Prior pregnancy complications and maternal cardiovascular disease in young Korean women within 10 years after pregnancy.

BACKGROUND: This study aimed to compare obstetric outcomes in Korean women with and without future cardiovascular disease (CVD) within 10 years after pregnancy, and assessed whether pregnancy complications are independent risk factors, and whether the combination of pregnancy complications has an additive function for risk factors for CVD. METHODS: This was a nationwide population-based study combining the database of the Korea National Health Insurance claims and National Health Screening Programs to assess preeclampsia, low birth weight (LBW), and preterm delivery as risk factors for CVD. Cox proportional hazards models was used to evaluate the risk of total CVD, ischemic heart disease (IHD), and stroke after the pregnancy complications, with adjustment for potential confounding variables. RESULTS: Women with CVD were likely to have a higher prevalence of pregnancy complications than women without CVD. The risk of total CVD was associated with preeclampsia (adjusted hazard ratio (HR), 1.60 [95% confidence interval (CI) 1.50-1.72]), LBW (1.20 [1.12-1.28]), and preterm delivery (1.32 [1.22-1.42]), after adjustment for confounders, including cardiovascular risk factors before pregnancy. The risk estimates of pregnancy complications for IHD were higher than those for stroke. In this study, the risk of total CVD was higher in the combined presence of preeclampsia and preterm delivery (2.23 [1.57-3.17] or all three complications (2.06 [1.76-2.40]), relative to no complications. The highest HR was noted in the risk of all pregnancy complications for IHD (2.39 [1.98-2.89]). CONCLUSION: Preeclampsia, preterm delivery, and LBW were independently associated with CVD in young Korean women. In addition, the combination of pregnancy complications had less-than-additive effects on CVD incidence.

Doubly-robust methods for differences in restricted mean lifetimes using pseudo-observations.

In clinical studies or trials comparing survival times between two treatment groups, the restricted mean lifetime (RML), defined as the expectation of the survival from time 0 to a prespecified time-point, is often the quantity of interest that is readily interpretable to clinicians without any modeling restrictions. It is well known that if the treatments are not randomized (as in observational studies), covariate adjustment is necessary to account for treatment imbalances due to confounding factors. In this article, we propose a simple doubly-robust pseudo-value approach to effectively estimate the difference in the RML between two groups (akin to a metric for estimating average causal effects), while accounting for confounders. The proposed method combines two general approaches: (a) group-specific regression models for the time-to-event and covariate information, and (b) inverse probability of treatment assignment weights, where the RMLs are replaced by the corresponding pseudo-observations for survival outcomes, thereby mitigating the estimation complexities in presence of censoring. The proposed estimator is double-robust, in the sense that it is consistent if at least one of the two working models remains correct. In addition, we explore the potential of available machine learning algorithms in causal inference to reduce possible bias of the causal estimates in presence of a complex association between the survival outcome and covariates. We conduct extensive simulation studies to assess the finite-sample performance of the pseudo-value causal effect estimators. Furthermore, we illustrate our methodology via application to a dataset from a breast cancer cohort study. The proposed method is implementable using the R package drRML, available in GitHub.

Twelve-month post-treatment parameters are superior in predicting hepatocellular carcinoma in patients with chronic hepatitis B.

BACKGROUND & AIMS: There are currently several prediction models for hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) receiving oral antiviral therapy. However, most models are based on pre-treatment clinical parameters. The current study aimed to develop a novel and practical prediction model for HCC by using both pre- and post-treatment parameters in this population. METHODS: We included two treatment-naïve CHB cohorts who were initiated on oral antiviral therapies: the derivation cohort (n = 1480, Korea prospective SAINT cohort) and the validation cohort (n = 426, the US retrospective Stanford Bay cohort). We employed logistic regression, decision tree, lasso regression, support vector machine and random forest algorithms to develop the HCC prediction model and selected the most optimal method. RESULTS: We evaluated both pre-treatment and the 12-month clinical parameters on-treatment and found the 12-month on-treatment values to have superior HCC prediction performance. The lasso logistic regression algorithm using the presence of cirrhosis at baseline and alpha-foetoprotein and platelet at 12 months showed the best performance (AUROC = 0.843 in the derivation cohort. The model performed well in the external validation cohort (AUROC = 0.844) and better than other existing prediction models including the APA, PAGE-B and GAG models (AUROC = 0.769 to 0.818). CONCLUSIONS: We provided a simple-to-use HCC prediction model based on presence of cirrhosis at baseline and two objective laboratory markers (AFP and platelets) measured 12 months after antiviral initiation. The model is highly accurate with excellent validation in an external cohort from a different country (AUROC 0.844) (Clinical trial number: KCT0003487).

