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Comparative benefit of malaria chemoprophylaxis modelled in United Kingdom travellers
Travel Medicine and Infectious Disease (2014) 12, 726e732
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.elsevierhealth.com/journals/tmid
Comparative benefit of malaria chemoprophylaxis modelled in United Kingdom travellers* Stephen Toovey a,*, Keith Nieforth b, Patrick Smith b, Patricia Schlagenhauf c, Miriam Adamcova d, Iain Tatt d, Danitza Tomianovic d, Gabriel Schnetzler d a
Pegasus Research, Basel, Switzerland d3 Medicine, Parsippany, NJ, USA c University of Zurich Centre for Travel Medicine, WHO Collaborating Centre for Travellers’ Health, Institute for Social and Preventive Medicine, Zurich, Switzerland d F. Hoffmann-La Roche, Basel, Switzerland b
Received 6 March 2014; received in revised form 30 July 2014; accepted 7 August 2014
Available online 28 September 2014
KEYWORDS Mefloquine; Atovaquoneproguanil; Doxycycline; Chloroquine; Prophylaxis
Summary Background: Chemoprophylaxis against falciparum malaria is recommended for travellers from non-endemic countries to malarious destinations, but debate continues on benefit, especially with regard to mefloquine. Quantification of benefit for travellers from the United Kingdom (UK) was modelled to assist clinical and public health decision making. Methods: The model was constructed utilising: World Tourism Organization data showing total number of arrivals from the UK in countries with moderate or high malaria risk; data from a retrospective UK Clinical Practice Research Datalink (CPRD) drug utilisation study; additional information on chemoprophylaxis, case fatality and tolerability were derived from the travel medicine literature. Chemoprophylaxis with the following agents was considered: atovaquone-proguanil (AP), chloroquine with and without proguanil (C P), doxycycline (Dx), mefloquine (Mq). The model was validated for the most recent year with temporally matched datasets for UK travel destinations and imported malaria (2007) against UK Health Protection Agency data on imported malaria. Results: The median (mean) duration of chemoprophylaxis for each agent in weeks (CPRD) was: AP 3.3 (3.5), C P 9 (12.1), Dx 8 (10.3), Mq 9 (12.3): the maximum duration of use of all regimens was 52 weeks. The model correctly predicted falciparum malaria deaths and gave a robust estimate of total cases e model: 5 deaths from 1118 cases; UK Health Protection Agency: 5 deaths from 1153 cases. The number needed to take chemoprophylaxis (NNP) to
* The abstract of this paper was presented as a poster at the 8th European Conference on Tropical Medicine and International Health in Copenhagen, Denmark, September 10e13, 2013. * Corresponding author. E-mail address: [email protected] (S. Toovey).
http://dx.doi.org/10.1016/j.tmaid.2014.08.005 1477-8939/ª 2014 Published by Elsevier Ltd.
Benefit of malaria chemoprophylaxis
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prevent a case of malaria considered against the ‘background’ reported incidence in non-users of chemoprophylaxis deemed in need of chemoprophylaxis was: C P 272, Dx 269, Mq 260, AP 252; the NNP to prevent a UK traveller malaria death was: C P 62613, Dx 61923, Mq 59973, AP 58059; increasing the ‘background’ rate by 50% yielded NNPs of: C P 176, Dx 175, Mq 171, AP 168. The impact of substituting atovaquone-proguanil for all mefloquine usage resulted in a 2.3% decrease in estimated infections. The number of travellers experiencing moderate adverse events (AE) or those requiring medical attention or drug withdrawal per case prevented is as follows: C P 170, Mq 146, Dx 114, AP 103. Conclusions: The model correctly predicted the number of malaria deaths, providing a robust and reliable estimate of the number of imported malaria cases in the UK, and giving a measure of benefit derived from chemoprophylaxis use against the likely adverse events generated. Overall numbers needed to prevent a malaria infection are comparable among the four options and are sensitive to changes in the background infection rates. Only a limited impact on the number of infections can be expected if Mq is substituted by AP. ª 2014 Published by Elsevier Ltd.
1. Introduction Falciparum malaria is a progressive and potentially lethal disease in patients who do not possess some degree of preexisting immunity to Plasmodium falciparum, the causative parasite; such immunity is usually acquired through having grown up in, and having continued to reside in, a malaria endemic region [1]. Thus, most travellers from developed countries will be at elevated risk of serious and potentially fatal illness should they visit a malaria endemic region. Emigrants from malarious regions settled in non-malarious countries lose protective immunity over time, and hence are at increased risk of clinical malaria should they visit malarious destinations, typically upon making a return visit to their countries of origin. Settled immigrants do however retain some residual semi-immunity and are less likely to die from malaria than non-immune travellers [2]. Antimalarial chemoprophylaxis is accordingly recommended for travellers from malaria free countries who visit malarious regions, to prevent development of acute malaria and its complications, including severe disease and death [3]. All medication is associated with the risk of developing adverse events (AEs), and these risks are quite well characterised for the antimalarial chemoprophylactic agents in current use: mefloquine, atovaquone-proguanil, doxycycline, chloroquine with and without proguanil [4], however, to enable a more complete assessment of the benefit-risk ratio for antimalarial chemoprophylaxis, quantification of benefit would be helpful. To this end we have modelled the benefits of chemoprophylaxis for travellers from the United Kingdom visiting moderate and high-risk malarious destinations. As travellers to low-risk malaria destinations are often recommended stand-by emergency medication rather than chemoprophylaxis, we excluded such destinations from our datasets [5].
