THEO MURPHY (AUSTRALIA) HIGH FLYERS THINK TANK

Preventative health: Science and technology in the prevention and early detection of disease

University of Sydney (Eastern Avenue Complex), Thursday 6 November 2008

Chair: Professor Kurt Lambeck

Jens Coorssen: A non-scientific aspect; you [Liz Hartland] raised the issue that perhaps the government should institute special requests for funding. I would be very wary about recommending that, as it has all but stifled the Canadian research system since they were instituted about seven years ago: they are broadly seen as unhelpful in terms of actually getting science done.

Liz Hartland: That's interesting because we modelled our comments on the NIH model, which has, I think, 21 calls for particular types of research applications. My impression is – not that I have one of those grants – that they are quite effective in stimulating certain types of research areas. But I will take that on board.

Rohan Williams: I don't want to target your talk in particular, because this point has been made several times today. But I thought just in general, that the new genetic technologies have got a bit of a bad rap. I guess, like any new technology, we think it is going to do a lot of wonderful things. But, in terms of genome-wide association studies [GWA], I think one important aspect is the simplicity of a lot of the phenotypes that have been used to date. If you take something as crude as blood pressure, measure it in 10,000 people and do a GWA, it is not really surprising that you don't tease out a lot of the important genetic determinants of phenotypic variations. So perhaps some thought towards more complex and more sensitive phenotypic descriptors – albeit more complicated ones – might be generally useful in this kind of space.

Liz Hartland: Yes, I think that is a fair comment. I probably should have added into what I wrote up there that we are not just monitoring people's genomes; we are monitoring the microbes that they have. Ideally, we would monitor also their natural flora, because we know that people's natural microbiota influences things like their T-cell receptor repertoire. So we would hopefully monitor other aspects of their health – their immune responses – and therefore get a phenotype out of this information as well. But, yes, it is important to back it up with a phenotype.

Ben Cowie: I think one aspect that has been touched on by all of the presentations today, including many this morning, is that we need to not only come up with novel solutions and devote scientific and technological research to getting insights into these things, but there is also translation from those insights into policy and then translation from policy into practice. We can talk about these sorts of solutions endlessly, but it is not just a question of proving that they are effective; it is then getting that message through to the policymakers who fund these interventions and then finally, getting them on the ground with clinicians using them.

Just taking an example from the area that I have been doing research in, with hepatitis B – despite the CDC recommending for many years now that people who are born in countries with a high prevalence of hepatitis B or greater than 10 per cent – when they did a study looking at the actual testing of people in New York City through clinics that were actually funded partly through this research, less than half of the people born in those countries had ever been tested for hepatitis B. So we can come up with these technological solutions, but I think at least as much effort needs to be given to getting the translation of those answers into practice.

Liz Hartland: I agree. When I talked about the links that we need to make with the policymakers, I should have talked also about those we need to make with the community. So you are right. Health promotion is wrapped up in that, and it is extremely important. At Melbourne University we call that 'knowledge transfer', but at least it is being recognised as an essential part of your research profile as a scientist.

Graham Brown: My comment is on that last point. I think something that not only the National Preventative Health Taskforce but also the Academy can do, is to recognise that we still are a scientifically illiterate country, where people give equal weight to crystal therapy and homeopathic and complementary medicine as to evidence based science, and we have a huge amount to do on that. I am sure that the National Preventative Health Taskforce knows that, but I would think the Academy could do a lot. If we look at the successful interventions with seat belts, crash helmets and tobacco, it has usually been not only with biomedical research – they have been part of it – but mainly civil society, law and politics. That is the sort of group that I think the Academy can assist the National Preventative Health Taskforce with in bringing to conclusions, particularly even now with the gap between what we know and what actually happens.

Marissa Lassere: Again, this is a general comment. All four groups talked about biomarkers as being an important way forward. I suppose I just want to flag that the statistical validation of biomarkers is in its infancy. A lot of discovery has to take place in that area of research. I think that may well be underestimated by some people who work within this area, and the possibility of false positives looms very highly.

Liz Hartland: I think it is going to need backup testing as well. It cannot be, as you say, at the moment a definitive type of test.

Marissa Lassere: But even the underlying statistics or mathematics of it has not been quite worked out. A lot of research has gone on for the last 20 years, most of it international research, looking at how one validates biomarkers and surrogate endpoints in lieu of clinical endpoints in trials. Work is now being done to suggest that all that has been done in the last 20 years is wrong from a statistical point of view.

