- Email: [email protected]
Incident diabetes in clinical trials of antihypertensive drugs – Authors' reply
Correspondence
3
4
5
Glenny AM, Altman DG, Song F, et al. Indirect comparisons of competing interventions. Health Technol Assess 2005; 9: 1–134. Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med 2002; 21: 2313–24. Whitehead A. A Bayesian approach to meta-analysis. In: Whitehead A, ed. Meta-analysis of controlled clinical trials. Chichester: John Wiley & Sons, 2002: 259–82.
I declare that I have no conflict of interest.
G D Johnston [email protected] Queen’s University, Belfast BT9 7BL, UK 1
2
1·0
100% ARBs ACE inhibitors Calcium-channel blockers β blockers Diuretics
0·9 0·8
80% 60%
0·7
40%
0·6
20% Patients discontinuing drug therapy Risk of developing diabetes
0·5
0
10
20 30 Years available
40
0%
Proportion of patients who discontinued therapy after 12 months3
Odds ratio for development of diabetes1
See Department of Error page 1518
I would like to propose an alternative explanation for the results published by William Elliott and Peter Meyer.1 I suggest that they are an example of the old truism that new drugs always seem safer and better tolerated than older drugs. The higher doses used in early studies with β blockers and diuretics could also be a confounding factor because the metabolic effects are dose-related.2 If we plot the odds ratio for developing diabetes against the time each class of antihypertensive drug has been available on the market, a remarkably straight line results (figure). An even better fit is seen if we use Bloom’s data3 on the number of patients who discontinue treatment with the different agents. I suggest that we are not identifying better tolerated drugs but simply comparing a great amount of information related to adverse effects of older drugs with fewer data on newer agents, with all the intrinsic biases that these analyses produce.
50
Figure: Odds ratio for development of diabetes versus length of availability of different classes of antihypertensive drug ARBs=angiotensin-receptor blockers. ACE=angiotensin-converting enzyme.
1514
3
Elliott WJ, Meyer PM. Incident diabetes in clinical trials of antihypertensive drugs: a network meta-analysis. Lancet 2007; 369: 201–07. Johnston GD. Dose-response relationships with antihypertensive drugs. Pharmac Ther 1992; 55: 53. Bloom BS. Continuation of initial antihypertensive medication after 1 year of therapy. Clin Ther 1998; 20: 671–81.
Authors’ reply We thank Simon Lam, Andrew Owen, and G D Johnston for their queries: they prompted an ab initio recalculation of all our results. We regret to report that we have discovered errors involving the odds ratios for INSIGHT and SCOPE, which result in several alterations to both figure 3 and table 2 in our original paper, but no changes to our overall conclusions. We agree with Lam and Owen that our modelling of random effects is a potential weakness of the network meta-analytic approach; Lumley included Bayesian modelling as a possible extension of the technique in his original paper.1 We are, however, pleased that, when we use the placebo as “standard” (as did Lam and Owen) in our corrected analyses, the incidence of diabetes for each class of drug became: angiotensin-receptor blocker (ARB) 0·84 (95% CI 0·70–1·00), angiotensin-converting enzyme (ACE) inhibitor 0·90 (0·78–1·04), calciumchannel blocker 1·05 (0·90–1·24), β blocker 1·25 (1·05–1·48), and diuretic 1·34 (1·12–1·60). These results are within 1–2% of those resulting from the Bayesian analysis (and well within the “incoherence” of our model); therefore we agree with Lam and Owen’s final sentence. Although we agree with Johnston that incident diabetes with diuretics and β blockers is probably doserelated,2 we do not have sufficient patient-level or other clinical trial data to validate this assumption. Because
