scholarly journals Characterisation, identification, clustering, and classification of disease

2020 ◽  
Author(s):  
A.J. Webster ◽  
K. Gaitskell ◽  
I. Turnbull ◽  
B.J. Cairns ◽  
R. Clarke
Keyword(s):  
Risk Factors ◽  
Statistical Power ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Disease Risk ◽  
Neurological Diseases ◽  
Disease Incidence ◽  
Disease Onset ◽  
Laboratory Findings ◽  
Clustering And Classification

Data-driven classifications are improving statistical power and refining prognoses for a range of respiratory, infectious, autoimmune, and neurological diseases. Studies have used molecular information, age of disease incidence, and sequences of disease onset (“disease trajectories”). Here we consider whether easily measured risk factors such as height and BMI can usefully characterise diseases in UK Biobank data, combining established statistical methods in new but rigorous ways to provide clinically relevant comparisons and clusters of disease. Over 400 common diseases were selected for study on the basis of clinical and epidemiological criteria, and a conventional proportional hazards model was used to estimate associations with 12 established risk factors. Comparing men and women, several diseases had strongly sex-dependent associations of disease risk with BMI. Despite this, a large proportion of diseases affecting both sexes could be identified by their risk factors, and equivalent diseases tended to cluster adjacently. This included 10 diseases presently classified as “Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified”. Many clusters are associated with a shared, known pathogenesis, others suggest likely but presently unconfirmed causes. The specificity of associations and shared pathogenesis of many clustered diseases, provide a new perspective on the interactions between biological pathways, risk factors, and patterns of disease such as multimorbidity.

scholarly journals Characterisation, identification, clustering, and classification of disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. J. Webster ◽  
K. Gaitskell ◽  
I. Turnbull ◽  
B. J. Cairns ◽  
R. Clarke
Keyword(s):  
Risk Factors ◽  
Statistical Power ◽  
Proportional Hazards ◽  
Disease Risk ◽  
Neurological Diseases ◽  
Disease Incidence ◽  
Disease Onset ◽  
Laboratory Findings ◽  
Clustering And Classification ◽  
New Perspective

AbstractThe importance of quantifying the distribution and determinants of multimorbidity has prompted novel data-driven classifications of disease. Applications have included improved statistical power and refined prognoses for a range of respiratory, infectious, autoimmune, and neurological diseases, with studies using molecular information, age of disease incidence, and sequences of disease onset (“disease trajectories”) to classify disease clusters. Here we consider whether easily measured risk factors such as height and BMI can effectively characterise diseases in UK Biobank data, combining established statistical methods in new but rigorous ways to provide clinically relevant comparisons and clusters of disease. Over 400 common diseases were selected for analysis using clinical and epidemiological criteria, and conventional proportional hazards models were used to estimate associations with 12 established risk factors. Several diseases had strongly sex-dependent associations of disease risk with BMI. Importantly, a large proportion of diseases affecting both sexes could be identified by their risk factors, and equivalent diseases tended to cluster adjacently. These included 10 diseases presently classified as “Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified”. Many clusters are associated with a shared, known pathogenesis, others suggest likely but presently unconfirmed causes. The specificity of associations and shared pathogenesis of many clustered diseases provide a new perspective on the interactions between biological pathways, risk factors, and patterns of disease such as multimorbidity.

scholarly journals 761Characterisation and clustering of diseases by their association with well-known risk factors

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Anthony Webster ◽  
Kezia Gaitskell ◽  
Iain Turnbull ◽  
Ben Cairns ◽  
Robert Clarke
Keyword(s):  
Risk Factors ◽  
Multiple Testing ◽  
Statistical Power ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Neurological Diseases ◽  
Disease Onset ◽  
Significant Risk ◽  
Multivariate Statistical ◽  
Age Related