Unidentified participant: When is that coming out?

Marissa Lassere: I've published something; get the book entitled Statistical validation of surrogate endpoints [The evaluation of surrogate endpoints (Statistics for biology and health)]. It was written [edited] by Marc Buyse, Tomasz Burzykowski and someone else [Geert Molenberghs]. Two of these people are investigators on one of my NHMRC grants where we are looking at how one statistically validates biomarkers now using synthetic data. We know what the gold standard is, so we know what the answers are supposed to be. So we are going to go back and look at the statistical methods we have developed and recommended; do they find the signal that they are supposed to find.

Ian Hickie: I made a comment earlier when an argument almost broke out about what evidence is. I think one difference in our area is how much evidence is good enough evidence when you want to put the evidence into practice. The worst thing from a political or translational point of view is to put something up and have someone say, 'Oh no, the evidence isn't good enough' – whether it is folate supplementation in food or a recommendation for fish oils, dietary changes or a certain amount of exercise. Often in the science community, with narrowly defined things from RCTs [randomised controlled trials] or a narrowly defined Preventative Healthcare Taskforce, somebody is not yet convinced it is good enough in a particular way.

I think one of the real potential advantages of the Preventative Health Taskforce is national agreements: 'At what point do you act?' We have seen this in tobacco, road crashes and everything else – particularly in complex situations. You need to make clear decisions at the point at which you decide the evidence is good enough. It will continue to develop as you then implement the public policy that you look at.

We get opportunities which are not always based on 'now the science is ready'. Personally, I had the opportunity with Beyondblue. It was a national thing: 'What should we do?' We actually created what became the perinatal depression program around then. There was a lot of resistance to doing anything perinatal because people did not like the idea that screening had not yet shown that predicting postnatal depression was a justified intervention. But that missed the point that there was an opportunity to take a better look at maternal mental health. We did the same thing in a school environment. You can create programs where the science is good enough to engage in an area, and that is often very acceptable to the society in which we live, which you then have continuing evidence from.

So I hope that with these sorts of issues there is a better use of evidence in the particular way that interacts with social policy. It is not always that the community has to be protected. It can be engaged in the discussion if there is a commitment to the continuation of that kind of evidence.

I was interested in Kurt's response to somebody else: 'So you are about to do something to me without the evidence.' Perhaps you would like to comment. How much evidence? As long as you have enough information.

Kurt Lambeck: The question was: how much evidence? But to do something on the basis of no evidence, as it was put at that moment, I think is untenable; to my mind, it is not on.

Ian Hickie: I think specialists in fields are often in danger of getting no evidence or particular niceties about the evidence that miss the point and really miss opportunity. There is opportunity out there now in the world around diabetes, obesity and exercise. What are we going to say? We are being asked to say it. There are opportunities in the alcohol area which have been there a while. And even though for example, there is a J-shaped curve with mental health – not drinking at all is actually bad for your mental health and drinking a little is good – but, if you get into some sets of arguments, you can miss the opportunity in certain kinds of areas. I would be interested in people's wider notions of how the Academy and thinkers in the area might contribute in a more realistic way to the social policy and inform community debate.

Unidentified participant: Just to comment on that. It is not about not having evidence. The example I can think of is revised urban planning to create opportunities for people to move, to exercise, like having cycle paths and limiting cars. There was a nice picture from Paul Zimmet this morning where cyclists had priority on roads. These things would clearly increase exercise in people. Actually, there is good evidence that increasing the amount of physical activity and exercise people do, has health effects in various forms. It is not that there is no evidence but, of course, you can't say, 'Oh, now we'll restructure Melbourne' – and not do it in Sydney – 'and have a randomised trial; we'll observe it for the next 100 years and maybe then we will have a national policy later on.'

These are things that typically you can't test in a randomised clinically controlled trial, so we don't have hard evidence. But they are still good ideas and there is a lot of underlying science, and we should do them; that is the point. So the evidence criterion can be a barrier to actually improving things if it is not done properly.

