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Douglas G Altman

Publications and source records attributed to Douglas G Altman.

At least 73 records · Page 4Linked to original sources
PubMed2004

Improving design and analysis of research: lessons from clinical research.

There is a clear need to optimise the use of animals in research and to ensure that the studies that are done make a worthwhile contribution to scientific knowledge. Research that has an inappropriate study design, or is improperly analysed or interpreted, may mislead and is not defensible. Published reviews of the quality of design and analysis in clinical studies are used to see what lessons can be drawn in respect of animal research. The need for clear and full reporting of research is discussed.

Clinical Protocols↗
PubMed2004

Reported use of data monitoring committees in the main published reports of randomized controlled trials: a cross-sectional study.

BACKGROUND: We describe a review of published main reports of randomized controlled trials (RCTs), in order to measure the frequency of reported use of data monitoring committees (DMCs) and factors associated with reported DMC use. METHODS: Twenty-four higher impact general and specialist medical journals were handsearched for main reports of RCTs in order to provide a cross-sectional sample of trials published in the year 2000. Additionally, the same general medical journals were handsearched for 1990 to allow a comparison across time. RESULTS: Of 662 RCTs published in 2000, 120 (18%) explicitly reported using a DMC, while 107 (16%) reported planned interim analyses. Overall, about a quarter (24%) reported at least one of these. A higher proportion of trials reported using a DMC in 2000 than 1 990 (70/282, 25% versus 21/204, 10%) in the general medical journals. Logistic regression models suggested the more important variables associated with increased reported DMC use were: later year of publication, publication in general medical journal, survival-based endpoint, multicentre trial, increasing number of patients recruited, at least one arm involving a placebo, at least one arm involving a drug, factorial design and USA involvement in the trial. CONCLUSIONS: In 2000, about a quarter of main RCT reports mention use of a DMC. Actual use of DMCs is likely to be somewhat greater. Reporting use of a DMC was more likely for larger and longer trials among other factors. We believe the factors affecting reported use affect actual use. It is recommended that when a DMC oversees a trial, brief details should be explicitly included in the main trial paper. Standard nomenclature for DMCs is recommended.

Clinical Trials Data Monitoring Committees↗
PubMed2004

Systematic qualitative review of the literature on data monitoring committees for randomized controlled trials.

AIMS: To systematically review the published literature on data monitoring committees (DMCs) for randomized controlled trials (RCT) and summarize information and opinions on best practice. This was part of the DAMOCLES project. METHODS: A systematic and comprehensive search of five online bibliographic databases was performed, identifying 4007 potentially relevant articles. These were assessed in two stages by the authors. The 84 most relevant articles were agreed and were supplemented with extracts from 16 books: ultimately, 100 sources were reviewed. A series of 23 questions plus subquestions were developed to structure the data extraction and interpretation process. RESULTS: Much has been written about DMCs but by a rather small community of authors. The papers included some results of surveys, but were mainly opinion pieces based on the authors' beliefs, practices and experiences. There is a lack of empirical evidence for many aspects of DMCs. There was a great range of detail in the literature relating to the prespecified questions. It was generally agreed that interim monitoring of accumulating data was necessary in some form for most trials. Questions such as membership of the DMC featured widely in the literature with opinions and practice ranging from 3-20 members, of whom between none and all should be independent. There was a consensus that formal statistical methods should be used as tools to guide decision making rather than as hard rules. Conversely, topics such as the training and experience required for DMC membership were discussed in very few papers. CONCLUSIONS: There is a consensus in the published literature in a number of areas, although there are many different models for structure and functions of a DMC. While uncertainty remains about some issues, it is strongly recommended that an explicit set of guidelines (Charter) is prepared for each DMC prior to the start of the trial specifying clearly how it will operate.

Clinical Trials Data Monitoring Committees↗
PubMed2003

Indirect comparison meta-analysis of aspirin therapy after coronary surgery.

