Typhoon Haiyan and beyond The recent Super Typhoon Haiyan, the third category 5 typhoon to strike the Philippines since 2010, tore through Tacloban in the province of Leyte and affected about 13 million people; only 4 weeks after Super Typhoon Usagi affected more than 2·7 million people in southern China. With increasing numbers of disasters related to climate change (from 99 in 1980 to 269 in 2011),1 Asia is likely to be hit by more typhoons with stronger intensity in the coming decades. The 2013 World Disaster Report identified access to information and technology as major challenges for community disaster preparedness, survival, and recovery.2 Media coverage of typhoons and their aftermath often focuses on the immediate ravages, injuries, deaths, and economic loss; however, typhoons and hurricanes bring along less visible long-term consequences for health. After major hurricanes and floods, water-borne diseases, such as leptospirosis, 3 can arise from contamination of water and food crops; lack of shelter and population displacement to crowded conditions often leads to a high incidence of chronic respiratory diseases; standing water can serve as a hotbed for mosquito breeding and hence vectorborne illnesses; injuries increase the risks of tetanus; and damaged wires can cause electric shock and fire. While these immediate effects might be recorded and reported, well-organised longitudinal data and comprehensive surveillance information are often limited in low-income settings, and, as a result, information about the longterm physical and mental health consequences of floods for the population is not available to guide evidence-based disaster emergency preparedness and response planning. The Hyogo Framework for Action identified capacity building and www.thelancet.com Vol 382 December 7, 2013

development of disaster healthrisk-resilience policies by national governments for disaster-prone communities as key priorities for action.4 To do so, the research agenda at the community level should identify predictors of and barriers to the ability of households and communities to respond to disaster warnings, and also assess the effectiveness with which information about health responses after a disaster is delivered. Research also needs to explore the best way to organise surveillance data and systems to reduce post-disaster health risks. How to mobilise community volunteers to engage in evidencebased post-disaster health actions remains a major operational challenge for governments, front-line workers, and academics, and gaps in technical knowledge must be tackled.5 We declare that we have no conflicts of interest.

*Emily Y Y Chan, Sida Liu, Kevin K C Hung [email protected] Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China 1


3 4


UN Office for Disaster Risk Reduction. Number of climate-related disasters around the world (1980-2011). http://www.preventionweb.net/ files/20120613_ClimateDisaster1980-2011. pdf (accessed Nov 20, 2013). International Federation of Red Cross. 2013 World Disaster Report. http://www. worlddisastersreport.org/en/ (accessed Nov 17, 2013). McCurry J. Philippines struggles to recover from typhoons. Lancet 2009; 374: 1489. UN International Strategy for Disaster Reduction. Hyogo Framework for Action 2005–2015. http://www.unisdr.org/2005/ wcdr/intergover/official-doc/L-docs/Hyogoframework-for-action-english.pdf (accessed Nov 20, 2013). Chan EYY. Bottom-up disaster resilience. Nat Geosci 2013; 6: 327–28.

Efficacy of antipsychotic drugs for schizophrenia We read with great interest Stefan Leucht and colleagues’ meta-analysis (Sept 14, p 951).1 It is remarkable that the five newest antipsychotics— ziprasidone, aripiprazole, asenapine,

iloperidone, and lurasidone—are at the bottom of the efficacy and all-cause discontinuation figures, although there are no known pharmacological differences to explain these findings. Here, we suggest that they form a subclass of antipsychotics with administration issues that lower total drug exposure. We believe that pharmacokinetics can explain the differences in efficacy of antipsychotics. First, some antipsychotics have characteristics that require more collaboration by patients during administration, which complicates drug regimen implementation in a population where half do not adhere to their treatment. 2 Ziprasidone has to be taken with 500 calories, lurasidone with 350 calories, and asenapine has to melt under the tongue, cannot be swallowed, and cannot be exposed to drinks, food, or smoking for 10 min.3 Moreover, ziprasidone and asenapine require twice daily dosing, another unfavourable factor for implementation.3 Second, titration of iloperidone, ziprasidone, and aripiprazole is challenging in clinical practice— patients have intolerable side-effects before reaching therapeutic doses. In clinical trials with a fixed timepoint at 6 weeks, the titration delay can lower the final score on efficacy and affect results in a multiple-treatments meta-analysis. Furthermore, the lack of personalised titration schedules can lead to early discontinuation. We argue that, apart from clozapine, all antipsychotics could be equally effective if compared using therapeutic blood levels. Regulatory bodies should require these blood concentrations to approve future psychotropics. Comparing values for patients who received personalised medicine would give a better picture of the reality. We declare that we have no conflicts of interest.

*Philippe D Vincent, Edouard Kouassi [email protected]

Victor Kintanar/Demotix/Corbis


Published Online November 23, 2013 http://dx.doi.org/10.1016/ S0140-6736(13)62415-0

Submissions should be made via our electronic submission system at http://ees.elsevier.com/ thelancet/



Faculty of Pharmacy, Université de Montréal, Montréal, QC H3T 1J4, Canada (PDV); Pharmacy Department, Institut Universitaire en Santé Mentale de Montréal, Montréal, QC, Canada (PDV, EK); and Department of Medicine and Medical Specialities, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada (EK) 1



Leucht S, Cipriani A, Spineli L, et al. Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. Lancet 2013; 382: 951–62. Velligan DI, Weiden PJ, Sajatovic M, et al. Assessment of adherence problems in patients with serious and persistent mental illness: recommendations from the expert consensus guidelines. J Psychiatr Pract 2010; 16: 34–45. Taylor D, Paton C, Kapur S. The Maudsley prescribing guidelines in psychiatry, 11 edn. Hoboken, NJ: Wiley-Blackwell, 2012.