Alex Barratt: Following up on the evidence issue, I think that the US Preventive Services Taskforce has a really nice approach to this – we could do a lot worse than to adopt their approach – which is to look at the benefits and the harms of the possible options that you are evaluating for whatever the particular decision is that you want to make. If the benefits clearly outweigh the harms, then you go ahead and do it. If you are looking at something like putting in a cycle path where the harms to health are going to be fairly minimal – leaving aside the bike accidents and stuff – but, as you say, we know that exercise is good for people, then you don't require level A evidence. Just get on and do it. But, if it is a finely balanced thing such as mammography screening where there are benefits but there are also harms, you do need randomised trial evidence before you go ahead and do that.

Liz Hartland: Or in the development of new vaccines and immunotherapeutics, where there is potential for great harm.

Alex Barratt: Yes. I think you have to have a moving standard of the amount of evidence that is required, depending on what the condition is. We are only a small country, but the US Preventive Services Taskforce has gone a long way down this road and I think there are lessons for us there.

The second thing though that I really wanted to say, before we got on to this evidence discussion, was to put in a plug for Geoffrey Rose and Alex Wood's group, who said that this is really about social problems. Yes, you can achieve a bit in terms of public health and preventative medicine if you target individuals and try to change them; but, by and large, you achieve much more if you try to shift the whole population. I think that having this preventative taskforce is a fantastic opportunity, and we really don't want to miss that opportunity to do the big picture things that make the whole of the population more healthy rather than testing and labelling a small proportion of the population and trying to intervene with them.

Paul Korner: I'd like to make just a general point about the program. Shall I do that now?

Kurt Lambeck: It you would like to, yes.

Paul Korner: I have absolutely no quarrel with the four groups of medical conditions that have been selected, but one of the real omissions in the program is the topic of cardiovascular disease, because it is one of the major health problems. In many ways it's a sort of funny historical thing, thanks to organisations like the Cardiovascular Institute at NIH and the National Heart Foundation in Australia, in areas like hypotension and atherosclerosis, we really aren't in bad shape. But that doesn't really mean that there isn't still an enormous amount that can be done, both on the preventative side and with the prevention of complications. I have enjoyed the program today; but, if we are thinking of doing a symposium on preventative medicine again, that really should be one of the things that are included. We would find then that it has more in common with some of the mental diseases than psychiatrists probably realise and it would give some of this sort of collaborative research a bit of a kick along.

Harriet Hiscock: There are just a couple of things. I think it would be great to have some policy people here next year. I have been working with state governments, and they don't really understand research in the health policy department and I don't expect them to. It is our job to educate them. Getting them along to forums like this, that's the best way to start getting your ideas adopted into policy. The other thing is that we think the RCT is the gold standard. We're trying to convince some of our departments to do staged rollouts of intervention and to do an RCT that way. It has been two years in the making, but I think we are slowly getting towards it.

Adam Elshaug: Appreciating that today is about science and technology and it is also about prevention, some of our key note presenters this morning have said that a lot of the determinants for health are social determinants. As has just been mentioned by Alex Barratt, true prevention in, say, mental health – and I am not an expert in mental health; just looking at ever-increasing work hours and how they might be contributing to anxiety or family breakdown and therefore to mental health – true prevention would mean that those people are never seen in the clinics of Ian and Nick. But Ian and Nick and everyone else in their respective areas in this room can contribute to the policies that may ameliorate or address those problems at the social determinant level. I think Bruce Armstrong had an important point this morning in his talk where he identified primary prevention, secondary prevention and then what might be considered alternative tertiary care. If the publications and recommendations from today could be put under those headings, I think that would be a useful contribution for the audience that ends up reading them. Thank you.

Jeffrey Craig: My comment is that there is another group of people to invite to the party: patient advocacy groups. For example, there are a lot of good genetic support networks. Overseas, patient advocacy groups are becoming more and more involved in policy making and research agendas. I wonder whether any of the Academy staff could comment on their involvement.

Kurt Lambeck: I just want to make a general comment. What we are aiming to do here is to find out what the important issues are in the science. The subsequent steps depend very much on the final recommendations that come out of this process. Reports in the past have finished up with government or wherever we think they need to go and often actions will follow out of that. I don't think it is our purpose here today to try to solve all the problems; we are just trying to understand what the problems and issues are. So we have a somewhat more limited aim for today, I think.

