Downloaded from http://heart.bmj.com/ on June 9, 2015 - Published by group.bmj.com
Editorial
Poverty, development and cardiovascular trials: More questions than answers? Amitava Banerjee Cardiovascular disease (CVD) is the leading cause of global mortality and morbidity, and the vast majority of the disease burden is in low-income countries (LICs) and lowincome to middle-income countries (LMICs).1 CVD research, including clinical trials, is among the most productive in biomedical science, whether in terms of funding, publications or novel treatment strategies.2 However, the majority of this research does not represent the population where the highest proportion of CVD is concentrated, that is, LICs and LMICs.3 Therefore, research findings may not be applicable to most of the patients with CVD in the world, for example, risk prediction tools, projections of incidence and outcome, new drugs and devices and healthcare infrastructure. The so-called ‘10– 90 gap’, where only 10% is allocated to poor countries that bear 90% of the world’s disease burden, describes the global inequity in research funding but underestimates the actual inequality in terms of research publications and research capacity.4 The associations between health, poverty and development are not in question.5 The role of poverty and development in cause and effect of CVD, and more broadly, non-communicable diseases, is crucial, yet under-recognised and underplayed in research, clinical practice and policy spheres. The paradox is that CVD, particularly coronary artery disease (CAD), is probably one of the most fertile grounds for research and trials worldwide compared with other disease areas. Increasing number of trials and registries are recruiting patients in lower-income countries.6–8 A major motivation for this shift is the lower cost of recruitment and trial management in these settings; however, a potential positive spin-off is that results of trials may be more applicable to the global burden of disease. Roy and colleagues report the associations between human development index and outcomes in the Targeted Platelet Correspondence to Dr Amitava Banerjee, University of Birmingham Centre for Cardiovascular Sciences, College of Medical & Dental Sciences, School of Clinical and Experimental Medicine, Edgbaston, Birmingham, West Midlands B15 2TT, UK; [email protected]
Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trial population.9 The TRILOGY ACS trial included patients with ACS without revascularisation, randomly assigning them to prasugrel or clopidogrel with background low-dose aspirin. In their analysis, the authors consider 9301 patients with ACS from 51 countries. Using 2010 country-level United Nations Human Development Indices (HDIs) and per-capita gross national income (GNI), they compare baseline characteristics and clinical outcomes.10 The authors are to be commended for investigating this important and understudied aspect of the increasingly globalised clinical trial paradigm. Although an increasing number of epidemiological studies and trials include analyses of socioeconomic status as an indicator of poverty8 10 11 and relationship with CVD outcomes, no previous study has considered human development as a risk factor. TRILOGY ACS enrolled 3659 patients from 27 very high-HDI countries, 3744 from 18 high-HDI countries and 1898 from 6 medium-HDI countries. A major feature of this trial (as with the majority of clinical trials across all diseases) is that LICs (where the low HDI population of the world is concentrated) were not recruitment strategy. Roy and coauthors showed significant variation in baseline characteristics among countries by HDI, with the lowest cardiovascular risk profile in medium-HDI countries.9 The lower observed event rates for the composite outcome of cardiovascular death, myocardial infarction (MI) or stroke in patients from medium-HDI and high-HDI countries compared with medium-HDI countries were explained by the differences in baseline characteristics. In the analyses based on GNI, event rates for the composite endpoint were lower in LMICs versus upper–middle income and high-income countries, largely attributable to MI rates.9 These differences persisted despite adjustment for baseline characteristics and are contrary to recent ACS registries. The authors speculate that this finding may be explained by (a) the recruitment strategy (which included patients Banerjee A. Heart February 2015 Vol 101 No 4
listed for medical management, thereby reducing inter-country differences due to access to and timing of interventional therapies); (b) differences in healthcareseeking behaviour in LICs or (c) use of more sensitive diagnostic strategies to detect MI in higher-income countries. These variations in baseline characteristics and outcomes identified by Roy and colleagues are instructive in considerations of trial design and in the interpretation and application of trial findings. As stated by the authors, ‘This trial highlights the fact that despite the application of uniform study eligibility criteria, baseline characteristics differed significantly among patients from different HDI-classified countries in this global study of patients with ACS9’. It is important to note that more variation in baseline characteristics would be expected if individuals from low-HDI settings were included. The issues raised by the analysis of HDI are