Women with multiple gestations have an increased risk of development of hypertension in the future.

BACKGROUND: Multiple gestations are associated with an increased incidence of preeclampsia. However, there exists no evidence for an association between multiple gestations and development of hypertension(HTN) later in life. This study aimed to determine whether multiple gestations are associated with HTN beyond the peripartum period. METHODS: In this retrospective nationwide population-based study, women who delivered a baby between January 1, 2007, and December 31, 2008, and underwent a national health screening examination within one year prior to their pregnancy were included. Subsequently, we tracked the occurrence of HTN during follow-up until December 31, 2015, using International Classification of Diseases-10th Revision codes. RESULTS: Among 362,821 women who gave birth during the study period, 4,944 (1.36%) women had multiple gestations. The cumulative incidence of HTN was higher in multiple gestations group compared with singleton group (5.95% vs. 3.78%, p < 0.01, respectively). On the Cox proportional hazards models, the risk of HTN was increased in women with multiple gestations (HR 1.35, 95% CI 1.19, 1.54) compared with those with singleton after adjustment for age, primiparity, preeclampsia, atrial fibrillation, body mass index, blood pressure, diabetes mellitus, high total cholesterol, abnormal liver function test, regular exercise, and smoking status. CONCLUSIONS: Multiple gestations are associated with an increased risk of HTN later in life. Therefore, guidelines for the management of high-risk patients after delivery should be established.

Integrative Proteo-genomic Analysis to Construct CNA-protein Regulatory Map in Breast and Ovarian Tumors.

Recent development in high throughput proteomics and genomics profiling enable one to study regulations of genome alterations on protein activities in a systematic manner. In this article, we propose a new statistical method, ProMAP, to systematically characterize the regulatory relationships between proteins and DNA copy number alterations (CNA) in breast and ovarian tumors based on proteogenomic data from the CPTAC-TCGA studies. Because of the dynamic nature of mass spectrometry instruments, proteomics data from labeled mass spectrometry experiments usually have non-ignorable batch effects. Moreover, mass spectrometry based proteomic data often possesses high percentages of missing values and non-ignorable missing-data patterns. Thus, we use a linear mixed effects model to account for the batch structure and explicitly incorporate the abundance-dependent-missing-data mechanism of proteomic data in ProMAP. In addition, we employ a multivariate regression framework to characterize the multiple-to-multiple regulatory relationships between CNA and proteins. Further, we use proper statistical regularization to facilitate the detection of master genetic regulators, which affect the activities of many proteins and often play important roles in genetic regulatory networks. Improved performance of ProMAP over existing methods were illustrated through extensive simulation studies and real data examples. Applying ProMAP to the CPTAC-TCGA breast and ovarian cancer data sets, we identified many genome regions, including a few novel ones, whose CNA were associated with protein and or phosphoprotein abundances. For example, in breast tumors, a small region in 8p11.21 was recognized as the second biggest hub in the CNA-phosphoprotein regulatory map, and further investigation of the regulatory targets suggests the potential role of 8p11.21 CNA in perturbing oxygen binding and transport activities in tumor cells. This and other findings from our analyses help to characterize the impacts of CNAs on protein activity landscapes and cast light on the genetic regulation mechanisms underlying these tumors.

Peripheral blood transcriptome analysis and development of classification model for diagnosing antibody-mediated rejection vs accommodation in ABO-incompatible kidney transplant.

The major obstacle to successful ABO blood group-incompatible kidney transplantation (ABOi KT) is antibody-mediated rejection (AMR). This study aimed to investigate transcriptional profiles through RNA sequencing and develop a minimally invasive diagnostic tool for discrimination between accommodation and early acute AMR in ABOi KT. Twenty-eight ABOi KT patients were selected: 18 with accommodation and 10 with acute AMR at the 10th day posttransplant protocol biopsy. Complete transcriptomes of their peripheral blood were analyzed by RNA sequencing. Candidate genes were selected by bioinformatics analysis, validated with quantitative polymerase chain reaction, and used to develop a classification model to diagnose accommodation. A total of 1385 genes were differentially expressed in accommodation compared with in AMR with P-adjusted < .05. Functional annotation and gene set enrichment analysis identified several immune-related and immunometabolic pathways. A 5-gene classification model including COX7A2L, CD69, CD14, CFD, and FOXJ3 was developed by logistic regression analysis. The model was further validated with an independent cohort and discriminated between accommodation and AMR with 92.7% sensitivity, 85.7% specificity, and 91.7% accuracy. Our study suggests that a classification model based on peripheral blood transcriptomics may allow minimally invasive diagnosis of acute AMR vs accommodation and subsequent patient-tailored immunosuppression in ABOi KT.