2. Materials and methods The model attempts to track the flow of travellers from the United Kingdom to moderate and high-risk malaria
destinations in calendar year 2007, the latest year for which complete data sets for all model variables were available, and to assess the benefit conferred by the use of chemoprophylaxis. The data sources utilised to populate the model are detailed below. The numbers of travellers at travel related risk of malaria exposure were obtained from the United Nations World Tourism Organization (UNWTO) dataset, “Data on Outbound Tourism (2012)” [6]. Destination countries were then cross referenced to country risk category from the US CDC malaria risk tables [7]. For the purposes of this model, countries on the CDC list were reclassified by a malariologist as high, low, or no risk destinations for malaria. In the case of countries such as South Africa, which are mostly malaria free, but which do contain only localised high risk malarious regions, the risk for the whole country was set to ‘no risk’ in order to not overinflate “high risk” exposure. To ascertain the number of UK travellers who sought advice and were assessed by health care professional prior to departure, numbers were obtained from those reported in a survey of departing passengers conducted in 2003 at Heathrow Airport, London, UK, and from the results of a field study of UK travellers [8,9]. The allocation of travellers to each of the four chemoprophylactic drug groups, mefloquine, atovaquoneproguanil, doxycycline, chloroquine and proguanil was determined from the results of a separate study by Blo ¨chliger et al. of prescribing patterns in UK general practice, conducted using the UK Community Practice Research Database (formerly known as the UK General Practice Research Database) [10]. The split between agents, derived from the absolute number of travellers prescribed each chemoprophylactic agent is as follows: mefloquine 15.3%, atovaquone-proguanil 65.6%, doxycycline 14%, and chloroquine with and without proguanil 5.1%. Malaria infection and death rates in UK travellers for the calendar year 2007 were obtained from published UK Health Protection Agency data [11]. The number of reported cases of malaria occurring in UK users of each chemoprophylactic agent was based upon the analysis of
728 Zuckerman et al., which also reported for the calendar year 2007 [12]. Likely AE rates associated with the use of each of the chemoprophylactic agents of interest were obtained from a double-blind, randomised study of Swiss, German and Israeli travellers, thought to be of acceptably similar profile to UK travellers, an equivalent UK study not being available [4]. Mild AEs were not included in the model, only those categorised as either moderate, requiring medical attention, or leading to cessation of usage: given the seriousness of malaria, mild AEs were thought to be generally tolerable and not disruptive of travel. In addition, as the percentages applied were obtained from a clinical study, a setting in which AEs are solicited and which may overestimate the ‘real world’ AE incidence, a further analysis of the AE burden was undertaken. This second analysis considered only those AEs that required medical attention. For both analyses, the AE rate for each regimen, regardless of infection status, was multiplied by the NNP infection, generating the AE burden for each case of malaria prevented, for each regimen, this number being a measure of the benefit-risk ratio for each agent. Overall mortality was taken as published by the UK Health Protection Agency [11], and was applied to users of chemoprophylaxis, and the adjusted total of non-users, to generate the number of fatalities for each of these two groups; these were then summed to provide the total number of malaria deaths. The model was a decision-tree type model, implemented in Microsoft Excel. The model incorporated data-derived event probabilities, including the number of individuals receiving prophylaxis, infection rates with and without prophylaxis, infection-related morbidity and mortality, and drug-related adverse event rates. The model was populated with the actual measured or reported values from the abovementioned sources, to generate a base case scenario, with the following inputs entered into the model: the total number of UK travellers to risk destinations was set at 1,768,210 [6], with the fraction of this total using chemoprophylaxis set at 0.78 [9]; the fraction of chemoprophylaxis users taking each of the four regimens was: mefloquine 0.153, atovaquone-proguanil 0.656, doxycycline 0.14, chloroquine with and without proguanil 0.051 [10]; the fraction of travellers not using malaria chemoprophylaxis because they had been advised against usage was set at 0.37 [8]. The infection rate amongst users of each of the four chemoprophylactic regimens was calculated from the known number of cases in the UK and published utilisation data, applying the usage ratios derived from the Blo ¨chliger drug utilisation study [10e12]. The infection rate amongst non-users of chemoprophylaxis was adjusted for those deemed not at actual risk of becoming infected [8]. Infections per group were summed to provide the total number of cases. Infection rates per person-week of exposure were calculated for each chemoprophylaxis regimen, being the quotient of the total number of infections calculated for that regimen, and the product of the total number of regimen users and mean duration of usage. For each of the four agents, the number of travellers that would need to be prescribed the agent to prevent one death from malaria, and the number needed to prevent one
S. Toovey et al. clinical malaria infection were calculated, being the reciprocal of the difference in rates with adjusted nonusers of chemoprophylaxis, expressed as NNP death and NNP infection respectively. Although the adopted approach is reasonably ‘grounded in reality’ inasmuch as the model was based on real world data, there are nevertheless likely to be differences between the four chemoprophylaxis groups with respect to their destinations, as well as other unmeasured variables, including variations in background malaria intensity, with malaria transmission rates not being geographically uniform within countries. Additionally, the proportion of travellers not using chemoprophylaxis subsequent to taking professional advice could vary between groups and destinations. We therefore also examined the impact of varying rates of malaria infection on the NNP for each agent, by generating a range of values that may be more reflective of the risk spectrum within destination countries: a range of values from 80% to 200% of the actual estimated infection rate in non-users of chemoprophylaxis deemed at risk of infection was utilised. A further sensitivity analysis was undertaken to examine what the impact of increasing and decreasing mefloquine’s share of total chemoprophylactic prescriptions might have on the total predicted number of malaria infections and deaths. We additionally investigated the impact of a higher malaria death rate in infected travellers, examining what the impact on mortality would be if the UK rate were increased to the 3% mortality reported by Germany for nonimmune tourists for the period 1993e2004 [13], as well as a higher rate of 4% that might reflect likely level of care in some lesser experienced centres.