antihypertensive drugs within any class differ with respect to time on the market, we arbitrarily divided the ACE inhibitors into old (captopril, enalapril, lisinopril) and new agents. After rerunning our network meta-analysis, incoherence dropped precipitously (ω=0·000005). New ACE inhibitors are associated with a much lower risk of incident diabetes (0·42, 0·31–0·57), but the effect of old ACE inhibitors (0·71, 0·56–0·89) is about the same as in the base case (0·67, 0·57–0·79). This difference was not seen after subdividing old (verapamil, nifedipine, diltiazem) and new calciumchannel blockers. Counterexamples to the “old truism” that new antihypertensive drugs are safer and better tolerated than older drugs include vasopeptidase inhibitors3 and endothelin antagonists.4 The truism might be an example of selection bias, in that poorly tolerated drugs are typically not brought to market; risk of incident diabetes has historically not been a criterion for antihypertensive drug development. Last, the Candesartan Antihypertensive Survival Evaluation in Japan (CASE-J) study revealed a significant (p=0·03) 36% prevention of diabetes with an ARB (vs a calcium-channel blocker).5 We will be pleased to update our network meta-analysis results when the details of this study are published, but the conclusions are consistent with our model. WJE has received research grants and honoraria from various manufacturers of antihypertensive drugs (Pfizer, AstraZeneca, Novartis, Bristol-Myers Squbb, Sanofi-Aventis, Biovail, Abbott Laboratories, Solvay, Kos). PMM has received consulting fees from Takeda. PMM’s work on this project was supported in part by NIH grant K25 HL68139-01A1.
*William J Elliott, Peter M Meyer [email protected] Department of Preventive Medicine, Rush Medical College of Rush University at Rush University Medical Center, Chicago, IL 60612, USA 1
2
Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med 2002; 21: 2313–24. Elliott WJ. Glucose and cholesterol elevations during thiazide therapy: intention-to-treat vs actual-on-therapy experience. Am J Med 1995; 99: 261–69.
www.thelancet.com Vol 369 May 5, 2007
3 4
5
Weber MA. Vasopeptidase inhibitors. Lancet 2001; 358: 1526–32. Battistini B, Berthiaume N, Kelland NF, Webb DJ, Kohan DE. Profile of past and current clinical trials involving endothelin receptor antagonists: the novel “-sentan” class of drug. Exp Biol Med 2006; 231: 653–95. Brookes L. The “Global Challenge” statement from the ISH 2006 meeting, with many clinical trial results. Medscape Cardiol 2006; 10. http:// www.medscape.com/viewarticle/547752_ print (accessed Nov 21, 2006).
Target haemoglobin concentrations in chronic kidney disease The Comment (Feb 3, p 346)1 accompanying the meta-analysis (p 381)2 on target haemoglobin concentrations in anaemic patients with chronic kidney disease is surprising in its conclusion. It is widely recognised that meta-analyses have several intrinsic problems: study selection is one. For instance, the nine studies chosen by Arintaya Phrommintikul and colleagues1 for their meta-analysis included patients who required dialysis as well as those who did not yet require end-stage intervention. Additionally, diabetic and non-diabetic patients with different stages of chronic kidney disease were included, as were some patients with haemoglobin concentrations up to 160 g/L. Are these nine studies truly comparable? We recently examined two of the nine studies: CREATE (NCT00321919) and CHOIR (NCT00211120).3 We concluded that, until more studies were completed, “it seems wisest to refrain from complete correction of anemia in persons with chronic kidney disease”. The meta-analysis by Phrommintikul and colleagues1 does not cause us to rethink our conclusions. Ongoing trials, such as TREAT, continue because the investigators and the data safety monitoring board, reviewing all available data, feel that the questions raised are far from settled. Indeed, the reaction to the CREATE and CHOIR studies has been quite variable in the larger nephrology www.thelancet.com Vol 369 May 5, 2007
community, some members of which even articulate that the data from the CHOIR and CREATE studies, the only two in the Lancet meta-analysis done in predialysis patients, are not compelling.4 Patients with renal disease deserve a solid evidence base, and the research should continue. JRI is a past president of the local National Kidney Foundation Affiliate of the US states of MA, RI, NH, and VT—a voluntary position. GR is a member of the TREAT Executive Committee. The consulting remuneration is paid to Ospedali Riuniti di Bergamo for charity care outside the field of nephrology.
