- Email: [email protected]
Quantity and Quality in Medical Research
Correspondence
JACC Vol. 56, No. 6, 2010 August 3, 2010:525–30
patients who progress to symptomatic Chagas’ disease, we suggested AAB measurement in asymptomatic Chagas’ patients for cardiomyopathy and megacolon risk assessment. We now present first indications supporting our concept. At a median 31 months (range 27 to 47 months) after the primary patient classification, we were able to contact 36 of our primarily asymptomatic patients, of whom 15 were AAB-negative and 21 AAB-positive. In the second investigation, none of the AABnegative patients reported clinical symptoms and had electrocardiographic characteristics indicative of progression to symptomatic Chagas’ disease. Among the AAB-positive patients of the primary investigation, a 40-year-old woman presented with cardiomyopathy diagnosed by electrocardiogram, demonstrating the progression to symptomatic chronic Chagas’ disease. In the primary study, this woman had had the typical cardiomyopathy AAB composition of beta1-AAB combined with M2-AAB. A second patient, a 31-year-old woman, presented with clinically diagnosed megacolon. This woman was burdened in the primary investigation with M2-AAB positivity and borderline positivity for beta2-AAB, which suggest megacolon risk. Despite the tentative nature of the information presented here, we hope that this first successful step in the evaluation of AAB measurement in asymptomatic Chagas’ patients for cardiomyopathy and megacolon risk assessment will further our concept and encourage other scientists to take part in its evaluation. However, considering the time- and cost-intensive bioassay used for the AAB measurement (1), the development of cost-limited but standardized and more universally available enzyme-linked immunosorbent assays seems to be an essential prerequisite. Initiatives in the enzyme-linked immunosorbent assay development should, in our view, first focus on M2-AAB. Both patients who progressed to symptomatic Chagas’ disease presented with M2-AAB in the asymptomatic stage. Therefore, we would like to suggest M2-AAB as the preferential tool in the risk assessment of asymptomatic Chagas’ patients. The use of M2-AAB for risk assessment was also seen as a promising strategy by others (2). Using M2-AAB as a risk marker would also account for the function of M2-AAB in driving the alterations in the autonomic nerve system (3,4) that have frequently been discussed in the pathogenesis of Chagas’ heart and gastrointestinal disease. Silvia Gilka Muñoz Saravia, PhD Annekathrin Haberland, PhD Sabine Bartel, PhD Raul Araujo, MD Gregorio Valda, MD Diana Duchen, MS Ivan Diaz Ramirez, MD Adrian Constantin Borges, MD, PhD Gerd Wallukat, PhD *Ingolf Schimke, PhD *Medizinische Klinik für Kardiologie und Angiologie CCM, Charité Universitätsmedizin Berlin Berlin 10117 Germany E-mail: [email protected] doi:10.1016/j.jacc.2010.02.057
527
REFERENCES
1. Wallukat G, Munoz Saravia GS, Haberland A, et al. Distinct patterns of autoantibodies against G-protein– coupled receptors in Chagas’ cardiomyopathy and megacolon: their potential impact for early risk assessment in asymptomatic Chagas’ patients. J Am Coll Cardiol 2010;55:463– 8. 2. Goin JC, Leiros CP, Borda E, Sterin-Borda L. Interaction of human chagasic IgG with the second extracellular loop of the human muscarinergic acetylcholine receptor: functional and pathological implications. FASEB J 1997;11:77– 83. 3. Goin JC, Borda ES, Auger S, Storino R, Sterin-Borda L. Cardiac M(2) muscarinic cholinoceptor activation by human chagasic autoantibodies: association with bradycardia. Heart 1999:82:273– 8. 4. Sterin-Borda L, Goin JC, Bilder CR, Iantorno G, Hernando AC, Borda E. Interaction of human chagasic IgG with human colon muscarinic acetylcholine receptor: molecular and functional evidence. Gut 2001;49:699 –705.