3. Results The model correctly predicted the total number of malaria deaths in the UK in 2007, yielding a result of five deaths, which matched exactly the official HPA statistic. The model predicted the total number of cases to be 1118, which is a very close estimate (97%) of the 1153 actual malaria infections recorded by the HPA in 2007. The NNP infection and NNP death for each of the four agents, based upon actual drug prescription patterns within the UK, are presented in Table 1; the impact of changes in the malaria transmission, or ’background rate’ on NNP infection and NNP death are similarly included in Table 1. As would be expected, both of these numbers fall as the background rate increases, and vice versa. Altering the prescription pattern within the model, by swapping mefloquine and atovaquone-proguanil usages, had no impact on the number of predicted deaths but did yield a 9.8% increase in the number of infections, from 1118 to 1228. The impact of substituting atovaquone-proguanil for all mefloquine usage, i.e. setting mefloquine usage to zero and atovaquone-proguanil to 80.9% of total usage, was similar, with predicted deaths remaining at 5, and predicted infections decreasing slightly (2.3%) from 1118 to 1092. These results are summarised in Table 2. Increasing the mortality rate from the actual observed rate in the UK (<1%) to 3% and beyond resulted in a large increase in deaths amongst non-users of chemoprophylaxis,
Benefit of malaria chemoprophylaxis
729
Table 1 Number of travellers that need to be prescribed chemoprophylaxis to prevent one malaria infection (NNP infection) and one death (NNP death) as a function of the background malaria rate in travellers not using antimalarial chemoprophylaxis. 80%
Mefloquine Atovaquone-proguanil Doxycycline Chloroquine proguanil
100% baseline
120%
150%
200%
NNP death
NNP infection
NNP death
NNP infection
NNP death
NNP infection
NNP death
NNP infection
NNP death
NNP infection
75744 72718 78882 80005
329 316 342 347
59973 58059 61923 62613
260 252 269 272
49637 48319 50965 51432
215 210 221 223
39441 38604 40275 40566
171 168 175 176
29382 28915 29843 30002
128 125 130 130
and consequently a significant impact on NNP death: the NNP death falls to below 9000 for all regimens if the higher mortality rate of 3% is applied. These results are presented in Table 3. Infection rates per person week of exposure for each agent were as follows: mefloquine 0.0000128, atovaquoneproguanil 0.00000897, doxycycline 0.0000271, chloroquine with and without proguanil 0.0000264. The model revealed mefloquine and atovaquone-proguanil to have roughly similar overall infection rates, while the infection rates for users of doxycycline and chloroquine with and without proguanil were similar and approximately two to three times those seen with atovaquone-proguanil and mefloquine. The AE burden as number of travellers affected per malaria case prevented, considering medication cessation, moderate AEs, and AEs requiring medical attention is as
follows: chloroquine with or without proguanil 170, mefloquine 146, doxycycline 114, and atovaquone-proguanil 103.; the AE burden considering just those AEs requiring medical attention is substantially lower: chloroquine with or without proguanil 33, mefloquine 29, atovaquoneproguanil 18, doxycycline 16 (Table 4).
4. Discussion Despite the utilised data having been drawn from different sources, the model provided remarkably accurate predictions for the number of deaths and infections, and hence we believe useful NNP infection and NNP death statistics. It was interesting to note that there was little difference between the four agents studied in terms of their NNP infection and NNP death results.
730
S. Toovey et al. way of comparison, the number of individuals aged greater than 65 years old needed to be vaccinated (NNV) against influenza to prevent one hospitalisation is estimated to be 777; to prevent one hospitalisation for invasive pneumococcal disease in those above 65 years of age, the pneumococcus vaccine NNV is estimated to be 3333 [14]. It should also be borne in mind that the UK has a particularly good record in treating malaria, with a very low mortality rate [11]. In countries with higher mortality, the NNP death would accordingly expected to be lower: substituting the UK’s 0.43% reported mortality with that of the 3% reported by Krause et al. for Germany, the NNP death for mefloquine would drop from 59973 to 8676 [13]. Of interest was the impact on NNP of even a slight (20%) increase in the ‘background’ malaria rate. As the actual risk faced by any individual traveller can never be known with certainty and varies within countries [15], some travellers will be at higher risk, reducing the NNP infection and NNP death for further; Table 1 attempts to illustrate the impact on travellers of these variations. The AE rates utilised are those reported by Swiss, German and Israeli travellers for subjectively moderate AEs, AEs requiring medical attention, and withdrawals, with the total rates for each regimen being: chloroquine with and without proguanil 62.7%, mefloquine 56.2%, doxycycline 42.5%, atovaquone-proguanil 40.8% [4]. The AE rates applied for events requiring medical attention were chloroquine with and without proguanil 12.4%, mefloquine 10.5%, doxycycline 5.9%, atovaquone-proguanil 6.7% [4]. By way of context, moderate to severe AE rates reported in a placebo controlled head to head comparison of atovaquone-proguanil against mefloquine were 10% for
Table 2 Impact of altering mefloquine and atovaquoneproguanil prescription share on estimated number of malaria cases and deaths. Prescription share
Actual share: Mefloquine 15.3% Atovaquoneproguanil 65.6% Reversed share: Mefloquine 65.6% Atovaquoneproguanil 15.3% Without mefloquine: Mefloquine 0% Atovaquoneproguanil 80.9%
Estimated total deaths
Estimated total infections
No.
% Change
No.
% Change
5
e
1118
e
5
0
1228
þ9.8%
5
0
1092
2.3%
The Number Needed to Prevent one case of malaria (NNP infection) for the UK of 260e272 (i.e. for every 260e270 users of malaria chemoprophylaxis, one case of malaria is prevented) should provide reassurance to prescribers, given the severe and rapidly progressive nature of falciparum malaria in non-immunes such as travellers, and the real risk of permanent and serious sequelae and death. This NNP infection figure argues strongly for chemoprophylaxis, especially given the conservative nature of the model. By
Table 3 death).
Impact of varying mortality rate in infected travellers on deaths and number needed to prevent one death (NNP Mortality rate
a
No chemoprophylaxis Mefloquine Atovaquone-proguanil Doxycycline Chloroquine proguanil a
0.434% (current UK rate)
1%
NNP death
Deaths
NNP death
Deaths
NNP death
3% Deaths
NNP death
4% Deaths
e 59973 58059 61923 62613
4.254 0.145 0.123 0.234 0.004
e 26028 25198 26874 27174
9.803 0.333 0.284 0.539 0.010
e 8676 8399 8958 9058
29.409 1.000 0.852 1.616 0.030
e 6507 6299 6719 6793
39.212 1.334 1.136 2.155 0.040
Adjusted for non-use on advice.
