Journal of the National Cancer Institute
-
J. Natl. Cancer Inst. · May 2016
Performing Survival Analyses in the Presence of Competing Risks: A Clinical Example in Older Breast Cancer Patients.
An important consideration in studies that use cause-specific endpoints such as cancer-specific survival or disease recurrence is that risk of dying from another cause before experiencing the event of interest is generally much higher in older patients. Such competing events are of major importance in the design and analysis of studies with older patients, as a patient who dies from another cause before the event of interest cannot reach the endpoint. In this Commentary, we present several clinical examples of research questions in a population-based cohort of older breast cancer patients with a high frequency of competing events and discuss implications of choosing models that deal with competing risks in different ways. ⋯ Two approaches are commonly used to model the association between prognostic factors and cause-specific survival: the Cox proportional hazards model and the Fine and Gray model. We discuss both models and show that in etiologic research the Cox Proportional Hazards model is recommended, while in predictive research the Fine and Gray model is often more appropriate. In conclusion, in studies with cause-specific endpoints in populations with a high frequency of competing events, researchers should carefully choose the most appropriate statistical method to prevent incorrect interpretation of results.
-
J. Natl. Cancer Inst. · May 2016
Delineation of MGMT Hypermethylation as a Biomarker for Veliparib-Mediated Temozolomide-Sensitizing Therapy of Glioblastoma.
Sensitizing effects of poly-ADP-ribose polymerase inhibitors have been studied in several preclinical models, but a clear understanding of predictive biomarkers is lacking. In this study, in vivo efficacy of veliparib combined with temozolomide (TMZ) was evaluated in a large panel of glioblastoma multiforme (GBM) patient-derived xenografts (PDX) and potential biomarkers were analyzed. ⋯ Veliparib statistically significantly enhances (P < .001) the efficacy of TMZ in tumors with MGMT promoter hypermethylation. Based on these data, MGMT promoter hypermethylation is being used as an eligibility criterion for A071102 (NCT02152982), the phase II/III clinical trial evaluating TMZ/veliparib combination in patients with GBM.