Prediction of survival risks with adjusted gene expression through risk-gene networks.

MOTIVATION: Network-based analysis of biomedical data has been extensively studied over the last decades. As a successful application, gene networks have been used to illustrate interactions among genes and explain the associated phenotypes. However, the gene network approaches have not been actively applied for survival analysis, which is one of the main interests of biomedical research. In addition, a few previous studies using gene networks for survival analysis construct networks mainly from prior knowledge, such as pathways, regulations and gene sets, while the performance considerably depends on the selection of prior knowledge. RESULTS: In this paper, we propose a data-driven construction method for survival risk-gene networks as well as a survival risk prediction method using the network structure. The proposed method constructs risk-gene networks with survival-associated genes using penalized regression. Then, gene expression indices are hierarchically adjusted through the networks to reduce the variance intrinsic in datasets. By illustrating risk-gene structure, the proposed method is expected to provide an intuition for the relationship between genes and survival risks. The risk-gene network is applied to a low grade glioma dataset, and produces a hypothesis of the relationship between genetic biomarkers of low and high grade glioma. Moreover, with multiple datasets, we demonstrate that the proposed method shows superior prediction performance compared to other conventional methods. AVAILABILITY AND IMPLEMENTATION: The R package of risk-gene networks is freely available in the web at http://cdal.korea.ac.kr/NetDA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Paradoxical long-term impact of maternal influenza infection on neonates and infants.

BACKGROUND: Pregnant women are at high risk of influenza-related morbidity and mortality. In addition, maternal influenza infection may lead to adverse birth outcomes. However, there is insufficient data on long-term impact of maternal influenza infection. METHODS: This study was conducted to assess the impact of maternal influenza infection on birth outcomes and long-term influence on infants by merging the Korea National Health Insurance (KNHI) claims database and National Health Screening Program for Infants and Children (NHSP-IC). Mother-offspring pairs were categorized by maternal influenza infection based on the ICD-10 code. RESULTS: Multivariate analysis revealed that maternal influenza infection significantly increased the risk of preterm birth (OR 1.408) and low birth weight (OR 1.198) irrespective of gestational age. The proportion of low birth weight neonates was significantly higher in influenza-infected women compared to those without influenza. However, since the fourth health screening (30-80 months after birth), the fraction of underweight was no longer different between children from influenza-infected and non-infected mothers, whereas the rates of overweight increased paradoxically in those born to mothers with influenza infection. CONCLUSIONS: Maternal influenza infection might have long-term effects on the health of children and adolescents even after infancy.

Clinical Predictors Implicated in the Incidence of Acute Pyelonephritis during the Antepartum Period: A Population-Based Cohort Study.

INTRODUCTION: Acute pyelonephritis (APN) is a common infection during pregnancy that increases the risk of unfavorable maternal and fetal outcomes. However, it has not been clearly elucidated which demographic and clinical characteristics are associated with the incidence of APN during pregnancy. OBJECTIVE: This population-based cohort study aimed to determine the risk factors for APN during pregnancy. METHODS: Using the database of the Health Insurance Review and Assessment Service of South Korea, we enrolled Korean women who delivered infants between 2010 and 2014 in Korea and had complete health examination records within 1 year of pregnancy. We performed multivariate logistic regression analysis to evaluate the risk factors for APN during pregnancy. RESULTS: Of 370,248 women, 2,526 (0.7% of the total participants) were treated for APN while in hospitalization during pregnancy. Younger age, history of previous APN within 1 year of pregnancy, and abnormal results of health examination before pregnancy, such as high fasting glucose level (>100 mg/dL) and proteinuria, were associated with an increased risk of APN during pregnancy. CONCLUSION: Certain maternal demographic and clinical characteristics were associated with the incidence of APN during pregnancy, and these should be monitored closely during antenatal care.