Julie R Ingelfinger, *Giuseppe Remuzzi [email protected] Harvard Medical School, Massachusetts General Hospital, and the New England Journal of Medicine, Boston, MA, USA (JRI); and Department of Medicine and Transplantation, Ospedali Riuniti di Bergamo, and Mario Negri Institute for Pharmacological Research, Bergamo, Italy (GR) 1
2
3
4
Strippoli GFM, Tognoni G, Navaneethan SD, Nicolucci A, Craig JC. Haemoglobin targets: we were wrong, time to move on. Lancet 2007; 369: 346–49. Phrommintikul A, Haas SJ, Elsik M, Krum H. Mortality and target haemoglobin concentrations in anaemic patients with chronic kidney disease treated with erythropoietin: a meta-analysis. Lancet 2007; 369: 381–88. Remuzzi G, Ingelfinger JR. Correction of anemia—payoffs and problems. N Engl J Med 2006; 355: 2144–46. Levin A. Understanding recent haemoglobin trials in CKD: methods and lessons learned from CREATE and CHOIR. Nephrol Dial Transplant 2007; 22: 309–12.
In their meta-analysis,1 Arintaya Phrommintikul and colleagues use appropriate analytical methods, but their adjustment for heterogeneity between studies addresses statistical heterogeneity only and not the heterogeneity caused by different study populations. The meta-analysis mixes studies that are exclusively on haemodialysis patients2 with studies in individuals with earlier stages of chronic kidney disease not yet requiring dialysis treatment.3 Additionally, use of “high” versus “low” haemoglobin as a dichotomous outcome might not be appropriate, since the ranges in each category are too broad and heterogeneous—eg, the high target of haemoglobin ranges between 120 and 160 g/L.
The study by Besarab and colleagues2 contributes 50–75% of the weight in the meta-analysis. In that study, the population consisted of people who were older and had more comorbidities than the US population of haemodialysis patients; all patients had either heart failure or ischaemic heart disease.2 Moreover, the two treatment groups differed in at least two important factors that might have confounded the analysis—ie, the dialysis dose and intravenous iron treatment, which might have been biased in favour of the low haematocrit group.2 Studying a contemporary 2-year cohort of 58 058 haemodialysis patients, we showed a nadir of mortality at a haemoglobin concentration of 120–130 g/L, with an increasing mortality at haemoglobin concentrations above 135 g/L or below 115 g/L.4 Given the above issues and many other unanswered questions in the field, we are puzzled as to how the accompanying Comment by Giovanni Strippoli and colleagues5 could declare that “we were wrong” about the potential link between higher haemoglobin and better survival and that it is “time to move on”, as if the meta-analysis had closed this chapter once and for all.
The printed journal includes an image merely for illustration
KK-Z has consulted for or received honoraria from Amgen, Ortho-Biotec, Roche, Watson, and Vifor, the manufacturers of medications used in the treatment of anaemia in chronic kidney disease.
Deborah L Regidor, *Kamyar Kalantar-Zadeh [email protected] Harbor-UCLA Medical Center, 1124 W Carson St, C-1 Annex, Torrance, CA 90502, USA 1
2
3
Phrommintikul A, Haas SJ, Elsik M, Krum H. Mortality and target haemoglobin concentrations in anaemic patients with chronic kidney disease treated with erythropoietin: a meta-analysis. Lancet 2007; 369: 381–88. Besarab A, Bolton WK, Browne JK, et al. The effects of normal as compared with low hematocrit values in patients with cardiac disease who are receiving hemodialysis and epoetin. N Engl J Med 1998; 339: 584–90. Singh AK, Szczech L, Tang KL, et al. Correction of anemia with epoetin alfa in chronic kidney disease. N Engl J Med 2006; 355: 2085–98.
