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Introduction: In patients with metastatic melanoma, progression of a single tumour lesion (solitary progression) after response to immune checkpoint inhibition (ICI) is increasingly treated with local therapy. We evaluated the role of local therapy for solitary progression in melanoma. Patients and methods: Patients with metastatic melanoma treated with ICI between 2010 and 2019 with solitary progression as first progressive event were included from 17 centres in 9 countries. Follow-up and survival are reported from ICI initiation. Results: We identified 294 patients with solitary progression after stable disease in 15%, partial response in 55% and complete response in 30%. The median follow-up was 43 months; the median time to solitary progression was 13 months, and the median time to subsequent progression after treatment of solitary progression (TTSP) was 33 months. The estimated 3-year overall survival (OS) was 79%; median OS was not reached. Treatment consisted of systemic therapy (18%), local therapy (36%), both combined (42%) or active surveillance (4%). In 44% of patients treated for solitary progression, no subsequent progression occurred. For solitary progression during ICI (n = 143), the median TTSP was 29 months. Both TTSP and OS were similar for local therapy, ICI continuation and both combined. For solitary progression post ICI (n = 151), the median TTSP was 35 months. TTSP was higher for ICI recommencement plus local therapy than local therapy or ICI recommencement alone (p = 0.006), without OS differences. Conclusion: Almost half of patients with melanoma treated for solitary progression after initial response to ICI had no subsequent progression. This study suggests that local therapy can benefit patients and is associated with favourable long-term outcomes.

BACKGROUND: Aggression in children has genetic and environmental causes. Studies of aggression can pool existing datasets to include more complex models of social effects. Such analyses require large datasets with harmonized outcome measures. Here, we made use of a reference panel for phenotype data to harmonize multiple aggression measures in school-aged children to jointly analyze data from five large twin cohorts.METHODS: Individual level aggression data on 86,559 children (42,468 twin pairs) were available in five European twin cohorts measured by different instruments. A phenotypic reference panel was collected which enabled a model-based phenotype harmonization approach. A bi-factor integration model in the integrative data analysis framework was developed to model aggression across studies while adjusting for rater, age, and sex. Finally, harmonized aggression scores were analyzed to estimate contributions of genes, environment, and social interaction to aggression. The large sample size allowed adequate power to test for sibling interaction effects, with unique dynamics permitted for opposite-sex twins.RESULTS: The best-fitting model found a high level of overall heritability of aggression (~60%). Different heritability rates of aggression across sex were marginally significant, with heritability estimates in boys of ~64% and ~58% in girls. Sibling interaction effects were only significant in the opposite-sex twin pairs: the interaction effect of males on their female co-twin differed from the effect of females on their male co-twin. An aggressive female had a positive effect on male co-twin aggression, whereas more aggression in males had a negative influence on a female co-twin.CONCLUSIONS: Opposite-sex twins displayed unique social dynamics of aggressive behaviors in a joint analysis of a large, multinational dataset. The integrative data analysis framework, applied in combination with a reference panel, has the potential to elucid

Parallel meta-analysis is a popular approach for increasing the power to detect genetic effects in genome-wide association studies across multiple cohorts. Consortia studying the genetics of behavioral phenotypes are oftentimes faced with systematic differences in phenotype measurement across cohorts, introducing heterogeneity into the meta-analysis and reducing statistical power. This study investigated integrative data analysis (IDA) as an approach for jointly modeling the phenotype across multiple datasets. We put forth a bi-factor integration model (BFIM) that provides a single common phenotype score and accounts for sources of study-specific variability in the phenotype. In order to capitalize on this modeling strategy, a phenotype reference panel was utilized as a supplemental sample with complete data on all behavioral measures. A simulation study showed that a mega-analysis of genetic variant effects in a BFIM were more powerful than meta-analysis of genetic effects on a cohort-specific sum score of items. Saving the factor scores from the BFIM and using those as the outcome in meta-analysis was also more powerful than the sum score in most simulation conditions, but a small degree of bias was introduced by this approach. The reference panel was necessary to realize these power gains. An empirical demonstration used the BFIM to harmonize aggression scores in 9-year old children across the Netherlands Twin Register and the Child and Adolescent Twin Study in Sweden, providing a template for application of the BFIM to a range of different phenotypes. A supplemental data collection in the Netherlands Twin Register served as a reference panel for phenotype modeling across both cohorts. Our results indicate that model-based harmonization for the study of complex traits is a useful step within genetic consortia., Funding Agencies:"ACTION: Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies" from the European Commission/European Union Seventh Framework Program FP7-602768United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA DA-018673