Influenza is a common, almost ubiquitous, disease caused by influenza virus infection. Annual risks of infection can exceed 20% in some years [1,2]. However the great majority of influenza virus infections do not present as the classical triad of fever, cough and fatigue [3-5], and a substantial proportion of infections, perhaps even more than half, are asymptomatic [1,2]. Even symptomatic illnesses are generally self-limiting but a small proportion of persons with influenza virus infections will require admission to hospital, intensive care and a smaller proportion will die [6]. These outcomes are uncommon and are influenced by age, with risk increased at the two extremes of life, and the presence of co-morbidities [7]. For instance, unadjusted annual risk estimates of laboratory confirmed influenza hospitalisation in hospitals from the Emerging Infections Program in the United States between 2005 and 2011 ranged from 20-72 per 100,000 for children aged 0-4 years, 16-64 per 100,000 for adults aged at least 65 years but only 5-14 per 100,000 for adults aged 20-64 years, although higher in the first year after H1N1pdm09 emerged [8]. About 10-30% of people hospitalised with influenza will require intensive care [9-11], and about 3-10% of patients hospitalised with laboratory confirmed influenza will die [10-12].
Because serious outcomes are relatively rare, randomised controlled trials (RCTs) for the prevention of influenza by vaccination or the treatment of influenza with anti-viral drugs in ambulatory settings have not been designed with sufficient power to examine them. RCTs of vaccines [13] and anti-viral drugs [14] have shown efficacy against suspected and laboratory-confirmed influenza acquired and managed in the community but there are no RCTs with outcomes of hospitalisation or death due to laboratory-confirmed influenza. Indeed it is generally acknowledged that when outcomes are rare, the RCT is not necessarily the study design of choice. The classic case control study, in which cases and controls are ascertained retrospectively, has often been the preferred alternative design. Recently, a variation of the classic design has become popular for studying vaccine effectiveness against specific outcomes, including hospitalisation due to laboratory confirmed influenza. Referred to as the case test-negative design, patients with respiratory symptoms are ascertained prospectively and vaccine coverage is compared between those who test positive and those who test negative for influenza, adjusting for potential confounders [15]. These studies have shown that inactivated influenza vaccines are associated with around a 50% lower risk of hospital admission for laboratory confirmed influenza [16,17]. This is similar to effectiveness estimates from community observational studies using the same design [18,19], and efficacy estimates from meta-analyses of community-based trials [13].
For information on the effectiveness of anti-viral medications among hospitalised patients, we likewise need to rely on observational studies. A recent review critically examined published cohort studies assessing oseltamivir treatment for laboratory-confirmed influenza and found evidence suggesting protection against mortality in four studies, all of which were judged to be of reasonable quality, and between which there was no statistical heterogeneity [20].
However, even the best designed observational studies may be subject to residual bias, and we can all agree that further placebo-controlled trials should be conducted to improve the evidence base [14,20]. These studies would require only a small fraction of the resources invested in stockpiling for pandemic preparedness. However RCTs of anti-viral medication in outpatients with increased risk of complications, and in patients hospitalised soon after onset of symptoms, may no longer be feasible because oseltamivir is the accepted front-line treatment against these groups of patients with suspected or confirmed influenza [21-23] and such trials may no longer be granted ethical approval. The same argument applies to influenza vaccination for people aged 65 years and over. In the absence of data from RCTs, observational studies provide the next best level of evidence. Case test-negative studies of influenza vaccines have confirmed their effectiveness (not efficacy, which is the measure of effect from trials) against laboratory confirmed influenza requiring hospitalisation. Cohort studies of antiviral medication used to treat laboratory confirmed influenza have suggested protection against death [20,24]. Ignoring imperfect evidence from observational studies, while pointing to the lack of better quality (but also imperfect) evidence from trials, can lead to conclusions based on the absence of evidence, rather than the evidence of absence.
It is almost trivial to note that policy should be based on the best level of available evidence, but a policy vacuum should not be left when there are no RCTs that address a specific policy question. There have been recent discussions about the efficacy of influenza vaccines against serious outcomes in the elderly because of the absence of trial data and the policy implications of this missing evidence [25]. There is a similar current discussion about the efficacy of anti-viral medication [14,26]. Because of the absence of RCTs, contemporary policies related to influenza vaccination and treatment with anti-viral medications for serious laboratory-confirmed outcomes, including hospitalisation and death, need to incorporate findings from observational studies.
