944
between HIV and JC virus. Of particular relevance is the finding that the HIV-1regulatory protein, tat, can stimulate JC virus gene expression in glial cell cultures.2° However, researchers have not yet detected dual HIV and JCV infection of the same CNS cell populations in vivo,21 which hinders extrapolation of this finding to the clinical setting. Areas of JC-induced demyelination are sometimes massively infiltrated by HIV-infected macrophages/microglial cells, which suggests that recruitment of these cells to damaged areas of the brain contributes to pathogenesis.21 Finally, and most important, what hope is there for an effective treatment for this distressing condition? Favourable responses to cytarabine or zidovudine22-24 have occasionally been reported, but these successes are greatly outnumbered by cases in which no effect has been observed. Preliminary results of an open trial of high dose alpha-interferon with zidovudine in HIV-related PML also show little benefit.25 What should clinicians do? Patients with HIV-related PML should receive antiretroviral therapy. Empirical treatment with other antiviral agents should be initiated only in those who fulfil major clinical and diagnostic criteria. Any therapy should be accompanied by full virological monitoring (eg, regular lumbar punctures for detection of JC genome in cerebrospinal fluid) and clinical documentation. Berger JR, Kaszovitz B, Post MJD, Dickinson G. Progressive multifocal leukoencephalopathy associated with human immunodeficiency virus infection. Ann Intern Med 1987; 107: 78-87. 2. Lang W, Miklossy J, Deravz JP, Pizzolato GP, Probst A, Schaffner J. Neuropathology of the acquired immunodeficiency syndrome (AIDS): 1.
report of 135 consecutive autopsy cases from Switzerland. Acta Neuropathol 1989; 77: 379-90. 3. McCance D, Gardner SD. Papovaviruses: papillomaviruses and polyomaviruses. In: Zuckerman AJ, Banatvala JE, Pattison JR, eds. Principles and practice of clinical virology, 2nd ed. Chichester: Wiley, 1990: 531-60. 4. Blake K, Pillay D, Knowles W, Brown DWG, Griffiths PD, Taylor B. JC virus associated meningoencephalitis in an immunocompetent girl. Arch Dis Child 1992; 67: 956-57. 5. Coleman D, Wolfendale M, Daniel R, et al. A prospective study of human polyomavirus infection in pregnancy. J Infect Dis 1980; 142: 1-8. 6. Andrews CA, Shah KV, Daniel RW, Hirsch MS, Rubm RH. A serologic investigation of BK virus and JC virus infections in recipients of renal allografts. J Infect Dis 1988; 158: 176-81. 7. Kitamura T, Aso Y, Kuniyoshi N, Hara K, Yogo Y. High incidence of urinary JC virus excretion in nonimmunocompromised older patients. J Infect Dis 1990; 161: 1128-33. 8. Hair LS, Nuovo G, Powers JM, Sisti MB, Britton CB, Miller JR. Progressive multifocal leukoencephalopathy in patients with human immunodeficiency virus. Hum Pathol 1992; 23: 663-67. 9. Hogan TF, Padgett BL, Walker DL. Human polyomaviruses. In: Belshe RB, ed. Textbook of human virology. St Louis: Mosby/Year Book, 1991: 970-1000. 10. Price RW, Nielsen S, Horten B, et al. Progressive multifocal leucoencephalopathy: a burnt-out case. Ann Neurol 1983; 13: 485-90. 11. Vandersteenhoven JJ, Dbaibo G, Boyko OB, et al. Progressive multifocal
leukoencephalopathy in pediatric acquired immunodeficiency syndrome. Pediatr Infect Dis J 1992; 11: 232-37. 12. Berger JR, Scott G, Albrecht J, Belman AL, Tornatore C, Major EO. Progressive multifocal leukoencephalopathy in HIV-infected children. AIDS 1992; 6: 837-41. 13. Guilleux MH, Steiner RE, Young IR. MR imaging in progressive multifocal leukoencephalopathy. AJNR 1986; 7: 1033-35. 14. Tomatore C, Berger JR, Houff SA, et al. Detection of JC virus DNA in peripheral lymphocytes from patients with and without progressive multifocal leukoencephalopathy. Ann Neurol 1992; 31: 454-62. 15. Quinlivan EB, Norris M, Bouldin TW, et al. Subclinical central nervous system infection with JC virus in patients with AIDS. J Infect Dis 1992; 166: 80-85.