Cross-activating c-Met/ß1 integrin complex drives metastasis and invasive resistance in cancer.

The molecular underpinnings of invasion, a hallmark of cancer, have been defined in terms of individual mediators but crucial interactions between these mediators remain undefined. In xenograft models and patient specimens, we identified a c-Met/ß1 integrin complex that formed during significant invasive oncologic processes: breast cancer metastases and glioblastoma invasive resistance to antiangiogenic VEGF neutralizing antibody, bevacizumab. Inducing c-Met/ß1 complex formation through an engineered inducible heterodimerization system promoted features crucial to overcoming stressors during metastases or antiangiogenic therapy: migration in the primary site, survival under hypoxia, and extravasation out of circulation. c-Met/ß1 complex formation was up-regulated by hypoxia, while VEGF binding VEGFR2 sequestered c-Met and ß1 integrin, preventing their binding. Complex formation promoted ligand-independent receptor activation, with integrin-linked kinase phosphorylating c-Met and crystallography revealing the c-Met/ß1 complex to maintain the high-affinity ß1 integrin conformation. Site-directed mutagenesis verified the necessity for c-Met/ß1 binding of amino acids predicted by crystallography to mediate their extracellular interaction. Far-Western blotting and sequential immunoprecipitation revealed that c-Met displaced α5 integrin from ß1 integrin, creating a complex with much greater affinity for fibronectin (FN) than α5ß1. Thus, tumor cells adapt to microenvironmental stressors induced by metastases or bevacizumab by coopting receptors, which normally promote both cell migration modes: chemotaxis, movement toward concentrations of environmental chemoattractants, and haptotaxis, movement controlled by the relative strengths of peripheral adhesions. Tumor cells then redirect these receptors away from their conventional binding partners, forming a powerful structural c-Met/ß1 complex whose ligand-independent cross-activation and robust affinity for FN drive invasive oncologic processes.

Predicting peripartum blood transfusion: focusing on pre-pregnancy characteristics.

BACKGROUND: Obstetric hemorrhage is one of the most common causes of obstetrical morbidity and mortality, and transfusion is the most important management for hemorrhage. The aim of our study was to investigate the pre-pregnancy and pregnancy risk factors for peripartum transfusion. METHODS: Women who delivered a baby from 2010 to 2014 in Korea and participated in the Korean National Health Screening Program for Infants and Children were included. To analyze pre-pregnant risk factors for peripartum transfusion, an additional analysis was done for women who underwent a National Health Screening Examination within 1 year before pregnancy, including maternal waist circumference, body mass index, blood pressure, laboratory tests and history of smoking. Multivariable logistic regression analysis was used to estimate the risk factors for peripartum transfusion. RESULTS: Of the total 1,980,126 women who met the inclusion criteria, 36,868 (1.86%) were transfused at peripartum. In a multivariable regression model, the pregnancy risk factors for peripartum transfusion included maternal age above 35 years [odds ratio (OR): 1.41; 95% confidence interval (CI): 1.32-1.50], preterm birth (OR: 2.39; 95% CI: 2.15-2.65), and maternal hypertension (OR: 2.49; 95% CI: 2.24-2.77). Pre-pregnancy risk factors including fasting glucose level of more than 126 mg/dL (OR: 1.11; 95% CI: 1.02-1.20), current-smoker status (OR: 1.20; 95% CI: 1.06-1.37), and waist-circumference less than 80 cm (OR: 1.18; 95% CI: 1.06-1.30) were independently associated with peripartum blood transfusion. CONCLUSIONS: Several pre-pregnancy and pregnancy risk factors were associated with peripartum blood transfusion. Some identified factors are modifiable before conception, and our study validated peripartum blood transfusion as a form of triage.

Comparative Evaluation of the Biodegradability and Wrinkle Reduction Efficacy of Human-Derived Collagen Filler and Hyaluronic Acid Filler.