In their multiple-treatments metaanalysis1 ranking reported efficacy and tolerability of 15 antipsychotics, Stefan Leucht and colleagues’ tabulated the standardised mean difference (SMD) for all pairwise treatment comparisons and order of efficacy ranking. We have concerns with the limitations of the ranking analysis based on multiple-treatments metaanalysis when the treatment network is sparse, asymmetric, and quality-biased. For example, the SMD for amisulpride (vs placebo) and the majority of treatment comparisons between the 15 antipsychotics (figure 2)1 were based on indirect evidence, rendering impossible verification of the necessary consistency assumptions when comparing any two treatments through a third comparator.2 The results for amisulpride, ranked second best after clozapine, particularly illustrate these challenges. All amisulpride treatment comparisons were missing, except for five trials versus olanzapine (four with reporting bias), six trials versus haloperidol (three with reporting bias), and four trials versus risperidone (one with reporting bias). To derive SMDs for amisulpride, these 15 active-controlled trials were combined with trials sharing a common comparator of olanzapine (63 trials), haloperidol (88 trials), or risperidone (57 trials). Our previous studies suggest the magnitude of SMD decreased significantly with 1874

increased placebo response,3 leading to diminished treatment effect size over time.4,5 It is therefore difficult to interpret an efficacy ranking order based on SMD when comparing and combining studies done in different populations of patients at different time periods, thereby generating inconsistencies, which cannot be assessed. COS has served as a paid consultant for Pfizer, Sunovion US, Memory Pharmaceutical, and Wyeth. OA participated in the Pfizer sponsored study of ziprasidone HCl, and received grant support, funding, or has served as a paid consultant for Janssen-Ortho, Eli Lilly US, Eli Lilly Canada, Novartis, Sepracor US, and Sunovion US. GR has received support from Novartis Canada, Medicure, and Neurocrine Bioscience, did research sponsored by Pfizer, and has received consultant fees from CanAm Bioresearch, and Winnipeg, as well as speaker’s fees from Novartis.

*Cynthia O Siu, Ofer Agid, Gary Remington [email protected] Data Power, Flemington, NJ 08822, USA (COS); and Center for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada (OA, GR) 1





Leucht S, Cipriani A, Spineli L, et al. Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. Lancet 2013; 382: 951–62. Song F, Altman D, Glenny AM, Deeks J. Validity of indirect comparison for estimating efficacy of competing interventions: empirical evidence from published meta-analyses. BMJ 2003; 326: 472. Agid O, Siu CO, Potkin SG, et al. Meta-regression analysis of placebo response in antipsychotic trials 1970–2010. Am J Psychiatry 2013; 170: 1335–44. Kemp AS, Schooler NR, Kalali AH, et al. What is causing the reduced drug placebo difference in recent schizophrenia clinical trials and what can be done about it? Schizophr Bull 2010; 36: 504–09. Chen YF, Wang SJ, Khin NA, Hung HMJ, Laughren TP. Trial design issues and treatment effect modeling in multi-regional schizophrenia trials. Pharmaceut Statist 2010; 9: 217–29.

Authors’ reply Philippe Vincent and Edouard Kouassi make a valid point about the complex pharmacokinetics of some newer antipsychotic drugs. We believe that knowledge of these pharmacokinetics is essential for getting the best results from treatment and that these issues might be under-recognised in clinical practice. For example, even though the

majority of the trials included in our meta-analysis1 were phase 3 studies with strict protocols, it cannot be ruled out that ziprasidone or lurasidone were sometimes taken without sufficient food. To check plasma levels can be a good idea, but these are expensive and subject to substantial interindividual variability. We agree with Cynthia Siu and colleagues that the validity of a multiple-treatments meta-analysis increases the more the network is connected. In an ideal world all treatments would have been compared directly, but this will never be the case across 15 antipsychotic drugs. The value of and need for indirect evidence is greater in the absence of direct evidence (ie, randomised controlled trials comparing antipsychotics headto-head).2 Therefore, a sparse network is an incentive for multiple-treatments meta-analysis, not an obstacle. With regard to the amisulpride example, it was reassuring that its efficacy results were consistent with those of previous conventional pairwise meta-analyses.3,4 In the discussion,1 we acknowledged that increasing placebo response is a major concern of current antipsychotic drug trials that might have affected the results of the newest drugs. We addressed such potentially confounding effects by multiple sensitivity and metaregression analyses (among others by excluding placebo-controlled studies or haloperidol-controlled studies, and by implementing publication year in the model), but there might be other ones. Moreover, there is evidence that increasing placebo response has been paralleled by an (albeit less pronounced) increase in drug response, which could theoretically attenuate increasing placebo response (see table 2 in Khin and colleagues’ report5). If it were all about publication year, chlorpromazine and haloperidol would have turned out as the most efficacious drugs. The dogma of equal efficacy of antipsychotic drugs was established in 1969,6 but it has never been systematically addressed in a comprehensive way since. Since www.thelancet.com Vol 382 December 7, 2013

Efficacy of antipsychotic drugs for schizophrenia.

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