1515
Science Photo Library
Correspondence
3
4
5
Glenny AM, Altman DG, Song F, et al. Indirect comparisons of competing interventions. Health Technol Assess 2005; 9: 1–134. Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med 2002; 21: 2313–24. Whitehead A. A Bayesian approach to meta-analysis. In: Whitehead A, ed. Meta-analysis of controlled clinical trials. Chichester: John Wiley & Sons, 2002: 259–82.
I declare that I have no conflict of interest.
G D Johnston [email protected] Queen’s University, Belfast BT9 7BL, UK 1
2
1·0
100% ARBs ACE inhibitors Calcium-channel blockers β blockers Diuretics
0·9 0·8
80% 60%
0·7
40%
0·6
20% Patients discontinuing drug therapy Risk of developing diabetes
0·5
0
10
20 30 Years available
40
0%
Proportion of patients who discontinued therapy after 12 months3
Odds ratio for development of diabetes1
See Department of Error page 1518
I would like to propose an alternative explanation for the results published by William Elliott and Peter Meyer.1 I suggest that they are an example of the old truism that new drugs always seem safer and better tolerated than older drugs. The higher doses used in early studies with β blockers and diuretics could also be a confounding factor because the metabolic effects are dose-related.2 If we plot the odds ratio for developing diabetes against the time each class of antihypertensive drug has been available on the market, a remarkably straight line results (figure). An even better fit is seen if we use Bloom’s data3 on the number of patients who discontinue treatment with the different agents. I suggest that we are not identifying better tolerated drugs but simply comparing a great amount of information related to adverse effects of older drugs with fewer data on newer agents, with all the intrinsic biases that these analyses produce.
50
Figure: Odds ratio for development of diabetes versus length of availability of different classes of antihypertensive drug ARBs=angiotensin-receptor blockers. ACE=angiotensin-converting enzyme.
1514
3
Elliott WJ, Meyer PM. Incident diabetes in clinical trials of antihypertensive drugs: a network meta-analysis. Lancet 2007; 369: 201–07. Johnston GD. Dose-response relationships with antihypertensive drugs. Pharmac Ther 1992; 55: 53. Bloom BS. Continuation of initial antihypertensive medication after 1 year of therapy. Clin Ther 1998; 20: 671–81.
Authors’ reply We thank Simon Lam, Andrew Owen, and G D Johnston for their queries: they prompted an ab initio recalculation of all our results. We regret to report that we have discovered errors involving the odds ratios for INSIGHT and SCOPE, which result in several alterations to both figure 3 and table 2 in our original paper, but no changes to our overall conclusions. We agree with Lam and Owen that our modelling of random effects is a potential weakness of the network meta-analytic approach; Lumley included Bayesian modelling as a possible extension of the technique in his original paper.1 We are, however, pleased that, when we use the placebo as “standard” (as did Lam and Owen) in our corrected analyses, the incidence of diabetes for each class of drug became: angiotensin-receptor blocker (ARB) 0·84 (95% CI 0·70–1·00), angiotensin-converting enzyme (ACE) inhibitor 0·90 (0·78–1·04), calciumchannel blocker 1·05 (0·90–1·24), β blocker 1·25 (1·05–1·48), and diuretic 1·34 (1·12–1·60). These results are within 1–2% of those resulting from the Bayesian analysis (and well within the “incoherence” of our model); therefore we agree with Lam and Owen’s final sentence. Although we agree with Johnston that incident diabetes with diuretics and β blockers is probably doserelated,2 we do not have sufficient patient-level or other clinical trial data to validate this assumption. Because
