Prognostic factors are necessary and sufficient for assessing the natural history of cancer, selecting the optimal therapy and evaluating the effectiveness of treatment. Because prognostic factors are predictive to the extent that they participate in the disease process, anything that participates in the disease process is a potential prognostic factor. Any investigation of the disease process, therefore, can result in the identification of new prognostic factors. As researchers move down explanatory levels of analysis, and especially when they explore the molecular genetic level, they increase explanatory complexity. One result of this increase in complexity is the proliferation of prognostic factors. In addition, methodologic and technical issues arise related to the identification, replication and validation of molecular genetic factors. The combination of the proliferation of putative factors and the lack of replication and validation of findings has resulted in confusion in the prognostic factor domain. In this paper we explore some of the reasons for the ambiguity surrounding the non-extent of disease putative prognostic factors and how these ambiguities can be resolved. Specifically, we: 1. define and describe prognostic factors, as a type of predictive factor, 2. explain why, and under what conditions, combining factors may increase predictive accuracy, and 3. describe the advantages and disadvantages of commonly used statistical methods for combining predictive factors, and 4. recommend an approach to the reporting of prognostic factor research results.
|Number of pages||9|
|Journal||CME Journal of Gynecologic Oncology|
|State||Published - 1999|
- Prognostic factor