Sue Skull: I want to respond very briefly to two earlier comments. The first is about the US Preventive Services Taskforce, which is modelled on the Canadian model, so it has been around for a fair while. I think it is a really important way to go also here in Australia, but I do not think it can be separated from the very important issue of translating what are essentially policy statements into actual changes in practice. You still can't make those changes without active health promotion and ongoing evaluation of those promotions.

My second point is to reiterate what Harriet [Hiscock] said on the importance of interface between researchers and policymakers. We at Menzies [School of Public Health, Northern Territory] have just entered into a three-year partnership with the Northern Territory health department to provide research support and education. It's proving to be a very exciting and fruitful relationship across a number of levels, particularly when it comes to rolling out changes in policy, which otherwise may not have been evaluated correctly, and just educating across the board. We have shown managers and policymakers the basics of research and how to interpret it.

Alex Brown: I'll be quick. The discussion around translation and engagement with policy and policy changes is an incredibly complicated discussion because, to get evidence into a policy, there's no natural sequence, no logical solution and no practical way that you can get it done. Evidence alone won't lead to policy. If we knew how policymakers thought, it would make our job a lot easier to sell it to them.

The classic example is Aboriginal health. Most policies that have been directed around Aboriginal health over the last 10 to 20 years have had absolutely no evidence whatsoever. The way we do it is that we try to come up with an issue that is really important and then pitch it to the right person who might be interested and who then might take it to the other person who might be interested, who will then tell you that it's probably worthwhile. They ask, 'How much money do you need?' You tell them how much money you need and they say, 'Oh, well I don't think so.' Usually you need to know the right person who will advocate on behalf of you and the issue. So I think our discussion about engaging with policy has to be, over time, a little bit more sophisticated, because policymakers don't necessarily listen to evidence, even if it's given to them on a plate. That's just a comment.

Kurt Lambeck: I think you are making a couple of assumptions. One is that you think policymakers think and the other one is that they listen. But I take the point. This is something that we are acutely aware of. We have our own channels that we use when opportunities arise. Rather than having a formal process for doing these things, we tend to use our own network to bring issues up. One of the mechanisms that I have mentioned several times already is through the Prime Minister's Science, [Engineering and Innovation] Council, for example; that is one process we do use. But we also do it by addressing issues directly with ministers when we think there is an opportune time to do so. But we don't have a formal process for doing that, because – I agree with you – that wouldn't get very far. I think you've got to jump at opportunities.

Bruce Armstrong: I just thought I'd chip in on this issue of getting research into policy. It can, in fact, work very well. Just to give an illustration, we have here in New South Wales a body called the Population Health Priority Taskforce, which I chair and which has on it other people with quite strong science backgrounds. The initial agenda that we put to the New South Wales Department of Health, which is the auspicing body for this taskforce, was in fact very strongly evidence based; it was based on the best research evidence at the time. The policymakers involved were enthusiastic to take it up and a fair proportion of it has been implemented.

So the key to success really is working directly with the policymakers in two ways: firstly, in formulating the things that need to be researched, and working with the policymakers to do the research so that they are actively engaged in that process, understanding why it is important and contributing their insights. Then it becomes almost natural that what works will go into practice. If you do not have that, then working closely with them in these committee structures and otherwise can achieve a great deal.

Unidentified participant: On this topic of policy or, I guess, influence, which is starting to heat up our discussion, another way of being successful is to bypass the policymakers and go direct to the people – whatever you want to call them: consumers, patients or Joe Blow on the street. Take the example of climate change. How many intergovernmental reports were governments successfully avoiding until the actual community demanded a response? That ended up changing several governments around the world. I think as scientists, if we are really honest about being in the preventative medicine game, we should start being better communicators – I think there are lots of great communicators here today – and start a more focused interaction with people through the media, through grassroots organisations and just through direct communication.

Nick Glozier: Just following on from something someone else said earlier on, I am a bit concerned that this whole process assumes a slightly or overtly technocratic approach to the prevention and early detection of disease. Whilst in my particular area early detection may well be amenable to that, the idea that we have to leave out socioeconomic factors which we know are absolutely vital to tackling and preventing disease, is going to make us look rather detached from the real word. I think that is a concern that this report might have, unless we can build that within a wider matrix, a wider approach.