Abstract Background Data-driven classifications are improving statistical power, refining prognoses, and improving our understanding of autoimmune, respiratory, infectious, and neurological diseases. Classifications have used molecular information, age of incidence, and sequences of disease onset (“disease trajectories”). Here we consider whether associations with easily-measured established risk factors such as height and BMI can usefully characterise disease. Methods UK Biobank data and their linked hospital episode statistics were used to study 172 common age-related diseases. A proportional hazards model was used to estimate associations with potential risk-factors and to adjust for well-known confounders. Diseases were compared and hierarchically clustered using novel but rigorous multivariate statistical methods. Results For diseases affecting both sexes, over 38% can be uniquely identified by their associations with risk factors. Equivalent diseases often clustered adjacently. After an FDR multiple-testing adjustment, roughly 5% have statistically significant differences. Similar remarks applied to several symptoms of unknown cause. Many clustered diseases are associated with a shared, known pathogenesis, others suggest likely but unconfirmed causes. Conclusions Risk factors for disease can be surprisingly precise and can be used to cluster diseases in a meaningful way. Risk factors for men and women may differ for some diseases. Several symptoms of unknown cause have disease-specific, statistically significant risk factors. Key messages Big datasets and modern statistics are providing new insights into the relationships between diseases and their associations with risk-factors. Diseases can be identified and clustered by their associations with well-known risk factors.

scholarly journals Causal attribution fractions for epidemiological studies, applied to a UK Biobank study of smoking and BMI

2021 ◽  
Author(s):  
Anthony Webster
Keyword(s):  
Risk Factors ◽  
Proportional Hazards ◽  
Disease Risk ◽  
Causal Attribution ◽  
Disease Incidence ◽  
World Health Organisation ◽  
Epidemiological Studies ◽  
World Health ◽  
Proportional Hazard ◽  
Uk Biobank

Epidemiological studies often use proportional hazard models to estimate associations between potential risk factors and disease risk. It is emphasised that when the "backdoor criteria" from causal-inference applies, if diseases are sufficiently rare, then the proportional hazard model can be used to estimate causal associations. When the "frontdoor criteria" applies (allowing causal estimates with unmeasured confounders), similar estimates are found to mediation analyses with measured confounders. Reasons for this are discussed. An attribution fraction is constructed using the average causal effects (ACE) of exposures on the population, and simple methods for its evaluation are suggested. It differs from the attribution fraction used by the World Health Organisation (WHO), except for specific circumstances where the latter can agree or provide a bound. A counterfactual argument determines an individual's attribution fraction Af in terms of proportional hazard estimates, as Af = 1 − 1/R, where R is an individual's relative risk. Causally meaningful attribution fractions cannot be constructed for all known risk factors or confounders, but there are important cases where they can. As an example, systematic proportional hazards studies with UK Biobank data estimate the attribution fractions of smoking and BMI for 226 diseases. The attribution of risk is characterised in terms of disease chapters from the International Classification of Diseases (ICD-10), and the diseases most strongly attributed to smoking and BMI are identified. The result is a quantitative characterisation of the causal influence of smoking and BMI on the landscape of disease incidence in the UK Biobank population.

scholarly journals Prevalence, Risk Factors, and Complications of Cholelithiasis in Adults With Short Bowel Syndrome: A Longitudinal Cohort Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Xuejin Gao ◽  
Li Zhang ◽  
Siwen Wang ◽  
Yaqin Xiao ◽  
Deshuai Song ◽  
...  
Keyword(s):  
Risk Factors ◽  
Short Bowel Syndrome ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Clinical Trial Registration ◽  
Short Bowel ◽  
Kaplan Meier ◽  
Clinical Consequences

Background: Patients with short bowel syndrome (SBS) are at a high risk of cholestasis or cholelithiasis. This study aimed to determine the incidence, risk factors, and clinical consequences of cholelithiasis in adults with SBS over an extended period.Methods: All eligible adults diagnosed with SBS and admitted to a tertiary hospital center between January 2010 and December 2019 were retrospectively identified from the hospital records database. Kaplan–Meier analysis was used to estimate the cumulative incidence of SBS during the 10-year period. For assessment the risk factors for cholelithiasis, we used multivariate Cox proportional hazards model with estimation of hazard ratio (HR) with 95% confidence intervals (95 %CI).Results: This study enrolled 345 eligible patients with SBS. Kaplan–Meier analysis revealed that 72 patients (20.9%) developed cholelithiasis during the 10-year observation period. In multivariate analyses using the Cox proportional hazard model revealed that the remnant jejunum (HR = 2.163; 95% confidence interval [CI]: 1.156–4.047, p = 0.016) and parenteral nutrition dependence (HR = 1.783; 95% CI: 1.077–2.952, p = 0.025) were independent risk factors for cholelithiasis in adults with SBS. Twenty-eight patients developed symptoms and/or complications in the cholelithiasis group. Proportions of acute cholecystitis or cholangitis and acute pancreatitis were significantly increased in the cholelithiasis group compared with the non-cholelithiasis group (31.9 vs. 7.7%, p < 0.01; and 6.9 vs. 1.1%, p = 0.003, respectively).Conclusion: Because of the adverse clinical consequences of cholelithiasis, adult patients with SBS should be closely monitored, and preventive interventions should be considered.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT04867538.