Table 4 Adverse event (AE) burden for each case of P. falciparum prevented by chemoprophylaxis, for moderate AEs, AEs requiring medical attention, and cessation of use; and for AEs requiring medical attention only.
Chloroquine proguanil Doxycycline Mefloquine Atovaquone-proguanil
Number needed to prevent one infection
Total AE rate %
Total AEs/ infection prevented
AEs requiring medical attention rate %
AEs requiring medical attention/infection prevented
272 269 260 252
63 43 56 41
171 114 146 103
12 6 11 7
33 16 26 18
Benefit of malaria chemoprophylaxis atovaquone-proguanil, and 19% for mefloquineq [16]. The different settings and methods make comparisons difficult, but both studies do note the association of neuropsychiatric AEs with mefloquine. A Cochrane Collaboration review of chemoprophylactic AE rates found the highest overall AE rate in chloroquine with and without proguanil users, but noted the incidence of neuropsychiatric AEs to be highest in mefloquine users, with reports of mefloquine neurotoxicity having been reviewed elsewhere [17,18]. The overall burden of AEs associated with chemoprophylaxis use (Table 4) and the rarity of serious AEs associated with chemoprophylaxis, as observed in a Cochrane Collaboration review, point to a favourable benefit risk profile for chemoprophylaxis [18]. With respect to mefloquine specifically, a very large study by Steffen et al. reported the incidence of serious neuropsychiatric AEs in European travellers at 1 per 10,600 travellers, also indicating the rarity of such events [19]. In addition, a recent retrospective data analysis of the UK general practice research database suggests a similar risk of neuropsychiatric disorders for users and for non-users of anti-malarial chemoprophylaxis [20]. It was this relative infrequency of serious AEs that prevented their inclusion in the model. It may be that the estimates obtained for the AE burden in this model overestimate the true incidence, as they are based upon a placebo controlled study of travellers, in which a 16% incidence of placebo associated AEs was reported in the weeks prior to travel [4]. This model has been additionally utilised to estimate the effect of substituting mefloquine completely by atovaquone-proguanil. Such a complete substitution would results in only a minimal improvement of outcomes, however. There are some obvious limitations in this model: one being that the last year for which contemporaneous data sets could be obtained was 2007. Another would be that the datasets used were disparate in source, and were themselves samples, apart from the UNWTO travellers’ destination data. The model also takes no account of the benefits obtained from personal and environmental protection measures, and the number of travellers who take chemoprophylaxis despite not being at actual risk of malaria [8,9,21e24]. Mitigating to some extent the heterogeneity of the data sources are the conservative decision to classify countries with limited geographic malarious ranges as non-malarious, and the possible under-reporting of malaria, although the UK is acknowledged to have a robust and reliable surveillance system [25]. Travellers who fall ill with malaria while abroad will also not have their data captured for use in this model, with greater under-reporting more likely in nonusers of chemoprophylaxis. Additionally, increasing awareness by the travelling public of the risks posed by malaria might have led to a higher proportion undergoing pre-travel assessment in 2007, compared with that reported in the 2003 airport survey [9]. Another weakness of the model is that it assumes travel destinations, traveller type (tourists, VFR et al.) and itineraries are the same for all four agents. This is unlikely to be the case, given the differing costs and contra-indications for these agents. A possible clue to the nature of these differences is the differing median durations of use for
731 each, as reported from the UK CPRD study, with atovaquone-proguanil having a shorter median duration of use than mefloquine: 3.3 versus 9 weeks respectively [10]. The duration of the post malaria eexposure prophylaxis of an additional 3 weeks with mefloquine compared to atovaquone-proguanil does not sufficiently explain the difference. One may speculate it reflects different types of travel, with the shorter duration travel being more compatible with resort type holiday travel, and longer duration travel more compatible with backpacking and adventurous travel, and thus possibly higher risk for malaria. The higher cost of atovaquone-proguanil might also make it less likely to be used by younger travellers or VFR travellers with constrained budgets, but favoured by more affluent travellers able to afford the extra convenience of atovaquone-proguanil’s limited post-exposure use. Whatever the explanation, it seems reasonable that the actual malaria risk faced by travellers could be different for the four agents, tempering direct comparisons between the different agents when assessing benefits. Nevertheless, altering the usage split between agents has no impact on the number of deaths, and very little impact on the number of predicted infections. The model correctly predicts the number of malaria deaths in the UK and provides a robust and reliable estimate of the number of imported malaria cases in the UK. Measures of the protective benefit conferred by all four commonly prescribed chemoprophylaxis agents, expressed as NNP to prevent one infection or one death, are very similar for mefloquine, atovaquone-proguanil, doxycycline, and chloroquine with and without proguanil. There appears to be little change in benefit when mefloquine use is substituted by atovaquone-proguanil, and vice versa. The model goes some way to quantifying the benefit-risk ratio of chemoprophylaxis, and may help inform policy on chemoprophylaxis.
Financial disclosure This work was funded by F. Hoffmann e La Roche, Basel, Switzerland. ST is a paid consultant to F. Hoffmann e La Roche, Basel, Switzerland. PS has received research grants and speakers’ honoraria from Glaxo Smith Kline and research grants, speakers’ honoraria and consultancy fees from F. Hoffmann-La Roche. Miriam Adamcova, Gabriel Schnetzler, Iain Tatt and Danitza Tomianovic were employees of F. Hoffmann-La Roche when this research work was undertaken.