Unidentified participant: I just want to follow on from that. I think all four speakers had as one of their topics that we needed better data integration and want risk prediction. I think we have to think about what we do not have. Epidemiologists have been good at finding environmental risk factors and genetic epidemiologists have found genetic control of diseases. But what we do not have is a big cohort of people who are measured for both environmental and genetic risk factors. It is one thing linking data back, but we really need to set up studies which are prospective, which are very expensive and long term. But they will allow us to answer some of the questions that we don't know the answers to at the moment.
Unidentified participant: I just want to follow up on that last comment about community engagement and relate it back to health promotion. I earlier mentioned the importance of evaluating health promotion and that must involve feedback from both community and health providers about their attitudes towards those interventions. Immunisation is obviously a really critical area with the rollout of all these new vaccines, but it is equally applicable to other health interventions. Without that feedback, without knowing about community concerns and without information coming back from community and provider, we can't possibly continue to have effective promotions.

Jackie Street: To follow up on that, I think we need better ways of collecting that information.

Unidentified participant: While we are freewheeling, I have a suggestion for the taskforce. There's a thing called a citizens' jury, which I saw used in New Zealand. They did one on breast cancer screening and the policy for it. I just wonder whether we could use the concept of a citizens' jury to get some people off the street. Like they did in New Zealand, you may have to spend a fair bit of time educating them, giving them the information that they need, but then you could really put some structured questions to them. I think that model of a citizens' jury would be a way of collecting some of that community data and feeding it into this process.

Unidentified participant: We found it very effective.

Kurt Lambeck: In listening to the four summaries this afternoon – and keep in mind that I'm hardly an expert; I've never done a course in any of the biological sciences or medical areas in my life – it did strike me that a number of common messages have come across. I wonder whether it is worthwhile or helpful for us to explore and identify those. Is there any point in pursuing that? Let me hear them from you rather than having me state what I understand them to be.

Unidentified participant: Everyone mentioned data linkage.

Kurt Lambeck: Yes, that is obviously a very important one.

Mark Stoové: With regard to data linkage, I think what is really important – this sort of comes back also to that engagement with policymakers and government as well – is the education of those in positions where they can allow data linkage to proceed to really understand the power of linking that data in a case­by­case basis. Having attempted a number of data linkage studies in Victoria, some of which have came off and some of which have not, the lack of understanding of your average public-health public servant is not high in this regard. That engagement with government is really important when presenting ideas around data linkage.

Kurt Lambeck – That's your role to get that message across, isn't it?

Mark Stoové: Absolutely.

Graham Brown: I would emphasise what came up at the end. I think the majority of public health practitioners would believe strongly in the socioeconomic determinants of health and that societal change in changing populations is extremely important. But it was asked that the focus for today be around what science and technology add to that. We don't think it is a substitute, but we're looking for mechanisms by which it can add value to that activity. I don't know whether there is consensus on that.

Ian Hickie: Just picking up on Nick's [Glozier] point, I do not think people are ignoring the socioeconomic, but it is also how science and technology can contribute. One way is through environmental surveillance. Information technology allows people to report about their lives and what is happening. We were discussing in our group recording aspects of their lives and receiving information back so that they are engaged continuously. For example, one that was raised randomly was about excess work hours causing mental health problems; that is commonly believed. All the evidence is to the opposite; underemployment, in fact, leads to mental health problems. But, if it is true that changing work practices and changing ways in which families are structured cause such problems, you can actually record that. Information technology allows people to participate in large studies; they do not have to be always organised from above. We were discussing in our group this thing called '45 and Up' here in New South Wales, where a quarter of a million people choose to join a study and provide information increasingly on line about their lives and what they are doing to stay healthy. In many ways, information technology overcomes many of the barriers created by socioeconomic disadvantage and it also allows continuing environmental surveillance in a changing world.

My comment about the Preventative Health Taskforce is that they tend to react about 40 years later, to state the bleeding obvious. The environments we live in change all the time. People want to know about cannabis usage in relation to mental health or illicit drug usage in relation to mental health. Many of these issues are not solved, but people can provide information about what is happening and what the likely effects are and that information can be used. I think there are really underutilised areas in information technology for environmental surveillance where people participate, provide information and get information back, which they can use.