OBJECTIVES: To evaluate the efficacy of low and medium dose aspirin therapy after coronary surgery by using an indirect comparison meta-analysis. DATA SOURCES: Systematic literature search of Medline, Embase, Cochrane controlled trials register, and trial register sites on the internet. STUDY SELECTION: Outcome was evaluated by angiography and reported as graft occlusion and rate of events in patients. Trials that did not include aspirin as the sole therapy or did not have a placebo control arm were excluded. Articles were assessed for eligibility and quality and grouped according to dosage. The estimated difference in effect of low and medium dose aspirin on graft occlusion was obtained by combining the estimated log relative risks of low dose with placebo and medium dose with placebo. RESULTS: For graft occlusion, the medium dose trials yielded a relative risk reduction of 45% compared with 26% for the low dose trials. The greater effect in the medium dose trials is summarised by a relative risk ratio of 0.74 (95% confidence interval 0.52 to 1.06; P = 0.10) for graft occlusion and 0.81 (0.57 to 1.16; P = 0.25) for events in patients. CONCLUSIONS: Medium dose aspirin may more successfully reduce graft occlusion than low dose regimens within the first year after coronary surgery.

Aspirin↗
PubMed2003

Analysis and reporting of factorial trials: a systematic review.

CONTEXT: Although factorial trials have become common, standards for the analysis and reporting of such trials have not been established and, despite concerns about the possibility of unrecognized interactions between therapies in factorial trials, the magnitude of this potential problem is unknown. OBJECTIVE: To examine the rationale, methods, and analysis of randomized factorial trials. DATA SOURCES AND STUDY SELECTION: We searched MEDLINE, EMBASE, and the Cochrane Controlled Trials Register using the terms factorial, interaction, 2 x 2, 2 by 2, and incremental to identify factorial randomized trials published from January 2000 to July 2002. To identify trials missed by the electronic search, we performed a hand search of English-language trials in a defined topic area (using the term myocardial ischemia [exp]) listed in MEDLINE (1966-2002), EMBASE (1980-2002), and the Cochrane Controlled Trials Register, as well as all trials in any topic area published in December 2000, excluding trials reporting only continuous surrogate end points. The final set of 33 eligible publications described 29 unique trials. DATA EXTRACTION: Two investigators independently identified factorial trials, generated a list of items affecting validity of results, and abstracted these items from each trial. DATA SYNTHESIS: The sensitivity of electronic searching for identifying factorial trials was 76%. Our 3-pronged search strategy identified 44 factorial trials with clinically important binary outcomes: 36 (82%) were done for reasons of efficiency (testing 2 interventions in the same patient population), and 8 (18%) were done to assess the incremental benefits of combining the 2 treatments. All but 1 of the trials reported treatment effects by comparing all patients who received treatment A (ie, those receiving either A alone or both A and B) vs all those not receiving treatment A (ie, those receiving either B alone or neither A nor B). Twenty-nine of the 44 trials (66%) reported the data from each of the treatment groups separately; 26 trials (59%) reported testing for interactions between the treatments. Only 2 of 31 (6%) comparisons demonstrated a statistically significant interaction between the 2 treatments. CONCLUSIONS: Accurate interpretation of factorial trials depends on the transparent reporting of data for each treatment cell. Despite concerns about unrecognized interactions, our findings suggest that investigators are appropriately restricting their use of the factorial design to those situations in which 2 (or more) treatments do not have the potential for substantive interaction.

Data Interpretation, Statistical↗
PubMed2003

Validity of indirect comparison for estimating efficacy of competing interventions: empirical evidence from published meta-analyses.