fundamental to the methodology of clinical trials that are increasingly multinational and increasingly global in their nature. Global epidemiological studies have highlighted that similar risk factors explain CVD, regardless of the geographical region of the world.11 13 However, small differences in risk factor profile and baseline characteristics of the study population can have important effects on outcomes of clinical trials. Even within countries, there are significant variations in baseline characteristics, particularly countries as large as India. Therefore, considerable variations are to be expected between countries and by HDI or GNI. Although clinical trials attempt to recruit similar patients at all trial sites, there will be differences in risk factor profiles, presentation, treatment and outcome. Figure 1 shows two simplified pathways: from ‘real-world’ populations to clinical trials and from trials back to individuals in the ‘real-world’ population. When considering the global impact of novel treatments, whether in individuals or populations, the current trial model is too simplified and there are many factors that influence the actual effect of a drug in the real world.12 In considering global aspects of clinical trials, it is helpful to return to the theory of clinical trials and epidemiological definitions (box 1). Trials such as TRILOGY ACS are measuring efficacy of treatments and not their effectiveness. In order to use a treatment on the basis of a trial, the reader must be convinced of both the internal validity and the external validity (also known as generalisability) of the trial (figure 1).12 The internal validity relies on the minimisation of bias and confounding 245
Downloaded from http://heart.bmj.com/ on June 9, 2015 - Published by group.bmj.com
Editorial
Figure 1 From populations to trials and trials to populations. and the recognition of interaction (also known as effect modification). First, the role of country-level factors, such as HDI and GNI, can introduce biases, confounding and effect modification into a clinical trial. Using the TRILOGY ACS trial as an example, if participants in LICs were less likely to seek medical attention than in high-income countries, there may be a selection bias among the individuals included in the trial, for example, the LIC participants may present later in their
disease process with a worse risk factor profile. Second, if patients in low-GNI or low-HDI countries had less access to secondary prevention drugs such as statins and β-blockers, then GNI or HDI may be a potential confounder in the overall treatment effect observed for prasugrel. Third, HDI and GNI may show interactions between traditional risk factors and clinical outcomes such as MI. External validity and effectiveness studies are relatively neglected in clinical
Box 1 Definitions of epidemiological terms relevant to clinical trials [26][27] Efficacy: Can the treatment work under ideal circumstances? Effectiveness: Will the treatment work in real-world circumstances? Internal validity: Are the effects described due to the treatment? External validity: Can the results be reasonably applied to a definable group of patients in a particular clinical setting in routine practice? Bias: A systematic error in the design, recruitment, data collection or analysis that results in an erroneous estimation of the real effect of the exposure and the outcome. Confounding: The effect or association between an exposure and outcome is affected by the presence of another variable. Positive confounding (when the observed association is biased away from the null) and negative confounding (when the observed association is biased towards the null) both occur. Interaction (also known as ‘effect modification’): a variable that differentially ( positively and negatively) modifies the observed effect of a risk factor on disease status. Different groups have different risk estimates when effect modification is present. 246
trials, and yet as trials recruit more patients from countries of varying geography, income and development, generalisability of trial findings is crucial.12 14 15 Geographical variation can lead to misleading subgroup analyses in multinational cardiovascular trials,14 15 and HDI and GNI, as measures of country-level income and development, provide additional information about trial participants. It is well documented that geographical variations (and other country-level factors) in trial study populations and outcomes can have important effects on heterogeneity and statistical power calculations. Investigators must take these factors into account when designing, conducting and analysing trials to enable the proper interpretation of their trial findings.9 Predefined subgroups with regards to geographical location, poverty and development are the gold standard.14 As suggested by Rothwell, external validity should be part of (a) further research, (b) stricter requirements for trials submitted to pharmaceutical licensing authorities, (c) guidelines on the reporting of trials and systematic reviews and (d) primary reports of trials or systematic reviews in publications.12 An analysis of poverty and development with respect to clinical trials must mention ethical considerations of multinational trials. The PURE study has emphasised that simple off-patent drugs are not necessarily available and adherence is very poor. For example, in