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Antonio Vinci - One of the best experts on this subject based on the ideXlab platform.
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can risk be predicted an umbrella systematic review of current risk prediction models for cardiovascular diseases diabetes and hypertension
BMJ Open, 2019Co-Authors: Francesca Lucaroni, Domenico Cicciarella Modica, Mattia Macino, Leonardo Palombi, Alessio Abbondanzieri, Giulia Agosti, Giorgia Biondi, Liat Morciano, Antonio VinciAbstract:Objective To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases. Design Umbrella systematic review. Data sources PubMed, Scopus, Cochrane Library. Eligibility criteria Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18–65 years old) population, published in English language. Data extraction and synthesis Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study selection 3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added. Study appraisal The methodological quality of the included studies was assessed using the AMSTAR tool. Risk of bias in individual studies Risk of Bias evaluation was carried out using the ROBIS tool. Results Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone. Limitations Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out. Conclusions Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and Employment History, social network relationships, income and education. PROSPERO registration number CRD42018088012.
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can risk be predicted an umbrella systematic review of current risk prediction models for cardiovascular diseases diabetes and hypertension
BMJ Open, 2019Co-Authors: Francesca Lucaroni, Domenico Cicciarella Modica, Mattia Macino, Leonardo Palombi, Alessio Abbondanzieri, Giulia Agosti, Giorgia Biondi, Liat Morciano, Antonio VinciAbstract:Objective To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases. Design Umbrella systematic review. Data sources PubMed, Scopus, Cochrane Library. Eligibility criteria Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18–65 years old) population, published in English language. Data extraction and synthesis Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study selection 3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added. Study appraisal The methodological quality of the included studies was assessed using the AMSTAR tool. Risk of bias in individual studies Risk of Bias evaluation was carried out using the ROBIS tool. Results Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone. Limitations Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out. Conclusions Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and Employment History, social network relationships, income and education. PROSPERO registration number CRD42018088012.
Otto Wong - One of the best experts on this subject based on the ideXlab platform.
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a hospital based case control study of acute myeloid leukemia in shanghai analysis of environmental and occupational risk factors by subtypes of the who classification
Chemico-Biological Interactions, 2010Co-Authors: Otto Wong, Fran Harris, Thomas W Armstrong, Fu HuaAbstract:The objectives were: (1) to investigate potential environmental and occupational risk factors of acute myeloid leukemia (AML), and (2) to explore the relationships between risk factors and AML subtypes according to the World Health Organization (WHO) classification. The investigation was a hospital-based case-control study consisting of 722 newly diagnosed AML cases (August 2003 through June 2007) and 1444 individually gender-age-matched patient controls at 29 hospitals in Shanghai. A 17-page questionnaire was used to obtain information on demographics, medical History, family History, lifestyle risk factors, Employment History, residential History, and occupational and non-occupational exposures. Certain occupations of interest triggered a second questionnaire, which was occupation-specific and asked for more details about jobs, tasks, materials used and work environment. Exposure assessments were based on the questionnaires, on-site workplace investigations, data published in the Chinese literature, historical exposure measurements maintained by government health agencies, and expert opinions of a panel of local scientists who were familiar with workplaces in Shanghai. Risk estimates (odds ratios and 95% confidence intervals) of individual risk factors were calculated using conditional logistic regression models. A number of potential environmental and occupational risk factors were associated with an increased risk of AML (all subtypes combined) and/or individual subtypes; including home or workplace renovation, living on a farm, planting crops, raising livestock or animals, farm workers, metal workers, rubber and plastic workers, wood and furniture workers, printers, loading and unloading workers, automobile manufacturing, general construction, and food and beverage industry (restaurants and other eateries). Exposures associated with an increased risk of AML (all subtypes combined) and/or individual subtypes included benzene, diesel fuel, metals, insecticides, fertilizers, glues and adhesives, paints and other coatings, and inks and pigments. Multivariate models were used to adjust for potential confounding exposures, and several potential risk factors were subsequently eliminated. The results of the investigation indicated that some risk factors applied to all or most subtypes (e.g., living on a farm and overall AML and several subtypes), while others to specific subtypes only (e.g., raising livestock and AML with multilineage dysplasia). Thus, some risk factors were subtype-specific. The difference in risk by subtype underscores the importance of the etiologic commonality and heterogeneity of AML subtypes.