It is being increasingly recognised that influenza infection in the community is common, and that infections are associated with a wide clinical spectrum, but the serious consequences of infection are generally uncommon [2]. An improved understanding of this apparent contradiction, coupled with better quality data on the management of the serious outcomes of influenza virus infection, should lead to improved evidence-based policies for the control of influenza.
References
1. Monto AS, Koopman JS, Longini IM, Jr. Tecumseh study of illness. XIII. Influenza infection and disease, 1976-1981. Am J Epidemiol 1985; 121(6):811-22.
2. Hayward AC, Fragaszy EB, Bermingham A, et al. Comparative community burden and severity of seasonal and pandemic influenza: results of the Flu Watch cohort study. Lancet Respir Med 2014 (in press).
3. Thursky K, Cordova SP, Smith D, Kelly H. Working towards a simple case definition for influenza surveillance. J Clin Virol 2003; 27(2):170-9.
4. Call SA, Vollenweider MA, Hornung CA, Simel DL, McKinney WP. Does this patient have influenza? JAMA 2005; 293(8):987-97.
5. Lau LL, Nishiura H, Kelly H, Ip DK, Leung GM, Cowling BJ. Household transmission of 2009 pandemic influenza A (H1N1): a systematic review and meta-analysis. Epidemiology 2012; 23(4):531-42.
6. Wu JT, Ma ES, Lee CK, et al. The infection attack rate and severity of 2009 pandemic H1N1 influenza in Hong Kong. Clin Infect Dis 2010; 51(10):1184-91.
7. Uyeki TM. Preventing and controlling influenza with available interventions. N Engl J Med 2014; 370(9):789-91.
8. Kostova D, Reed C, Finelli L, et al. Influenza Illness and Hospitalizations Averted by Influenza Vaccination in the United States, 2005-2011. PLoS One 2013; 8(6):e66312.
9. Campbell CN, Mytton OT, McLean EM, et al. Hospitalization in two waves of pandemic influenza A(H1N1) in England. Epidemiol Infect 2011; 139(10):1560-9.
10. Louie JK, Acosta M, Winter K, et al. Factors associated with death or hospitalization due to pandemic 2009 influenza A(H1N1) infection in California. JAMA 2009; 302(17):1896-902.
11. Bagdure D, Curtis DJ, Dobyns E, Glode MP, Dominguez SR. Hospitalized children with 2009 pandemic influenza A (H1N1): comparison to seasonal influenza and risk factors for admission to the ICU. PLoS One 2010; 5(12):e15173.
12. Myles PR, Semple MG, Lim WS, et al. Predictors of clinical outcome in a national hospitalised cohort across both waves of the influenza A/H1N1 pandemic 2009-2010 in the UK. Thorax 2012; 67(8):709-17.
13. Osterholm MT, Kelley NS, Sommer A, Belongia EA. Efficacy and effectiveness of influenza vaccines: a systematic review and meta-analysis. Lancet Infect Dis 2012; 12(1):36-44.
14. Jefferson T, Jones MA, Doshi P, et al. Neuraminidase inhibitors for preventing and treating influenza in healthy adults and children. Cochrane database of systematic reviews (Online) 2014; 4:CD008965.
15. Foppa IM, Haber M, Ferdinands JM, Shay DK. The case test-negative design for studies of the effectiveness of influenza vaccine. Vaccine 2013; 31(30):3104-9.
16. Puig-Barbera J, Arnedo-Pena A, Pardo-Serrano F, et al. Effectiveness of seasonal 2008-2009, 2009-2010 and pandemic vaccines, to prevent influenza hospitalizations during the autumn 2009 influenza pandemic wave in Castellon, Spain. A test-negative, hospital-based, case-control study. Vaccine 2010; 28(47):7460-7.
17. Talbot HK, Griffin MR, Chen Q, Zhu Y, Williams JV, Edwards KM. Effectiveness of seasonal vaccine in preventing confirmed influenza-associated hospitalizations in community dwelling older adults. J Infect Dis 2011; 203(4):500-8.