a recent analysis of patients with CAD in India, Pakistan and Bangladesh, the proportion taking antiplatelet agents, β-blockers, angiotensin-converting enzyme inhibitors and statins were 11.6%, 11.9%, 6.4% and 4.8%, respectively. Among patients with CAD and stroke, 81.5% were taking no medications at all. Individuals from lower socioeconomic status areas within the study were less likely to take medications.11 In this environment, how can we analyse the internal or external validity of trials of new antiplatelet agents, novel anticoagulants and other drugs that have been the subject of recent multinational trials?6–9 What is the role of prasugrel in an environment when aspirin and other proven, off-patent secondary prevention therapies are so frequently absent and what is the real likelihood of new drugs being sustainably used in these settings? It should be noted that these are concerns in international CVD trials where low-GNI and low-HDI countries are currently not included; the ethical issues are likely to be more challenging with the involvement of LICs. There has been considerable debate about Banerjee A. Heart February 2015 Vol 101 No 4
Downloaded from http://heart.bmj.com/ on June 9, 2015 - Published by group.bmj.com
Editorial these ethical issues in HIV/AIDS and infectious diseases research over the last two decades, but surprisingly little in the CVD literature.16–18 These discussions must be led by those countries where clinical trials are rapidly increasing, such as India.19 As well as considering poverty and development as covariates in analyses of trial outcomes, the broader ethical concerns related to poverty and development must be tackled and lessons should be learned from the infectious diseases arena. Competing interests None. Provenance and peer review Commissioned; internally peer reviewed. ▸ Additional material is published online only. To view please visit the journal online (http://dx.doi.org/10. 1136/heartjnl-2014-306946).
Heart 2015;101:245–247. doi:10.1136/heartjnl-2014-306946 10
REFERENCES 1
2
3
4
5 6
7
To cite Banerjee A. Heart 2015;101:245–247. Received 26 October 2014 Revised 30 October 2014 Accepted 31 October 2014 Published Online First 23 December 2014
▸ http://dx.doi.org/10.1136/heartjnl-2014-306389
Banerjee A. Heart February 2015 Vol 101 No 4
8
9
Sanderson JE, Mayosi B, Yusuf S, et al. Global burden of cardiovascular disease. Heart 2007;93:1175. Huffman MD, Baldridge A, Bloomfield GS, et al. Global cardiovascular research output, citations, and collaborations: a time-trend, bibliometric analysis (1999–2008). PLoS ONE 2013;8:e83440. Heneghan C, Blacklock C, Perera R, et al. Evidence for non-communicable diseases: analysis of Cochrane reviews and randomised trials by World Bank classification. BMJ Open 2013;3:pii:e003298. Horton R. Medical journals: evidence of bias against the diseases of poverty. Lancet 2003; 361:712–13. Sen A. Health in development. Bull World Health Organ 1999;77:619–23. Fox KA, Goodman SG, Klein W, et al. Management of acute coronary syndromes. Variations in practice and outcome; findings from the Global Registry of Acute Coronary Events (GRACE). Eur Heart J 2002;23:1177–89. Connolly SJ, Ezekowitz MD, Yusuf S, et al. RE-LY Steering Committee and Investigators. RE-LY Steering Committee and Investigators. Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med 2009;361:1139–51. Yusuf S, Flather M, Pogue J, et al. Variations between countries in invasive cardiac procedures and outcomes in patients with suspected unstable angina or myocardial infarction without initial ST elevation. OASIS (Organisation to Assess Strategies for Ischaemic Syndromes) Registry Investigators. Lancet 1998;352:507–14. Roy A, Roe MT, Neely ML, et al. Impact of Human Development Index on the profile and outcomes of
11
12
13
14
15
16 17
18
19
acute coronary syndrome patients. Heart 2015;101:279–86. Anand S, Sen A. Human Development Index: Methodology and Measurement. Human Development Occasional Papers HDOCPA-1994-02. Human Development Report Office, United Nations Development Programme; 1994. http://hdr.undp.org/en/media/ Anand_and_Sen_HDI.pdf (accessed 19 Oct 2014). Gupta R, Islam S, Mony P, et al. Socioeconomic factors and use of secondary preventive therapies for cardiovascular diseases in South Asia: The PURE study. Eur J Prev Cardiol 2014 Jun 18. pii:2047487314540386 [Epub ahead of print]. Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?”. Lancet 2005;365:82–93. Yusuf S, Hawken S, Ounpuu S, et al.; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004;364:937–52. Pocock S, Calvo G, Marrugat J, et al. International differences in treatment effect: do they really exist and why? Eur Heart J 2013;34:1846–52. Nallamothu BK, Hayward RA, Bates ER. Beyond the randomized clinical trial: the role of effectiveness studies in evaluating cardiovascular therapies. Circulation 2008;118:1294–303. Angell M. The ethics of clinical research in the Third World. N Engl J Med 1997;337:847–9. Shah S, Elmer S, Grady C. Planning for posttrial access to antiretroviral treatment for research participants in developing countries. Am J Public Health 2009;99:1556–62. Matee MI, Manyando C, Ndumbe PM, et al. European and Developing Countries Clinical Trials Partnership (EDCTP): the path towards a true partnership. BMC Public Health 2009;9:249. Clinical trials in India: ethical concerns. Bull World Health Organ 2008;86:581–2.