JC, Griffiths PD, Emery VC. Quantification of human cytomegalovirus DNA using the polymerase chain reaction. J Gen
16. Fox
Virol 1992; 73: 2405-08. 17. Houff SA, Major EO, Katz DA, et al. Involvement of JC virus-infected mononuclear cells from the bone marrow and spleen in the pathogenesis of progressive multifocal leukoencephalopathy. N EnglJ Med 1988; 318: 301-05. 18. Loeber G, Domes K. DNA rearrangements in organ-specific variants of polyomavirus JC strain GS. J Virol 1988; 62: 1730-35. 19. Berger JR, Mucke L. Prolonged survival and partial recovery in AIDS-associated progressive multifocal leukoencephalopathy. Neurology 1988; 38: 1060-65. 20. Tada H, Rappaport J, Lashgari M, Amini S, Wong-Stall F, Khalili K. Trans-activation of the JC virus late promoter by the tat protein of type 1 human immunodeficiency virus in glial cells. Proc Natl Acad Sci USA 1990; 87: 3479-83. 21. Vazeux R, Cumont M, Girard PM, et al. Severe encephalitis resulting from coinfections with HIV and JC virus. Neurology 1990; 40: 944-48. 22. Portegies P, Algra PR, Hollak CEM, et al. Response to cytarabine in progressive multifocal leucoencephalopathy in AIDS. Lancet 1991; 337: 680-81. 23. O’Riordan T, Daly PA, Hutchinson M, Shattock AG, Gardner SD. Progressive multifocal leukoencephalopathy—remission with cytarabine. J Infect 1990; 20: 51-54. 24. Conway B, Halliday WC, Brunham RC. Human immunodeficiency virus-associated progressive multifocal leukoencephalopathy: apparent response to 3’-azido-3’deoxythymidine. Rev Infect Dis 1990; 12: 479-82. 25. Berger JR, Pall L, McArthur J, et al. Pilot study of recombinant alpha 2a interferon in the treatment of AIDS-related progressive multifocal leukoencephalopathy. Neurology 1992; 42 (suppl 3): 257.
Cross
design synthesis: a new strategy for studying medical outcomes?
Methods for evaluating medical interventions do usually result from governmental solicitation. However, this is what has happened in the USA, where Congress commissioned guidelines from the program evaluation and methodology division of the General Accounting Office. They in turn produced a detailed report advocating a strategy for medical effectiveness research which they call cross design not
synthesis.1 The policy issue underlying the production of this report relates to improving cost-effectiveness of health services, against a backdrop of concern about perceived spiralling health care expenditure. The technical issue arises from the difficulties of applying results of randomised controlled trials (RCTs) to clinical practice-patients seldom conform to the characteristics of participants in RCTs. Thus, unjustified assumptions are required when results of trials of treatment, say for acute myocardial infarction, mainly carried out on middle-aged men, are applied to women and the elderly.2 Meta-analyses can make it harder to move from judging whether a treatment is, in principle, efficacious, to deciding how to manage a particular patient. Subgroup analyses of RCTs, such as those produced by vigorous manipulation of the European Coronary Surgery Study data,3lead to post-hoc verdicts of questionable reliability. So, in the absence of RCTs in every conceivable patient subgroup, are there reliable methods of effectiveness research to guide therapeutic decisions? This is the key question addressed by the General Accounting Office. The strategy they recommend
945
consists of combining the results of RCTs with findings from the analysis of databases of patient records. These databases link details of patient
characteristics,
treatments
received, and outcomes,
which allows estimates of effectiveness of treatments to be made.4 The advantage of database analyses is that they are closer to "real life"-ie, the settings may be substantially different from those of the university medical centres participating in clinical trials.5 Consequently, the findings are thought to be readily applicable to clinical practice. However, when one has to make decisions about effectiveness of this increased treatments, generalisability is bought at a potentially high cost. Non-comparability of treatment groups is always a drawback with database analyses.6 Without randomisation, treatment decisions will depend upon patients’ characteristics, so the treatment groups will differ in many other ways than the therapy they receive. It is therefore difficult to attribute differences in outcome to the treatment itself. The usual solution to this problem is to resort to statistical adjustment for the factors that differ between the treatment groups. In a series of reports,’-9 the Duke University Medical Center cardiovascular disease database has been analysed in just this manner to compare outcomes for coronary artery bypass surgery with those of medical treatment for angina. Patients undergoing bypass surgery generally do better, the differences observed between the treatments being mainly similar to those seen in the RCTs.7 Once the predictions of the database analyses have been shown to be similar to the RCT results, statistical models based on the observational data can be used to predict outcomes for particular patient groups, even ones not included in the trials. Such "projecting to empty strata" is indeed a central feature of the effectiveness research strategy advocated by the General Accounting Office report. Although this approach is superficially attractive, it could produce seriously misleading results. In the Duke database, the medically and surgically treated groups were strikingly different in some respects--eg, about half the former and two-thirds of the latter had had a myocardial infarction.8 Previous myocardial infarction is an important factor indicating poor prognosis, so this discrepancy favours the surgically treated group. Moreover, statistical adjustments for unmeasured or inadequately characterised confounding factors can produce strong associations that are nevertheless completely spurious. 10,11 In another database analysis, coronary artery bypass was compared with angioplasty for coronary revascularisation. In the initial analysis,S an apparent advantage was shown for angioplasty after statistical adjustment for differences between treatment groups in terms of age, sex, race, and selected comorbid conditions. After further adjustment for thirty-seven baseline characteristics, the advantage for angioplasty was reduced from a 30% lower mortality rate (p = 0-002) to a non-significant 5% reduction in