Quantity and Quality in Medical Research We read with interest the papers by Kaul et al. (1) and Stone et al. (2), published in a recent issue of the Journal. Both highlight vividly the all too commonly found errors and limitations in current medical literature. While the causes of such a state of affairs are multiple, we believe the sheer volume of scientific papers published nowadays is a major contributor. To illustrate this point, a PubMed listings search using the criteria “human, randomized controlled trial” reveals an astounding growth in the number of studies published in each 10-year strata, starting February 4, 1950: 1950 to 1960, no items found; 1960 to 1970, 1,076 studies found; 1970 to 1980, 9,622 studies; 1980 to 1990, 36,066 studies; 1990 to 2000, 91,194 studies; and 2000 to 2010, 136,109 studies found. In the past year alone, 11,276 such papers were found using PubMed. While such a rate of growth may be partly due to widespread use of standardized methodology and the establishment of a worldwide scientific community, less exalted factors such as industry pressures (3) and the “publish or perish” drive (4) may also be at play. It is, therefore, difficult to argue that each or even most of these studies will be sound in their conceptual development, performance, analysis, and interpretation. In truth, the scientific enterprise has in many ways become the scientific industry, and the challenges we now face transcend technical or methodological limitations. Rather than quantity, we must now focus on quality and its indispensable antecedents, competence and integrity. *Iyad N. Daher, MD Syed Wamique Yusuf, MD *Department of Cardiology University of Texas M.D. Anderson Cancer Center 1400 Pressler, Unit 1451 Houston, Texas 77030 E-mail: [email protected] doi:10.1016/j.jacc.2010.02.058
528
Correspondence
REFERENCES
1. Kaul S, Diamond GA. Trial and error. How to avoid commonly encountered limitations of published clinical trials. J Am Coll Cardiol 2010;55:415–27. 2. Stone GW, Pocock SJ. Randomized trials, statistics, and clinical inference. J Am Coll Cardiol 2010;55:428 –31. 3. Lanier WL. Bidirectional conflicts of interest involving industry and medical journals: who will champion integrity? Mayo Clin Proc 2009; 84:771–5. 4. Neill US. Publish or perish, but at what cost? J Clin Invest 2008;118:2368.
JUPITER “Moderate CKD” Subgroup Is Not Truly “Moderate” Chronic Kidney Disease Given that trials of lipid lowering in patients with chronic kidney disease (CKD) requiring dialysis have been neutral (1), and the only evidence for lipid-lowering therapy in patients with CKD not requiring dialysis is based on secondary analyses, such as the Pravastatin Pooling Project (2), it is commendable that a subgroup defined by kidney function was examined in JUPITER (Justification for the Use of Statins in Prevention–an Intervention Trial Evaluating Rosuvastatin), as reported recently in this journal (3). However, we do not believe that it is appropriate to call this a subgroup with “moderate CKD.” The JUPITER CKD subgroup is influenced by the limitations of the Modified Diet in Renal Disease (MDRD) equation for estimating glomerular filtration rate (GFR) and the study inclusion criteria. Moderate CKD is defined by a GFR of 30 to 59 ml/min, with or without other evidence of kidney damage, but should be present for 3 months to be truly “chronic” kidney disease (4). The MDRD GFR equation uses the serum creatinine, age, sex, and African American ethnicity to estimate GFR but underestimates GFR at higher levels (5). The characteristics of this JUPITER subgroup that suggest the term “moderate CKD” is inappropriate are as follows: 1. In the CKD subgroup, 50% of participants had a GFR between 51 and 58 ml/min, and 25% had a GFR between 58 and 60 ml/min (Table 1 [3]). At least one-fourth of patients could have been misclassified simply due to variability in the creatinine assay (6). The authors do not report whether creatinine was measured centrally or what calibration procedures were used. 2. Female participants were substantially over-represented in the CKD subgroup, whereas African-American participants were substantially under-represented (Table 1 [3]). The multipliers in the MDRD equation result in lower GFRs for women and higher GFRs for African Americans with the same serum creatinine, and the problem of a universal cutoff of 60 ml/min causing 50% more women than men to be classified as having CKD has been described (7). 3. The 10-year age difference between women and men in the inclusion criteria may result in more females having a GFR
JACC Vol. 56, No. 6, 2010 August 3, 2010:525–30
⬍60 ml/min. In an age-specific MDRD GFR “reference range” in a population free of vascular disease, hypertension, diabetes, or kidney disease, the median GFR in women age 60 to 64 years was 10 ml/min lower compared with men age 50 to 54 years (7). The results were described as similar with the Cockroft-Gault equation, but it would be interesting to see how the characteristics, or indeed the classification, of the patients was altered. We do not question the effect of the intervention in the patients described or the use of the MDRD equation for this purpose. However, patients seen by nephrologists and cardiologists with a GFR between 30 and 59 ml/min (“moderate” CKD by the K/DOQI [Kidney Disease Outcomes Quality Initiative] classification) have a high prevalence of diabetes and cardiovascular disease (excluded by design in the JUPITER trial) and higher, rather than lower, systolic blood pressure than people with normal kidney function. We suggest that this JUPITER subgroup is better described as “patients with an MDRD GFR ⬍60 ml/min on 1 occasion” to avoid inappropriate extrapolation of these results.
