Towards decision-making using individualized risk estimates for personalized medicine: A systematic review of genomic classifiers of solid tumors.

Recent advances in the understanding of the genetic underpinnings of cancer offer the promise to customize cancer treatments to the individual through the use of genomic classifiers (GCs). At present, routine clinical utilization of GCs is uncommon and their current scope and status, in a broad sense, are unknown. As part of a registered review (PROSPERO 2014:CRD42014013371), we systematically reviewed the literature evaluating the utility of commercially available GCs by searching Ovid Medline (PubMed), EMBASE, the Cochrane Database of Systematic Reviews, and CINAHL on September 2, 2014. We excluded articles involving pediatric malignancies, non-solid or non-invasive cancers, hereditary risk of cancer, non-validated GCs, and GCs involving fewer than 3 biomarkers. A total of 3,625 studies were screened, but only 37 met the pre-specified inclusion criteria. Of these, 15 studies evaluated outcomes and clinical utility of GCs through clinical trials, and the remainder through the use of mathematical models. Most studies (29 of 37) were specific to hormone-receptor positive breast cancer, whereas only 4 studies evaluated GCs in non-breast cancer (prostate, colon, and lung cancers). GCs have spurred excitement across disciplines in recent decades. While there are several GCs that have been validated, the general quality of the data are weak. Further research, including prospective validation is needed, particularly in the non-breast cancer GCs.

Impact of Urban Neighborhood Disadvantage on Late Stage Breast Cancer Diagnosis in Virginia.

Research suggests that residents of inner-city urban neighborhoods have higher rates of late stage cancer diagnosis. Identifying urban neighborhoods with high rates of both concentrated disadvantage and late stage cancer diagnosis may assist health care providers to target screening interventions to reduce disparities. The purposes of this study were to (1) create an index to evaluate concentrated disadvantage (CD) using non-racial measures of poverty, (2) determine the impact of neighborhood CD on late stage breast cancer diagnosis in US cities, and (3) to understand the role of obesity on this relationship. We used census block group- (CBG) level poverty indicators from five Virginia cities to develop the index. Breast cancer cases of women aged 18-65 who lived in the five cities were identified from the 2000-2012 Virginia Cancer Registry. A logistic regression model with random intercept was used to evaluate the impact of disadvantage on late stage breast cancer diagnosis. CBG-level maps were developed to geographically identify neighborhoods with both high rates of CD and late breast cancer staging. Over 900 CBGs and 6000 breast cases were included. Global fit of the concentrated disadvantage model was acceptable. The effect of disadvantage on late stage was significant (OR = 1.0083, p = 0.032). Inner-city poverty impacts risk of late stage breast cancer diagnosis. Area-level obesity is highly correlated with neighborhood poverty (ρ = 0.74, p < 0.0001) but the mediating direct and indirect effects are non-significant. Intervening in these high poverty neighborhoods may help combat disparities in late stage diagnosis for urban poor and for minorities living in these underserved neighborhoods, but more study is needed to understanding the complex relationship between concentrated neighborhood poverty, obesity, and late stage diagnosis.

Cost-effectiveness of the Decipher Genomic Classifier to Guide Individualized Decisions for Early Radiation Therapy After Prostatectomy for Prostate Cancer.

BACKGROUND: Controversy exists regarding the effectiveness of early adjuvant versus salvage radiation therapy after prostatectomy for prostate cancer. Estimates of prostate cancer progression from the Decipher genomic classifier (GC) could guide informed decision-making and improve the outcomes for patients. MATERIALS AND METHODS: We developed a Markov model to compare the costs and quality-adjusted life years (QALYs) associated with GC-based treatment decisions regarding adjuvant therapy after prostatectomy with those of 2 control strategies: usual care (determined from patterns of care studies) and the alternative of 100% adjuvant radiation therapy. Using the bootstrapping method of sampling with replacement, the cases of 10,000 patients were simulated during a 10-year time horizon, with each subject having individual estimates for cancer progression (according to GC findings) and noncancer mortality (according to age). RESULTS: GC-based care was more effective and less costly than 100% adjuvant radiation therapy and resulted in cost savings up to an assay cost of $11,402. Compared with usual care, GC-based care resulted in more QALYs. Assuming a $4000 assay cost, the incremental cost-effectiveness ratio was $90,833 per QALY, assuming a 7% usage rate of adjuvant radiation therapy. GC-based care was also associated with a 16% reduction in the percentage of patients with distant metastasis at 5 years compared with usual care. CONCLUSION: The Decipher GC could be a cost-effective approach for genomics-driven cancer treatment decisions after prostatectomy, with improvements in estimated clinical outcomes compared with usual care. The individualized decision analytic framework applied in the present study offers a flexible approach to estimate the potential utility of genomic assays for personalized cancer medicine.