mortality. 12 Further analysis of the same database produced a subgroup of low-risk patients in whom angioplasty retained its advantage even after full statistical adjustment. Although this result might simply reflect diminished ability to characterise prognostic factors in low-risk patients, such a possibility does not emerge clearly either in the scientific report5 or in subsequent press accounts.13 In one of the early cross design syntheses mentioned in the General Accounting Office report, when Eddy et all brought together findings from RCTs, case-control studies, and simple observation they concluded that mammography would reduce mortality for women under fifty. However, evidence that has accrued since publication of the analysis challenges its conclusions and the issue remains unresolved.l5 Similarly, various database analyses that suggested a higher postoperative mortality with transurethral resection for prostatic hypertrophy than with open prostatectomy16,17 have been challenged by a more recent study that suggests that sicker patients are assigned to the transurethral procedure and that more complete adjustment for comorbidity eliminates the apparent excess mortality risk associated with this operation.18 Thus, while database analyses call into question prevailing management of prostatic hypertrophy and indicate the need for an RCT, they do not provide urologists with the information they require to make the best decision for their patients. Patient databases can be made simple to analyse, and such analyses can suggest important areas of medical practice that require further scrutiny. The danger is that the type of data collected, often for administrative reasons, can dictate the type of questions about therapeutic effectiveness that are asked. One researcher happily writes "I utilize data that is available. I do not start out with ’what is the problem, what is the outcome?’ I say ’Given this data, what can I do with it?’ ".19 Use of the neologisms "database analyst" and "cross design investigator" in the General Accounting Office report brings to mind the new profession of meta-analyst. The meta-analysis industry, while contributing greatly to identification of appropriate therapeutic strategies 20 has branches that extend the domain to include potentially misleading combinations of incommensurate findings from observational studies.21,22 The mystique of the statistical techniques involved can hex commentators
overvaluing a potentially uninformative "rigorous meta-analysis"23 that pools inappropriate data. Moreover, the "primary content expertise in methodology rather than in the field under study"24 possessed by some meta-analysts can lead to into
conclusions that take no heed of the realities of clinical practice or of human biology. Observational data cannot provide definitive answers to questions about therapeutic effectiveness, but the difficulties of. applying the results of metaanalyses of RCTs to individual patients remain.zs
946
Treatment decisions still have to be made, patients will continue to be treated, and useful information can be derived by finding out what happens to patients after treatment and comparing this to expectations from other data sources, including RCTs. The risk with cross design synthesis is that the more expensive, time-consuming, and reliable component-RCTswill increasingly be replaced by database analyses. Formal methods of combining results from different study techniques can confuse rather than clarify the issues and should not substitute for informed interpretation of all the evidence. Accounting Office. Cross design synthesis: a new strategy for medical effectiveness research. Washington, DC: GAO, 1992. 2. Gurwitz JH, Col NF, Avorn J. The exclusion of the elderly and women from clinical trials in acute myocardial infarction. JAMA 1992; 268: 1. General
1417-22. 3. Varnauskas E. Twelve year
follow-up of survival in the randomised European coronary surgery study. N Engl J Med 1988; 319: 332-37. 4. Editorial. Databases for health care outcomes. Lancet 1989; ii: 195-96. 5. Hartz AJ, Kuhn EM, Pryor DB, et al. Mortality after coronary angioplasty and coronary artery bypass surgery (the National Medicare Experience). Am J Cardiol 1992; 70: 179-85. 6. Green SB, Byar DP. Using observational data from registries to compare treatments: the fallacy of omnimetrics. Stat Med 1984; 3: 361-70. 7. Hlatky MA, Califf RM, Harrell FE, Lee KL, Mark DB, Pryor DB. Comparison of predictions based on observational data with the results of randomised controlled clinical trials of coronary artery bypass surgery. JACC 1988; 11: 237-45. 8. Califf RM, Harrell FE, Lee KL, et al. The evolution of medical and surgical therapy for coronary artery disease: a 15-year perspective. JAMA 1989; 261: 2077-86. 9. Hlatky MA. Using databases to evaluate therapy. Star Med 1991; 10: 647-52. 10. Petitti DB, Perlman JA, Sidney S. Postmenopausal estrogen use and heart disease. N Engl J Med 1986; 315: 131-32. 11. Davey Smith G, Phillips AN, Neaton JD. Smoking as "independent" risk factor for suicide: illustration of an artifact from observational epidemiology? Lancet 1992; 340: 709-12. 12. Roper WL, Winkenwerder W, Hackbarth GM, Krakauer H. Effectiveness in health care: an initiative to evaluate and improve medical practice. N Engl J Med 1988; 319: 1197-202. 13. Risks in 2 angina treatments weighed. International Herald Tribune 1992 14.