*Matthew A. Roberts, MBBS, PhD David L. Hare, MBBS, DPM *Department of Nephrology Austin Health and the University of Melbourne P.O. Box 5555 Heidelberg, Victoria 3084 Australia E-mail: [email protected] doi:10.1016/j.jacc.2010.04.025
REFERENCES
1. Fellstrom BC, Jardine AG, Schmieder RE, et al. Rosuvastatin and cardiovascular events in patients undergoing hemodialysis. N Engl J Med 2009;360:1395– 407. 2. Tonelli M, Isles C, Curhan GC, et al. Effect of pravastatin on cardiovascular events in people with chronic kidney disease. Circulation 2004;110:1557– 63. 3. Ridker PM, Macfadyen J, Cressman M, Glynn RJ. Efficacy of rosuvastatin among men and women with moderate chronic kidney disease and elevated high-sensitivity C-reactive protein a secondary analysis from the JUPITER (Justification for the Use of Statins in Prevention–an Intervention Trial Evaluating Rosuvastatin) trial. J Am Coll Cardiol 2010;55:1266 –73. 4. National Kidney Foundation K/DOQI. Clinical practice guidelines for chronic kidney disease. Evaluation, classification, and stratification. Part 4-definition and classification of stages of chronic kidney disease. Am J Kidney Dis 2002;39:S46 –75. 5. Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med 2006;354:2473– 83. 6. Coresh J, Astor BC, McQuillan G, et al. Calibration and random variation of the serum creatinine assay as critical elements of using equations to estimate glomerular filtration rate. Am J Kidney Dis 2002;39:920 –9. 7. Fox CS, Larson MG, Leip EP, Culleton B, Wilson PW, Levy D. Predictors of new-onset kidney disease in a community-based population. JAMA 2004;291:844 –50.
JACC Vol. 56, No. 6, 2010 August 3, 2010:525–30
patients who progress to symptomatic Chagas’ disease, we suggested AAB measurement in asymptomatic Chagas’ patients for cardiomyopathy and megacolon risk assessment. We now present first indications supporting our concept. At a median 31 months (range 27 to 47 months) after the primary patient classification, we were able to contact 36 of our primarily asymptomatic patients, of whom 15 were AAB-negative and 21 AAB-positive. In the second investigation, none of the AABnegative patients reported clinical symptoms and had electrocardiographic characteristics indicative of progression to symptomatic Chagas’ disease. Among the AAB-positive patients of the primary investigation, a 40-year-old woman presented with cardiomyopathy diagnosed by electrocardiogram, demonstrating the progression to symptomatic chronic Chagas’ disease. In the primary study, this woman had had the typical cardiomyopathy AAB composition of beta1-AAB combined with M2-AAB. A second patient, a 31-year-old woman, presented with clinically diagnosed megacolon. This woman was burdened in the primary investigation with M2-AAB positivity and borderline positivity for beta2-AAB, which suggest megacolon risk. Despite the tentative nature of the information presented here, we hope that this first successful step in the evaluation of AAB measurement in asymptomatic Chagas’ patients for cardiomyopathy and megacolon risk assessment will further our concept and encourage other scientists to take part in its evaluation. However, considering the time- and cost-intensive bioassay used for the AAB measurement (1), the development of cost-limited but standardized and more universally available enzyme-linked immunosorbent assays seems to be an essential prerequisite. Initiatives in the enzyme-linked immunosorbent assay development should, in our view, first focus on M2-AAB. Both patients who progressed to symptomatic Chagas’ disease presented with M2-AAB in the asymptomatic stage. Therefore, we would like to suggest M2-AAB as the preferential tool in the risk assessment of asymptomatic Chagas’ patients. The use of M2-AAB for risk assessment was also seen as a promising strategy by others (2). Using M2-AAB as a risk marker would