OBJECTIVE: To determine the validity of adjusted indirect comparisons by using data from published meta-analyses of randomised trials. DESIGN: Direct comparison of different interventions in randomised trials and adjusted indirect comparison in which two interventions were compared through their relative effect versus a common comparator. The discrepancy between the direct and adjusted indirect comparison was measured by the difference between the two estimates. DATA SOURCES: Database of abstracts of reviews of effectiveness (1994-8), the Cochrane database of systematic reviews, Medline, and references of retrieved articles. RESULTS: 44 published meta-analyses (from 28 systematic reviews) provided sufficient data. In most cases, results of adjusted indirect comparisons were not significantly different from those of direct comparisons. A significant discrepancy (P<0.05) was observed in three of the 44 comparisons between the direct and the adjusted indirect estimates. There was a moderate agreement between the statistical conclusions from the direct and adjusted indirect comparisons (kappa 0.51). The direction of discrepancy between the two estimates was inconsistent. CONCLUSIONS: Adjusted indirect comparisons usually but not always agree with the results of head to head randomised trials. When there is no or insufficient direct evidence from randomised trials, the adjusted indirect comparison may provide useful or supplementary information on the relative efficacy of competing interventions. The validity of the adjusted indirect comparisons depends on the internal validity and similarity of the included trials.

Data Interpretation, Statistical↗
PubMed2003

The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials.

To comprehend the results of a randomised controlled trial (RCT), readers must understand its design, conduct, analysis, and interpretation. That goal can be achieved only through total transparency from authors. Despite several decades of educational efforts, the reporting of RCTs needs improvement. Investigators and editors developed the original CONSORT (Consolidated Standards of Reporting Trials) statement to help authors improve reporting by use of a checklist and flow diagram. The revised CONSORT statement presented here incorporates new evidence and addresses some criticisms of the original statement. The checklist items pertain to the content of the Title, Abstract, Introduction, Methods, Results, and Discussion. The revised checklist includes 22 items selected because empirical evidence indicates that not reporting this information is associated with biased estimates of treatment effect, or because the information is essential to judge the reliability or relevance of the findings. We intended the flow diagram to depict the passage of participants through an RCT. The revised flow diagram depicts information from four stages of a trial (enrollment, intervention allocation, follow- up, and analysis). The diagram explicitly shows the number of participants, for each intervention group, included in the primary data analysis. Inclusion of these numbers allows the reader to judge whether the authors have done an intention- to-treat analysis. In sum, the CONSORT statement is intended to improve the reporting of an RCT, enabling readers to understand a trial's conduct and to assess the validity of its results.

Humans↗
PubMed2003

Charts of fetal size: kidney and renal pelvis measurements.

OBJECTIVE: To construct new size charts for fetal kidney measurements and to define normal limits for renal pelvic antero-posterior diameter. METHODS: A prospective, cross-sectional study was carried out in the ultrasound department of a large hospital. Six hundred and sixty-three fetuses were scanned only once for the purpose of the study at gestations between 14 and 42 weeks. Centiles for kidney dimensions were estimated by combining separate fractional polynomial regression models fitted to the mean and standard deviation, assuming that the measurements have a normal distribution at each gestational age. Centiles for renal pelvic diameter were obtained using quantile regression. RESULTS: Size charts for fetal kidney dimensions [antero-posterior (AP), transverse, length and volume] and renal pelvis diameter are presented and compared with previously published data. CONCLUSION: We present new size charts for fetal kidney size that take into consideration the increasing variability with gestational age. These data should aid the prenatal diagnosis of renal pathology by defining renal size and the upper limits of normal pelvic dilatation. They may be particularly useful in the third trimester where there is limited data available. Our data confirm that it is reasonable to use an upper limit of 7 mm for the AP diameter in late pregnancy.

Adult↗
PubMed2003

Developing a prognostic model in the presence of missing data: an ovarian cancer case study.

When developing prognostic models in medicine, covariate data are often missing and the standard response is to exclude those individuals whose data are incomplete from the analyses. This practice leads to a reduction in the statistical power, and may lead to biased results. We wished to develop a prognostic model for overall survival from 1,189 primary cases (842 deaths) of epithelial ovarian cancer. A complete case analysis restricted the sample size to 518 (380 deaths). After applying a multiple imputation (MI) framework we included three real values for each one imputed, and constructed a model composed of more statistically significant prognostic factors and with increased predictive ability. Missing values can be imputed in cases where the reason for the data being missing is known, particularly where it can be explained by available data. This will increase the power of an analysis and may produce models that are more statistically reliable and applicable within clinical practice.

Adolescent↗