Aug 27: 7. Eddy DM, Hasselblad V, McGivney W, Hendee W. The value of mammography screening in women under age 50 years. JAMA 1988;
259: 1512-19. 15. Editorial. Breast cancer screening in women under 50. Lancet 1991; 337: 1575-76. 16. Roos NP, Wennberg JE, Malenka DJ, et al. Mortality and reoperation after open and transurethral resection of the prostate for benign prostatic hyperplasia. N Engl J Med 1989; 320: 1120-24. 17. Andersen TF, Bronnum-Hansen H, Sejr T, Roepstorff C. Elevated mortality following transurethral resection of the prostate for benign hypertrophy! But why? Med Care 1990; 28: 870-79. 18. Concato J, Horowitz RI, Feinstein AR, Elmore JG, Schiff SF. Problems of comorbidity in mortality after prostatectomy. JAMA 1992; 267: 1077-82. 19. Blumberg MS. Potentials and limitations of database research illustrated by the QMMP AMI Medicare mortality study. Stat Med 1991; 10: 637-46. 20. Chalmers I, Dickerson K, Chalmers TC. Getting to grips with Archie Cochrane’s agenda. BMJ 1992; 305: 786-88. 21. Berlin JA, Colditz GA. A meta-analysis of physical activity in the prevention of coronary heart disease. Am J Epidemiol 1990; 132: 612-28. 22. Law MR, Thompson SG. Low serum cholesterol and the risk of cancer: an analysis of the published prospective studies. Cancer Causes Control
1991; 2: 253-61. JE, Tosteson H, Ridker PM, et al. The primary prevention of myocardial infarction. N Engl J Med 1992; 326: 1406-16.
23. Manson 24.
Naylor CD. Two cheers for meta-analysis: problems and opportunities in aggregating results of clinical trials. Can Med Assoc J 1988; 138:
891-95. 25. Kassirer JP. Clinical trials and meta-analysis: what do N Engl J Med 1992; 327: 273-74.
they do for us?.
South-East Asia in the twenty-first
century Over the past fifty years, the population in every country in South-East Asia has more than doubled. Fortunately food production has increased slightly faster than populations and the great epidemics have at least been contained. The last major famine was in 1943 in Bengal and there have been no epidemics of cholera, smallpox, and plague to match those in the 19th and early 20th centuries. Yet this story, which reflects much credit on the people and the health services in each country, is one of only limited successes. All the old health problems, except smallpox, remain, although some of them are less
pressing. In World Health Organisation terms the SouthEast Asia region (SEAR) consists of Bangladesh,
Bhutan, India, Indonesia, Maldives, Myanmar (Burma), Nepal, Sri Lanka, and Thailand; Malaysia, Pakistan, and Singapore are included in neighbouring regions. Nearly 1 -3 billion people-about a quarter of the world’s population-live in SEAR, and the health services in each country face broadly similar pressures. As a guide to development of the most appropriate policies for the region, the WHO regional director, Dr U. Ko Ko, asked Dr C. Gopalan to undertake a review. Gopalan’s report,1 which is refreshingly free of sociological and medical jargon, is available. Over 30% of the population live in towns, and five towns in the region are expected to have a population of over 10 million by the year 2000. Many urban dwellers live in shanty towns, where there are immense difficulties in providing potable water and effective sewerage systems. The high population density favours the spread of infectious diseases, especially those causing diarrhoea. Many women in urban slums, unlike their counterparts in the country, have to seek work in factories, shops, or as domestic servants, which restricts opportunities for breastfeeding and for preparing wholesome meals for older children. Huge rises in the number of elderly individuals are predicted for early in the next century in India, Indonesia, Sri Lanka, and Thailand. Old people in these countries are traditionally respected and cared for in their homes, as part of an extended family. The demographic changes that are now taking place will inevitably put many families under stress and the need for geriatric services throughout the region will
now
increase steadily. The increase in population has not been only among the poor. There are now many prosperous middle-class people with affluent lifestyles. Obesity, diabetes, hypertension, and ischaemic heart disease have followed in the wake of their prosperity, and are certain to place greatly increased demands on health services. Large health education programmes will be
required.