Abstract TP196: New Zealand Workforce Stroke Incidence: Urban and Rural Risk Factor Evaluation

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Hope E Buell ◽  
Patricia Metcalf ◽  
Daniel Exeter
Keyword(s):  
Risk Factors ◽  
New Zealand ◽  
Stroke Risk ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Smoking Status ◽  
Prior History ◽  
Stroke Incidence ◽  
Stroke Outcomes ◽  
The Impact

This analysis aims to assess the impact of urban and rural risk factors on a model of stroke incidence in a New Zealand workforce population. The New Zealand study consisted of 4,926 subjects prospectively enrolled at 46 worksites. The subjects were aged 40-78 years at baseline and had no prior history of stroke. This prospective study defines stroke events experienced by the study subjects during follow-up between 1988 and 2012 based on hospital admission coding. Proportional hazards regression models were fit using baseline characteristics. The difference in stroke outcomes for urban and rural worksites was also evaluated. Results demonstrate that baseline demographic, physical exam, and behavioural measures impact stroke outcomes. While the baseline distribution of stroke risk factors such as Pacific Island ethnicity, smoking status, and increased blood pressure indicates a potentially higher risk of stroke in the rural population, the proportional hazards model does not identify increased stroke risk for rural workers. Additional analysis of the diet, exercise and Quality of Life measures for these subjects may provide further information into the stroke risk profiles of individuals working in different locales.

Risk factors for disease progression in low-teens normal-tension glaucoma

2019 ◽  
Vol 104 (1) ◽  
pp. 81-86 ◽  
Author(s):  
Sung Uk Baek ◽  
Ahnul Ha ◽  
Dai Woo Kim ◽  
Jin Wook Jeoung ◽  
Ki Ho Park ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Progression ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Normal Tension Glaucoma ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Diurnal Iop

Background/AimsTo investigate the risk factors for disease progression of normal-tension glaucoma (NTG) with pretreatment intraocular pressure (IOP) in the low-teens.MethodsOne-hundred and two (102) eyes of 102 patients with NTG with pretreatment IOP≤12 mm Hg who had been followed up for more than 60 months were retrospectively enrolled. Patients were divided into progressor and non-progressor groups according to visual field (VF) progression as correlated with change of optic disc or retinal nerve fibre layer defect. Baseline demographic and clinical characteristics including diurnal IOP and 24 hours blood pressure (BP) were compared between the two groups. The Cox proportional hazards model was used to identify the risk factors for disease progression.ResultsThirty-six patients (35.3%) were classified as progressors and 66 (64.7%) as non-progressors. Between the two groups, no significant differences were found in the follow-up periods (8.7±3.4 vs 7.7±3.2 years; p=0.138), baseline VF mean deviation (−4.50±5.65 vs −3.56±4.30 dB; p=0.348) or pretreatment IOP (11.34±1.21 vs 11.17±1.06 mm Hg; p=0.121). The multivariate Cox proportional hazards model indicated that greater diurnal IOP at baseline (HR=1.609; p=0.004), greater fluctuation of diastolic BP (DBP; HR=1.058; p=0.002) and presence of optic disc haemorrhage during follow-up (DH; HR=3.664; p=0.001) were risk factors for glaucoma progression.ConclusionIn the low-teens NTG eyes, 35.3% showed glaucoma progression during the average 8.7 years of follow-up. Fluctuation of DBP and diurnal IOP as well as DH were significantly associated with greater probability of disease progression.