also account for the function of M2-AAB in driving the alterations in the autonomic nerve system (3,4) that have frequently been discussed in the pathogenesis of Chagas’ heart and gastrointestinal disease. Silvia Gilka Muñoz Saravia, PhD Annekathrin Haberland, PhD Sabine Bartel, PhD Raul Araujo, MD Gregorio Valda, MD Diana Duchen, MS Ivan Diaz Ramirez, MD Adrian Constantin Borges, MD, PhD Gerd Wallukat, PhD *Ingolf Schimke, PhD *Medizinische Klinik für Kardiologie und Angiologie CCM, Charité Universitätsmedizin Berlin Berlin 10117 Germany E-mail: [email protected] doi:10.1016/j.jacc.2010.02.057
527
REFERENCES
1. Wallukat G, Munoz Saravia GS, Haberland A, et al. Distinct patterns of autoantibodies against G-protein– coupled receptors in Chagas’ cardiomyopathy and megacolon: their potential impact for early risk assessment in asymptomatic Chagas’ patients. J Am Coll Cardiol 2010;55:463– 8. 2. Goin JC, Leiros CP, Borda E, Sterin-Borda L. Interaction of human chagasic IgG with the second extracellular loop of the human muscarinergic acetylcholine receptor: functional and pathological implications. FASEB J 1997;11:77– 83. 3. Goin JC, Borda ES, Auger S, Storino R, Sterin-Borda L. Cardiac M(2) muscarinic cholinoceptor activation by human chagasic autoantibodies: association with bradycardia. Heart 1999:82:273– 8. 4. Sterin-Borda L, Goin JC, Bilder CR, Iantorno G, Hernando AC, Borda E. Interaction of human chagasic IgG with human colon muscarinic acetylcholine receptor: molecular and functional evidence. Gut 2001;49:699 –705.
Quantity and Quality in Medical Research We read with interest the papers by Kaul et al. (1) and Stone et al. (2), published in a recent issue of the Journal. Both highlight vividly the all too commonly found errors and limitations in current medical literature. While the causes of such a state of affairs are multiple, we believe the sheer volume of scientific papers published nowadays is a major contributor. To illustrate this point, a PubMed listings search using the criteria “human, randomized controlled trial” reveals an astounding growth in the number of studies published in each 10-year strata, starting February 4, 1950: 1950 to 1960, no items found; 1960 to 1970, 1,076 studies found; 1970 to 1980, 9,622 studies; 1980 to 1990, 36,066 studies; 1990 to 2000, 91,194 studies; and 2000 to 2010, 136,109 studies found. In the past year alone, 11,276 such papers were found using PubMed. While such a rate of growth may be partly due to widespread use of standardized methodology and the establishment of a worldwide scientific community, less exalted factors such as industry pressures (3) and the “publish or perish” drive (4) may also be at play. It is, therefore, difficult to argue that each or even most of these studies will be sound in their conceptual development, performance, analysis, and interpretation. In truth, the scientific enterprise has in many ways become the scientific industry, and the challenges we now face transcend technical or methodological limitations. Rather than quantity, we must now focus on quality and its indispensable antecedents, competence and integrity. *Iyad N. Daher, MD Syed Wamique Yusuf, MD *Department of Cardiology University of Texas M.D. Anderson Cancer Center 1400 Pressler, Unit 1451 Houston, Texas 77030 E-mail: [email protected] doi:10.1016/j.jacc.2010.02.058
528
Correspondence
REFERENCES
1. Kaul S, Diamond GA. Trial and error. How to avoid commonly encountered limitations of published clinical trials. J Am Coll Cardiol 2010;55:415–27. 2. Stone GW, Pocock SJ. Randomized trials, statistics, and clinical inference. J Am Coll Cardiol 2010;55:428 –31. 3. Lanier WL. Bidirectional conflicts of interest involving industry and medical journals: who will champion integrity? Mayo Clin Proc 2009; 84:771–5. 4. Neill US. Publish or perish, but at what cost? J Clin Invest 2008;118:2368.