between HIV and JC virus. Of particular relevance is the finding that the HIV-1regulatory protein, tat, can stimulate JC virus gene expression in glial cell cultures.2° However, researchers have not yet detected dual HIV and JCV infection of the same CNS cell populations in vivo,21 which hinders extrapolation of this finding to the clinical setting. Areas of JC-induced demyelination are sometimes massively infiltrated by HIV-infected macrophages/microglial cells, which suggests that recruitment of these cells to damaged areas of the brain contributes to pathogenesis.21 Finally, and most important, what hope is there for an effective treatment for this distressing condition? Favourable responses to cytarabine or zidovudine22-24 have occasionally been reported, but these successes are greatly outnumbered by cases in which no effect has been observed. Preliminary results of an open trial of high dose alpha-interferon with zidovudine in HIV-related PML also show little benefit.25 What should clinicians do? Patients with HIV-related PML should receive antiretroviral therapy. Empirical treatment with other antiviral agents should be initiated only in those who fulfil major clinical and diagnostic criteria. Any therapy should be accompanied by full virological monitoring (eg, regular lumbar punctures for detection of JC genome in cerebrospinal fluid) and clinical documentation. Berger JR, Kaszovitz B, Post MJD, Dickinson G. Progressive multifocal leukoencephalopathy associated with human immunodeficiency virus infection. Ann Intern Med 1987; 107: 78-87. 2. Lang W, Miklossy J, Deravz JP, Pizzolato GP, Probst A, Schaffner J. Neuropathology of the acquired immunodeficiency syndrome (AIDS): 1.
report of 135 consecutive autopsy cases from Switzerland. Acta Neuropathol 1989; 77: 379-90. 3. McCance D, Gardner SD. Papovaviruses: papillomaviruses and polyomaviruses. In: Zuckerman AJ, Banatvala JE, Pattison JR, eds. Principles and practice of clinical virology, 2nd ed. Chichester: Wiley, 1990: 531-60. 4. Blake K, Pillay D, Knowles W, Brown DWG, Griffiths PD, Taylor B. JC virus associated meningoencephalitis in an immunocompetent girl. Arch Dis Child 1992; 67: 956-57. 5. Coleman D, Wolfendale M, Daniel R, et al. A prospective study of human polyomavirus infection in pregnancy. J Infect Dis 1980; 142: 1-8. 6. Andrews CA, Shah KV, Daniel RW, Hirsch MS, Rubm RH. A serologic investigation of BK virus and JC virus infections in recipients of renal allografts. J Infect Dis 1988; 158: 176-81. 7. Kitamura T, Aso Y, Kuniyoshi N, Hara K, Yogo Y. High incidence of urinary JC virus excretion in nonimmunocompromised older patients. J Infect Dis 1990; 161: 1128-33. 8. Hair LS, Nuovo G, Powers JM, Sisti MB, Britton CB, Miller JR. Progressive multifocal leukoencephalopathy in patients with human immunodeficiency virus. Hum Pathol 1992; 23: 663-67. 9. Hogan TF, Padgett BL, Walker DL. Human polyomaviruses. In: Belshe RB, ed. Textbook of human virology. St Louis: Mosby/Year Book, 1991: 970-1000. 10. Price RW, Nielsen S, Horten B, et al. Progressive multifocal leucoencephalopathy: a burnt-out case. Ann Neurol 1983; 13: 485-90. 11. Vandersteenhoven JJ, Dbaibo G, Boyko OB, et al. Progressive multifocal
leukoencephalopathy in pediatric acquired immunodeficiency syndrome. Pediatr Infect Dis J 1992; 11: 232-37. 12. Berger JR, Scott G, Albrecht J, Belman AL, Tornatore C, Major EO. Progressive multifocal leukoencephalopathy in HIV-infected children. AIDS 1992; 6: 837-41. 13. Guilleux MH, Steiner RE, Young IR. MR imaging in progressive multifocal leukoencephalopathy. AJNR 1986; 7: 1033-35. 14. Tomatore C, Berger JR, Houff SA, et al. Detection of JC virus DNA in peripheral lymphocytes from patients with and without progressive multifocal leukoencephalopathy. Ann Neurol 1992; 31: 454-62. 15. Quinlivan EB, Norris M, Bouldin TW, et al. Subclinical central nervous system infection with JC virus in patients with AIDS. J Infect Dis 1992; 166: 80-85.