Epidemiology, Risk Factors, and Outcomes After Early Posttransplant Clostridiodes difficile Infection in Renal Transplant Recipients

2019 ◽  
Vol 53 (10) ◽  
pp. 1020-1025
Author(s):  
Margaret R. Jorgenson ◽  
Jillian L. Descourouez ◽  
Dou-Yan Yang ◽  
Glen E. Leverson ◽  
Christopher M. Saddler ◽  
...  
Keyword(s):  
Risk Factors ◽  
Renal Transplant ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Female Gender ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Secondary Outcome ◽  
Induction Agent ◽  
Renal Transplant Recipients

Background: Modifiable risk-factors associated with Clostridioides difficile infection (CDI) in renal-transplant (RTX) have not been clearly established and peri-transplant risk has not been described. Objective: Evaluate epidemiology, risk-factors and outcomes after CDI occurring in the first 90 days after RTX (CDI-90).Methods: Observational cohort study/survival analysis of adult RTX recipients from 1/1/2012-12/31/2015. Primary outcome was CDI-90 incidence/risk-factors. Secondary outcome was evaluation of post-90 day transplant outcomes. Results: 982 patients met inclusion criteria; 46 with CDI-90 and 936 without (comparator). CDI incidence in the total population was 4.7% at 90 days, 6.3% at 1 year, and 6.4% at 3 years. Incidence of CDI-90 was 5%; time to diagnosis was 19.4±25 days (median 7). Risk-factors for CDI-90 were alemtuzumab induction (Hazard ratio [HR] 1.5, 95% CI(1.1-2.0), p = 0.005) and age at transplant (HR 1.007/year, 95% CI (1.002-1.012), p= 0.007). However, risk-factors for CDI at any time were different; donation-after-circulatory-death (DCD) donor (HR 2.5 95% CI (1.3-4.9), p = 0.008) and female gender (HR 1.6 95% CI (1.0-2.7), p = 0.049). On Kaplan-Meier, CDI-90 appeared to have an impact on patient/graft survival, however when analyzed in a multivariable stepwise Cox proportional hazards model, only age was significantly associated with survival ( p = 0.002). Conclusion and Relevance: Incidence of CDI-90 is low, mostly occurring in the first post-operative month. Risk-factors vary temporally based on time from transplant. In the early post-op period induction agent and age at transplant are significant, but not after. Associations between CDI and negative graft outcomes appear to be largely driven by age. Future studies validating these risk-factors as well as targeted prophylaxis strategies and their effect on long term graft outcomes and the host microbiome are needed.

scholarly journals Longterm Outcomes of 188 Japanese Patients with Eosinophilic Granulomatosis with Polyangiitis

2018 ◽  
Vol 45 (8) ◽  
pp. 1159-1166 ◽  
Author(s):  
Aiko Saku ◽  
Shunsuke Furuta ◽  
Masaki Hiraguri ◽  
Kei Ikeda ◽  
Yoshihisa Kobayashi ◽  
...  
Keyword(s):  
Granulomatosis With Polyangiitis ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Disease Onset ◽  
Japanese Patients ◽  
Eosinophilic Granulomatosis With Polyangiitis ◽  
Factors Associated ◽  
Hazards Model ◽  
Eosinophilic Granulomatosis ◽  
Eosinophil Counts

Objective.Patients with eosinophilic granulomatosis with polyangiitis (EGPA) frequently experience relapses, which lead to cumulative organ damage. In this retrospective observational study, we aimed to reveal the risk factors for relapse in EGPA.Methods.A total of 188 Japanese patients with EGPA diagnosed between 1996 and 2015 were identified from medical records in 10 hospitals. The diagnosis was based on the American College of Rheumatology 1990 criteria or Lanham’s criteria. Baseline characteristics, treatments, asthma exacerbation, and relapses were evaluated by retrospective chart review.Results.The median followup period was 56 months. The median age at disease onset was 59.7 years. At the disease onset, 95.2% of the patients had a history of bronchial asthma and 44.7% were positive for antineutrophil cytoplasmic antibodies. The cumulative survival and relapse-free survival rates at 5 years were 89.6% and 64.0%, respectively. Multivariate analysis with 2 models, proportional hazards, and competing risk models, was performed to identify the factors associated with relapse. The proportional hazards model identified azathioprine (AZA) maintenance therapy and high eosinophil counts at onset as independent factors with lower relapse risks, and high immunoglobulin E (IgE) levels at onset as a risk factor for relapse. The competing risk model identified no statistically significant factors.Conclusion.Although potential benefit of AZA maintenance therapy in preventing relapse of EGPA was suggested by the proportional hazards model, there was a discrepancy in the results between the models. Eosinophil counts and IgE levels at onset were also identified as candidates of factors associated with relapse in EGPA.