Conflict of interest At the time the bulk of this manuscript was written, I was fully employed by F. Hoffmann-La Roche Ltd. As of December 2013, I was no longer employed by F. Hoffman-La Roche Ltd e Danitza Tomianovic Employee of F. Haffmann-La Roche Ltd e Gabriel Schnetzler None e Iain Tatt I am a consultant for Hoffmann-La Roche e Keith Nieforth
732 I am employee of F. Hoffmann-La Roche e Miriam Adamcova PS has received research grants and speakers’ honoraria from Glaxo Smith Kline and research grants, speakers’ honoraria and consultancy fees from F. Hoffmann-La Roche e Patricia Schlagenhauf None e Patrick Smith None e Stephen Toovey
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Comparative benefit of malaria chemoprophylaxis modelled in United Kingdom travellers* Stephen Toovey a,*, Keith Nieforth b, Patrick Smith b, Patricia Schlagenhauf c, Miriam Adamcova d, Iain Tatt d, Danitza Tomianovic d, Gabriel Schnetzler d a
Pegasus Research, Basel, Switzerland d3 Medicine, Parsippany, NJ, USA c University of Zurich Centre for Travel Medicine, WHO Collaborating Centre for Travellers’ Health, Institute for Social and Preventive Medicine, Zurich, Switzerland d F. Hoffmann-La Roche, Basel, Switzerland b
Received 6 March 2014; received in revised form 30 July 2014; accepted 7 August 2014
Available online 28 September 2014
KEYWORDS Mefloquine; Atovaquoneproguanil; Doxycycline; Chloroquine; Prophylaxis
Summary Background: Chemoprophylaxis against falciparum malaria is recommended for travellers from non-endemic countries to malarious destinations, but debate continues on benefit, especially with regard to mefloquine. Quantification of benefit for travellers from the United Kingdom (UK) was modelled to assist clinical and public health decision making. Methods: The model was constructed utilising: World Tourism Organization data showing total number of arrivals from the UK in countries with moderate or high malaria risk; data from a retrospective UK Clinical Practice Research Datalink (CPRD) drug utilisation study; additional information on chemoprophylaxis, case fatality and tolerability were derived from the travel medicine literature. Chemoprophylaxis with the following agents was considered: atovaquone-proguanil (AP), chloroquine with and without proguanil (C P), doxycycline (Dx), mefloquine (Mq). The model was validated for the most recent year with temporally matched datasets for UK travel destinations and imported malaria (2007) against UK Health Protection Agency data on imported malaria. Results: The median (mean) duration of chemoprophylaxis for each agent in weeks (CPRD) was: AP 3.3 (3.5), C P 9 (12.1), Dx 8 (10.3), Mq 9 (12.3): the maximum duration of use of all regimens was 52 weeks. The model correctly predicted falciparum malaria deaths and gave a robust estimate of total cases e model: 5 deaths from 1118 cases; UK Health Protection Agency: 5 deaths from 1153 cases. The number needed to take chemoprophylaxis (NNP) to
* The abstract of this paper was presented as a poster at the 8th European Conference on Tropical Medicine and International Health in Copenhagen, Denmark, September 10e13, 2013. * Corresponding author. E-mail address: [email protected] (S. Toovey).
http://dx.doi.org/10.1016/j.tmaid.2014.08.005 1477-8939/ª 2014 Published by Elsevier Ltd.
Benefit of malaria chemoprophylaxis
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prevent a case of malaria considered against the ‘background’ reported incidence in non-users of chemoprophylaxis deemed in need of chemoprophylaxis was: C P 272, Dx 269, Mq 260, AP 252; the NNP to prevent a UK traveller malaria death was: C P 62613, Dx 61923, Mq 59973, AP 58059; increasing the ‘background’ rate by 50% yielded NNPs of: C P 176, Dx 175, Mq 171, AP 168. The impact of substituting atovaquone-proguanil for all mefloquine usage resulted in a 2.3% decrease in estimated infections. The number of travellers experiencing moderate adverse events (AE) or those requiring medical attention or drug withdrawal per case prevented is as follows: C P 170, Mq 146, Dx 114, AP 103. Conclusions: The model correctly predicted the number of malaria deaths, providing a robust and reliable estimate of the number of imported malaria cases in the UK, and giving a measure of benefit derived from chemoprophylaxis use against the likely adverse events generated. Overall numbers needed to prevent a malaria infection are comparable among the four options and are sensitive to changes in the background infection rates. Only a limited impact on the number of infections can be expected if Mq is substituted by AP. ª 2014 Published by Elsevier Ltd.
1. Introduction Falciparum malaria is a progressive and potentially lethal disease in patients who do not possess some degree of preexisting immunity to Plasmodium falciparum, the causative parasite; such immunity is usually acquired through having grown up in, and having continued to reside in, a malaria endemic region [1]. Thus, most travellers from developed countries will be at elevated risk of serious and potentially fatal illness should they visit a malaria endemic region. Emigrants from malarious regions settled in non-malarious countries lose protective immunity over time, and hence are at increased risk of clinical malaria should they visit malarious destinations, typically upon making a return visit to their countries of origin. Settled immigrants do however retain some residual semi-immunity and are less likely to die from malaria than non-immune travellers [2]. Antimalarial chemoprophylaxis is accordingly recommended for travellers from malaria free countries who visit malarious regions, to prevent development of acute malaria and its complications, including severe disease and death [3]. All medication is associated with the risk of developing adverse events (AEs), and these risks are quite well characterised for the antimalarial chemoprophylactic agents in current use: mefloquine, atovaquone-proguanil, doxycycline, chloroquine with and without proguanil [4], however, to enable a more complete assessment of the benefit-risk ratio for antimalarial chemoprophylaxis, quantification of benefit would be helpful. To this end we have modelled the benefits of chemoprophylaxis for travellers from the United Kingdom visiting moderate and high-risk malarious destinations. As travellers to low-risk malaria destinations are often recommended stand-by emergency medication rather than chemoprophylaxis, we excluded such destinations from our datasets [5].
