The proportions of elderly patients in all cancers have been rising steadily and the trend is expected to continue. Lung cancer causes more deaths than the next four leading causes of cancer deaths combined. Patients older than 70 years constitute 47% of all lung cancer patients at the time of diagnosis. Significant proportions of elderly lung patients are excluded from either curative or life-extending therapy and elderly lung patients are less likely to participate in clinical trials. The research community has recommended enrolling more elderly lung patients in clinical trials, including trials specifically designed for them, and further investigation to define the "fit" and "frail" elderly patient populations. As a prelude to such trials, there is a need to improve our understanding of the current status of elderly lung cancer patients and the potential risks and benefits associated with chemotherapy and radiation. We will assemble data from existing phase II/III trials in the period 1990-2010 for non-small cell and small cell lung cancer from six national cancer cooperative groups to evaluate the benefits and risks of treating elderly lung cancer patients with radiation and chemotherapy. In comparison to their younger counterparts, the pooled analysis on the cooperative group data offers an opportunity to evaluate patient characteristics and clinical outcomes of the elderly patients as well as the benefits and risks of chemotherapy and radiation. Recognizing that the population of elderly lung cancer patients is a heterogeneous population, which can be classified into several subgroups based on their clinical profiles, we will develop and validate an Elderly Prognostic Index (EPI) to optimize treatment strategies and aid the assignment of elderly patients to therapies. The primary goal of this research is to perform pooled analyses of clinical studies from multi-center cooperative groups to address questions specific to elderly patients.
We aim to characterize the current status of elderly lung cancer patients who participated in cooperative group trials, to compare efficacy and toxicity between treatment strategies, to apply novel statistical tools for pooled analysis, to establish an accurate and reproducible prognostic index for treatment assignments, and to assess and control the impact of potential imbalance of baseline covariates using casual inference methods. The results of this project will help design and implement future elderly- specific trials. Specifi Aim 1: Using elderly lung cancer data aggregated from hundreds of clinical trials, we compare 1a) efficacy and toxicity of sequential chemotherapy and radiation vs. concurrent chemoradiotherapy in locally advanced Non-Small Cell Lung Cancer;and 1b) the efficacy and toxicity of platinum vs. non-platinum-based therapy in extensive and limited Small Cell Lung Cancer patients with different baseline characteristics.
Specific Aim 2 : We will 2a) build the EPI, a predictive model that helps assign elderly patients in elderly-specific trials;and 2b) utilize statistical methods for causal inference to evaluate and control the impact of imbalanced baseline covariates.
While more than half of lung cancer patients are elderly, the elderly patients have been less studied and are more likely to be suboptimally treated than their younger counterparts. This project will provide information regarding efficacy and toxicity of several treatment strategies and help resolve important issues regarding the management of elderly patients with lung cancer. Our research is expected to have significant impact on existing clinical practice and the design of elderly-specific lung cancer clinical trials.
|Pang, Herbert; Wang, Xiaofei (2016) Statistical aspect of translational and correlative studies in clinical trials. Chin Clin Oncol 5:11|
|Wang, Xiaofei; Berry, Mark F (2016) Risk calculators are useful but.... J Thorac Cardiovasc Surg 151:706-7|
|Wang, Xiaofei; Gu, Lin; Zhang, Ying et al. (2015) Validation of survival prognostic models for non-small-cell lung cancer in stage- and age-specific groups. Lung Cancer 90:281-7|
|Rushing, Christel; Bulusu, Anuradha; Hurwitz, Herbert I et al. (2015) A leave-one-out cross-validation SAS macro for the identification of markers associated with survival. Comput Biol Med 57:123-9|