•Foster Care.•Kinship Care.•Social justice.•Child Welfare.•Policy Analysis.•Cross-national perspectives.
Scholars largely agree that placements with relative caregivers are best for children. ...However, the regulations that jurisdictions apply to determine eligibility for foster care licensure may limit relative caregivers’ access to the benefits of licensure. This analysis considers foster care regulations in three jurisdictions and the effects of policy decisions on eligibility for relative caregivers and placement options for children in out-of-home care. Finland, New Zealand, and Wisconsin all have a stated priority for placement of children with relative caregivers. However, even with a stated priority, the implementation of policies in practice differs by jurisdiction. Finland is adequate in prioritizing child and family well-being but lacks coherence and has regulations that are at high risk of bias. New Zealand’s policies are adequate and coherent, though their highly regulated system is at risk of perpetuating inequity for indigenous populations. Wisconsin regulations are coherent in supporting safety, however, the financial support provided to foster parents is inadequate and the highly regulated standards perpetuate inequity for low-income families and families of color. Findings suggest that the structure of out-of-home care policies and the priorities of the governments who oversee them inform the implementation of policy in practice and differential outcomes experienced by the children and families they are meant to support. Limiting a relative caregiver’s ability to be licensed as a foster parent is a form of social exclusion, reducing their access to available support and limiting child access to relative care. Equitable access to foster care licensure would provide relative caregivers with additional tools to meet the needs of children in their care. Revisions to foster care licensing practices should prioritize placement with relatives by increasing flexibility in non-safety related requirements for relative caregivers in order to provide children with access to culturally appropriate placement options.
Objective: Evidence on the cost-effectiveness of screening for colorectal cancer (CRC) in the German general population remains scarce as key input parameters, the costs to treat CRC, are largely ...unknown. Here, we provide detailed estimates on CRC treatment costs over time. Methods: Using insurance claims data from the Vilua healthcare research database, we included subjects with newly diagnosed CRC and subjects who died of CRC between 2012 and 2016. We assessed annualized CRC-related inpatient, outpatient and medication costs for up to five years after first diagnosis and prior to death, stratified by sex and age. Findings: We identified 1748 and 1117 subjects with follow-up data for at least 1 year after diagnosis and prior to death, respectively. In those newly diagnosed, average costs were highest in the first year after diagnosis (men, EUR 16,375−16,450; women, EUR 10,071−13,250) and dropped steeply in the following years, with no consistent pattern of differences with respect to age. Costs prior to death were substantially higher as compared to the initial phase of care and consistently on a high level even several years before death, peaking in the final year of life, with strong differences by sex and age (men vs. women, <70 years, EUR 34,351 vs. EUR 31,417; ≥70 years, EUR 14,463 vs. EUR 9930). Conclusion: Once clinically manifest, CRC causes substantial treatment costs over time, particularly in the palliative care setting. Strong differences in treatment costs by sex and age warrant further investigation.
According to recent evidence, the prognostic value of Vitamin D (VitD) status for colorectal cancer (CRC) patients might be confined to patients with the GG genotype of
, a functional polymorphism of ...the VitD receptor gene. We aimed to validate these findings in a cohort of CRC patients. Post-operative serum 25-hydroxyvitamin D concentration was determined by mass spectrometry and
genotyping was performed from blood or buccal swabs using standard methods. Joint associations of VitD status and
with overall survival (OS), CRC-specific survival (CSS), recurrence-free survival (RFS), and disease-free survival (DFS) were assessed using Cox regression. For patients with GG genotype, adjusted hazard ratios (95% confidence interval) for the associations of sufficient compared with deficient VitD were 0.63 (0.50-0.78), 0.68 (0.50-0.90), 0.66 (0.51-0.86), and 0.62 (0.50-0.77) for OS, CSS, RFS, and DFS, respectively. These associations were weaker and not statistically significant for the AA/AG genotype. Interaction between VitD status and genotype did not reach statistical significance. VitD deficiency is an independent predictor of poorer survival, particularly for the GG
carriers, suggesting a potential role of VitD supplementation according to VitD status and genotype, which should be evaluated in randomised trials.
Current evidence on the association between smoking and colorectal cancer (CRC) prognosis after diagnosis is heterogeneous and few have investigated dose‐response effects or outcomes other than ...overall survival. Therefore, the association of smoking status and intensity with several prognostic outcomes was evaluated in a large population‐based cohort of CRC patients; 3,130 patients with incident CRC, diagnosed between 2003 and 2010, were interviewed on sociodemographic factors, smoking behavior, medication and comorbidities. Tumor characteristics were collected from medical records. Vital status, recurrence and cause of death were documented for a median follow‐up time of 4.9 years. Using Cox proportional hazards regression, associations between smoking characteristics and overall, CRC‐specific, non‐CRC related, recurrence‐free and disease‐free survival were evaluated. Among stage I–III patients, being a smoker at diagnosis and smoking ≥15 cigarettes/day were associated with lower recurrence‐free (adjusted hazard ratios (aHR): 1.29; 95% confidence interval (CI): 0.93–1.79 and aHR: 1.31; 95%‐CI: 0.92–1.87) and disease‐free survival (aHR: 1.26; 95%‐CI: 0.95–1.67 and aHR: 1.29; 95%‐CI: 0.94–1.77). Smoking was associated with decreased survival in stage I–III smokers with pack years ≥20 (Overall survival: aHR: 1.40; 95%‐CI: 1.01–1.95), in colon cancer cases (Overall survival: aHR: 1.51; 95%‐CI: 1.05–2.17) and men (Recurrence‐free survival: aHR: 1.51; 95%‐CI: 1.09–2.10; disease‐free survival: aHR: 1.49; 95%‐CI: 1.12–1.97), whereas no associations were seen among women, stage IV or rectal cancer patients. The observed patterns support the existence of adverse effects of smoking on CRC prognosis among nonmetastatic CRC patients. The potential to enhance prognosis of CRC patients by promotion of smoking cessation, embedded in tertiary prevention programs warrants careful evaluation in future investigations.
