Journal of the National Cancer Institute
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J. Natl. Cancer Inst. · Jun 2016
An Ethical Framework for Allocating Scarce Life-Saving Chemotherapy and Supportive Care Drugs for Childhood Cancer.
Shortages of life-saving chemotherapy and supportive care agents for children with cancer are frequent. These shortages directly affect patients' lives, compromise both standard of care therapies and clinical research, and create substantial ethical challenges. Efforts to prevent drug shortages have yet to gain traction, and existing prioritization frameworks lack concrete guidance clinicians need when faced with difficult prioritization decisions among equally deserving children with cancer. ⋯ The framework provides reasoning for explicit decision-making in the face of an actual drug shortage. Moreover, it minimizes bias that might occur when individual clinicians or institutions are forced to make bedside rationing and prioritization decisions and addresses the challenge that individual clinicians face when confronted with bedside decisions regarding allocation. Whenever possible, allocation decisions should be supported by evidence-based recommendations. "Curability," prognosis, and the incremental importance of a particular drug to a given patient's outcome are the critical factors to consider when deciding how to allocate scarce life-saving cancer drugs.
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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.
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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.