JC, Griffiths PD, Emery VC. Quantification of human cytomegalovirus DNA using the polymerase chain reaction. J Gen
16. Fox
Virol 1992; 73: 2405-08. 17. Houff SA, Major EO, Katz DA, et al. Involvement of JC virus-infected mononuclear cells from the bone marrow and spleen in the pathogenesis of progressive multifocal leukoencephalopathy. N EnglJ Med 1988; 318: 301-05. 18. Loeber G, Domes K. DNA rearrangements in organ-specific variants of polyomavirus JC strain GS. J Virol 1988; 62: 1730-35. 19. Berger JR, Mucke L. Prolonged survival and partial recovery in AIDS-associated progressive multifocal leukoencephalopathy. Neurology 1988; 38: 1060-65. 20. Tada H, Rappaport J, Lashgari M, Amini S, Wong-Stall F, Khalili K. Trans-activation of the JC virus late promoter by the tat protein of type 1 human immunodeficiency virus in glial cells. Proc Natl Acad Sci USA 1990; 87: 3479-83. 21. Vazeux R, Cumont M, Girard PM, et al. Severe encephalitis resulting from coinfections with HIV and JC virus. Neurology 1990; 40: 944-48. 22. Portegies P, Algra PR, Hollak CEM, et al. Response to cytarabine in progressive multifocal leucoencephalopathy in AIDS. Lancet 1991; 337: 680-81. 23. O’Riordan T, Daly PA, Hutchinson M, Shattock AG, Gardner SD. Progressive multifocal leukoencephalopathy—remission with cytarabine. J Infect 1990; 20: 51-54. 24. Conway B, Halliday WC, Brunham RC. Human immunodeficiency virus-associated progressive multifocal leukoencephalopathy: apparent response to 3’-azido-3’deoxythymidine. Rev Infect Dis 1990; 12: 479-82. 25. Berger JR, Pall L, McArthur J, et al. Pilot study of recombinant alpha 2a interferon in the treatment of AIDS-related progressive multifocal leukoencephalopathy. Neurology 1992; 42 (suppl 3): 257.
Cross
design synthesis: a new strategy for studying medical outcomes?
Methods for evaluating medical interventions do usually result from governmental solicitation. However, this is what has happened in the USA, where Congress commissioned guidelines from the program evaluation and methodology division of the General Accounting Office. They in turn produced a detailed report advocating a strategy for medical effectiveness research which they call cross design not
synthesis.1 The policy issue underlying the production of this report relates to improving cost-effectiveness of health services, against a backdrop of concern about perceived spiralling health care expenditure. The technical issue arises from the difficulties of applying results of randomised controlled trials (RCTs) to clinical practice-patients seldom conform to the characteristics of participants in RCTs. Thus, unjustified assumptions are required when results of trials of treatment, say for acute myocardial infarction, mainly carried out on middle-aged men, are applied to women and the elderly.2 Meta-analyses can make it harder to move from judging whether a treatment is, in principle, efficacious, to deciding how to manage a particular patient. Subgroup analyses of RCTs, such as those produced by vigorous manipulation of the European Coronary Surgery Study data,3lead to post-hoc verdicts of questionable reliability. So, in the absence of RCTs in every conceivable patient subgroup, are there reliable methods of effectiveness research to guide therapeutic decisions? This is the key question addressed by the General Accounting Office. The strategy they recommend
945
consists of combining the results of RCTs with findings from the analysis of databases of patient records. These databases link details of patient
characteristics,
treatments
received, and outcomes,
which allows estimates of effectiveness of treatments to be made.4 The advantage of database analyses is that they are closer to "real life"-ie, the settings may be substantially different from those of the university medical centres participating in clinical trials.5 Consequently, the findings are thought to be readily applicable to clinical practice. However, when one has to make decisions about effectiveness of this increased treatments, generalisability is bought at a potentially high cost. Non-comparability of treatment groups is always a drawback with database analyses.6 Without randomisation, treatment decisions will depend upon patients’ characteristics, so the treatment groups will differ in many other ways than the therapy they receive. It is therefore difficult to attribute differences in outcome to the treatment itself. The usual solution to this problem is to resort to statistical adjustment for the factors that differ between the treatment groups. In a series of reports,’-9 the Duke University Medical Center cardiovascular disease database has been analysed in just this manner to compare outcomes for coronary artery bypass surgery with those of medical treatment for angina. Patients undergoing bypass surgery generally do better, the differences observed between the treatments being mainly similar to those seen in the RCTs.7 