Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Doug Altman is active.

Publication


Featured researches published by Doug Altman.


BMJ | 1995

Estimating sample sizes for binary, ordered categorical, and continuous outcomes in two group comparisons.

Michael J. Campbell; Steven A. Julious; Doug Altman

Sample size calculations are now mandatory for many research protocols, but the ones useful in common situations are not all easily accessible. This paper outlines the ways of calculating sample sizes in two group studies for binary, ordered categorical, and continuous outcomes. Formulas and worked examples are given. Maximum power is usually achieved by having equal numbers in the two groups. However, this is not always possible and calculations for unequal group sizes are given.


The Lancet | 2014

International standards for newborn weight, length, and head circumference by gestational age and sex: the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project

J.A. Villar; Leila Cheikh Ismail; Cesar G. Victora; E O Ohuma; Enrico Bertino; Doug Altman; Ann Lambert; A T Papageorghiou; M. Carvalho; Y A Jaffer; Michael G. Gravett; Manorama Purwar; Io Frederick; Alison Noble; R Pang; Fernando C. Barros; Cameron Chumlea; Zulfiqar A. Bhutta; S Kennedy

BACKGROUNDnIn 2006, WHO published international growth standards for children younger than 5 years, which are now accepted worldwide. In the INTERGROWTH-21(st) Project, our aim was to complement them by developing international standards for fetuses, newborn infants, and the postnatal growth period of preterm infants.nnnMETHODSnINTERGROWTH-21(st) is a population-based project that assessed fetal growth and newborn size in eight geographically defined urban populations. These groups were selected because most of the health and nutrition needs of mothers were met, adequate antenatal care was provided, and there were no major environmental constraints on growth. As part of the Newborn Cross-Sectional Study (NCSS), a component of INTERGROWTH-21(st) Project, we measured weight, length, and head circumference in all newborn infants, in addition to collecting data prospectively for pregnancy and the perinatal period. To construct the newborn standards, we selected all pregnancies in women meeting (in addition to the underlying population characteristics) strict individual eligibility criteria for a population at low risk of impaired fetal growth (labelled the NCSS prescriptive subpopulation). Women had a reliable ultrasound estimate of gestational age using crown-rump length before 14 weeks of gestation or biparietal diameter if antenatal care started between 14 weeks and 24 weeks or less of gestation. Newborn anthropometric measures were obtained within 12 h of birth by identically trained anthropometric teams using the same equipment at all sites. Fractional polynomials assuming a skewed t distribution were used to estimate the fitted centiles.nnnFINDINGSnWe identified 20,486 (35%) eligible women from the 59,137 pregnant women enrolled in NCSS between May 14, 2009, and Aug 2, 2013. We calculated sex-specific observed and smoothed centiles for weight, length, and head circumference for gestational age at birth. The observed and smoothed centiles were almost identical. We present the 3rd, 10th, 50th, 90th, and 97th centile curves according to gestational age and sex.nnnINTERPRETATIONnWe have developed, for routine clinical practice, international anthropometric standards to assess newborn size that are intended to complement the WHO Child Growth Standards and allow comparisons across multiethnic populations.nnnFUNDINGnBill & Melinda Gates Foundation.


Trials | 2010

Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal.

David M. Kent; Peter M. Rothwell; John P. A. Ioannidis; Doug Altman; Rodney A. Hayward

Mounting evidence suggests that there is frequently considerable variation in the risk of the outcome of interest in clinical trial populations. These differences in risk will often cause clinically important heterogeneity in treatment effects (HTE) across the trial population, such that the balance between treatment risks and benefits may differ substantially between large identifiable patient subgroups; the average benefit observed in the summary result may even be non-representative of the treatment effect for a typical patient in the trial. Conventional subgroup analyses, which examine whether specific patient characteristics modify the effects of treatment, are usually unable to detect even large variations in treatment benefit (and harm) across risk groups because they do not account for the fact that patients have multiple characteristics simultaneously that affect the likelihood of treatment benefit. Based upon recent evidence on optimal statistical approaches to assessing HTE, we propose a framework that prioritizes the analysis and reporting of multivariate risk-based HTE and suggests that other subgroup analyses should be explicitly labeled either as primary subgroup analyses (well-motivated by prior evidence and intended to produce clinically actionable results) or secondary (exploratory) subgroup analyses (performed to inform future research). A standardized and transparent approach to HTE assessment and reporting could substantially improve clinical trial utility and interpretability.


PLOS ONE | 2014

Choosing important health outcomes for comparative effectiveness research: a systematic review.

Elizabeth Gargon; Binu Gurung; Nancy Medley; Doug Altman; Jane M Blazeby; Mike Clarke; Paula Williamson