BACKGROUND: The development of fillers for wrinkle prevention is growing to meet rising demands to reduce the aging of skin. OBJECTIVE: In this experiment, we confirmed the effects of human collagen and hyaluronic acid filler biodegradation for wrinkle reduction using a photo-aging mouse model. MATERIALS AND METHODS: A total of 10 hairless mice (SKH1-Hrhr) were randomly divided into two groups and injected with hyaluronic acid and human-derived collagen filler. At 0, 2, 4, 8, and 12 weeks, PRIMOSlite®, folliscope, and MRI were used to evaluate the biodegradability of the fillers after the injections. We also studied the photo-aging mouse model for skin roughness and histological evaluation and confirmed that the filler injection had excellent anti-wrinkle effects. RESULTS: Human-derived collagen fillers had excellent biodegradability compared to that of hyaluronic acid fillers. The skin surface roughness in the photo-aging mouse models was significantly reduced after injections of human-derived collagen filler. CONCLUSION: Our results showed that the human-derived collagen filler had excellent biodegradability and effectively reduced wrinkle formation in a photo-aging mouse model. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

A multivariate distance-based analytic framework for microbial interdependence association test in longitudinal study.

Human microbiome is the collection of microbes living in and on the various parts of our body. The microbes living on our body in nature do not live alone. They act as integrated microbial community with massive competing and cooperating and contribute to our human health in a very important way. Most current analyses focus on examining microbial differences at a single time point, which do not adequately capture the dynamic nature of the microbiome data. With the advent of high-throughput sequencing and analytical tools, we are able to probe the interdependent relationship among microbial species through longitudinal study. Here, we propose a multivariate distance-based test to evaluate the association between key phenotypic variables and microbial interdependence utilizing the repeatedly measured microbiome data. Extensive simulations were performed to evaluate the validity and efficiency of the proposed method. We also demonstrate the utility of the proposed test using a well-designed longitudinal murine experiment and a longitudinal human study. The proposed methodology has been implemented in the freely distributed open-source R package and Python code.

Differential relationship between waist circumference and mortality according to age, sex, and body mass index in Korean with age of 30-90 years; a nationwide health insurance database study.

BACKGROUND: A recent concept is that obesity, assessed by body mass index (BMI), is not always a sign of poor health. Thus, in order to use obesity metrics in clinical decision making, it is important to clarify the relationship between waist circumference (WC), a proxy for abdominal obesity, and mortality. METHODS: Data were used from 8,796,759 subjects aged between 30 and 90 years, who had participated in the Korea National Health Screening Examination between January 1, 2009 and December 31, 2009 and survived at least 1 year post screening. Data from a mean follow-up time of an additional 5.3 years (time at risk) were analyzed for the relationship between WC and mortality according to age, sex, and BMI category. RESULTS: An increased WC of more than 90 cm in men and 85 cm in women showed a definite negative influence on mortality. However, the detailed relationship between WC and mortality was J-shaped or U-shaped according to age, sex, and BMI category. In the normal BMI group, the optimal WC range with the lowest mortality was < 70 cm in men and 70-75 cm in women, whereas in obese individuals a WC between 80 and 90 cm in men and 75 and 85 cm in women showed the lowest mortality. The association between increased WC and higher mortality tended to be more obvious in normal-weight women than in normal-weight men or obese women. Furthermore, in normal-weight and obese women, the effect of increased WC on mortality was more critical for subjects aged < 60 years rather than those aged ≥ 60 years. CONCLUSIONS: Abdominal obesity, as measured by WC, showed a significant negative association on mortality, and its association with mortality was different according to age, sex, and BMI category. Therefore, WC should be considered in the assessment of obesity-related health risks, and individualized cut-off points for the definition of a healthy WC according to age, sex, and BMI category are necessary.

Recurrent Risk of Preterm Birth in the Third Pregnancy in Korea.

BACKGROUND: Although preterm delivery is the most common cause of infant morbidity and mortality, an obvious cause cannot be found in most cases. Preterm delivery is known to be the most important risk factor for preterm birth in a subsequent pregnancy. We aimed to evaluate the recurrence rate of premature births for subsequent pregnancies in women with a history of a preterm birth. METHODS: Study data were collected from the Korea National Health Insurance (KNHI) claims database and data from a national health-screening program for infants and children. We enrolled women who had their first delivery between January 1, 2007 and December 31, 2007 and a subsequent delivery before 2014. RESULTS: Preterm delivery had a significant higher risk of preterm birth in a subsequent singleton pregnancy. The risk of preterm birth at second pregnancy was 2.2% in women whose first delivery at ≥ 37 weeks and 18.6% in women whose first delivery at < 37 weeks (relative risks [RR], 8.64; 95% confidence interval [CI], 7.94-9.40). In the analysis of the third pregnancy, we compared women with an initial term birth followed by preterm birth and women with an initial preterm birth followed by a subsequent term birth. A history of a just preceding preterm birth at < 37 weeks was the most relevant factor for recurrence of preterm delivery in a subsequent pregnancy (26.6%, RR, 4.01; 95% CI, 2.45-6.58). CONCLUSION: We found that the prognosis of a third pregnancy was more closely related to the outcome of the second pregnancy to that of the first pregnancy.