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a hospital based case control study of acute myeloid leukemia in shanghai analysis of personal characteristics lifestyle and environmental risk factors by subtypes of the who classification
Regulatory Toxicology and Pharmacology, 2009Co-Authors: Otto Wong, Fran Harris, Wang Yiying, Fu HuaAbstract:Abstract Objectives The objectives are (1) to investigate and identify potential risk factors (personal characteristics, lifestyle and environmental factors) of acute myeloid leukemia (AML), and (2) to explore the relationships between potential risk factors and AML subtypes according to the World Health Organization (WHO) classification of myeloid neoplasms. Materials and methods The investigation was a hospital-based case-control study consisting of 722 confirmed AML cases and 1444 individually gender-age-matched patient controls at 29 hospitals in Shanghai. A 17-page questionnaire was used to obtain information on: demographics, medical History, family History, lifestyle risk factors, Employment History, residential History, and environmental and occupational exposures. Certain occupations of interest triggered a second questionnaire, which was occupation-specific and asked for more details about jobs, tasks, materials used and work environment. Risk estimates (odds ratios and 95% confidence intervals) were calculated using conditional logistic regression models. Results Several potential risk factors of AML (all subtypes combined) and individual subtypes were identified; including low-level education, body mass index (BMI), blood transfusion, smoking, alcohol consumption, home or workplace renovation, living on a farm, planting crops, raising livestock or animals, Employment as farm workers or in the agricultural industry, and exposures to insecticides or fertilizers. Some risk factors applied to all or several subtypes (such as low-level education and living on a farm), while others were limited to one or two specific subtypes (such as home/office renovation and acute promyelocytic leukemia). An inverse association was found between BMI and overall AML or the sub-category “AML not otherwise categorized”, whereas a positive association between BMI and the subtype acute promyelocytic leukemia was detected. An unexpected finding was the association between the use of traditional Chinese medicines and a reduced risk of AML in general as well as several major subtypes. Conclusions The study identified a number of risk factors for AML in general as well as for some specific subtypes. Some of the risk factors were subtype-specific. The difference in risk by subtype underscores the importance of investigating the etiologic commonality and heterogeneity of AML by subtype in epidemiologic research.
Fu Hua - One of the best experts on this subject based on the ideXlab platform.
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a hospital based case control study of acute myeloid leukemia in shanghai analysis of environmental and occupational risk factors by subtypes of the who classification
Chemico-Biological Interactions, 2010Co-Authors: Otto Wong, Fran Harris, Thomas W Armstrong, Fu HuaAbstract:The objectives were: (1) to investigate potential environmental and occupational risk factors of acute myeloid leukemia (AML), and (2) to explore the relationships between risk factors and AML subtypes according to the World Health Organization (WHO) classification. The investigation was a hospital-based case-control study consisting of 722 newly diagnosed AML cases (August 2003 through June 2007) and 1444 individually gender-age-matched patient controls at 29 hospitals in Shanghai. A 17-page questionnaire was used to obtain information on demographics, medical History, family History, lifestyle risk factors, Employment History, residential History, and occupational and non-occupational exposures. Certain occupations of interest triggered a second questionnaire, which was occupation-specific and asked for more details about jobs, tasks, materials used and work environment. Exposure assessments were based on the questionnaires, on-site workplace investigations, data published in the Chinese literature, historical exposure measurements maintained by government health agencies, and expert opinions of a panel of local scientists who were familiar with workplaces in Shanghai. Risk estimates (odds ratios and 95% confidence intervals) of individual risk factors were calculated using conditional logistic regression models. A number of potential environmental and occupational risk factors were associated with an increased risk of AML (all subtypes combined) and/or individual subtypes; including home or workplace renovation, living on a farm, planting crops, raising livestock or animals, farm workers, metal workers, rubber and plastic workers, wood and furniture workers, printers, loading and unloading workers, automobile manufacturing, general construction, and food and beverage industry (restaurants and other eateries). Exposures associated with an increased risk of AML (all subtypes combined) and/or individual subtypes included benzene, diesel fuel, metals, insecticides, fertilizers, glues and adhesives, paints and other coatings, and inks and pigments. Multivariate models were used to adjust for potential confounding exposures, and several potential risk factors were subsequently eliminated. The results of the investigation indicated that some risk factors applied to all or most subtypes (e.g., living on a farm and overall AML and several subtypes), while others to specific subtypes only (e.g., raising livestock and AML with multilineage dysplasia). Thus, some risk factors were subtype-specific. The difference in risk by subtype underscores the importance of the etiologic commonality and heterogeneity of AML subtypes.