What's new?
Smoking is an established risk factor for a variety of cancers, including colorectal cancer, but evidence regarding its impact on the prognosis of colorectal cancer patients remains sparse. In this population‐based study of 3,130 colorectal cancer patients, smoking was associated with reduced survival among patients with nonmetastatic colon cancer. The analyses suggested that the association may be more pronounced in men than women. Future studies should take into account relationships between smoking and other lifestyle factors and should explore the potential role of using the “teachable moment” of cancer diagnosis in the promotion of smoking cessation.
The heterogeneity among colorectal tumors is probably due to differences in developmental pathways and might associate with patient survival times. We studied the relationship among markers of ...different subtypes of colorectal tumors and patient survival.
We pooled data from 7 observational studies, comprising 5010 patients with colorectal cancer. All the studies collected information on microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and mutations in KRAS and BRAF in tumors. Tumors with complete marker data were classified as type 1 (MSI-high, CIMP-positive, with pathogenic mutations in BRAF but not KRAS), type 2 (not MSI-high, CIMP-positive, with pathogenic mutations in BRAF but not KRAS), type 3 (not MSI-high or CIMP, with pathogenic mutations in KRAS but not BRAF), type 4 (not MSI-high or CIMP, no pathogenic mutations in BRAF or KRAS), or type 5 (MSI-high, no CIMP, no pathogenic mutations in BRAF or KRAS). We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for associations of these subtypes and tumor markers with disease-specific survival (DSS) and overall survival times, adjusting for age, sex, stage at diagnosis, and study population.
Patients with type 2 colorectal tumors had significantly shorter time of DSS than patients with type 4 tumors (HRDSS 1.66; 95% CI 1.33–2.07), regardless of sex, age, or stage at diagnosis. Patients without MSI-high tumors had significantly shorter time of DSS compared with patients with MSI-high tumors (HRDSS 0.42; 95% CI 0.27–0.64), regardless of other tumor markers or stage, or patient sex or age.
In a pooled analysis of data from 7 observational studies of patients with colorectal cancer, we found that tumor subtypes, defined by combinations of 4 common tumor markers, were associated with differences in survival time. Colorectal tumor subtypes might therefore be used in determining patients’ prognoses.
Within the framework of precision medicine, the stratification of individual genetic susceptibility based on inherited DNA variation has paramount relevance. However, one of the most relevant ...pitfalls of traditional Polygenic Risk Scores (PRS) approaches is their inability to model complex high-order non-linear SNP-SNP interactions and their effect on the phenotype (e.g. epistasis). Indeed, they incur in a computational challenge as the number of possible interactions grows exponentially with the number of SNPs considered, affecting the statistical reliability of the model parameters as well. In this work, we address this issue by proposing a novel PRS approach, called High-order Interactions-aware Polygenic Risk Score (hiPRS), that incorporates high-order interactions in modeling polygenic risk. The latter combines an interaction search routine based on frequent itemsets mining and a novel interaction selection algorithm based on Mutual Information, to construct a simple and interpretable weighted model of user-specified dimensionality that can predict a given binary phenotype. Compared to traditional PRSs methods, hiPRS does not rely on GWAS summary statistics nor any external information. Moreover, hiPRS differs from Machine Learning-based approaches that can include complex interactions in that it provides a readable and interpretable model and it is able to control overfitting, even on small samples. In the present work we demonstrate through a comprehensive simulation study the superior performance of hiPRS w.r.t. state of the art methods, both in terms of scoring performance and interpretability of the resulting model. We also test hiPRS against small sample size, class imbalance and the presence of noise, showcasing its robustness to extreme experimental settings. Finally, we apply hiPRS to a case study on real data from DACHS cohort, defining an interaction-aware scoring model to predict mortality of stage II-III Colon-Rectal Cancer patients treated with oxaliplatin.
Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical labels, whereas ...biomarkers are often continuous measurements. We hypothesize that regression-based DL outperforms classification-based DL. Therefore, we develop and evaluate a self-supervised attention-based weakly supervised regression method that predicts continuous biomarkers directly from 11,671 images of patients across nine cancer types. We test our method for multiple clinically and biologically relevant biomarkers: homologous recombination deficiency score, a clinically used pan-cancer biomarker, as well as markers of key biological processes in the tumor microenvironment. Using regression significantly enhances the accuracy of biomarker prediction, while also improving the predictions' correspondence to regions of known clinical relevance over classification. In a large cohort of colorectal cancer patients, regression-based prediction scores provide a higher prognostic value than classification-based scores. Our open-source regression approach offers a promising alternative for continuous biomarker analysis in computational pathology.
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