Computer-assisted measurement of primary tumor area is prognostic of recurrence-free survival in stage IB melanoma patients.

Current staging guidelines are insufficient to predict which patients with thin primary melanoma are at high risk of recurrence. Computer-assisted image analysis may allow for more practical and objective histopathological analysis of primary tumors than traditional light microscopy. We studied a prospective cohort of stage IB melanoma patients treated at NYU Langone Medical Center from 2002 to 2014. Primary tumor width, manual area, digital area, and conformation were evaluated in a patient subset via computer-assisted image analysis. The associations between histologic variables and survival were evaluated using Cox proportional hazards model. Logistic regressions were used to build a classifier with clinicopathological characteristics to predict recurrence status. Of the 655 patients with stage IB melanoma studied, a subset of 149 patient tumors (63 recurred, 86 did not recur) underwent computer-assisted histopathological analysis. Increasing tumor width (hazard ratios (HR): 1.17, P=0.01) and digital area (HR: 1.08, P<0.01) were significantly associated with worse recurrence-free survival, whereas non-contiguous conformation (HR: 0.57, P=0.05) was significantly associated with better recurrence-free survival. The novel histopathological classifier composed of digital area, conformation, and baseline variables effectively distinguished recurrent cases from non-recurrent cases (AUC: 0.733, 95% confidence interval (CI): 0.647-0.818), compared to the baseline classifier alone (AUC: 0.635, 95% CI: 0.545-0.724). Primary tumor cross-sectional area, width, and conformation measured via computer-assisted analysis may help identify high-risk patients with stage IB melanoma.

Outcomes in Melanoma Patients Treated with BRAF/MEK-Directed Therapy or Immune Checkpoint Inhibition Stratified by Clinical Trial versus Standard of Care.

OBJECTIVES: Since 2011, metastatic melanoma treatment has evolved with commercial approval of BRAF- and MEK-targeted therapy and CTLA-4- and PD-1-blocking antibodies (immune checkpoint inhibitors, ICI). While novel therapies have demonstrated improved prognosis in clinical trials, few studies have examined the evolution of prognosis and toxicity of these drugs among an unselected population. We assess whether survival and toxicity reported in trials, which typically exclude most patients with brain metastases and poor performance status, are recapitulated within a commercial access population. METHODS: 182 patients diagnosed with stage IV melanoma from July 2006 to December 2013 and treated with BRAF- and/or MEK-targeted therapy or ICI were prospectively studied. Outcomes and clinicopathologic differences between trial and commercial cohorts were assessed. RESULTS: Patients receiving commercial therapy (vs. on trial) had poorer prognostic features (i.e., brain metastases) and lower median overall survival (mOS) when assessed across all treatments (9.2 vs. 17.5 months, p = 0.0027). While toxicity within trial and commercial cohorts did not differ, patients who experienced toxicity had increased mOS (p < 0.001), irrespective of stratification by trial status or therapy. CONCLUSION: Metastatic melanoma patients receiving commercial treatment may represent a different clinical population with poor prognostic features compared to trial patients. Toxicity may prognosticate treatment benefit.

Melanoma brain metastases: correlation of imaging features with genomic markers and patient survival.

Purpose To identify MR imaging features of melanoma brain metastases (MBM) that correlate with genetic profile of melanoma and patient survival. Materials and methods Patients with newly diagnosed melanoma metastases were identified from institutional database A retrospective review of brain MRI was performed focusing on lesion number, size, T1-, T2- and diffusion-weighted signal characteristics, hemorrhage, necrosis, enhancement pattern and edema. Genomic (BRAF status), treatment and survival data was collected. Results 98 patients were included in final analysis. A strong correlation was found between size of the largest lesion and the percent of lesions with T1-weighted hyperintense signal (R = 0.49), percent of lesions with size >1 cm (0.55), and the lesions that are clearly hemorrhagic (0.43). The analyzed imaging parameters were found to be independent of BRAF mutation status. The median survival of subjects with single lesion (9.1 months) was significantly higher than the median survival of subjects with more than 1 lesion (4.9 months) (p = 0.002). Patients with 2-18 lesions had significantly longer survival (5.6 months) than with >18 lesions (2 months) (p < 0.001). Other imaging parameters such as lesion size, T1-weighted hyperintensity, number of lesions with edema and hemorrhage were not found to be significantly related to survival. BRAF inhibitor treatment was found to be the most significant prognostic factor (p = 0.002) among patients with multiple lesions. Conclusion There is a statistically significant correlation between number of brain metastases and survival. In patients with multiple lesions, BRAF inhibitor treatment was the most significant prognostic factor.