antihypertensive drugs within any class differ with respect to time on the market, we arbitrarily divided the ACE inhibitors into old (captopril, enalapril, lisinopril) and new agents. After rerunning our network meta-analysis, incoherence dropped precipitously (ω=0·000005). New ACE inhibitors are associated with a much lower risk of incident diabetes (0·42, 0·31–0·57), but the effect of old ACE inhibitors (0·71, 0·56–0·89) is about the same as in the base case (0·67, 0·57–0·79). This difference was not seen after subdividing old (verapamil, nifedipine, diltiazem) and new calciumchannel blockers. Counterexamples to the “old truism” that new antihypertensive drugs are safer and better tolerated than older drugs include vasopeptidase inhibitors3 and endothelin antagonists.4 The truism might be an example of selection bias, in that poorly tolerated drugs are typically not brought to market; risk of incident diabetes has historically not been a criterion for antihypertensive drug development. Last, the Candesartan Antihypertensive Survival Evaluation in Japan (CASE-J) study revealed a significant (p=0·03) 36% prevention of diabetes with an ARB (vs a calcium-channel blocker).5 We will be pleased to update our network meta-analysis results when the details of this study are published, but the conclusions are consistent with our model. WJE has received research grants and honoraria from various manufacturers of antihypertensive drugs (Pfizer, AstraZeneca, Novartis, Bristol-Myers Squbb, Sanofi-Aventis, Biovail, Abbott Laboratories, Solvay, Kos). PMM has received consulting fees from Takeda. PMM’s work on this project was supported in part by NIH grant K25 HL68139-01A1.
*William J Elliott, Peter M Meyer [email protected] Department of Preventive Medicine, Rush Medical College of Rush University at Rush University Medical Center, Chicago, IL 60612, USA 1
2
Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med 2002; 21: 2313–24. Elliott WJ. Glucose and cholesterol elevations during thiazide therapy: intention-to-treat vs actual-on-therapy experience. Am J Med 1995; 99: 261–69.
www.thelancet.com Vol 369 May 5, 2007
3 4
5
Weber MA. Vasopeptidase inhibitors. Lancet 2001; 358: 1526–32. Battistini B, Berthiaume N, Kelland NF, Webb DJ, Kohan DE. Profile of past and current clinical trials involving endothelin receptor antagonists: the novel “-sentan” class of drug. Exp Biol Med 2006; 231: 653–95. Brookes L. The “Global Challenge” statement from the ISH 2006 meeting, with many clinical trial results. Medscape Cardiol 2006; 10. http:// www.medscape.com/viewarticle/547752_ print (accessed Nov 21, 2006).
Target haemoglobin concentrations in chronic kidney disease The Comment (Feb 3, p 346)1 accompanying the meta-analysis (p 381)2 on target haemoglobin concentrations in anaemic patients with chronic kidney disease is surprising in its conclusion. It is widely recognised that meta-analyses have several intrinsic problems: study selection is one. For instance, the nine studies chosen by Arintaya Phrommintikul and colleagues1 for their meta-analysis included patients who required dialysis as well as those who did not yet require end-stage intervention. Additionally, diabetic and non-diabetic patients with different stages of chronic kidney disease were included, as were some patients with haemoglobin concentrations up to 160 g/L. Are these nine studies truly comparable? We recently examined two of the nine studies: CREATE (NCT00321919) and CHOIR (NCT00211120).3 We concluded that, until more studies were completed, “it seems wisest to refrain from complete correction of anemia in persons with chronic kidney disease”. The meta-analysis by Phrommintikul and colleagues1 does not cause us to rethink our conclusions. Ongoing trials, such as TREAT, continue because the investigators and the data safety monitoring board, reviewing all available data, feel that the questions raised are far from settled. Indeed, the reaction to the CREATE and CHOIR studies has been quite variable in the larger nephrology www.thelancet.com Vol 369 May 5, 2007
community, some members of which even articulate that the data from the CHOIR and CREATE studies, the only two in the Lancet meta-analysis done in predialysis patients, are not compelling.4 Patients with renal disease deserve a solid evidence base, and the research should continue. JRI is a past president of the local National Kidney Foundation Affiliate of the US states of MA, RI, NH, and VT—a voluntary position. GR is a member of the TREAT Executive Committee. The consulting remuneration is paid to Ospedali Riuniti di Bergamo for charity care outside the field of nephrology.