18. Kelly HA, Sullivan SG, Grant KA, Fielding JE. Moderate influenza vaccine effectiveness with variable effectiveness by match between circulating and vaccine strains in Australian adults aged 20-64 years, 2007-2011. Influenza Other Respir Viruses 2013; 7(5):729-37.
19. Ohmit SE, Petrie JG, Malosh RE, et al. Influenza vaccine effectiveness in the community and the household. Clin Infect Dis 2013; 56(10):1363-9.
20. Freemantle N, Shallcross LJ, Kyte D, Rader T, Calvert MJ. Oseltamivir: the real world data. BMJ 2014; 348.
21. Fiore AE, Fry A, Shay D, et al. Antiviral agents for the treatment and chemoprophylaxis of influenza --- recommendations of the Advisory Committee on Immunization Practices (ACIP). MMWR Recomm Rep 2011; 60(1):1-24.
22. World Health Organization. WHO Guidelines for Pharmacological Management of Pandemic Influenza A(H1N1) 2009 and Other Influenza Viruses. Geneva, 2010.
23. Public Health England. PHE guidance on use of antiviral agents for the treatment and prophylaxis of influenza. [cited April 21, 2014]; Available from: http://www.hpa.org.uk/webc/HPAwebFile/HPAweb_C/1317140666783
24. Muthuri SG, Venkatesan S, Myles PR, et al. Effectiveness of neuraminidase inhibitors in reducing mortality in patients admitted to hospital with influenza A H1N1pdm09 virus infection: a meta-analysis of individual participant data. The Lancet Respiratory Medicine 2014 (in press).
25. Doshi P. Influenza vaccines: time for a rethink. JAMA Intern Med 2013; 173(11):1014-6.
26. Krumholz HM. Neuraminidase inhibitors for influenza. BMJ 2014; 348.
Competing interests:
BJC has received research funding from MedImmune Inc. and Sanofi Pasteur, and consults for Crucell NV. The authors report no other potential conflicts of interest.
26 April 2014
Heath Kelly
Epidemiologist
Benjamin J. Cowling (School of Public Health, The University of Hong Kong, Hong Kong)
Rapid Response:
Re: Neuraminidase inhibitors for influenza
Influenza is a common, almost ubiquitous, disease caused by influenza virus infection. Annual risks of infection can exceed 20% in some years [1,2]. However the great majority of influenza virus infections do not present as the classical triad of fever, cough and fatigue [3-5], and a substantial proportion of infections, perhaps even more than half, are asymptomatic [1,2]. Even symptomatic illnesses are generally self-limiting but a small proportion of persons with influenza virus infections will require admission to hospital, intensive care and a smaller proportion will die [6]. These outcomes are uncommon and are influenced by age, with risk increased at the two extremes of life, and the presence of co-morbidities [7]. For instance, unadjusted annual risk estimates of laboratory confirmed influenza hospitalisation in hospitals from the Emerging Infections Program in the United States between 2005 and 2011 ranged from 20-72 per 100,000 for children aged 0-4 years, 16-64 per 100,000 for adults aged at least 65 years but only 5-14 per 100,000 for adults aged 20-64 years, although higher in the first year after H1N1pdm09 emerged [8]. About 10-30% of people hospitalised with influenza will require intensive care [9-11], and about 3-10% of patients hospitalised with laboratory confirmed influenza will die [10-12].
Because serious outcomes are relatively rare, randomised controlled trials (RCTs) for the prevention of influenza by vaccination or the treatment of influenza with anti-viral drugs in ambulatory settings have not been designed with sufficient power to examine them. RCTs of vaccines [13] and anti-viral drugs [14] have shown efficacy against suspected and laboratory-confirmed influenza acquired and managed in the community but there are no RCTs with outcomes of hospitalisation or death due to laboratory-confirmed influenza. Indeed it is generally acknowledged that when outcomes are rare, the RCT is not necessarily the study design of choice. The classic case control study, in which cases and controls are ascertained retrospectively, has often been the preferred alternative design. Recently, a variation of the classic design has become popular for studying vaccine effectiveness against specific outcomes, including hospitalisation due to laboratory confirmed influenza. Referred to as the case test-negative design, patients with respiratory symptoms are ascertained prospectively and vaccine coverage is compared between those who test positive and those who test negative for influenza, adjusting for potential confounders [15]. These studies have shown that inactivated influenza vaccines are associated with around a 50% lower risk of hospital admission for laboratory confirmed influenza [16,17]. This is similar to effectiveness estimates from community observational studies using the same design [18,19], and efficacy estimates from meta-analyses of community-based trials [13].