247
Downloaded from http://heart.bmj.com/ on June 9, 2015 - Published by group.bmj.com
Poverty, development and cardiovascular trials: More questions than answers? Amitava Banerjee Heart 2015 101: 245-247 originally published online December 23, 2014
doi: 10.1136/heartjnl-2014-306946 Updated information and services can be found at: http://heart.bmj.com/content/101/4/245
These include:
Supplementary Supplementary material can be found at: Material http://heart.bmj.com/content/suppl/2014/12/23/heartjnl-2014-306946. DC1.html
References Email alerting service
Topic Collections
This article cites 8 articles, 2 of which you can access for free at: http://heart.bmj.com/content/101/4/245#BIBL Receive free email alerts when new articles cite this article. Sign up in the box at the top right corner of the online article.
Articles on similar topics can be found in the following collections Drugs: cardiovascular system (8367) Epidemiology (3480) Acute coronary syndromes (2601)
Notes
To request permissions go to: http://group.bmj.com/group/rights-licensing/permissions To order reprints go to: http://journals.bmj.com/cgi/reprintform To subscribe to BMJ go to: http://group.bmj.com/subscribe/
Editorial
Poverty, development and cardiovascular trials: More questions than answers? Amitava Banerjee Cardiovascular disease (CVD) is the leading cause of global mortality and morbidity, and the vast majority of the disease burden is in low-income countries (LICs) and lowincome to middle-income countries (LMICs).1 CVD research, including clinical trials, is among the most productive in biomedical science, whether in terms of funding, publications or novel treatment strategies.2 However, the majority of this research does not represent the population where the highest proportion of CVD is concentrated, that is, LICs and LMICs.3 Therefore, research findings may not be applicable to most of the patients with CVD in the world, for example, risk prediction tools, projections of incidence and outcome, new drugs and devices and healthcare infrastructure. The so-called ‘10– 90 gap’, where only 10% is allocated to poor countries that bear 90% of the world’s disease burden, describes the global inequity in research funding but underestimates the actual inequality in terms of research publications and research capacity.4 The associations between health, poverty and development are not in question.5 The role of poverty and development in cause and effect of CVD, and more broadly, non-communicable diseases, is crucial, yet under-recognised and underplayed in research, clinical practice and policy spheres. The paradox is that CVD, particularly coronary artery disease (CAD), is probably one of the most fertile grounds for research and trials worldwide compared with other disease areas. Increasing number of trials and registries are recruiting patients in lower-income countries.6–8 A major motivation for this shift is the lower cost of recruitment and trial management in these settings; however, a potential positive spin-off is that results of trials may be more applicable to the global burden of disease. Roy and colleagues report the associations between human development index and outcomes in the Targeted Platelet Correspondence to Dr Amitava Banerjee, University of Birmingham Centre for Cardiovascular Sciences, College of Medical & Dental Sciences, School of Clinical and Experimental Medicine, Edgbaston, Birmingham, West Midlands B15 2TT, UK; [email protected]
Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trial population.9 The TRILOGY ACS trial included patients with ACS without revascularisation, randomly assigning them to prasugrel or clopidogrel with background low-dose aspirin. In their analysis, the authors consider 9301 patients with ACS from 51 countries. Using 2010 country-level United Nations Human Development Indices (HDIs) and per-capita gross national income (GNI), they compare baseline characteristics and clinical outcomes.10 The authors are to be commended for investigating this important and understudied aspect of the increasingly globalised clinical trial paradigm. Although an increasing number of epidemiological studies and trials include analyses of socioeconomic status as an indicator of poverty8 10 11 and relationship with CVD outcomes, no previous study has considered human development as a risk factor. TRILOGY ACS enrolled 3659 patients from 27 very high-HDI countries, 3744 from 18 high-HDI countries and 1898 from 6 medium-HDI countries. A major feature of this trial (as with the majority of clinical trials across all diseases) is that LICs (where the low HDI population of the