Does Computed Tomography or Positron Emission Tomography Response After Neoadjuvant Chemotherapy for Resectable Non–Small-Cell Lung Cancer Predict Survival?

Abstract

Over the last several decades, measuring tumors on sequential imaging studies has played an essential role in managing patients with lung cancer. Using standardized Response Evaluation Criteria in Solid Tumors (RECIST) at designated time points, patients are stratified into a response category based on the percent change in tumor size. The RECIST guidelines represent an objective assessment of disease, are used to determine duration and reinstitution of therapy, and are ultimately intended as a surrogate marker to predict outcome. Interestingly, this paradigm has been propagated for decades without clear data to support that change in tumor size on radiologic studies will accurately reflect survival. The limitations in stratification by imaging criteria can probably be attributed to the arbitrary selection of percent change used to determine response categories and, more importantly, to the paucity of biologic information in an anatomic abnormality described on a radiographic study. Lung tumors are heterogeneous, and the host response is variable; often a robust inflammatory response to the tumor itself may produce the majority of the radiographic abnormality. Thus, although many investigators have suggested that more accurate tumor measurements, including three-dimensional volumetrics and better resolution, are needed to improve patient stratification, these technical features do not address the fundamental issue of the tumor’s biologic behavior. In the current issue, Tanvetyanon et al report an intriguing prospective trial that examined the ability of changes in computed tomography (CT) or [F]fluorodeoxyglucose (FDG) positron emission tomography (PET) before and after neoadjuvant chemotherapy for resectable non–small-cell lung cancer (NSCLC) to predict survival. This analysis was performed to help define an appropriate imaging evaluation for these patients so that therapy, and hopefully outcome, could be optimized. After thorough analysis, they found that the CT response as measured by the RECIST criteria seems to predict outcomes only in resectable stage III patients. They did not find a statistically significant correlation between the CT response and survival in resectable stage I and II disease. More interestingly, the investigators studied whether FDG-PET was a better predictor of survival compared with conventional imaging. No matter how the data were analyzed, the investigators could not find changes in FDG uptake that predicted outcome. Serial PET studies did not provide the requisite information needed to guide patient management. Although the numbers of patients in this study are relatively small, the conclusions are clear—change in tumor size on CT after neoadjuvant therapy for early-stage resectable NSCLC patients and change in FDG uptake after neoadjuvant therapy for all resectable NSCLC patients did not predict survival. This is a complex conclusion that begs the questions of how to best approach these patients if treatment is to be optimized and why this traditional, seemingly logical measurement strategy is ineffective. The fundamental concept that a tumor cell response equals tumor size response needs to be reconsidered. In some cases, therapy may destroy only the most susceptible tumor cells, leaving the more virulent resistant tumor cells to proliferate. In addition, if there is an increase in the inflammatory reaction, the lesion size could remain stable or even increase. In other cases, the tumor size could potentially decrease, but this may be a result of a reduction in the host inflammatory response, and tumor cells would remain or even propagate. It has been reported that survival correlates with tumor cell viability after therapy and not necessarily with the radiographic response. Despite these limitations, there is currently no alternative approach to response evaluation, and patients are still observed with serial imaging. It would be much more advantageous to work toward a system that predicts, at the time of diagnosis, the most favorable therapeutic plan. Unfortunately, although this is a laudatory goal, attempts to develop personalized medicine and targeted therapy have not yet proved sufficient to enter standard clinical practice. Thus, there remains an unmet need to develop better diagnostic tools. When FDG-PET was introduced into the imaging armamentarium, it was a new direction for radiology that extended beyond traditional anatomic and morphologic information. PET has proved to be useful in some scenarios in the thorax, including differentiating benign from malignant nodules and staging patients with lung cancer. However, the exact mechanism of FDG uptake and distribution within the various cells in a tumor remains unclear. Studies have shown no significant correlation between FDG activity in lung tumors and glucose transporters. Only through a better understanding of the molecular mechanisms that are responsible for radiotracer uptake JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 26 NUMBER 28 OCTOBER 1 2008