For information on the effectiveness of anti-viral medications among hospitalised patients, we likewise need to rely on observational studies. A recent review critically examined published cohort studies assessing oseltamivir treatment for laboratory-confirmed influenza and found evidence suggesting protection against mortality in four studies, all of which were judged to be of reasonable quality, and between which there was no statistical heterogeneity [20].
However, even the best designed observational studies may be subject to residual bias, and we can all agree that further placebo-controlled trials should be conducted to improve the evidence base [14,20]. These studies would require only a small fraction of the resources invested in stockpiling for pandemic preparedness. However RCTs of anti-viral medication in outpatients with increased risk of complications, and in patients hospitalised soon after onset of symptoms, may no longer be feasible because oseltamivir is the accepted front-line treatment against these groups of patients with suspected or confirmed influenza [21-23] and such trials may no longer be granted ethical approval. The same argument applies to influenza vaccination for people aged 65 years and over. In the absence of data from RCTs, observational studies provide the next best level of evidence. Case test-negative studies of influenza vaccines have confirmed their effectiveness (not efficacy, which is the measure of effect from trials) against laboratory confirmed influenza requiring hospitalisation. Cohort studies of antiviral medication used to treat laboratory confirmed influenza have suggested protection against death [20,24]. Ignoring imperfect evidence from observational studies, while pointing to the lack of better quality (but also imperfect) evidence from trials, can lead to conclusions based on the absence of evidence, rather than the evidence of absence.
It is almost trivial to note that policy should be based on the best level of available evidence, but a policy vacuum should not be left when there are no RCTs that address a specific policy question. There have been recent discussions about the efficacy of influenza vaccines against serious outcomes in the elderly because of the absence of trial data and the policy implications of this missing evidence [25]. There is a similar current discussion about the efficacy of anti-viral medication [14,26]. Because of the absence of RCTs, contemporary policies related to influenza vaccination and treatment with anti-viral medications for serious laboratory-confirmed outcomes, including hospitalisation and death, need to incorporate findings from observational studies.
It is being increasingly recognised that influenza infection in the community is common, and that infections are associated with a wide clinical spectrum, but the serious consequences of infection are generally uncommon [2]. An improved understanding of this apparent contradiction, coupled with better quality data on the management of the serious outcomes of influenza virus infection, should lead to improved evidence-based policies for the control of influenza.
References
1. Monto AS, Koopman JS, Longini IM, Jr. Tecumseh study of illness. XIII. Influenza infection and disease, 1976-1981. Am J Epidemiol 1985; 121(6):811-22.
2. Hayward AC, Fragaszy EB, Bermingham A, et al. Comparative community burden and severity of seasonal and pandemic influenza: results of the Flu Watch cohort study. Lancet Respir Med 2014 (in press).
3. Thursky K, Cordova SP, Smith D, Kelly H. Working towards a simple case definition for influenza surveillance. J Clin Virol 2003; 27(2):170-9.
4. Call SA, Vollenweider MA, Hornung CA, Simel DL, McKinney WP. Does this patient have influenza? JAMA 2005; 293(8):987-97.
5. Lau LL, Nishiura H, Kelly H, Ip DK, Leung GM, Cowling BJ. Household transmission of 2009 pandemic influenza A (H1N1): a systematic review and meta-analysis. Epidemiology 2012; 23(4):531-42.
6. Wu JT, Ma ES, Lee CK, et al. The infection attack rate and severity of 2009 pandemic H1N1 influenza in Hong Kong. Clin Infect Dis 2010; 51(10):1184-91.
7. Uyeki TM. Preventing and controlling influenza with available interventions. N Engl J Med 2014; 370(9):789-91.
8. Kostova D, Reed C, Finelli L, et al. Influenza Illness and Hospitalizations Averted by Influenza Vaccination in the United States, 2005-2011. PLoS One 2013; 8(6):e66312.