world is concentrated) were not recruitment strategy. Roy and coauthors showed significant variation in baseline characteristics among countries by HDI, with the lowest cardiovascular risk profile in medium-HDI countries.9 The lower observed event rates for the composite outcome of cardiovascular death, myocardial infarction (MI) or stroke in patients from medium-HDI and high-HDI countries compared with medium-HDI countries were explained by the differences in baseline characteristics. In the analyses based on GNI, event rates for the composite endpoint were lower in LMICs versus upper–middle income and high-income countries, largely attributable to MI rates.9 These differences persisted despite adjustment for baseline characteristics and are contrary to recent ACS registries. The authors speculate that this finding may be explained by (a) the recruitment strategy (which included patients Banerjee A. Heart February 2015 Vol 101 No 4
listed for medical management, thereby reducing inter-country differences due to access to and timing of interventional therapies); (b) differences in healthcareseeking behaviour in LICs or (c) use of more sensitive diagnostic strategies to detect MI in higher-income countries. These variations in baseline characteristics and outcomes identified by Roy and colleagues are instructive in considerations of trial design and in the interpretation and application of trial findings. As stated by the authors, ‘This trial highlights the fact that despite the application of uniform study eligibility criteria, baseline characteristics differed significantly among patients from different HDI-classified countries in this global study of patients with ACS9’. It is important to note that more variation in baseline characteristics would be expected if individuals from low-HDI settings were included. The issues raised by the analysis of HDI are fundamental to the methodology of clinical trials that are increasingly multinational and increasingly global in their nature. Global epidemiological studies have highlighted that similar risk factors explain CVD, regardless of the geographical region of the world.11 13 However, small differences in risk factor profile and baseline characteristics of the study population can have important effects on outcomes of clinical trials. Even within countries, there are significant variations in baseline characteristics, particularly countries as large as India. Therefore, considerable variations are to be expected between countries and by HDI or GNI. Although clinical trials attempt to recruit similar patients at all trial sites, there will be differences in risk factor profiles, presentation, treatment and outcome. Figure 1 shows two simplified pathways: from ‘real-world’ populations to clinical trials and from trials back to individuals in the ‘real-world’ population. When considering the global impact of novel treatments, whether in individuals or populations, the current trial model is too simplified and there are many factors that influence the actual effect of a drug in the real world.12 In considering global aspects of clinical trials, it is helpful to return to the theory of clinical trials and epidemiological definitions (box 1). Trials such as TRILOGY ACS are measuring efficacy of treatments and not their effectiveness. In order to use a treatment on the basis of a trial, the reader must be convinced of both the internal validity and the external validity (also known as generalisability) of the trial (figure 1).12 The internal validity relies on the minimisation of bias and confounding 245
Downloaded from http://heart.bmj.com/ on June 9, 2015 - Published by group.bmj.com
Editorial
Figure 1 From populations to trials and trials to populations. and the recognition of interaction (also known as effect modification). First, the role of country-level factors, such as HDI and GNI, can introduce biases, confounding and effect modification into a clinical trial. Using the TRILOGY ACS trial as an example, if participants in LICs were less likely to seek medical attention than in high-income countries, there may be a selection bias among the individuals included in the trial, for example, the LIC participants may present later in their
disease process with a worse risk factor profile. Second, if patients in low-GNI or low-HDI countries had less access to secondary prevention drugs such as statins and β-blockers, then GNI or HDI may be a potential confounder in the overall treatment effect observed for prasugrel. Third, HDI and GNI may show interactions between traditional risk factors and clinical outcomes such as MI. External validity and effectiveness studies are relatively neglected in clinical