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a hospital based case control study of acute myeloid leukemia in shanghai analysis of personal characteristics lifestyle and environmental risk factors by subtypes of the who classification
Regulatory Toxicology and Pharmacology, 2009Co-Authors: Otto Wong, Fran Harris, Wang Yiying, Fu HuaAbstract:Abstract Objectives The objectives are (1) to investigate and identify potential risk factors (personal characteristics, lifestyle and environmental factors) of acute myeloid leukemia (AML), and (2) to explore the relationships between potential risk factors and AML subtypes according to the World Health Organization (WHO) classification of myeloid neoplasms. Materials and methods The investigation was a hospital-based case-control study consisting of 722 confirmed AML cases and 1444 individually gender-age-matched patient controls at 29 hospitals in Shanghai. A 17-page questionnaire was used to obtain information on: demographics, medical History, family History, lifestyle risk factors, Employment History, residential History, and environmental and occupational exposures. Certain occupations of interest triggered a second questionnaire, which was occupation-specific and asked for more details about jobs, tasks, materials used and work environment. Risk estimates (odds ratios and 95% confidence intervals) were calculated using conditional logistic regression models. Results Several potential risk factors of AML (all subtypes combined) and individual subtypes were identified; including low-level education, body mass index (BMI), blood transfusion, smoking, alcohol consumption, home or workplace renovation, living on a farm, planting crops, raising livestock or animals, Employment as farm workers or in the agricultural industry, and exposures to insecticides or fertilizers. Some risk factors applied to all or several subtypes (such as low-level education and living on a farm), while others were limited to one or two specific subtypes (such as home/office renovation and acute promyelocytic leukemia). An inverse association was found between BMI and overall AML or the sub-category “AML not otherwise categorized”, whereas a positive association between BMI and the subtype acute promyelocytic leukemia was detected. An unexpected finding was the association between the use of traditional Chinese medicines and a reduced risk of AML in general as well as several major subtypes. Conclusions The study identified a number of risk factors for AML in general as well as for some specific subtypes. Some of the risk factors were subtype-specific. The difference in risk by subtype underscores the importance of investigating the etiologic commonality and heterogeneity of AML by subtype in epidemiologic research.
Francesca Lucaroni - One of the best experts on this subject based on the ideXlab platform.
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can risk be predicted an umbrella systematic review of current risk prediction models for cardiovascular diseases diabetes and hypertension
BMJ Open, 2019Co-Authors: Francesca Lucaroni, Domenico Cicciarella Modica, Mattia Macino, Leonardo Palombi, Alessio Abbondanzieri, Giulia Agosti, Giorgia Biondi, Liat Morciano, Antonio VinciAbstract:Objective To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases. Design Umbrella systematic review. Data sources PubMed, Scopus, Cochrane Library. Eligibility criteria Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18–65 years old) population, published in English language. Data extraction and synthesis Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study selection 3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added. Study appraisal The methodological quality of the included studies was assessed using the AMSTAR tool. Risk of bias in individual studies Risk of Bias evaluation was carried out using the ROBIS tool. Results Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone. Limitations Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out. Conclusions Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and Employment History, social network relationships, income and education. PROSPERO registration number CRD42018088012.
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can risk be predicted an umbrella systematic review of current risk prediction models for cardiovascular diseases diabetes and hypertension
BMJ Open, 2019Co-Authors: Francesca Lucaroni, Domenico Cicciarella Modica, Mattia Macino, Leonardo Palombi, Alessio Abbondanzieri, Giulia Agosti, Giorgia Biondi, Liat Morciano, Antonio VinciAbstract:Objective To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases. Design Umbrella systematic review. Data sources PubMed, Scopus, Cochrane Library. Eligibility criteria Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18–65 years old) population, published in English language. Data extraction and synthesis Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study selection 3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added. Study appraisal The methodological quality of the included studies was assessed using the AMSTAR tool. Risk of bias in individual studies Risk of Bias evaluation was carried out using the ROBIS tool. Results Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone. Limitations Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out. Conclusions Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and Employment History, social network relationships, income and education. PROSPERO registration number CRD42018088012.
Alessio Abbondanzieri - One of the best experts on this subject based on the ideXlab platform.
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can risk be predicted an umbrella systematic review of current risk prediction models for cardiovascular diseases diabetes and hypertension
BMJ Open, 2019Co-Authors: Francesca Lucaroni, Domenico Cicciarella Modica, Mattia Macino, Leonardo Palombi, Alessio Abbondanzieri, Giulia Agosti, Giorgia Biondi, Liat Morciano, Antonio VinciAbstract:Objective To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases. Design Umbrella systematic review. Data sources PubMed, Scopus, Cochrane Library. Eligibility criteria Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18–65 years old) population, published in English language. Data extraction and synthesis Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study selection 3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added. Study appraisal The methodological quality of the included studies was assessed using the AMSTAR tool. Risk of bias in individual studies Risk of Bias evaluation was carried out using the ROBIS tool. Results Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone. Limitations Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out. Conclusions Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and Employment History, social network relationships, income and education. PROSPERO registration number CRD42018088012.
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can risk be predicted an umbrella systematic review of current risk prediction models for cardiovascular diseases diabetes and hypertension
BMJ Open, 2019Co-Authors: Francesca Lucaroni, Domenico Cicciarella Modica, Mattia Macino, Leonardo Palombi, Alessio Abbondanzieri, Giulia Agosti, Giorgia Biondi, Liat Morciano, Antonio VinciAbstract:Objective To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases. Design Umbrella systematic review. Data sources PubMed, Scopus, Cochrane Library. Eligibility criteria Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18–65 years old) population, published in English language. Data extraction and synthesis Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study selection 3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added. Study appraisal The methodological quality of the included studies was assessed using the AMSTAR tool. Risk of bias in individual studies Risk of Bias evaluation was carried out using the ROBIS tool. Results Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone. Limitations Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out. Conclusions Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and Employment History, social network relationships, income and education. PROSPERO registration number CRD42018088012.