scholarly journals Incidence and Survival Changes in Patients with Esophageal Adenocarcinoma during 1984–2013

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Zhang Haiyu ◽  
Pei Xiaofeng ◽  
Mo Xiangqiong ◽  
Qiu Junlan ◽  
Zheng Xiaobin ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Esophageal Adenocarcinoma ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Potential Risk Factors

Purpose. The morbidity of esophageal adenocarcinoma (EAC) has significantly increased in Western countries. We aimed to identify trends in incidence and survival in patients with EAC in the recent 30 years and then analyzed potential risk factors, including race, sex, age, and socioeconomic status (SES). Methods. All data were collected from the Surveillance, Epidemiology, and End Results or SEER database. Kaplan–Meier analysis and the Cox proportional hazards model were conducted to compare the differences in survival between variables, including sex, race, age, and SES, as well as to evaluate the association of these factors with prognosis. Results. A total of 16,474 patients with EAC were identified from 1984 to 2013 in the United States. Overall incidence increased every 10 years from 1.8 to 3.1 to 3.9 per 100. Overall survival gradually improved (p<0.0001), which was evident in male patients ((hazard ratio (HR) = 1.111; 95% confidence interval (CI) (1.07, 1.15)); however, the 5-year survival rate remained low (20.1%). The Cox proportional hazards model identified old age, black ethnicity, and medium/high poverty as risk factors for EAC (HR = 1.018; 95% CI (1.017, 1.019; HR = 1.240, 95% CI (1.151,1.336), HR = 1.000, 95% CI (1.000, 1.000); respectively). Conclusions. The incidence of EAC in the United States increased over time. Survival advantage was observed in white patients and patients in the low-poverty group. Sex was an independent prognostic factor for EAC, but this finding has to be confirmed by further research.

scholarly journals Defining heart disease risk for death in COVID-19 infection

QJM ◽  
2020 ◽  
Vol 113 (12) ◽  
pp. 876-882 ◽  
Author(s):  
J Li ◽  
T Guo ◽  
D Dong ◽  
X Zhang ◽  
X Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cox Regression ◽  
Disease Risk ◽  
Demographic Data ◽  
Kidney Injury ◽  
Laboratory Findings ◽  
Course Of Disease ◽  
Clinical Observations ◽  
Independent Risk Factors ◽  
Heart Disease Risk

Summary Background Cardiovascular disease (CVD) was in common in coronavirus disease 2019 (COVID-19) patients and associated with unfavorable outcomes. We aimed to compare the clinical observations and outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients with or without CVD. Methods Patients with laboratory-confirmed SARS-CoV-2 infection were clinically evaluated at Wuhan Seventh People’s Hospital, Wuhan, China, from 23 January to 14 March 2020. Demographic data, laboratory findings, comorbidities, treatments and outcomes were collected and analyzed in COVID-19 patients with and without CVD. Results Among 596 patients with COVID-19, 215 (36.1%) of them with CVD. Compared with patients without CVD, these patients were significantly older (66 vs. 52 years) and had higher proportion of men (52.5% vs. 43.8%). Complications in the course of disease were more common in patients with CVD, included acute respiratory distress syndrome (22.8% vs. 8.1%), malignant arrhythmias (3.7% vs. 1.0%) including ventricular tachycardia/ventricular fibrillation, acute coagulopathy(7.9% vs. 1.8%) and acute kidney injury (11.6% vs. 3.4%). The rate of glucocorticoid therapy (36.7% vs. 25.5%), Vitamin C (23.3% vs. 11.8%), mechanical ventilation (21.9% vs. 7.6%), intensive care unit admission (12.6% vs. 3.7%) and mortality (16.7% vs. 4.7%) were higher in patients with CVD (both P &lt; 0.05). The multivariable Cox regression models showed that older age (≥65 years old) (HR 3.165, 95% CI 1.722–5.817) and patients with CVD (HR 2.166, 95% CI 1.189–3.948) were independent risk factors for death. Conclusions CVD are independent risk factors for COVID-19 patients. COVID-19 patients with CVD were more severe and had higher mortality rate, early intervention and vigilance should be taken.

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