9. Campbell CN, Mytton OT, McLean EM, et al. Hospitalization in two waves of pandemic influenza A(H1N1) in England. Epidemiol Infect 2011; 139(10):1560-9.
10. Louie JK, Acosta M, Winter K, et al. Factors associated with death or hospitalization due to pandemic 2009 influenza A(H1N1) infection in California. JAMA 2009; 302(17):1896-902.
11. Bagdure D, Curtis DJ, Dobyns E, Glode MP, Dominguez SR. Hospitalized children with 2009 pandemic influenza A (H1N1): comparison to seasonal influenza and risk factors for admission to the ICU. PLoS One 2010; 5(12):e15173.
12. Myles PR, Semple MG, Lim WS, et al. Predictors of clinical outcome in a national hospitalised cohort across both waves of the influenza A/H1N1 pandemic 2009-2010 in the UK. Thorax 2012; 67(8):709-17.
13. Osterholm MT, Kelley NS, Sommer A, Belongia EA. Efficacy and effectiveness of influenza vaccines: a systematic review and meta-analysis. Lancet Infect Dis 2012; 12(1):36-44.
14. Jefferson T, Jones MA, Doshi P, et al. Neuraminidase inhibitors for preventing and treating influenza in healthy adults and children. Cochrane database of systematic reviews (Online) 2014; 4:CD008965.
15. Foppa IM, Haber M, Ferdinands JM, Shay DK. The case test-negative design for studies of the effectiveness of influenza vaccine. Vaccine 2013; 31(30):3104-9.
16. Puig-Barbera J, Arnedo-Pena A, Pardo-Serrano F, et al. Effectiveness of seasonal 2008-2009, 2009-2010 and pandemic vaccines, to prevent influenza hospitalizations during the autumn 2009 influenza pandemic wave in Castellon, Spain. A test-negative, hospital-based, case-control study. Vaccine 2010; 28(47):7460-7.
17. Talbot HK, Griffin MR, Chen Q, Zhu Y, Williams JV, Edwards KM. Effectiveness of seasonal vaccine in preventing confirmed influenza-associated hospitalizations in community dwelling older adults. J Infect Dis 2011; 203(4):500-8.
18. Kelly HA, Sullivan SG, Grant KA, Fielding JE. Moderate influenza vaccine effectiveness with variable effectiveness by match between circulating and vaccine strains in Australian adults aged 20-64 years, 2007-2011. Influenza Other Respir Viruses 2013; 7(5):729-37.
19. Ohmit SE, Petrie JG, Malosh RE, et al. Influenza vaccine effectiveness in the community and the household. Clin Infect Dis 2013; 56(10):1363-9.
20. Freemantle N, Shallcross LJ, Kyte D, Rader T, Calvert MJ. Oseltamivir: the real world data. BMJ 2014; 348.
21. Fiore AE, Fry A, Shay D, et al. Antiviral agents for the treatment and chemoprophylaxis of influenza --- recommendations of the Advisory Committee on Immunization Practices (ACIP). MMWR Recomm Rep 2011; 60(1):1-24.
22. World Health Organization. WHO Guidelines for Pharmacological Management of Pandemic Influenza A(H1N1) 2009 and Other Influenza Viruses. Geneva, 2010.
23. Public Health England. PHE guidance on use of antiviral agents for the treatment and prophylaxis of influenza. [cited April 21, 2014]; Available from: http://www.hpa.org.uk/webc/HPAwebFile/HPAweb_C/1317140666783
24. Muthuri SG, Venkatesan S, Myles PR, et al. Effectiveness of neuraminidase inhibitors in reducing mortality in patients admitted to hospital with influenza A H1N1pdm09 virus infection: a meta-analysis of individual participant data. The Lancet Respiratory Medicine 2014 (in press).
25. Doshi P. Influenza vaccines: time for a rethink. JAMA Intern Med 2013; 173(11):1014-6.
26. Krumholz HM. Neuraminidase inhibitors for influenza. BMJ 2014; 348.
Competing interests: BJC has received research funding from MedImmune Inc. and Sanofi Pasteur, and consults for Crucell NV. The authors report no other potential conflicts of interest.