2. Materials and methods The model attempts to track the flow of travellers from the United Kingdom to moderate and high-risk malaria
destinations in calendar year 2007, the latest year for which complete data sets for all model variables were available, and to assess the benefit conferred by the use of chemoprophylaxis. The data sources utilised to populate the model are detailed below. The numbers of travellers at travel related risk of malaria exposure were obtained from the United Nations World Tourism Organization (UNWTO) dataset, “Data on Outbound Tourism (2012)” [6]. Destination countries were then cross referenced to country risk category from the US CDC malaria risk tables [7]. For the purposes of this model, countries on the CDC list were reclassified by a malariologist as high, low, or no risk destinations for malaria. In the case of countries such as South Africa, which are mostly malaria free, but which do contain only localised high risk malarious regions, the risk for the whole country was set to ‘no risk’ in order to not overinflate “high risk” exposure. To ascertain the number of UK travellers who sought advice and were assessed by health care professional prior to departure, numbers were obtained from those reported in a survey of departing passengers conducted in 2003 at Heathrow Airport, London, UK, and from the results of a field study of UK travellers [8,9]. The allocation of travellers to each of the four chemoprophylactic drug groups, mefloquine, atovaquoneproguanil, doxycycline, chloroquine and proguanil was determined from the results of a separate study by Blo ¨chliger et al. of prescribing patterns in UK general practice, conducted using the UK Community Practice Research Database (formerly known as the UK General Practice Research Database) [10]. The split between agents, derived from the absolute number of travellers prescribed each chemoprophylactic agent is as follows: mefloquine 15.3%, atovaquone-proguanil 65.6%, doxycycline 14%, and chloroquine with and without proguanil 5.1%. Malaria infection and death rates in UK travellers for the calendar year 2007 were obtained from published UK Health Protection Agency data [11]. The number of reported cases of malaria occurring in UK users of each chemoprophylactic agent was based upon the analysis of
728 Zuckerman et al., which also reported for the calendar year 2007 [12]. Likely AE rates associated with the use of each of the chemoprophylactic agents of interest were obtained from a double-blind, randomised study of Swiss, German and Israeli travellers, thought to be of acceptably similar profile to UK travellers, an equivalent UK study not being available [4]. Mild AEs were not included in the model, only those categorised as either moderate, requiring medical attention, or leading to cessation of usage: given the seriousness of malaria, mild AEs were thought to be generally tolerable and not disruptive of travel. In addition, as the percentages applied were obtained from a clinical study, a setting in which AEs are solicited and which may overestimate the ‘real world’ AE incidence, a further analysis of the AE burden was undertaken. This second analysis considered only those AEs that required medical attention. For both analyses, the AE rate for each regimen, regardless of infection status, was multiplied by the NNP infection, generating the AE burden for each case of malaria prevented, for each regimen, this number being a measure of the benefit-risk ratio for each agent. Overall mortality was taken as published by the UK Health Protection Agency [11], and was applied to users of chemoprophylaxis, and the adjusted total of non-users, to generate the number of fatalities for each of these two groups; these were then summed to provide the total number of malaria deaths. The model was a decision-tree type model, implemented in Microsoft Excel. The model incorporated data-derived event probabilities, including the number of individuals receiving prophylaxis, infection rates with and without prophylaxis, infection-related morbidity and mortality, and drug-related adverse event rates. The model was populated with the actual measured or reported values from the abovementioned sources, to generate a base case scenario, with the following inputs entered into the model: the total number of UK travellers to risk destinations was set at 1,768,210 [6], with the fraction of this total using chemoprophylaxis set at 0.78 [9]; the fraction of chemoprophylaxis users taking each of the four regimens was: mefloquine 0.153, atovaquone-proguanil 0.656, doxycycline 0.14, chloroquine with and without proguanil 0.051 [10]; the fraction of travellers not using malaria chemoprophylaxis because they had been advised against usage was set at 0.37 [8]. The infection rate amongst users of each of the four chemoprophylactic regimens was calculated from the known number of cases in the UK and published utilisation data, applying the usage ratios derived from the Blo ¨chliger drug utilisation study [10e12]. The infection rate amongst non-users of chemoprophylaxis was adjusted for those deemed not at actual risk of becoming infected [8]. Infections per group were summed to provide the total number of cases. Infection rates per person-week of exposure were calculated for each chemoprophylaxis regimen, being the quotient of the total number of infections calculated for that regimen, and the product of the total number of regimen users and mean duration of usage. For each of the four agents, the number of travellers that would need to be prescribed the agent to prevent one death from malaria, and the number needed to prevent one
S. Toovey et al. clinical malaria infection were calculated, being the reciprocal of the difference in rates with adjusted nonusers of chemoprophylaxis, expressed as NNP death and NNP infection respectively. Although the adopted approach is reasonably ‘grounded in reality’ inasmuch as the model was based on real world data, there are nevertheless likely to be differences between the four chemoprophylaxis groups with respect to their destinations, as well as other unmeasured variables, including variations in background malaria intensity, with malaria transmission rates not being geographically uniform within countries. Additionally, the proportion of travellers not using chemoprophylaxis subsequent to taking professional advice could vary between groups and destinations. We therefore also examined the impact of varying rates of malaria infection on the NNP for each agent, by generating a range of values that may be more reflective of the risk spectrum within destination countries: a range of values from 80% to 200% of the actual estimated infection rate in non-users of chemoprophylaxis deemed at risk of infection was utilised. A further sensitivity analysis was undertaken to examine what the impact of increasing and decreasing mefloquine’s share of total chemoprophylactic prescriptions might have on the total predicted number of malaria infections and deaths. We additionally investigated the impact of a higher malaria death rate in infected travellers, examining what the impact on mortality would be if the UK rate were increased to the 3% mortality reported by Germany for nonimmune tourists for the period 1993e2004 [13], as well as a higher rate of 4% that might reflect likely level of care in some lesser experienced centres.