Box 1 Definitions of epidemiological terms relevant to clinical trials [26][27] Efficacy: Can the treatment work under ideal circumstances? Effectiveness: Will the treatment work in real-world circumstances? Internal validity: Are the effects described due to the treatment? External validity: Can the results be reasonably applied to a definable group of patients in a particular clinical setting in routine practice? Bias: A systematic error in the design, recruitment, data collection or analysis that results in an erroneous estimation of the real effect of the exposure and the outcome. Confounding: The effect or association between an exposure and outcome is affected by the presence of another variable. Positive confounding (when the observed association is biased away from the null) and negative confounding (when the observed association is biased towards the null) both occur. Interaction (also known as ‘effect modification’): a variable that differentially ( positively and negatively) modifies the observed effect of a risk factor on disease status. Different groups have different risk estimates when effect modification is present. 246
trials, and yet as trials recruit more patients from countries of varying geography, income and development, generalisability of trial findings is crucial.12 14 15 Geographical variation can lead to misleading subgroup analyses in multinational cardiovascular trials,14 15 and HDI and GNI, as measures of country-level income and development, provide additional information about trial participants. It is well documented that geographical variations (and other country-level factors) in trial study populations and outcomes can have important effects on heterogeneity and statistical power calculations. Investigators must take these factors into account when designing, conducting and analysing trials to enable the proper interpretation of their trial findings.9 Predefined subgroups with regards to geographical location, poverty and development are the gold standard.14 As suggested by Rothwell, external validity should be part of (a) further research, (b) stricter requirements for trials submitted to pharmaceutical licensing authorities, (c) guidelines on the reporting of trials and systematic reviews and (d) primary reports of trials or systematic reviews in publications.12 An analysis of poverty and development with respect to clinical trials must mention ethical considerations of multinational trials. The PURE study has emphasised that simple off-patent drugs are not necessarily available and adherence is very poor. For example, in a recent analysis of patients with CAD in India, Pakistan and Bangladesh, the proportion taking antiplatelet agents, β-blockers, angiotensin-converting enzyme inhibitors and statins were 11.6%, 11.9%, 6.4% and 4.8%, respectively. Among patients with CAD and stroke, 81.5% were taking no medications at all. Individuals from lower socioeconomic status areas within the study were less likely to take medications.11 In this environment, how can we analyse the internal or external validity of trials of new antiplatelet agents, novel anticoagulants and other drugs that have been the subject of recent multinational trials?6–9 What is the role of prasugrel in an environment when aspirin and other proven, off-patent secondary prevention therapies are so frequently absent and what is the real likelihood of new drugs being sustainably used in these settings? It should be noted that these are concerns in international CVD trials where low-GNI and low-HDI countries are currently not included; the ethical issues are likely to be more challenging with the involvement of LICs. There has been considerable debate about Banerjee A. Heart February 2015 Vol 101 No 4
Downloaded from http://heart.bmj.com/ on June 9, 2015 - Published by group.bmj.com
Editorial these ethical issues in HIV/AIDS and infectious diseases research over the last two decades, but surprisingly little in the CVD literature.16–18 These discussions must be led by those countries where clinical trials are rapidly increasing, such as India.19 As well as considering poverty and development as covariates in analyses of trial outcomes, the broader ethical concerns related to poverty and development must be tackled and lessons should be learned from the infectious diseases arena. Competing interests None. Provenance and peer review Commissioned; internally peer reviewed. ▸ Additional material is published online only. To view please visit the journal online (http://dx.doi.org/10. 1136/heartjnl-2014-306946).