Once the predictions of the database analyses have been shown to be similar to the RCT results, statistical models based on the observational data can be used to predict outcomes for particular patient groups, even ones not included in the trials. Such "projecting to empty strata" is indeed a central feature of the effectiveness research strategy advocated by the General Accounting Office report. Although this approach is superficially attractive, it could produce seriously misleading results. In the Duke database, the medically and surgically treated groups were strikingly different in some respects--eg, about half the former and two-thirds of the latter had had a myocardial infarction.8 Previous myocardial infarction is an important factor indicating poor prognosis, so this discrepancy favours the surgically treated group. Moreover, statistical adjustments for unmeasured or inadequately characterised confounding factors can produce strong associations that are nevertheless completely spurious. 10,11 In another database analysis, coronary artery bypass was compared with angioplasty for coronary revascularisation. In the initial analysis,S an apparent advantage was shown for angioplasty after statistical adjustment for differences between treatment groups in terms of age, sex, race, and selected comorbid conditions. After further adjustment for thirty-seven baseline characteristics, the advantage for angioplasty was reduced from a 30% lower mortality rate (p = 0-002) to a non-significant 5% reduction in
mortality. 12 Further analysis of the same database produced a subgroup of low-risk patients in whom angioplasty retained its advantage even after full statistical adjustment. Although this result might simply reflect diminished ability to characterise prognostic factors in low-risk patients, such a possibility does not emerge clearly either in the scientific report5 or in subsequent press accounts.13 In one of the early cross design syntheses mentioned in the General Accounting Office report, when Eddy et all brought together findings from RCTs, case-control studies, and simple observation they concluded that mammography would reduce mortality for women under fifty. However, evidence that has accrued since publication of the analysis challenges its conclusions and the issue remains unresolved.l5 Similarly, various database analyses that suggested a higher postoperative mortality with transurethral resection for prostatic hypertrophy than with open prostatectomy16,17 have been challenged by a more recent study that suggests that sicker patients are assigned to the transurethral procedure and that more complete adjustment for comorbidity eliminates the apparent excess mortality risk associated with this operation.18 Thus, while database analyses call into question prevailing management of prostatic hypertrophy and indicate the need for an RCT, they do not provide urologists with the information they require to make the best decision for their patients. Patient databases can be made simple to analyse, and such analyses can suggest important areas of medical practice that require further scrutiny. The danger is that the type of data collected, often for administrative reasons, can dictate the type of questions about therapeutic effectiveness that are asked. One researcher happily writes "I utilize data that is available. I do not start out with ’what is the problem, what is the outcome?’ I say ’Given this data, what can I do with it?’ ".19 Use of the neologisms "database analyst" and "cross design investigator" in the General Accounting Office report brings to mind the new profession of meta-analyst. The meta-analysis industry, while contributing greatly to identification of appropriate therapeutic strategies 20 has branches that extend the domain to include potentially misleading combinations of incommensurate findings from observational studies.21,22 The mystique of the statistical techniques involved can hex commentators
overvaluing a potentially uninformative "rigorous meta-analysis"23 that pools inappropriate data. Moreover, the "primary content expertise in methodology rather than in the field under study"24 possessed by some meta-analysts can lead to into
conclusions that take no heed of the realities of clinical practice or of human biology. Observational data cannot provide definitive answers to questions about therapeutic effectiveness, but the difficulties of. applying the results of metaanalyses of RCTs to individual patients remain.zs
946