3. Results The model correctly predicted the total number of malaria deaths in the UK in 2007, yielding a result of five deaths, which matched exactly the official HPA statistic. The model predicted the total number of cases to be 1118, which is a very close estimate (97%) of the 1153 actual malaria infections recorded by the HPA in 2007. The NNP infection and NNP death for each of the four agents, based upon actual drug prescription patterns within the UK, are presented in Table 1; the impact of changes in the malaria transmission, or ’background rate’ on NNP infection and NNP death are similarly included in Table 1. As would be expected, both of these numbers fall as the background rate increases, and vice versa. Altering the prescription pattern within the model, by swapping mefloquine and atovaquone-proguanil usages, had no impact on the number of predicted deaths but did yield a 9.8% increase in the number of infections, from 1118 to 1228. The impact of substituting atovaquone-proguanil for all mefloquine usage, i.e. setting mefloquine usage to zero and atovaquone-proguanil to 80.9% of total usage, was similar, with predicted deaths remaining at 5, and predicted infections decreasing slightly (2.3%) from 1118 to 1092. These results are summarised in Table 2. Increasing the mortality rate from the actual observed rate in the UK (<1%) to 3% and beyond resulted in a large increase in deaths amongst non-users of chemoprophylaxis,
Benefit of malaria chemoprophylaxis
729
Table 1 Number of travellers that need to be prescribed chemoprophylaxis to prevent one malaria infection (NNP infection) and one death (NNP death) as a function of the background malaria rate in travellers not using antimalarial chemoprophylaxis. 80%
Mefloquine Atovaquone-proguanil Doxycycline Chloroquine proguanil
100% baseline
120%
150%
200%
NNP death
NNP infection
NNP death
NNP infection
NNP death
NNP infection
NNP death
NNP infection
NNP death
NNP infection
75744 72718 78882 80005
329 316 342 347
59973 58059 61923 62613
260 252 269 272
49637 48319 50965 51432
215 210 221 223
39441 38604 40275 40566
171 168 175 176
29382 28915 29843 30002
128 125 130 130
and consequently a significant impact on NNP death: the NNP death falls to below 9000 for all regimens if the higher mortality rate of 3% is applied. These results are presented in Table 3. Infection rates per person week of exposure for each agent were as follows: mefloquine 0.0000128, atovaquoneproguanil 0.00000897, doxycycline 0.0000271, chloroquine with and without proguanil 0.0000264. The model revealed mefloquine and atovaquone-proguanil to have roughly similar overall infection rates, while the infection rates for users of doxycycline and chloroquine with and without proguanil were similar and approximately two to three times those seen with atovaquone-proguanil and mefloquine. The AE burden as number of travellers affected per malaria case prevented, considering medication cessation, moderate AEs, and AEs requiring medical attention is as
follows: chloroquine with or without proguanil 170, mefloquine 146, doxycycline 114, and atovaquone-proguanil 103.; the AE burden considering just those AEs requiring medical attention is substantially lower: chloroquine with or without proguanil 33, mefloquine 29, atovaquoneproguanil 18, doxycycline 16 (Table 4).
4. Discussion Despite the utilised data having been drawn from different sources, the model provided remarkably accurate predictions for the number of deaths and infections, and hence we believe useful NNP infection and NNP death statistics. It was interesting to note that there was little difference between the four agents studied in terms of their NNP infection and NNP death results.
730
S. Toovey et al. way of comparison, the number of individuals aged greater than 65 years old needed to be vaccinated (NNV) against influenza to prevent one hospitalisation is estimated to be 777; to prevent one hospitalisation for invasive pneumococcal disease in those above 65 years of age, the pneumococcus vaccine NNV is estimated to be 3333 [14]. It should also be borne in mind that the UK has a particularly good record in treating malaria, with a very low mortality rate [11]. In countries with higher mortality, the NNP death would accordingly expected to be lower: substituting the UK’s 0.43% reported mortality with that of the 3% reported by Krause et al. for Germany, the NNP death for mefloquine would drop from 59973 to 8676 [13]. Of interest was the impact on NNP of even a slight (20%) increase in the ‘background’ malaria rate. As the actual risk faced by any individual traveller can never be known with certainty and varies within countries [15], some travellers will be at higher risk, reducing the NNP infection and NNP death for further; Table 1 attempts to illustrate the impact on travellers of these variations. The AE rates utilised are those reported by Swiss, German and Israeli travellers for subjectively moderate AEs, AEs requiring medical attention, and withdrawals, with the total rates for each regimen being: chloroquine with and without proguanil 62.7%, mefloquine 56.2%, doxycycline 42.5%, atovaquone-proguanil 40.8% [4]. The AE rates applied for events requiring medical attention were chloroquine with and without proguanil 12.4%, mefloquine 10.5%, doxycycline 5.9%, atovaquone-proguanil 6.7% [4]. By way of context, moderate to severe AE rates reported in a placebo controlled head to head comparison of atovaquone-proguanil against mefloquine were 10% for
Table 2 Impact of altering mefloquine and atovaquoneproguanil prescription share on estimated number of malaria cases and deaths. Prescription share
Actual share: Mefloquine 15.3% Atovaquoneproguanil 65.6% Reversed share: Mefloquine 65.6% Atovaquoneproguanil 15.3% Without mefloquine: Mefloquine 0% Atovaquoneproguanil 80.9%
Estimated total deaths
Estimated total infections
No.
% Change
No.
% Change
5
e
1118
e
5
0
1228
þ9.8%
5
0
1092
2.3%
The Number Needed to Prevent one case of malaria (NNP infection) for the UK of 260e272 (i.e. for every 260e270 users of malaria chemoprophylaxis, one case of malaria is prevented) should provide reassurance to prescribers, given the severe and rapidly progressive nature of falciparum malaria in non-immunes such as travellers, and the real risk of permanent and serious sequelae and death. This NNP infection figure argues strongly for chemoprophylaxis, especially given the conservative nature of the model. By
Table 3 death).
Impact of varying mortality rate in infected travellers on deaths and number needed to prevent one death (NNP Mortality rate
a
No chemoprophylaxis Mefloquine Atovaquone-proguanil Doxycycline Chloroquine proguanil a
0.434% (current UK rate)
1%
NNP death
Deaths
NNP death
Deaths
NNP death
3% Deaths
NNP death
4% Deaths
e 59973 58059 61923 62613
4.254 0.145 0.123 0.234 0.004
e 26028 25198 26874 27174
9.803 0.333 0.284 0.539 0.010
e 8676 8399 8958 9058
29.409 1.000 0.852 1.616 0.030
e 6507 6299 6719 6793
39.212 1.334 1.136 2.155 0.040
Adjusted for non-use on advice.
