Patient heterogeneity and allocation bias: how should they be reported in clinical trials of chemotherapy for advanced gastric cancer?

Abstract

Successful phase III trials improve the standard of care for cancer patients by providing new treatment regimens that have superior survival rates, less toxicity, or both when compared with conventional regimens. However, the external validity or generalizability of trial results depends directly on the extent to which the results are applicable to the patient population of a specific practice. Selection bias can seriously influence the external validity of a clinical trial. Participants in clinical trials tend to have better survival outcomes than do nonparticipants. In addition, differences among the patient characteristics that are reported in trials complicate direct comparisons between reports. Therefore, the presentation of baseline patient characteristics is a critical component of any study report on treatment for cancer. Patient characteristics should be presented clearly, so that all readers—physicians, oncologists, and other healthcare decision-makers—can confirm, to the extent possible, whether the study population is representative of that seen in their clinical practice. Researchers are aggressively pursuing more effective treatments by conducting many global trials of new drugs, including those using molecular-targeted agents. However, various problems are emerging in interpreting and comparing the data from these clinical trials. The ToGA study has proven the survival benefits of adding trastuzumab to capecitabine (or 5-fluorouracil [5-FU]) and cisplatin in the treatment for patients with human epidermal growth factor receptor 2 (HER2)-positive, advanced gastric cancer [1]. The AVAGAST study failed to show significant prolongation of overall survival when bevacizumab was added to the chemotherapy for advanced gastric cancer [2]. Review of these studies reveals remarkable diversity in patient characteristics among different regions or countries (e.g., Asia, Europe, and the United States). Diversity existed in patient characteristics such as age, site of primary stomach cancer, and the rate of receipt of second-line chemotherapy, all factors which may influence trial outcomes. Asian countries contributed greatly to patient recruitment in these two global trials, but the proportion of patients enrolled from Asia was less than half of the trial populations. The realistic magnitude of benefit of the new drugs in Asian countries can only be estimated from the subgroup analyses. Investigators often want to know whether patients will respond differently to a treatment depending on prerandomization characteristics. Investigation of this clinical question can lead to important findings that indicate a treatment has a greater effect in some patients than in others. However, caution must be exercised in interpreting the results of subgroup analyses, because of the lack of statistical power with small sample sizes. Deciding on a course of clinical treatment based on subgroup analysis results is highly controversial. The simultaneous expansion of global clinical research and a deepening understanding of the need for individualized medicine have revealed the importance of reporting patient characteristics appropriately so that data from multiple, often international, trials can be more effectively integrated into subgroup analyses that have more statistical power. Results from these types of analyses allow researchers to test the relationships between various characteristics and endpoints, to construct hypotheses useful for answering clinical questions, and to plan new trials that will yield more effective treatments. This old—but new—topic has been addressed in This editorial refers to the article doi:10.1007/s10120-011-0083-8.