a synthetic sample of mimetite [Pb(5)(AsO(4))(3)Cl] with SrCO(3) as a by-product. The results of the Rietveld refinement, based on high resolution synchrotron X-ray powder diffraction data, show that the title compound crystallizes in the same structure as other halogenoapatites with general formula A(5)(YO(4))(3)X (A = divalent cation, Y = penta-valent cation, and X = F, Cl or Br) in the space group P6(3)/m. The structure consists of isolated tetra-hedral AsO(4) (3-) anions (the As atom and two O atoms have m symmetry), separated by two crystallographically independent Sr(2+) cations that are located on mirror planes and threefold rotation axes, respectively. One Sr atom is coordinated by nine O atoms and the other by six. The chloride anions (site symmetry ) are at the 2a sites and are located in the channels of the structure.

Rietveld refinement of Ba(5)(AsO(4))(3)Cl from high-resolution synchrotron data.

The apatite-type compound Ba(5)(AsO(4))(3)Cl, penta-barium tris-[arsenate(V)] chloride, has been synthesized by ion exchange at high temperature from a synthetic sample of mimetite (Pb(5)(AsO(4))(3)Cl) with BaCO(3) as a by-product. The results of the Rietveld refinement, based on high resolution synchrotron X-ray powder diffraction data, show that the title compound crystallizes in the same structure as other halogenoapatites with general formula A(5)(YO(4))(3)X (A = divalent cation, Y = penta-valent cation, X = Cl, Br) in space group P6(3)/m. The structure consists of isolated tetra-hedral AsO(4) (3-) anions (m symmetry), separated by two crystallographically independent Ba(2+) cations that are located on mirror planes and threefold rotation axes, respectively. The Cl(-) anions are at the 2b sites ( symmetry) and are located in the channels of the structure.