Background A core outcome set (COS) is a standardised set of outcomes which should be measured and reported, as a minimum, in all effectiveness trials for a specific health area. This will allow results of studies to be compared, contrasted and combined as appropriate, as well as ensuring that all trials contribute usable information. The COMET (Core Outcome Measures for Effectiveness Trials) Initiative aims to support the development, reporting and adoption of COS. Central to this is a publically accessible online resource, populated with all available COS. The aim of the review we report here was to identify studies that sought to determine which outcomes or domains to measure in all clinical trials in a specific condition and to describe the methodological techniques used in these studies. Methods We developed a multi-faceted search strategy for electronic databases (MEDLINE, SCOPUS, and Cochrane Methodology Register). We included studies that sought to determine which outcomes/domains to measure in all clinical trials in a specific condition. Results A total of 250 reports relating to 198 studies were judged eligible for inclusion in the review. Studies covered various areas of health, most commonly cancer, rheumatology, neurology, heart and circulation, and dentistry and oral health. A variety of methods have been used to develop COS, including semi-structured discussion, unstructured group discussion, the Delphi Technique, Consensus Development Conference, surveys and Nominal Group Technique. The most common groups involved were clinical experts and non-clinical research experts. Thirty-one (16%) studies reported that the public had been involved in the process. The geographic locations of participants were predominantly North America (nu200a=u200a164; 83%) and Europe (nu200a=u200a150; 76%). Conclusions This systematic review identified many health areas where a COS has been developed, but also highlights important gaps. It is a further step towards a comprehensive, up-to-date database of COS. In addition, it shows the need for methodological guidance, including how to engage key stakeholder groups, particularly members of the public.


BMJ | 2011

Inconsistency between direct and indirect comparisons of competing interventions: meta-epidemiological study

Fujian Song; Tengbin Xiong; Sheetal Parekh-Bhurke; Yoon K. Loke; Alex J. Sutton; Alison Eastwood; Richard Holland; Yen-Fu Chen; Anne-Marie Glenny; Jonathan J Deeks; Doug Altman

Objective To investigate the agreement between direct and indirect comparisons of competing healthcare interventions. Design Meta-epidemiological study based on sample of meta-analyses of randomised controlled trials. Data sources Cochrane Database of Systematic Reviews and PubMed. Inclusion criteria Systematic reviews that provided sufficient data for both direct comparison and independent indirect comparisons of two interventions on the basis of a common comparator and in which the odds ratio could be used as the outcome statistic. Main outcome measure Inconsistency measured by the difference in the log odds ratio between the direct and indirect methods. Results The study included 112 independent trial networks (including 1552 trials with 478u2009775 patients in total) that allowed both direct and indirect comparison of two interventions. Indirect comparison had already been explicitly done in only 13 of the 85 Cochrane reviews included. The inconsistency between the direct and indirect comparison was statistically significant in 16 cases (14%, 95% confidence interval 9% to 22%). The statistically significant inconsistency was associated with fewer trials, subjectively assessed outcomes, and statistically significant effects of treatment in either direct or indirect comparisons. Owing to considerable inconsistency, many (14/39) of the statistically significant effects by direct comparison became non-significant when the direct and indirect estimates were combined. Conclusions Significant inconsistency between direct and indirect comparisons may be more prevalent than previously observed. Direct and indirect estimates should be combined in mixed treatment comparisons only after adequate assessment of the consistency of the evidence.


Trials | 2011

The COMET (Core Outcome Measures in Effectiveness Trials) Initiative

Paula Williamson; Doug Altman; Jane M Blazeby; Mike Clarke; Elizabeth Gargon

Why standardise outcomes? The design of new trials would be simplified, the risk of measuring inappropriate outcomes would be reduced, and selective reporting of outcomes less likely. It would be easier to compare, contrast and combine studies in systematic reviews. Core outcome sets would help review authors to present their findings clearly and succinctly, for example within Summary of Findings tables.


Acta Paediatrica | 2007

Evaluation of the Ages and Stages Questionnaires in identifying children with neurosensory disability in the Magpie Trial follow-up study

Ly-Mee Yu; Edmund Hey; Lex W. Doyle; Barbara Farrell; Patsy Spark; Doug Altman; Lelia Duley

Aim: To evaluate performance of the Ages and Stages Questionnaires (full ASQ), and a shortened version (short ASQ), in detecting children with severe neurosensory disability in the Magpie Trial follow‐up study.


BMJ | 2016

External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis : opportunities and challenges

Richard D Riley; Joie Ensor; Kym Ie Snell; Thomas P. A. Debray; Doug Altman; Karel G.M. Moons; Gary S. Collins

Access to big datasets from e-health records and individual participant data (IPD) meta-analysis is signalling a new advent of external validation studies for clinical prediction models. In this article, the authors illustrate novel opportunities for external validation in big, combined datasets, while drawing attention to methodological challenges and reporting issues.


PLOS Medicine | 2014

Red blood cell transfusion and mortality in trauma patients: risk-stratified analysis of an observational study.

Pablo Perel; Tim Clayton; Doug Altman; Peter Croft; Ian J. Douglas; Harry Hemingway; Aroon D. Hingorani; Katherine I. Morley; Richard D Riley; Adam Timmis; Danielle van der Windt; Ian Roberts

Using a large multicentre cohort, Pablo Perel and colleagues evaluate the association of red blood cell transfusion with mortality according to the predicted risk of death for trauma patients. Please see later in the article for the Editors Summary


Trials | 2015

The COMET initiative database: progress and activities update (2014).

Elizabeth Gargon; Paula Williamson; Doug Altman; Jane M Blazeby; Mike Clarke

The COMET Initiative database is a repository of studies relevant to the development of core outcome sets (COS). Use of the website continues to increase, with more than 16,500 visits in 2014 (36 % increase over 2013), 12,257 unique visitors (47xa0% increase), 9780 new visitors (43 % increase) and a rise in the proportion of visits from outside the UK (8565 visits; 51 % of all visits). By December 2014, a total of 6588 searches had been completed, with 2383 in 2014 alone (11 % increase). The growing awareness of the need for COS is reflected in the website and database usage figures.xa0

Collaboration


Dive into the Doug Altman's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Mike Clarke

Queen's University Belfast

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

David Moher

Ottawa Hospital Research Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge