Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

Textor, Johannes; Zander, Benito van der; Gilthorpe, Mark S.; Liśkiewicz, Maciej; Ellison, George T. H.

doi:10.1093/ije/dyw341

Cited by 1,092 publications

(1,077 citation statements)

References 13 publications

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“…For each treatment exposure (pulmonary toxic chemotherapy, chest radiation, and thoracic surgery), unadjusted and adjusted models were fitted. We used directed acyclic graphs (DAGs) implemented in DAGitty to select a minimal sufficient adjustment set of variables to allow estimation of an unconfounded effect of each treatment exposure on respiratory admissions From the DAG (available at http://dagitty.net/m6dZKD2) the minimal sufficient adjustment set included deprivation, diagnosis age, diagnosis year, diagnostic group and treatment exposures. Further models were examined including an interaction term between age group (children and AYA) and pulmonary toxic chemotherapy and chest radiation to determine whether the association between treatment and risk of admission differed by age.…”

Section: Methodsmentioning

confidence: 99%

Respiratory morbidity in young people surviving cancer: Population‐based study of hospital admissions, treatment‐related risk factors and subsequent mortality

Smith

Glaser

Peckham

et al. 2019

Intl Journal of Cancer

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Respiratory diseases are a major cause of late morbidity and mortality amongst childhood cancer survivors. This population‐based study investigates respiratory hospital admissions in long‐term survivors of cancers diagnosed in young people to identify specific respiratory morbidities, treatment‐related risks and their relationship to subsequent morbidity and mortality. Population‐based cancer registrations in Yorkshire, England, diagnosed between 1990 and 2011 aged 0–29 years, were linked to inpatient Hospital Episode Statistics (HES) for admissions up to 2017. All 5‐year survivors were included in analysis (n = 4235). Admission rates were compared to age‐ and sex‐ matched general population rates. Competing risk regression models were used to assess associations between treatment exposures and risk of admission. Risk of death after admission was calculated using Cox regression. By age 40, cumulative incidence for an admission for any type of respiratory condition was 49%. Respiratory admission rates were 1.86 times higher in cancer survivors than in the general population (95% Confidence Interval (CI) 1.73–2.01), and varied by respiratory condition and age at diagnosis. Treatment with chemotherapy with known lung toxicity increased the risk of admission for all respiratory conditions (subdistribution Hazard ratio (sHR) = 1.26, 95%CI 1.03–1.53) and pneumonia (sHR = 1.48, 95%CI 1.01–2.17). Subsequent mortality was highest in those admitted for pneumonia compared to other respiratory conditions (28% and 15% respectively). Survivors of childhood and young adult cancer remain at significantly increased risk of respiratory complications several decades after treatment, emphasising the importance for clinical initiatives for prevention, early detection and treatment.

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Section: Methodsmentioning

confidence: 99%

Respiratory morbidity in young people surviving cancer: Population‐based study of hospital admissions, treatment‐related risk factors and subsequent mortality

Smith

Glaser

Peckham

et al. 2019

Intl Journal of Cancer

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“…Multivariable analyses were planned a priori using minimum sufficient adjustment sets derived from directed acyclic graphs of the hypothesized relationships among variables related to outcomes. Logistic and Cox proportional hazard regressions were used for CMV‐I, CMV‐D, and mortality outcomes, and linear regression was used for models with continuous outcomes.…”

Section: Methodsmentioning

confidence: 99%

The clinical and economic impact of cytomegalovirus infection in recipients of hematopoietic stem cell transplantation

Webb

Harrington

Schwartz

et al. 2018

Transplant Infectious Dis

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“…We run first a minimally adjusted Model 1 including sex, age, and centre (all exposures). Model 2 was adjusted by the minimally sufficient adjustment set, determined using directed acyclic graphs (DAGs) implemented in DAGitty software, available free on http://www.dagitty.net. The DAGs were built by identifying known factors affecting each of our exposures on SI (see DAGs in Supporting Information, Figure S1A–D).…”

Section: Introductionmentioning

confidence: 99%

Association of lifestyle factors and inflammation with sarcopenic obesity: data from the PREDIMED‐Plus trial

Abete

Konieczna

Zulet

et al. 2019

J cachexia sarcopenia muscle

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Background Sarcopenia is a progressive age‐related skeletal muscle disorder associated with increased likelihood of adverse outcomes. Muscle wasting is often accompanied by an increase in body fat, leading to ‘sarcopenic obesity’. The aim of the present study was to analyse the association of lifestyle variables such as diet, dietary components, physical activity (PA), body composition, and inflammatory markers, with the risk of sarcopenic obesity. Methods A cross‐sectional analysis based on baseline data from the PREDIMED‐Plus study was performed. A total of 1535 participants (48% women) with overweight/obesity (body mass index: 32.5 ± 3.3 kg/m2; age: 65.2 ± 4.9 years old) and metabolic syndrome were categorized according to sex‐specific tertiles (T) of the sarcopenic index (SI) as assessed by dual‐energy X‐ray absorptiometry scanning. Anthropometrical measurements, biochemical markers, dietary intake, and PA information were collected. Linear regression analyses were carried out to evaluate the association between variables. Results Subjects in the first SI tertile were older, less physically active, showed higher frequency of abdominal obesity and diabetes, and consumed higher saturated fat and less vitamin C than subjects from the other two tertiles (all P < 0.05). Multiple adjusted linear regression models evidenced significant positive associations across tertiles of SI with adherence to the Mediterranean dietary score (P‐trend < 0.05), PA (P‐trend < 0.0001), and the 30 s chair stand test (P‐trend < 0.0001), whereas significant negative associations were found with an inadequate vitamin C consumption (P‐trend < 0.05), visceral fat and leucocyte count (all P‐trend < 0.0001), and some white cell subtypes (neutrophils and monocytes), neutrophil‐to‐lymphocyte ratio, and platelet count (all P‐trend < 0.05). When models were additionally adjusted by potential mediators (inflammatory markers, diabetes, and waist circumference), no relevant changes were observed, only dietary variables lost significance. Conclusions Diet and PA are important regulatory mediators of systemic inflammation, which is directly involved in the sarcopenic process. A healthy dietary pattern combined with exercise is a promising strategy to limit age‐related sarcopenia.

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Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

Cited by 1,092 publications

References 13 publications

Respiratory morbidity in young people surviving cancer: Population‐based study of hospital admissions, treatment‐related risk factors and subsequent mortality

Respiratory morbidity in young people surviving cancer: Population‐based study of hospital admissions, treatment‐related risk factors and subsequent mortality

The clinical and economic impact of cytomegalovirus infection in recipients of hematopoietic stem cell transplantation

Association of lifestyle factors and inflammation with sarcopenic obesity: data from the PREDIMED‐Plus trial

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