Julie R Ingelfinger, *Giuseppe Remuzzi [email protected] Harvard Medical School, Massachusetts General Hospital, and the New England Journal of Medicine, Boston, MA, USA (JRI); and Department of Medicine and Transplantation, Ospedali Riuniti di Bergamo, and Mario Negri Institute for Pharmacological Research, Bergamo, Italy (GR) 1
2
3
4
Strippoli GFM, Tognoni G, Navaneethan SD, Nicolucci A, Craig JC. Haemoglobin targets: we were wrong, time to move on. Lancet 2007; 369: 346–49. Phrommintikul A, Haas SJ, Elsik M, Krum H. Mortality and target haemoglobin concentrations in anaemic patients with chronic kidney disease treated with erythropoietin: a meta-analysis. Lancet 2007; 369: 381–88. Remuzzi G, Ingelfinger JR. Correction of anemia—payoffs and problems. N Engl J Med 2006; 355: 2144–46. Levin A. Understanding recent haemoglobin trials in CKD: methods and lessons learned from CREATE and CHOIR. Nephrol Dial Transplant 2007; 22: 309–12.
In their meta-analysis,1 Arintaya Phrommintikul and colleagues use appropriate analytical methods, but their adjustment for heterogeneity between studies addresses statistical heterogeneity only and not the heterogeneity caused by different study populations. The meta-analysis mixes studies that are exclusively on haemodialysis patients2 with studies in individuals with earlier stages of chronic kidney disease not yet requiring dialysis treatment.3 Additionally, use of “high” versus “low” haemoglobin as a dichotomous outcome might not be appropriate, since the ranges in each category are too broad and heterogeneous—eg, the high target of haemoglobin ranges between 120 and 160 g/L.
The study by Besarab and colleagues2 contributes 50–75% of the weight in the meta-analysis. In that study, the population consisted of people who were older and had more comorbidities than the US population of haemodialysis patients; all patients had either heart failure or ischaemic heart disease.2 Moreover, the two treatment groups differed in at least two important factors that might have confounded the analysis—ie, the dialysis dose and intravenous iron treatment, which might have been biased in favour of the low haematocrit group.2 Studying a contemporary 2-year cohort of 58 058 haemodialysis patients, we showed a nadir of mortality at a haemoglobin concentration of 120–130 g/L, with an increasing mortality at haemoglobin concentrations above 135 g/L or below 115 g/L.4 Given the above issues and many other unanswered questions in the field, we are puzzled as to how the accompanying Comment by Giovanni Strippoli and colleagues5 could declare that “we were wrong” about the potential link between higher haemoglobin and better survival and that it is “time to move on”, as if the meta-analysis had closed this chapter once and for all.
The printed journal includes an image merely for illustration
KK-Z has consulted for or received honoraria from Amgen, Ortho-Biotec, Roche, Watson, and Vifor, the manufacturers of medications used in the treatment of anaemia in chronic kidney disease.
Deborah L Regidor, *Kamyar Kalantar-Zadeh [email protected] Harbor-UCLA Medical Center, 1124 W Carson St, C-1 Annex, Torrance, CA 90502, USA 1
2
3
Phrommintikul A, Haas SJ, Elsik M, Krum H. Mortality and target haemoglobin concentrations in anaemic patients with chronic kidney disease treated with erythropoietin: a meta-analysis. Lancet 2007; 369: 381–88. Besarab A, Bolton WK, Browne JK, et al. The effects of normal as compared with low hematocrit values in patients with cardiac disease who are receiving hemodialysis and epoetin. N Engl J Med 1998; 339: 584–90. Singh AK, Szczech L, Tang KL, et al. Correction of anemia with epoetin alfa in chronic kidney disease. N Engl J Med 2006; 355: 2085–98.
1515
Science Photo Library
Correspondence