Treatment decisions still have to be made, patients will continue to be treated, and useful information can be derived by finding out what happens to patients after treatment and comparing this to expectations from other data sources, including RCTs. The risk with cross design synthesis is that the more expensive, time-consuming, and reliable component-RCTswill increasingly be replaced by database analyses. Formal methods of combining results from different study techniques can confuse rather than clarify the issues and should not substitute for informed interpretation of all the evidence. Accounting Office. Cross design synthesis: a new strategy for medical effectiveness research. Washington, DC: GAO, 1992. 2. Gurwitz JH, Col NF, Avorn J. The exclusion of the elderly and women from clinical trials in acute myocardial infarction. JAMA 1992; 268: 1. General
1417-22. 3. Varnauskas E. Twelve year
follow-up of survival in the randomised European coronary surgery study. N Engl J Med 1988; 319: 332-37. 4. Editorial. Databases for health care outcomes. Lancet 1989; ii: 195-96. 5. Hartz AJ, Kuhn EM, Pryor DB, et al. Mortality after coronary angioplasty and coronary artery bypass surgery (the National Medicare Experience). Am J Cardiol 1992; 70: 179-85. 6. Green SB, Byar DP. Using observational data from registries to compare treatments: the fallacy of omnimetrics. Stat Med 1984; 3: 361-70. 7. Hlatky MA, Califf RM, Harrell FE, Lee KL, Mark DB, Pryor DB. Comparison of predictions based on observational data with the results of randomised controlled clinical trials of coronary artery bypass surgery. JACC 1988; 11: 237-45. 8. Califf RM, Harrell FE, Lee KL, et al. The evolution of medical and surgical therapy for coronary artery disease: a 15-year perspective. JAMA 1989; 261: 2077-86. 9. Hlatky MA. Using databases to evaluate therapy. Star Med 1991; 10: 647-52. 10. Petitti DB, Perlman JA, Sidney S. Postmenopausal estrogen use and heart disease. N Engl J Med 1986; 315: 131-32. 11. Davey Smith G, Phillips AN, Neaton JD. Smoking as "independent" risk factor for suicide: illustration of an artifact from observational epidemiology? Lancet 1992; 340: 709-12. 12. Roper WL, Winkenwerder W, Hackbarth GM, Krakauer H. Effectiveness in health care: an initiative to evaluate and improve medical practice. N Engl J Med 1988; 319: 1197-202. 13. Risks in 2 angina treatments weighed. International Herald Tribune 1992 14.
Aug 27: 7. Eddy DM, Hasselblad V, McGivney W, Hendee W. The value of mammography screening in women under age 50 years. JAMA 1988;
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they do for us?.
South-East Asia in the twenty-first
century Over the past fifty years, the population in every country in South-East Asia has more than doubled. Fortunately food production has increased slightly faster than populations and the great epidemics have at least been contained. The last major famine was in 1943 in Bengal and there have been no epidemics of cholera, smallpox, and plague to match those in the 19th and early 20th centuries. Yet this story, which reflects much credit on the people and the health services in each country, is one of only limited successes. All the old health problems, except smallpox, remain, although some of them are less
pressing. In World Health Organisation terms the SouthEast Asia region (SEAR) consists of Bangladesh,
Bhutan, India, Indonesia, Maldives, Myanmar (Burma), Nepal, Sri Lanka, and Thailand; Malaysia, Pakistan, and Singapore are included in neighbouring regions. Nearly 1 -3 billion people-about a quarter of the world’s population-live in SEAR, and the health services in each country face broadly similar pressures. As a guide to development of the most appropriate policies for the region, the WHO regional director, Dr U. Ko Ko, asked Dr C. Gopalan to undertake a review. Gopalan’s report,1 which is refreshingly free of sociological and medical jargon, is available. Over 30% of the population live in towns, and five towns in the region are expected to have a population of over 10 million by the year 2000. Many urban dwellers live in shanty towns, where there are immense difficulties in providing potable water and effective sewerage systems. The high population density favours the spread of infectious diseases, especially those causing diarrhoea. Many women in urban slums, unlike their counterparts in the country, have to seek work in factories, shops, or as domestic servants, which restricts opportunities for breastfeeding and for preparing wholesome meals for older children. Huge rises in the number of elderly individuals are predicted for early in the next century in India, Indonesia, Sri Lanka, and Thailand. Old people in these countries are traditionally respected and cared for in their homes, as part of an extended family. The demographic changes that are now taking place will inevitably put many families under stress and the need for geriatric services throughout the region will
now
increase steadily. The increase in population has not been only among the poor. There are now many prosperous middle-class people with affluent lifestyles. Obesity, diabetes, hypertension, and ischaemic heart disease have followed in the wake of their prosperity, and are certain to place greatly increased demands on health services. Large health education programmes will be
required.