Table 4 Adverse event (AE) burden for each case of P. falciparum prevented by chemoprophylaxis, for moderate AEs, AEs requiring medical attention, and cessation of use; and for AEs requiring medical attention only.
Chloroquine proguanil Doxycycline Mefloquine Atovaquone-proguanil
Number needed to prevent one infection
Total AE rate %
Total AEs/ infection prevented
AEs requiring medical attention rate %
AEs requiring medical attention/infection prevented
272 269 260 252
63 43 56 41
171 114 146 103
12 6 11 7
33 16 26 18
Benefit of malaria chemoprophylaxis atovaquone-proguanil, and 19% for mefloquineq [16]. The different settings and methods make comparisons difficult, but both studies do note the association of neuropsychiatric AEs with mefloquine. A Cochrane Collaboration review of chemoprophylactic AE rates found the highest overall AE rate in chloroquine with and without proguanil users, but noted the incidence of neuropsychiatric AEs to be highest in mefloquine users, with reports of mefloquine neurotoxicity having been reviewed elsewhere [17,18]. The overall burden of AEs associated with chemoprophylaxis use (Table 4) and the rarity of serious AEs associated with chemoprophylaxis, as observed in a Cochrane Collaboration review, point to a favourable benefit risk profile for chemoprophylaxis [18]. With respect to mefloquine specifically, a very large study by Steffen et al. reported the incidence of serious neuropsychiatric AEs in European travellers at 1 per 10,600 travellers, also indicating the rarity of such events [19]. In addition, a recent retrospective data analysis of the UK general practice research database suggests a similar risk of neuropsychiatric disorders for users and for non-users of anti-malarial chemoprophylaxis [20]. It was this relative infrequency of serious AEs that prevented their inclusion in the model. It may be that the estimates obtained for the AE burden in this model overestimate the true incidence, as they are based upon a placebo controlled study of travellers, in which a 16% incidence of placebo associated AEs was reported in the weeks prior to travel [4]. This model has been additionally utilised to estimate the effect of substituting mefloquine completely by atovaquone-proguanil. Such a complete substitution would results in only a minimal improvement of outcomes, however. There are some obvious limitations in this model: one being that the last year for which contemporaneous data sets could be obtained was 2007. Another would be that the datasets used were disparate in source, and were themselves samples, apart from the UNWTO travellers’ destination data. The model also takes no account of the benefits obtained from personal and environmental protection measures, and the number of travellers who take chemoprophylaxis despite not being at actual risk of malaria [8,9,21e24]. Mitigating to some extent the heterogeneity of the data sources are the conservative decision to classify countries with limited geographic malarious ranges as non-malarious, and the possible under-reporting of malaria, although the UK is acknowledged to have a robust and reliable surveillance system [25]. Travellers who fall ill with malaria while abroad will also not have their data captured for use in this model, with greater under-reporting more likely in nonusers of chemoprophylaxis. Additionally, increasing awareness by the travelling public of the risks posed by malaria might have led to a higher proportion undergoing pre-travel assessment in 2007, compared with that reported in the 2003 airport survey [9]. Another weakness of the model is that it assumes travel destinations, traveller type (tourists, VFR et al.) and itineraries are the same for all four agents. This is unlikely to be the case, given the differing costs and contra-indications for these agents. A possible clue to the nature of these differences is the differing median durations of use for
731 each, as reported from the UK CPRD study, with atovaquone-proguanil having a shorter median duration of use than mefloquine: 3.3 versus 9 weeks respectively [10]. The duration of the post malaria eexposure prophylaxis of an additional 3 weeks with mefloquine compared to atovaquone-proguanil does not sufficiently explain the difference. One may speculate it reflects different types of travel, with the shorter duration travel being more compatible with resort type holiday travel, and longer duration travel more compatible with backpacking and adventurous travel, and thus possibly higher risk for malaria. The higher cost of atovaquone-proguanil might also make it less likely to be used by younger travellers or VFR travellers with constrained budgets, but favoured by more affluent travellers able to afford the extra convenience of atovaquone-proguanil’s limited post-exposure use. Whatever the explanation, it seems reasonable that the actual malaria risk faced by travellers could be different for the four agents, tempering direct comparisons between the different agents when assessing benefits. Nevertheless, altering the usage split between agents has no impact on the number of deaths, and very little impact on the number of predicted infections. The model correctly predicts the number of malaria deaths in the UK and provides a robust and reliable estimate of the number of imported malaria cases in the UK. Measures of the protective benefit conferred by all four commonly prescribed chemoprophylaxis agents, expressed as NNP to prevent one infection or one death, are very similar for mefloquine, atovaquone-proguanil, doxycycline, and chloroquine with and without proguanil. There appears to be little change in benefit when mefloquine use is substituted by atovaquone-proguanil, and vice versa. The model goes some way to quantifying the benefit-risk ratio of chemoprophylaxis, and may help inform policy on chemoprophylaxis.
Financial disclosure This work was funded by F. Hoffmann e La Roche, Basel, Switzerland. ST is a paid consultant to F. Hoffmann e La Roche, Basel, Switzerland. PS has received research grants and speakers’ honoraria from Glaxo Smith Kline and research grants, speakers’ honoraria and consultancy fees from F. Hoffmann-La Roche. Miriam Adamcova, Gabriel Schnetzler, Iain Tatt and Danitza Tomianovic were employees of F. Hoffmann-La Roche when this research work was undertaken.
Conflict of interest At the time the bulk of this manuscript was written, I was fully employed by F. Hoffmann-La Roche Ltd. As of December 2013, I was no longer employed by F. Hoffman-La Roche Ltd e Danitza Tomianovic Employee of F. Haffmann-La Roche Ltd e Gabriel Schnetzler None e Iain Tatt I am a consultant for Hoffmann-La Roche e Keith Nieforth
732 I am employee of F. Hoffmann-La Roche e Miriam Adamcova PS has received research grants and speakers’ honoraria from Glaxo Smith Kline and research grants, speakers’ honoraria and consultancy fees from F. Hoffmann-La Roche e Patricia Schlagenhauf None e Patrick Smith None e Stephen Toovey
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