JUPITER “Moderate CKD” Subgroup Is Not Truly “Moderate” Chronic Kidney Disease Given that trials of lipid lowering in patients with chronic kidney disease (CKD) requiring dialysis have been neutral (1), and the only evidence for lipid-lowering therapy in patients with CKD not requiring dialysis is based on secondary analyses, such as the Pravastatin Pooling Project (2), it is commendable that a subgroup defined by kidney function was examined in JUPITER (Justification for the Use of Statins in Prevention–an Intervention Trial Evaluating Rosuvastatin), as reported recently in this journal (3). However, we do not believe that it is appropriate to call this a subgroup with “moderate CKD.” The JUPITER CKD subgroup is influenced by the limitations of the Modified Diet in Renal Disease (MDRD) equation for estimating glomerular filtration rate (GFR) and the study inclusion criteria. Moderate CKD is defined by a GFR of 30 to 59 ml/min, with or without other evidence of kidney damage, but should be present for 3 months to be truly “chronic” kidney disease (4). The MDRD GFR equation uses the serum creatinine, age, sex, and African American ethnicity to estimate GFR but underestimates GFR at higher levels (5). The characteristics of this JUPITER subgroup that suggest the term “moderate CKD” is inappropriate are as follows: 1. In the CKD subgroup, 50% of participants had a GFR between 51 and 58 ml/min, and 25% had a GFR between 58 and 60 ml/min (Table 1 [3]). At least one-fourth of patients could have been misclassified simply due to variability in the creatinine assay (6). The authors do not report whether creatinine was measured centrally or what calibration procedures were used. 2. Female participants were substantially over-represented in the CKD subgroup, whereas African-American participants were substantially under-represented (Table 1 [3]). The multipliers in the MDRD equation result in lower GFRs for women and higher GFRs for African Americans with the same serum creatinine, and the problem of a universal cutoff of 60 ml/min causing 50% more women than men to be classified as having CKD has been described (7). 3. The 10-year age difference between women and men in the inclusion criteria may result in more females having a GFR
JACC Vol. 56, No. 6, 2010 August 3, 2010:525–30
⬍60 ml/min. In an age-specific MDRD GFR “reference range” in a population free of vascular disease, hypertension, diabetes, or kidney disease, the median GFR in women age 60 to 64 years was 10 ml/min lower compared with men age 50 to 54 years (7). The results were described as similar with the Cockroft-Gault equation, but it would be interesting to see how the characteristics, or indeed the classification, of the patients was altered. We do not question the effect of the intervention in the patients described or the use of the MDRD equation for this purpose. However, patients seen by nephrologists and cardiologists with a GFR between 30 and 59 ml/min (“moderate” CKD by the K/DOQI [Kidney Disease Outcomes Quality Initiative] classification) have a high prevalence of diabetes and cardiovascular disease (excluded by design in the JUPITER trial) and higher, rather than lower, systolic blood pressure than people with normal kidney function. We suggest that this JUPITER subgroup is better described as “patients with an MDRD GFR ⬍60 ml/min on 1 occasion” to avoid inappropriate extrapolation of these results.
*Matthew A. Roberts, MBBS, PhD David L. Hare, MBBS, DPM *Department of Nephrology Austin Health and the University of Melbourne P.O. Box 5555 Heidelberg, Victoria 3084 Australia E-mail: [email protected] doi:10.1016/j.jacc.2010.04.025
REFERENCES
1. Fellstrom BC, Jardine AG, Schmieder RE, et al. Rosuvastatin and cardiovascular events in patients undergoing hemodialysis. N Engl J Med 2009;360:1395– 407. 2. Tonelli M, Isles C, Curhan GC, et al. Effect of pravastatin on cardiovascular events in people with chronic kidney disease. Circulation 2004;110:1557– 63. 3. Ridker PM, Macfadyen J, Cressman M, Glynn RJ. Efficacy of rosuvastatin among men and women with moderate chronic kidney disease and elevated high-sensitivity C-reactive protein a secondary analysis from the JUPITER (Justification for the Use of Statins in Prevention–an Intervention Trial Evaluating Rosuvastatin) trial. J Am Coll Cardiol 2010;55:1266 –73. 4. National Kidney Foundation K/DOQI. Clinical practice guidelines for chronic kidney disease. Evaluation, classification, and stratification. Part 4-definition and classification of stages of chronic kidney disease. Am J Kidney Dis 2002;39:S46 –75. 5. Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med 2006;354:2473– 83. 6. Coresh J, Astor BC, McQuillan G, et al. Calibration and random variation of the serum creatinine assay as critical elements of using equations to estimate glomerular filtration rate. Am J Kidney Dis 2002;39:920 –9. 7. Fox CS, Larson MG, Leip EP, Culleton B, Wilson PW, Levy D. Predictors of new-onset kidney disease in a community-based population. JAMA 2004;291:844 –50.