Heart 2015;101:245–247. doi:10.1136/heartjnl-2014-306946 10
REFERENCES 1
2
3
4
5 6
7
To cite Banerjee A. Heart 2015;101:245–247. Received 26 October 2014 Revised 30 October 2014 Accepted 31 October 2014 Published Online First 23 December 2014
▸ http://dx.doi.org/10.1136/heartjnl-2014-306389
Banerjee A. Heart February 2015 Vol 101 No 4
8
9
Sanderson JE, Mayosi B, Yusuf S, et al. Global burden of cardiovascular disease. Heart 2007;93:1175. Huffman MD, Baldridge A, Bloomfield GS, et al. Global cardiovascular research output, citations, and collaborations: a time-trend, bibliometric analysis (1999–2008). PLoS ONE 2013;8:e83440. Heneghan C, Blacklock C, Perera R, et al. Evidence for non-communicable diseases: analysis of Cochrane reviews and randomised trials by World Bank classification. BMJ Open 2013;3:pii:e003298. Horton R. Medical journals: evidence of bias against the diseases of poverty. Lancet 2003; 361:712–13. Sen A. Health in development. Bull World Health Organ 1999;77:619–23. Fox KA, Goodman SG, Klein W, et al. Management of acute coronary syndromes. Variations in practice and outcome; findings from the Global Registry of Acute Coronary Events (GRACE). Eur Heart J 2002;23:1177–89. Connolly SJ, Ezekowitz MD, Yusuf S, et al. RE-LY Steering Committee and Investigators. RE-LY Steering Committee and Investigators. Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med 2009;361:1139–51. Yusuf S, Flather M, Pogue J, et al. Variations between countries in invasive cardiac procedures and outcomes in patients with suspected unstable angina or myocardial infarction without initial ST elevation. OASIS (Organisation to Assess Strategies for Ischaemic Syndromes) Registry Investigators. Lancet 1998;352:507–14. Roy A, Roe MT, Neely ML, et al. Impact of Human Development Index on the profile and outcomes of
11
12
13
14
15
16 17
18
19
acute coronary syndrome patients. Heart 2015;101:279–86. Anand S, Sen A. Human Development Index: Methodology and Measurement. Human Development Occasional Papers HDOCPA-1994-02. Human Development Report Office, United Nations Development Programme; 1994. http://hdr.undp.org/en/media/ Anand_and_Sen_HDI.pdf (accessed 19 Oct 2014). Gupta R, Islam S, Mony P, et al. Socioeconomic factors and use of secondary preventive therapies for cardiovascular diseases in South Asia: The PURE study. Eur J Prev Cardiol 2014 Jun 18. pii:2047487314540386 [Epub ahead of print]. Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?”. Lancet 2005;365:82–93. Yusuf S, Hawken S, Ounpuu S, et al.; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004;364:937–52. Pocock S, Calvo G, Marrugat J, et al. International differences in treatment effect: do they really exist and why? Eur Heart J 2013;34:1846–52. Nallamothu BK, Hayward RA, Bates ER. Beyond the randomized clinical trial: the role of effectiveness studies in evaluating cardiovascular therapies. Circulation 2008;118:1294–303. Angell M. The ethics of clinical research in the Third World. N Engl J Med 1997;337:847–9. Shah S, Elmer S, Grady C. Planning for posttrial access to antiretroviral treatment for research participants in developing countries. Am J Public Health 2009;99:1556–62. Matee MI, Manyando C, Ndumbe PM, et al. European and Developing Countries Clinical Trials Partnership (EDCTP): the path towards a true partnership. BMC Public Health 2009;9:249. Clinical trials in India: ethical concerns. Bull World Health Organ 2008;86:581–2.
247
Downloaded from http://heart.bmj.com/ on June 9, 2015 - Published by group.bmj.com
Poverty, development and cardiovascular trials: More questions than answers? Amitava Banerjee Heart 2015 101: 245-247 originally published online December 23, 2014
doi: 10.1136/heartjnl-2014-306946 Updated information and services can be found at: http://heart.bmj.com/content/101/4/245
These include:
Supplementary Supplementary material can be found at: Material http://heart.bmj.com/content/suppl/2014/12/23/heartjnl-2014-306946. DC1.html
References Email alerting service
Topic Collections
This article cites 8 articles, 2 of which you can access for free at: http://heart.bmj.com/content/101/4/245#BIBL Receive free email alerts when new articles cite this article. Sign up in the box at the top right corner of the online article.
Articles on similar topics can be found in the following collections Drugs: cardiovascular system (8367) Epidemiology (3480) Acute coronary syndromes (2601)
Notes
To request permissions go to: http://group.bmj.com/group/rights-licensing/permissions To order reprints go to: http://journals.bmj.com/cgi/reprintform To subscribe to BMJ go to: http://group.bmj.com/subscribe/
