Scientific advances in the field of genetics and gene-expression profiling have revolutionized the concept of patient-tailored treatment. Analysis of differential gene-expression patterns across thousands of biological samples in a single experiment (as opposed to hundreds to thousands of experiments measuring the expression of one gene at a time), and extrapolation of these data to answer clinically pertinent questions such as those relating to tumor metastatic potential, can help define the best therapeutic regimens for particular patient subgroups. The use of microarrays provides a powerful technology, allowing in-depth analysis of gene-expression profiles. Currently, microarray technology is in a transition phase whereby scientific information is beginning to guide clinical practice decisions. Before microarrays qualify as a useful clinical tool, however, they must demonstrate reliability and reproducibility. The high-throughput nature of microarray experiments imposes numerous limitations, which apply to simple issues such as sample acquisition and data mining, to more controversial issues that relate to the methods of biostatistical analysis required to analyze the enormous quantities of data obtained. Methods for validating proposed gene-expression profiles and those for improving trial designs represent some of the recommendations that have been suggested. This Review focuses on the limitations of microarray analysis that are continuously being recognized, and discusses how these limitations are being addressed.

Background Individuals living with low income are less likely to participate in lung cancer screening (LCS) with low-dose computed tomography. Family physicians (FPs) are typically responsible for referring eligible patients to LCS; therefore, we sought to understand their perspectives on access to lung cancer screening for individuals living with low income in order to improve equity in access to LCS. Methods A theory-informed thematic analysis was conducted using data collected from 11 semi-structured interviews with FPs recruited from three primary care sites in downtown Toronto. Data was coded using the Systems Model of Clinical Preventative Care as a framework and interpretation was guided by the synergies of oppression analytical lens. Results Four overarching themes describe FP perspectives on access to LCS for individuals living with low income: the degree of social disadvantage that influences lung cancer risk and opportunities to access care; the clinical encounter, where there is often a mismatch between the complex health needs of low income individuals and structure of health care appointments; the need for equity-oriented health care, illustrated by the neglect of structural origins of health risk and the benefits of a trauma-informed approach; and finally, the multiprong strategies that will be needed in order to improve equity in health outcomes. Conclusion An equity-oriented and interdisciplinary team based approach to care will be needed in order to improve access to LCS, and attention must be given to the upstream determinants of lung cancer in order to reduce lung cancer risk.

services research and public health policy to take steps to include a diverse representation of patient voices through equity-focused PE.

Background: National cancer control plans (NCCPs) are important documents that guide strategic priorities in cancer care and plan for the appropriate allocation of resources based on the social, geographic and economic needs of a population. Despite the emphasis on health equity by the World Health Organization (WHO), few NCCPs have a focus on health equity. The Ontario Cancer Plan (OCP) IV, (2015 to 2019) is an example of an NCCP with clearly defined health equity goals and objectives. Methods: This paper presents a directed-content analysis of the OCP IV health equity goals and objectives, in light of the synergies of oppression analytical framework. Results: The OCP IV confines equity to an issue of access-to-care. As a result, it calls for training, funding, and social support services to increase accessibility for high-risk population groups. However, equity has a broader definition. And as such, it also implies that systematic differences in health outcomes between social groups should be minimal. This is particularly significant given that socially disadvantaged cancer patients in Ontario have distinctly poorer cancer-related health outcomes. Conclusion: Health systems are seeking ways to reduce the health equity gap. However, to reduce health inequities which are socially-based will require a recognition of the living and working conditions of patients which influence risk, mortality and survival. NCCPs represent a way to politically advocate for the determinants of health which profoundly influence cancer risk, outcomes and mortality.