Journal of the National Cancer Institute
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J. Natl. Cancer Inst. · Aug 2011
Comparative StudyMammographic breast density and subsequent risk of breast cancer in postmenopausal women according to tumor characteristics.
Few studies that investigated the associations between breast density and subsequent breast cancer according to tumor characteristics have produced inconclusive findings. We aimed to determine whether the associations between breast density and subsequent breast cancer varied by tumor characteristics. ⋯ The findings suggest that higher mammographic density is associated with more aggressive tumor characteristics and also with in situ tumors.
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J. Natl. Cancer Inst. · Jul 2011
ReviewRandomized phase II trials: a long-term investment with promising returns.
Given the multitude of novel anticancer drugs and the limited resources available to study them, phase II trials should identify drugs with the highest probability of succeeding in subsequent phase III trials. Currently, single-arm phase II trial results are interpreted relative to historical control subjects, introducing selection bias and confounding that may limit the validity of the conclusions. The rate of success (defined as a statistically significant difference between arms) in phase III oncology trials is only 40%, suggesting that current phase II trials are insufficiently informative. ⋯ There are a wide variety of randomized phase II designs that can be used, including the randomized discontinuation design, the delayed-start design, adaptive (Bayesian) designs, selection designs, and phase II/III designs. The barriers to widespread adoption of randomized phase II trials include time to completion, sample size considerations, and ethical concerns, but none are insurmountable. We conclude that randomized phase II trials are a worthy investment considering finite patient and financial resources and should be the rule rather than the exception for evaluating novel therapies in oncology.
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J. Natl. Cancer Inst. · Jul 2011
Lung cancer risk prediction: Prostate, Lung, Colorectal And Ovarian Cancer Screening Trial models and validation.
Identification of individuals at high risk for lung cancer should be of value to individuals, patients, clinicians, and researchers. Existing prediction models have only modest capabilities to classify persons at risk accurately. ⋯ The PLCO lung cancer risk models demonstrate high discrimination and calibration.