Impact of aging on host immune response and survival in melanoma: an analysis of 3 patient cohorts.

BACKGROUND: Age has been reported as an independent prognostic factor for melanoma-specific survival (MSS). We tested the hypothesis that age impacts the host anti-tumor immune response, accounting for age-specific survival outcomes in three unique melanoma patient cohorts. METHODS: We queried the U.S. population-based Surveillance, Epidemiology, and End Results Program (SEER), the prospective tertiary care hospital-based Interdisciplinary Melanoma Cooperative Group (IMCG) biorepository, and the Cancer Genome Atlas (TCGA) biospecimen database to test the association of patient age at time of melanoma diagnosis with clinicopathologic features and survival outcomes. Age groups were defined as ≤45 (young), 46-65 (intermediate), and >65 (older). Each age group in the IMCG and TCGA cohorts was stratified by tumor infiltrating lymphocyte (TIL) measurements and tested for association with MSS. Differential expression of 594 immunoregulatory genes was assessed in a subset of primary melanomas in the IMCG and TCGA cohorts using an integrative pathway analysis. RESULTS: We analyzed 304, 476 (SEER), 1241 (IMCG), and 292 (TCGA) patients. Increasing age at melanoma diagnosis in both the SEER and IMCG cohorts demonstrated a positive correlation with tumor thickness, ulceration, stage, and mortality, however age in the TCGA cohort did not correlate with mortality. Older age was associated with shorter MSS in all three cohorts. When the young age group in both the IMCG and TCGA cohorts was stratified by TIL status, there were no differences in MSS. However, older IMCG patients with brisk TILs and intermediate aged TCGA patients with high lymphocyte scores (3-6) had improved MSS. Gene expression analysis revealed top pathways (T cell trafficking, communication, and differentiation) and top upstream regulators (CD3, CD28, IFNG, and STAT3) that significantly changed with age in 84 IMCG and 43 TCGA primary melanomas. CONCLUSIONS: Older age at time of melanoma diagnosis is associated with shorter MSS, however age's association with clinicopathologic features is dependent upon specific characteristics of the study population. TIL as a read-out of the host immune response may have greater prognostic impact in patients older than age 45. Recognition of age-related factors negatively impacting host immune responses may provide new insights into therapeutic strategies for the elderly.

Impact of Socioeconomic Status and Ethnicity on Melanoma Presentation and Recurrence in Caucasian Patients.

OBJECTIVES: The impact of ethnicity and the socioeconomic status (SES) among Caucasians is not well studied. Here, we examine the impact of income on melanoma presentation and prognosis within a Caucasian cohort, accounting for ethnicity, as some reports suggest increased melanoma incidence in Ashkenazi Jewish (AJ) BRCA mutation carriers. METHODS: We studied prospectively enrolled primary melanoma patients at New York University. SES data were estimated using United States' Census Bureau data and patient zip codes. We evaluated associations between ethnicity, SES, and baseline characteristics using the χ² test and multivariate logistic regression. We compared survival distributions using Kaplan-Meier curves, log-rank tests, and Cox proportional hazard ratios. RESULTS: Of the 1,339 enrolled patients, AJ represented 32% (n = 423). Apart from AJ being older at presentation (p < 0.001), no significant differences were observed in baseline characteristics between ethnic groups. Patients with a median household income (MHI) lower than the median of the cohort were significantly more likely to present with advanced stages (p < 0.001) compared to patients with a higher MHI. Shorter overall (p = 0.016) and post-recurrence survival (p = 0.042) was also observed in patients from lower-income households. CONCLUSION: Data suggest that disparities in melanoma presentation in Caucasians stratify according to income independent of ethnic background.