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D G Altman

Publications and source records attributed to D G Altman.

At least 37 records · Page 2Linked to original sources
PubMed2001

A prognostic model for ovarian cancer.

About 6000 women in the United Kingdom develop ovarian cancer each year and about two-thirds of the women will die from the disease. Establishing the prognosis of a woman with ovarian cancer is an important part of her evaluation and treatment. Prognostic models and indices in ovarian cancer should be developed using large databases and, ideally, with complete information on both prognostic indicators and long-term outcome. We developed a prognostic model using Cox regression and multiple imputation from 1189 primary cases of epithelial ovarian cancer (with median follow-up of 4.6 years). We found that the significant (P< or = 0.05) prognostic factors for overall survival were age at diagnosis, FIGO stage, grade of tumour, histology (mixed mesodermal, clear cell and endometrioid versus serous papillary), the presence or absence of ascites, albumin, alkaline phosphatase, performance status on the ZUBROD-ECOG-WHO scale, and debulking of the tumour. This model is consistent with other models in the ovarian cancer literature; it has better predictive ability and, after simplification and validation, could be used in clinical practice.

Adolescent↗
PubMed2001

Effect of arterial revascularisation on survival: a systematic review of studies comparing bilateral and single internal mammary arteries.

BACKGROUND: Coronary artery bypass grafting (CABG) is the commonest major operation in most developed countries. A single internal mammary artery (IMA) graft has proven survival benefits, but the additional survival advantage of a second graft is unknown. We systematically reviewed published studies of bilateral versus single IMA grafts in CABG to assess any differences in survival. METHODS: We identified from Medline all studies in which single and bilateral IMA grafts were compared. We included studies in which at least 100 patients in each group had been followed up for at least 4 years. We assessed study quality on the basis of patient selection, comparability of intervention groups (especially for age, sex, ventricular function, and diabetes status), outcome assessment, and completeness of follow-up. Our primary outcome was survival. Estimates of treatment effect (single versus bilateral) expressed as hazard ratios were pooled across studies. FINDINGS: None of the studies was a randomised trial, but nine cohort studies met our inclusion criteria. Seven studies yielded survival data for meta-analysis, and included 15962 patients: 11269 single and 4693 bilateral IMA grafts. The bilateral group had significantly better survival than the single group (hazard ratio for death 0.81; 95% CI 0.70-0.94). Exclusion of methodologically weak studies improved survival rates with bilateral IMA grafts. INTERPRETATION: Because no study was a randomised trial, our results are more uncertain than is indicated by the 95% CI. Nevertheless, bilateral IMA grafts seem to give better survival rates than single grafts.

Aged↗
PubMed2001

Monitoring of large randomised clinical trials: a new approach with Bayesian methods.

BACKGROUND: In judging whether or not to continue enrolling patients into a randomised clinical trial, most data-monitoring and ethics committees (DMECs) rely on the p value for the difference in effect between the study groups. In the 1990s, two randomised controlled trials-one in patients with lung cancer and one in those with head and neck cancer-were instead monitored by Bayesian methods. We assessed the value of this approach in the monitoring of these clinical trials. METHODS: Before the trials opened, participating clinicians were asked their opinions on the expected difference between the study treatment (continuous hyperfractionated accelerated radiotherapy [CHART]) and conventional radiotherapy. These opinions were used to form an "enthusiastic" and a "sceptical" prior distribution. These prior distributions were combined with the trial data at each of the annual DMEC meetings. If, during monitoring, a result in favour of CHART was seen, the DMEC was to decide whether the results were sufficiently convincing to persuade a sceptic that CHART was worthwhile. Conversely, if there was apparently no or little difference, the DMEC was asked whether they thought the results sufficiently convincing to persuade an enthusiast that CHART was not worthwhile. FINDINGS: At each of the annual meetings, the DMEC concluded that there was insufficient evidence to convert either sceptics or enthusiasts, and that the trials should therefore remain open to recruitment. Neither trial was closed to recruitment earlier than planned. However if a conventional (p-value-based) stopping rule had been used, the lung-cancer trial would probably have been stopped. INTERPRETATION: This Bayesian approach to monitoring is simple to implement and straightforward for members of the DMEC to understand. In our opinion, it is more intuitively appealing than conventional approaches.

Bayes Theorem↗
PubMed2001

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

To comprehend the results of a randomized controlled trial (RCT), readers must understand its design, conduct, analysis and interpretation. That goal can only be achieved through complete 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 using a checklist and flow diagram. The revised CONSORT statement presented in this paper 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 the information is associated with biasedestimates of treatment effect or 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 includes 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 performed 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↗
PubMed2001

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

To comprehend the results of a randomized, controlled trial (RCT), readers must understand its design, conduct, analysis, and interpretation. That goal can be achieved only through complete transparency from authors. Despite several decades of educational efforts, the reporting of RCTs needs improvement. Investigators and editors developed the original CONSORT (Con solidated S tandards o f R eporting T rials) statement to help authors improve reporting by using a checklist and flow diagram. The revised CONSORT statement presented in this paper 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 the 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 includes the number of participants, for each intervention group, that are included in the primary data analysis. Inclusion of these numbers allows the reader to judge whether the authors have performed 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.

