To present guidelines for the analysis and presentation of clinical trials on prostate cancer.

Textbooks in statistics and oncology were searched for information, as were separate articles on the topic. Previously published advice was fused with own experience.

Minimum key points are given for the sections: Introduction, Materials and Methods, Results, Discussion, and Summary. The importance of 1 primary question in any clinical trial is stressed. The value of a detailed presentation of the trial design, the patient population and the inclusion/exclusion criteria, the characterization of the disease, the treatment schedules, and toxicity is underlined. Application of various statistical methods for different endpoints is suggested. Maturity of data, time for publication, and avoidance of publication bias are discussed. Some common pitfalls in the statistical analyses of clinical results are indicated. The impact of prognostic factors, proper staging procedures, and secondary treatments on the interpretation of survival analysis is pointed out. A shift from the (mis-)use of the P value in favor of confidence intervals is strongly encouraged. The use of comparing the survival of responders versus nonresponders is to be abandoned. A few practical hints concerning the presentation are offered. The minimum of data that should be presented in absolute numbers is indicated. Also, the data that should be provided in both graphic and numeric format are exemplified. Examples of essential graphic illustrations are provided. The need for improvements in the design, analysis, and presentation of clinical trials is reemphasized. Finally, numerous references are listed. The article is addressed not only to authors and readers of clinical trials, but also to editors of medical journals.

The suggested guidelines may be useful in the analysis, presentation, and interpretation of clinical trials on prostate cancer. Moreover, compliance with these guidelines may facilitate comparisons with other similar trials and also, the incorporation of single studies into metaanalyses.