In the 2020 Summit, the groups that were most in favour of IT were often the most disadvantaged. IT allows rural and remote, indigenous and disabled groups to participate and to provide information, where often they would be excluded. I was discussing with Graham [Brown] earlier that, if you look in the particular regions in which we work, many people would be excluded in India, China and south-east Asia. A lot of the IT and developments that we have talked about, although they might be developed in a developed country, will have very wide application. But there is an issue about using those to engage people. We clearly have a government that is committed to looking at the way in which information technology enables people to live a better life.

Marissa Lassere: I have two comments. First of all, the issue of Journal of Statistical Methods in Medical Research regarding the statistical validation of surrogate endpoints was June 2008. The second relates to data linkage, which again seems to be a theme throughout all four of the groups. It's not only that there are barriers in terms of the government wanting to release the data; part of the problem is the format that the data is in. The databases that we think are nice and pristine and clean and can be extracted for data linkage, I do not think are quite in that state. One thing that needs to be done is that, unfortunately, some resources have to be spent to upgrade the databases that contain the Medicare and in-patient hospital information. At the moment they are ever so slightly dirty and, when you want to do your data linkages, you might not be getting the right answer.

Kurt Lambeck: But that's true in virtually every area of science where the data is generally incomplete and full of errors.

Unidentified participant: It's administrative; that is right.

Kurt Lambeck: That is a common problem.

Unidentified participant: But in some other countries there are national standards – for example, in many European countries. However, even in Third World countries, there is a common standard so that you can actually pool data from Third World states. But here, every hospital has its own standards and they are not even speaking across states. That is a major problem. We have to embark on that standardisation, particularly for quality.

Kurt Lambeck: Yes. That would be a good starting point.

Raina Elley: I think all the groups have talked about data linkage and data collection. We do a lot of it ourselves in New Zealand, linking primary and secondary care data in labs and in pharmaceuticals by unique identifiers. But I think there is also a danger of collecting more and more data and not doing enough with it. So I think it is very important to have prospectively decided how you are going to use the databases. Sure, have them open to other people, but plan where you are going to end up with an intervention that actually changes health outcomes.

One of the things that we are doing in New Zealand is using databases like our predict database, which is web based and primary care based, to collect data which has strict validation rules in data standardisation to try and keep the data clean. At the same time it's used to deliver an intervention which provides electronic decision support around cardiovascular risk and diabetes management, with the primary care physicians using it to manage their patients. We have an incentive to do it to increase the reach of the technology. So it is not only data collection; it has changed the emphasis to intervention as well.

The other thing I was going to say was around mobile phones and socioeconomic status. In New Zealand and probably here too, a lot of lower socioeconomic people do not have a landline any more; they only have mobile phones. Quite a few of the interventions that are being developed now are about changing lifestyle – Robyn Whittaker, who is here, has done a lot of research around using mobile phones for smoking cessation – and we are also developing things such as lifestyle interventions around diet and physical activity. I think that will help to address some of the inequalities with the reach of some of our interventions. When we are thinking about developing interventions, we should always be thinking about whether our effects are increasing those inequalities or addressing them.

Bruce Armstrong: I just want to correct perhaps what is a misapprehension about data and data quality in Australia. We have had standardised health data in Australia now for a number of decades that is collected in a standard way by all state and territory health authorities from all hospitals. They are according to very well regulated standards and quality standards, although they are not perfect.

They are also linked now. Western Australia has an extensive linkage system. There is now an extensive linkage system here in New South Wales and through the National Collaborative Research Infrastructure Scheme that is being progressively spread across the whole country. It is likely that that will bring in some of the Commonwealth data sets, Medicare and the Pharmaceutical Benefits Scheme. Again, none of these are absolutely perfect, but there is an enormous amount that we can do with them now and an enormous amount that we will be able to do with them without further attention to data stance and data quality, which are really quite high in Australia.

Jeffrey Craig: One of the cross-group themes that I think was touched on was technology platforms and resources, for example, a good, possibly even national, biobank or biorepository with standard protocols where all standards could be treated the same or at least with a national agreement about the treatment and storage of samples for optimum downstream analysis and also optimising bioinformatic analysis of, for example, microwave results. I know there a lot of separate camps or groups around the country working on separate analysis methods. In general, Australia seems to be lagging behind the rest of the world in some aspects of bioinformatics. But, if you bring all the bioinformathematicians together, I guarantee that you will have more, and faster, analysis methods coming through.

Kurt Lambeck: If there are no further comments, I will call on John Chalmers to sum up.