PurposeAdolescent and young adult cancer survivors (AYAs) are at increased risk of long-term and late effects, and experience unmet needs, impacting their health-related quality of life (HRQoL). In... Show morePurposeAdolescent and young adult cancer survivors (AYAs) are at increased risk of long-term and late effects, and experience unmet needs, impacting their health-related quality of life (HRQoL). In order to provide and optimize supportive care and targeted interventions for this unique population, it is important to study HRQoL factors' interconnectedness on a population level. Therefore, this network analysis was performed with the aim to explore the interconnectedness between HRQoL factors, in the analysis described as nodes, among long-term AYAs.MethodsThis population-based cohort study used cross-sectional survey data of long-term AYAs, who were identified by the Netherlands Cancer Registry (NCR). Participants completed a one-time survey (SURVAYA study), including the EORTC survivorship questionnaire (QLQ-SURV111) to assess their long-term HRQoL outcomes and sociodemographic characteristics. The NCR provided the clinical data. Descriptive statistics and a network analysis, including network clustering, were performed.ResultsIn total, 3596 AYAs (on average 12.4 years post diagnosis) were included in our network analysis. The network was proven stable and reliable and, in total, four clusters were identified, including a worriment, daily functioning, psychological, and sexual cluster. Negative health outlook, part of the worriment cluster, was the node with the highest strength and its partial correlation with health distress was significantly different from all other partial correlations.ConclusionThis study shows the results of a stable and reliable network analysis based on HRQoL data of long-term AYAs, and identified nodes, correlations, and clusters that could be intervened on to improve the HRQoL outcomes of AYAs. Show less
BackgroundCheckpoint inhibitors have been shown to substantially improve the survival of patients with advanced melanoma. With this growing group of survivors treated with immunotherapies,... Show moreBackgroundCheckpoint inhibitors have been shown to substantially improve the survival of patients with advanced melanoma. With this growing group of survivors treated with immunotherapies, assessing their health-state utilities is essential and can be used for the calculation of quality-adjusted life years and for cost-effectiveness analyses. Therefore, we evaluated the health-state utilities in long-term advanced melanoma survivors.MethodsHealth-state utilities were evaluated in a cohort of advanced melanoma survivors 24-36 months (N = 37) and 36-plus months (N = 47) post-ipilimumab monotherapy. In addition, the health-state utilities of the 24-36 months survivor group were assessed longitudinally, and utilities of the combined survival groups (N = 84) were compared with a matched control population (N = 168). The EQ-5D was used to generate health-state utility values, and quality-of-life questionnaires were used to establish correlations and influencing factors of utility scores.ResultsHealth-state utility scores were similar between the 24-36 months'- and the 36-plus months' survival group (0.81 vs 0.86; p = .22). In survivors, lower utility scores were associated with symptoms of depression (beta = - .82, p = .022) and fatigue burden (beta = - .29, p = .007). Utility scores did not significantly change after 24-36 months of survival, and the utilities of survivors were comparable to the matched control population (0.84 vs 0.87; p = .07).DiscussionOur results show that long-term advanced melanoma survivors treated with ipilimumab monotherapy experience relatively stable and high health-state utility scores. Show less
Hulst, H.J. van der; Vos, J.L.; Tissier, R.; Smit, L.A.; Martens, R.M.; Beets-Tan, R.G.H.; ... ; Castelijns, J.A. 2022
Simple Summary Immunotherapy may induce early treatment response in head and neck squamous cell carcinoma (HNSCC) for some patients. Routine imaging parameters fail to diagnose these responses;... Show moreSimple Summary Immunotherapy may induce early treatment response in head and neck squamous cell carcinoma (HNSCC) for some patients. Routine imaging parameters fail to diagnose these responses; however, magnetic resonance (MR) diffusion-weighted imaging (DWI) may be able to do so. This study sought to correlate DWI parameters with treatment response early after immunotherapy treatment in HNSCC. We analyzed 24 patients with advanced HNSCC with imaging before and after the immunotherapy. We found that rounder tumors that were smaller in diameter before treatment were more likely to respond. A decrease in skewness of the tumor after treatment compared to before treatment, as well as an overall low skewness post-treatment, were linked to better treatment response. Though this study was explorative in nature, these results are promising for the predictive use of MR-DWI in HNSCC treated with immunotherapy. Background: Neoadjuvant immune checkpoint blockade (ICB) prior to surgery may induce early pathological responses in head and neck squamous cell carcinoma (HNSCC) patients. Routine imaging parameters fail to diagnose these responses early on. Magnetic resonance (MR) diffusion-weighted imaging (DWI) has proven to be useful for detecting HNSCC tumor mass after (chemo)radiation therapy. METHODS: 32 patients with stage II-IV, resectable HNSCC, treated at a phase Ib/IIa IMCISION trial (NCT03003637), were retrospectively analyzed using MR-imaging before and after two doses of single agent nivolumab (anti-PD-1) (n = 6) or nivolumab with ipilimumab (anti-CTLA-4) ICB (n = 26). The primary tumors were delineated pre- and post-treatment. A total of 32 features were derived from the delineation and correlated with the tumor regression percentage in the surgical specimen. Results: MR-DWI data was available for 24 of 32 patients. Smaller baseline tumor diameter (p = 0.01-0.04) and higher sphericity (p = 0.03) were predictive of having a good pathological response to ICB. Post-treatment skewness and the change in skewness between MRIs were negatively correlated with the tumor's regression (p = 0.04, p = 0.02). Conclusion: Pre-treatment DWI tumor diameter and sphericity may be quantitative biomarkers for the prediction of an early pathological response to ICB. Furthermore, our data indicate that ADC skewness could be a marker for individual response evaluation. Show less
The major challenge in analysing omic datasets is the strong dependencies which are present between samples and features. Taking into account and modelling the different dependency structures can... Show moreThe major challenge in analysing omic datasets is the strong dependencies which are present between samples and features. Taking into account and modelling the different dependency structures can lead to further improvements of our knowledge of the biological mechanisms. Therefore, improving our ability to predict diseases. This dissertation focuses on the development of new statistical methods designed to take into account the existing structures inside omic datasets by using mixed models, Gaussian graphical models, and machine learning approaches. Show less
Tissier, R.; Houwing-Duistermaat, J.; Rodriguez-Girondo, M. 2018