Algorithms↗
PubMed2001

The revised CONSORT statement for reporting randomized trials: explanation and elaboration.

Overwhelming evidence now indicates that the quality of reporting of randomized, controlled trials (RCTs) is less than optimal. Recent methodologic analyses indicate that inadequate reporting and design are associated with biased estimates of treatment effects. Such systematic error is seriously damaging to RCTs, which boast the elimination of systematic error as their primary hallmark. Systematic error in RCTs reflects poor science, and poor science threatens proper ethical standards. A group of scientists and editors developed the CONSORT (Con solidated S tandards o f R eporting T rials) statement to improve the quality of reporting of RCTs. The statement consists of a checklist and flow diagram that authors can use for reporting an RCT. Many leading medical journals and major international editorial groups have adopted the CONSORT statement. The CONSORT statement facilitates critical appraisal and interpretation of RCTs by providing guidance to authors about how to improve the reporting of their trials. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the CONSORT statement. The meaning and rationale for each checklist item are presented. For most items, at least one published example of good reporting and, where possible, references to relevant empirical studies are provided. Several examples of flow diagrams are included. The CONSORT statement, this explanatory and elaboration document, and the associated Web site ( http://www.consort-statement.org ) should be helpful resources to improve reporting of randomized trials. Throughout the text, terms marked with an asterisk are defined at end of text.

Algorithms↗
PubMed2001

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↗
PubMed2001

The efficacy of problem-solving treatments after deliberate self-harm: meta-analysis of randomized controlled trials with respect to depression, hopelessness and improvement in problems.

BACKGROUND: Brief problem-solving therapy is regarded as a pragmatic treatment for deliberate self-harm (DSH) patients. A recent meta-analysis of randomized controlled trials (RCTs) evaluating this approach indicated a trend towards reduced repetition of DSH but the pooled odds ratio was not statistically significant. We have now examined other important outcomes using this procedure, namely depression, hopelessness and improvement in problems. METHOD: Six trials in which problem-solving therapy was compared with control treatment were identified from an extensive literature review of RCTs of treatments for DSH patients. Data concerning depression, hopelessness and improvement in problems were extracted. Where relevant statistical data (e.g. standard deviations) were missing these were imputed using various statistical methods. Results were pooled using meta-analytical procedures. RESULTS: At follow-up, patients who were offered problem-solving therapy had significantly greater improvement in scores for depression (standardized mean difference = -0.36; 95% CI -0.61 to -0.11) and hopelessness (weighted mean difference =-3.2; 95% CI -4.0 to -2.41), and significantly more reported improvement in their problems (odds ratio = 2.31; 95% CI 1.29 to 4.13), than patients who were in the control treatment groups. CONCLUSIONS: Problem-solving therapy for DSH patients appears to produce better results than control treatment with regard to improvement in depression, hopelessness and problems. It is desirable that this finding is confirmed in a large trial, which will also allow adequate testing of the impact of this treatment on repetition of DSH.

Cognitive Behavioral Therapy↗
PubMed2001

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

To comprehend the results of a randomized, controlled trial (RCT), readers must understand its design, conduct, analysis, and interpretation. That goal can be achieved only through complete 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 using a checklist and flow diagram. The revised CONSORT statement presented in this paper 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 the 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 trial (enrollment, intervention allocation, follow-up, and analysis). The diagram explicitly includes the number of participants, for each intervention group, that are included in the primary data analysis. Inclusion of these numbers allows the reader to judge whether the authors have performed 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↗
PubMed2000

Statistics in medical journals: some recent trends.

I review some areas of medical statistics that have gained prominence over the last 5-10 years: meta-analysis, evidence-based medicine, and cluster randomized trials. I then consider several issues relating to data analysis and interpretation, many relating to the use and misuse of hypothesis testing, drawing on recent reviews of the use of statistics in medical journals. I also consider developments in the reporting of research in medical journals.

Data Interpretation, Statistical↗
PubMed2000

What do we mean by validating a prognostic model?

Prognostic models are used in medicine for investigating patient outcome in relation to patient and disease characteristics. Such models do not always work well in practice, so it is widely recommended that they need to be validated. The idea of validating a prognostic model is generally taken to mean establishing that it works satisfactorily for patients other than those from whose data it was derived. In this paper we examine what is meant by validation and review why it is necessary. We consider how to validate a model and suggest that it is desirable to consider two rather different aspects - statistical and clinical validity - and examine some general approaches to validation. We illustrate the issues using several case studies.

Accidental Falls↗