Background: Deprivation indices are often used to adjust for socio-economic disparities in health studies. Their role has been partially evaluated for certain population-level cancer outcomes, but examination of their role in ovarian cancer is limited. In this study, we evaluated a range of well-recognized deprivation indices in relation to cancer survival in a cohort of self-identified Black women diagnosed with ovarian cancer. This study aimed to determine if clinical or diagnostic characteristics lie on a mediating pathway between socioeconomic status (SES) and deprivation and ovarian cancer survival in a minority population that experiences worse survival from ovarian cancer. Methods: We used mediation analysis to look at the direct and indirect causal effects of deprivation indices with main mediators of the SEER stage at diagnosis and residual disease. The analysis employed Bayesian structural equation models with variable selection. We applied a joint Bayesian structural model for the mediator, including a Weibull mixed model for the vital outcome with deprivation as exposure. We selected modifiers via a Monte Carlo model selection procedure. Results: The results suggest that high SES-related indices, such as Yost, Kolak urbanicity (URB), mobility (MOB) and SES dimensions, and concentrated disadvantage index (CDI), all have a significant impact on improved survival. In contrast, area deprivation index (ADI)/Singh, and area level poverty (POV) did not have a major impact. In some cases, the indirect effects have very wide credible intervals, so the total effect is not well estimated despite the estimation of the direct effect. Conclusions: First, it is clear that commonly used indices such as Yost, or CDI both significantly impact the survival experience of Black women diagnosed with epithelial ovarian cancer. In addition, the Kolak dimension indices (URB, MOB, mixed immigrant: MICA and SES) also demonstrate a significant association, depending on the mediator. Mediation effects differ according to the mediator chosen.

Background/Aim: Keratinocyte carcinoma (KC) is a marker of increased risk of other cancer types. To assess if this association exhibits a dose-response relationship, a case-control study was carried out. Patients and Methods: This was a clinic-based study of cases with KC plus another type of cancer matched by age, race (all Caucasian), sex and histologic type to controls with KC only (n=48 matched pairs). Results: Compared with the KC only group, those with KC plus another cancer had a mean number of lesions that were 43%, 35%, and 41% greater for basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and total KC, respectively. The odds ratio (OR) of developing another type of cancer increased from 1.0 to 1.09 (95% confidence interval (CI)=0.23-5.13) to 2.12 (95%CI=0.50-9.08) according to whether the patient had zero, one, or ≥two BCC lesions; for SCC, the corresponding ORs were 1.0, 1.24 (95%CI=0.48-3.24), and 1.39 (95%CI=0.29-6.61). Conclusion: A dose-response relationship seems to exist between the number of skin lesions and the risk of another type of cancer, but the lack of statistical significance weakens this evidence.

Click on the article title to read more.

Background: Medicaid-insured patients experience higher rates of late-stage cancer diagnosis and worse survival than non-Medicaid patients. The impact of Medicaid enrollment timing on cancer outcomes is less clear. This study examines the association between Medicaid enrollment and timing with tumor stage and cancer-specific survival for breast, colorectal, and lung cancers. Methods: We analyzed SEER-Medicaid linked data for 276,755 breast, 104,784 colorectal, and 101,058 lung cancer patients < 65 years of age. Patients were categorized as non-Medicaid enrollees, pre-diagnosis enrollees (≥12 months before), or post-diagnosis enrollees (≤12 months after). Multivariable logistic regression estimated odds ratios of late-stage diagnosis, and cause-specific Cox proportional hazards models were used to assess cancer-specific survival, adjusting for demographic and socioeconomic factors. Results: Compared to non-Medicaid enrollees, post-diagnosis enrollees had the highest odds of late-stage diagnosis (breast cancer: OR: 3.41; colorectal cancer: OR: 3.78; lung cancer: OR: 1.87). Pre-diagnosis enrollees also had increased odds, but the association was weaker than post-diagnosis enrollees. Cancer-specific mortality was higher for both pre- and post-diagnosis enrollees compared to non-Medicaid enrollees for each cancer examined across tumor stage at diagnosis. Among Medicaid enrollees, those enrolled post-diagnosis had higher cancer-specific mortality than those enrolled pre-diagnosis for localized-stage colorectal (HR: 1.82) and lung cancer (HR: 1.30). In contrast, those enrolled post-diagnosis had lower mortality than those enrolled pre diagnosis for distant-stage breast cancer (HR: 0.91). Conclusions: Compared with cancer patients not insured by Medicaid, post-diagnosis Medicaid enrollment was associated with a greater likelihood of late-stage cancer and worse cancer-specific survival across each cancer type examined. Future research is warranted to examine the role of Medicaid enrollment timing in cancer care to better understand its impact on cancer outcomes.