The evolution of ways of deciding when clinical trials should stop recruiting
Authors: Peter Armitage
Journal: Journal of the Royal Society of Medicine (2014)

[Based on an interview of Peter Armitage (PA) by Iain Chalmers (IC) on 9 September 2013, in Wallingford, Oxfordshire] IC: You have spent more than half a century thinking about ways of deciding when clinical trials should stop recruiting. I would be surprised if there is anyone else in the world who has comparable experience. I am very grateful to you for being willing to be interviewed about the ways your views have evolved over that time. I have a memory of reading in one of Austin Bradford Hill’s articles on ‘the clinical trial’ that deciding when to discontinue recruitment to a trial often presents a quandary. Assuming that I am remembering his view correctly, do you share it? Can you recall where he wrote it? PA: I don’t know of any specific quotation from Bradford Hill’s writings, but I am sure he would have taken that view, which is certainly true. Curiously, in his expository papers on clinical trials he does not seem to spend much time on matters of trial size, being understandably more concerned about bias in assignment and assessment. The basic quandary is as follows. If the data, however imprecisely, suggest that there is a difference between treatments, the trial may be stopped too early and lead to an imprecise, inconclusive result. Despite the resulting uncertainty, it may be difficult to arrange further trials addressing the same question because of ethical concerns about further use of an apparently poorer treatment. On the other hand, if a trial goes on ‘too long’ it may have allowed too many patients to be treated with an inferior regimen. IC: I believe your interest in ways of deciding when trials should stop recruiting originated in statistical approaches that you had been using in industry. Is that correct? Did the mathematical paper you published in the Journal of the Royal Statistical Society in 1950 relate to your work in industry? PA: Yes. During the war I worked in a Ministry of Supply unit concerned with industrial sampling inspection and quality control, set up as part of the major push on armaments production. I was in the sampling inspection research group (SR17) led by G.A. Barnard. Typical products, such as fuses, were produced in large batches which were inspected by sampling, for example, by taking, say, 30 fuses and classifying them as defective or not. The batch would be failed if there were too many defectives and passed if there were very few. There was a clear advantage in taking an initial small sample and giving a pass/fail verdict if the answer was clear, and adding one or more additional samples in more equivocal cases. The sample size thus depended on the data. Work went on in the UK and USA on variants of this idea, leading to more general strategies of sequential sampling where the progression to larger samples was more continuous, with possible stopping at many stages. The theory was generalized by Abraham Wald, in a report which was sent to us in confidence and the basis of his 1947 book. I worked on various extensions of Wald’s methods, some of which were published later. There was an analogy here with clinical trials, except that if a clear difference in effectiveness between treatments appears early this may lead to early termination on ethical, rather than economic, grounds. After a final year back at Cambridge in 1946–1947 I was signed up for a permanent post in the scientific civil service, at the National Physical Laboratory, Teddington. I knew virtually nothing about medical statistics and was surprised and pleased to be offered a post under Austin Bradford Hill (ABH) in the Medical Research Council’s Statistical Research Unit at the London School of Hygiene and Tropical Medicine, starting December 1947. This came about because Edgar Fieller, my boss at the National Physical Laboratory, and Donald Reid (ABH’s head of epidemiology) commuted to London together from their Surrey suburb, and